PSYCHOLOGICAL
INQUIRY
An International Journal for the
Advancement of Psychological Theory
Volume 22, Number 3
2011
TARGET ARTICLE
Jamil Zaki
Kevin Ochsner
Reintegrating the Study of Accuracy Into Social Cognition Research
159
COMMENTARIES
Bahador Bahrami
Chris D. Frith
Interacting Minds: A Framework for Combining Process- and
Accuracy-Oriented Social Cognitive Research
183
Nicholas Epley
Tal Eyal
Integrations Need Both Breadth and Depth: Commentary on Zaki and Ochsner
187
Judith A. Hall
C. Randall Colvin
On Making a Thriving Field Even Better: Acknowledging the Past and
Looking to the Future
193
William Ickes
Everyday Mind Reading Is Driven by Motives and Goals
200
David A. Kenny
History, Dialectics, and Dynamics
207
Christian Keysers
Lawrie S. McKay
How to Make Social Neuroscience Social
210
Marco Iacoboni
Social Cognition, Accuracy, and Physiology
217
Elysia R. Todd
David C. Funder
Organizing Interactions in the Study of Judgmental Accuracy
219
REPLY
Jamil Zaki
Kerin Ochsner
On the Reintegration of Accuracy in Social Cognition Research: Let Us
Count the Ways
221
Psychological Inquiry, 22: 159–182, 2011
C Taylor & Francis Group, LLC
Copyright ISSN: 1047-840X print / 1532-7965 online
DOI: 10.1080/1047840X.2011.551743
TARGET ARTICLE
Reintegrating the Study of Accuracy Into Social Cognition Research
Jamil Zaki
Department of Psychology, Harvard University, Cambridge, Massachusetts
Kevin Ochsner
Department of Psychology, Columbia University, New York, New York
Understanding the contents of other minds is a vital and ubiquitous task that humans perform with impressive skill. As such, it is surprising that the majority of
social cognition research—whether behavioral or neuroscientific—focuses on the
processes people use when attempting to understand each other while ignoring how
well those attempts fare. Here we review historical reasons for the contemporary
dominance of process-oriented research as well as the resurgence in the last decades
of new approaches to studying interpersonal accuracy. Although in principle both
the accuracy-oriented and process-oriented approaches study related aspects of the
same phenomena, in practice they have made strikingly little contact with each other.
We argue that integrating these approaches could expand our understanding of social
cognition, both by suggesting new ways to synthesize extant data and generate novel
predictions and lines of research, and by providing a framework for accomplishing
such an integration. This integration can be especially useful in highlighting the
deeply contextualized nature of the relationships between social cognitive processes,
accuracy, and adaptive social behavior.
Introduction
tion,” which can refer to the whole host of faculties we
bring to bear in understanding all manner of transient
and enduring characteristics of other people, mind perception zeroes in on the specific task and accomplishment of understanding others’ internal mental states.
As such, for present purposes, it provides a convenient
shorthand for referring specifically to this ability.
So how do perceivers draw inferences about targets’ minds, and why are we so adept at it? Given the
importance of these two questions, it is unsurprising
that they have been a central focus of psychological
research for the greater part of a century, and more
recently have gained a great deal of attention in neuroscience. What is surprising, however, is the lopsided
way this attention has been distributed, focusing almost
entirely on answering the first—but not the second—
of these questions. The lion’s share of contemporary
research focuses on characterizing the cognitive and
neural processes perceivers engage when encountering other minds, while typically ignoring whether
the engagement of these processes leads to accurate
One of human beings’ most impressive accomplishments is our ability to understand what other people are intending, thinking, and feeling. This requires
perceivers (individuals focusing on someone else) to
translate the observable behaviors of social targets (individuals who are the focus of perceivers’ attention)
into inferences about those targets’ physically invisible but psychologically real, internal states. Whether
we’re sniffing out the intentions of a used car salesman or figuring out the right thing to say to an upset
friend, such inferences are critical to acting adaptively
in social situations. Luckily, we are consummate experts at this task, accurately reading the internal mental
states that guide other’s behavior with an ease and skill
that would be shocking if it wasn’t so universal (Fiske,
1992; Swann, 1984).
For simplicity, we refer to this ability as mind perception, following Epley and Waytz (2009). Unlike
global terms like “social cognition” or “person percep159
ZAKI AND OCHSNER
inferences about those minds. In other words, the majority of relevant research has focused on the question
of how perceivers respond to other minds, but not how
well they understand those minds. Although relatively
neglected, this second question is of clear importance,
as the goal of everyday social cognition is not to simply draw any type of inference about targets but to use
accurate inferences to guide social behavior.
How did this state of affairs come to pass, what
are its implications for the field, and should we do
anything about it? To address these questions, the remainder of this article is divided into four main parts.
In the first, we review the central role accuracy once
played in social psychological research and the historical trends responsible for its abandonment in favor of a near monopoly of process-oriented research.
Here we also briefly review the current understanding of mind perception processes gleaned from behavioral and neuroscientific research (for more comprehensive reviews, see Decety & Jackson, 2004; Fiske
& Taylor, 2007; Gilbert, 1998; Keysers & Gazzola,
2007; Macrae & Bodenhausen, 2000; Mitchell, 2009a;
Saxe, Carey, & Kanwisher, 2004) as well as the comparatively smaller number of research programs that
have developed novel approaches to measuring interpersonal accuracy (again, for more comprehensive reviews, see Funder, 1995; Ickes, 1997; Jussim, 2005;
Kenny & Albright, 1987; Kruglanski, 1989; Swann,
1984).
The second section builds on this historical foundation by arguing that a critical missing element in
mind perception research is the integration of processoriented and accuracy-oriented approaches within
studies and research programs. The essential argument
is that social cognition should reclaim its past tradition of thinking about accuracy and combine it with
the current focus on processes. Here we motivate and
describe a framework for integrating these usually independent approaches. This framework draws equally
from neuroscientific and behavioral research to explain
social cognitive phenomena at multiple levels of analysis, including neural systems, psychological processes,
behavioral accuracy, and other outcomes such as social well-being and the social deficits that characterize
many psychiatric disorders.
The third section highlights five kinds of novel
insights and predictions that can emerge from focusing
on the relationships between mind perception processes and accuracy—as opposed to either in isolation.
First, an integrated view can help to dispel some
incorrect, but pervasive, assumptions about mind perceivers’ abilities to be accurate, or the sources thereof.
Second, integrating processes and outcomes allows
for an interactionist approach to understanding when a
given social cognitive process contributes to accuracy
about others. Third, an integrated approach enables
researchers to connect social cognitive processes with
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their ostensive goals: Skillfully navigating the social
world and maintaining positive interpersonal relationships. Fourth, this multilevel approach can offer
new insights about parallels between the mechanisms
underlying mind perception and other, seemingly
disparate cognitive domains. Fifth, this approach
offers novel ways to study the social cognitive deficits
that characterize many psychiatric illnesses.
In the fourth and last section, we conclude by
summarizing the central arguments of the article and
touching on the ways an integrative approach can
move beyond the specific examples of mind perception
considered here and be applied to the study of other
domains of social cognition and person perception,
including prospection and dispositional inference.
Where Are We and How Did We Get Here?
The Rise and Fall of Accuracy Research
In important ways, the dominance of processoriented approaches to mind perception research stems
from a revolution older (and slightly less hostile) than
Cuba’s. In the first half of the 20th century, a central project of social psychology was determining the
sources of accurate interpersonal inferences. Scores
of studies were run with the goal of characterizing socalled good judges—that is, individuals naturally adept
at understanding other minds—who could be tapped
for jobs requiring interpersonal understanding, such as
being judges or therapists. This work drew on a large,
sometimes poorly organized, slew of criteria, both for
defining and predicting accuracy. Depending on the
study, accuracy was defined as a perceiver’s ability to
recognize emotional facial expressions in photographs,
provide personality ratings of targets that agreed with
expert opinions, group consensus, or targets’ self ratings, or to predict the behavior of target individuals or
groups. Predictors of accuracy varied just as broadly
and included gender, socioeconomic status, training in
psychology, number of siblings, general intelligence,
and aesthetic sensibility. Perhaps unsurprisingly, this
proliferation of independent and dependent variables
led to an explosion of relationships being tested, and
“good judges” often eluded capture behind a tangle
of correlations and effect sizes. Nevertheless, accuracy continued to enjoy a privileged status among
research topics; in summarizing more than 50 studies of “good judges” conducted by the mid-20th century, Taft (1955) remained confident that “the practical
importance of [accuracy research] in psychology is
obvious.”
Writing a quarter century later, Schneider, Hastorf,
and Ellsworth (1979) likely would have surprised Taft
with their conclusion that, amidst the zeitgeist of social cognition research, “the accuracy issue [had] all but
THE REINTEGRATION OF ACCURACY
faded from view” (p. 222). What happened in the intervening years? Although there are many explanations,
among the most salient are the arguments presented
by Lee Cronbach and his colleagues (Cronbach, 1955;
Gage & Cronbach, 1955) that were published only a
few months after Taft’s review. Cronbach presented a
simple methodological criticism of the search for good
judges: Quantifying accuracy as a subtraction between
a perceiver’s judgment and those of a target or group
ignored a host of factors that could affect perceivers’
apparent accuracy. For example, a perceiver with an
accurate base rate for extraversion in the population
could blindly apply that base rate to judge individuals
she had never met and still appear to be a relatively
“good judge.” In other words, Cronbach asserted that
accuracy researchers were not measuring what they
thought they were measuring—accuracy—but instead
were measuring the influence of other, potentially less
interesting phenomena.
A close read of the publications by Cronbach,
Nathaniel Gage, and others suggests that they did not
intend for their criticism to upend accuracy research
altogether. Instead, they hoped that more sophisticated
methods could help clarify the sources of accuracy by
decomposing them into a number of constituent parts.
In fact, many of the factors they described as relevant to
accuracy (e.g., the use of stereotypes, assumed similarity between perceivers and targets) are quite similar to
mind perception processes studied now (see the Experience Sharing and Mental State Attribution sections).
Gage and Cronbach presciently suggested that person
perception research would be served best by modeling the relationship between these processes (which
they referred to as “intermediary keys”) and the accuracy or inaccuracy of resulting perceptions (Gage,
Leavitt, & Cronbach, 1956). However, in lieu of taking up this challenge, accuracy researchers reacted by
“crowding the exits” (Gilbert, 1998, p. 91), abandoning their endeavors almost completely for more than 25
years (Funder, 1987, 1995; Gilbert, 1998; Ickes, 1997;
Ickes et al., 2000; Kenny & Albright, 1987).
Why did accuracy researchers so eagerly jump ship?
Retellings of this historical trend converge on two
points. First, the search for good judges suffered from
a dearth of organizing principles and, as such, produced a jumble of loosely related findings, in which
some factors predicted some types of accuracy some
of the time (Dymond, 1949; Taft, 1955). Findings of
any one study in this field were often idiosyncratic and
irreproducible, and did not sum into programmatic,
generative theoretical models. Second, no matter how
organized accuracy researchers might have made their
search for good judges, those judges—at least in the
way researchers conceived of them—may have been
more myth than reality. Early accuracy research staked
much of its identity on isolating personality traits that
would predict a perceiver’s accurate inferences about
targets’ personality traits. In both cases, traits were
defined as monolithic, stable qualities that should predict behavior across contexts. A good judge was considered to be someone who would accurately assess
all social targets in all situations, and targets’ selfreported personality traits were considered to be similarly constant. In the last 40 years, however, the idea
of traits as invariant predictors of behavior has given
way to an interactionist perspective, which describes
behavior as fundamentally dependent on both individuals and the situations they encounter (Bandura, 1978;
Mischel, 1968, 1973; Mischel & Shoda, 1995). This
reconceptualization—and the fact that the majority of
accuracy research preceded it—makes it unsurprising
that the search for good judges was plagued by the
low correlations and inconsistent relationships that also
characterized many trait-based predictions of behavior.
The general challenge to personality research issued
by Mischel and others (Mischel, 1968, 1973; Mischel
& Shoda, 1995) signaled a growing shift in attention toward the processes (or cognitive and affective “units”)
mediating the relationships between individuals and
situations as input and behavior as output. A similar
shift took place in psychology more broadly (Neisser,
1967) and in due time took over the troubled field of
interpersonal perception research.
The Reign of Process
Focusing on social cognitive processes, as opposed
to accuracy, has proven extremely generative, as it allowed researchers to “zoom in” on more tractable elements of mind perception, produced replicable findings
and generated relatively simple and falsifiable theoretical claims (for fantastic reviews of the process approach and its major findings, see Chaiken & Trope,
1999; Gilbert, 1998). At its root, process research was
strongly influenced by Heider (1958), who suggested
parallels between mind perception and object perception. Gage and Cronbach alluded to these parallels as
well, arguing that mind perception and visual perception both are “dominated far more by what the Judge
brings to it than what he takes in during it” (Gage &
Cronbach, 1955, p. 420).
Following the leads of Heider, Gage, and Cronbach,
process-oriented researchers set their sights inside perceivers’ heads. Instead of concerning themselves with
the accuracy of perceivers’ inferences about targets’
reported states or observable behaviors—or even with
actual social targets in any way—process models focused on a set of cognitive “tools” perceivers bring
to bear when drawing inferences about targets in general. Although many such tools have been described
(Ames, 2004; Chaiken & Trope, 1999; E. Smith & DeCoster, 2000), here we focus on two that have gained
a great deal of attention in both psychological and
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neuroscience research: experience sharing and mental
state attribution.
Experience Sharing
President Bill Clinton famously claimed to “feel the
pain” of Americans suffering during tough economic
times. Perceivers of all stripes share the intuition that
they vicariously experience the internal states of others. This idea also is found in 18th-century moral philosophy (Smith, 1790/2002), aesthetic theory (Lipps,
1903), and contemporary models of motor cognition
(Dijksterhuis & Bargh, 2001; Prinz, 1997). The common thread uniting these theories is that when observing targets experiencing an internal state, perceivers engage many of the cognitive and somatic processes they
would engage while experiencing those states themselves (Preston & de Waal, 2002).1 A link between the
perception of others’ states and the evocation of similar states in one’s self is supported by various data, including demonstrations that perceivers often adopt the
bodily postures (Chartrand & Bargh, 1999), facial expressions (Dimberg, Thunberg, & Elmehed, 2000), autonomic arousal (Vaughan & Lanzetta, 1980), and selfreported emotional states (Neumann & Strack, 2000)
of targets.
In the last 15 years, neuroscience research has
famously supported the idea of perception-action
matching by identifying brain regions that demonstrate properties consistent with experience sharing.
The common feature of these regions is that they
become engaged both when perceivers experience
an internal state themselves and when they observe
targets experiencing those states. The specific regions
demonstrating such shared activity for both self and
other experiences depend on the type of internal
state being shared (Decety & Jackson, 2004; Zaki &
Ochsner, 2011b). For example, when both executing
and observing motor acts, perceivers engage the socalled mirror neuron system, encompassing premotor,
inferior frontal, and inferior parietal cortex (Iacoboni,
2009; Rizzolatti & Craighero, 2004; Rizzolatti &
Sinigaglia, 2010). When experiencing and observing
nonpainful touch, perceivers engage somatosensory
cortex (Keysers, Kaas, & Gazzola, 2010; Keysers
et al., 2004). When experiencing pain and observing
(or knowing that) targets (are) in pain, perceivers also
engage somatosensory cortex (Avenanti, Bueti, Galati,
& Aglioti, 2005) and additionally recruit activity in
regions related to the interoceptive and affective components of pain, including anterior insula and anterior
1 In many ways, models of perception-action matching borrow
from the more general idea of “embodied cognition,” which posits
that concepts related to physical states (including, presumably, those
of other people) are processed through sensory and motor representations (Barsalou, 2008; Decety, 1996; Kosslyn, Thompson, &
Alpert, 1997; Niedenthal, Barsalou, Ric, & Krauth-Gruber, 2005; E.
R. Smith & Collins, 2009).
162
cingulate cortex (Jackson, Meltzoff, & Decety, 2005;
Morrison, Lloyd, di Pellegrino, & Roberts, 2004;
Ochsner et al., 2008; Singer et al., 2004). The insula
also is engaged both when perceivers feel disgust and
observe it in others (Jabbi, Swart, & Keysers, 2007;
Wicker et al., 2003), consistent with this region’s role
in processing information from the viscera (Craig,
2009; Lamm & Singer, 2010). Recent data suggest
that even the hippocampus and posterior medial
frontal cortex exhibit overlapping engagement during
action observation and imitation (Mukamel, Ekstrom,
Kaplan, Iacoboni, & Fried, 2010). For simplicity,
hereafter we refer to all brain regions demonstrating
this property as experience sharing systems (ESS),
with the understanding that this is a functional definition and not one based on specific cytoarchitectonic
properties or patterns of anatomical connectivity.
The general overlap between self and other experience instantiated in the ESS has generated a great
deal of excitement, for at least two reasons. First, as
noted earlier, the ESS has been put forward as the
likely neural basis of perception-action matching. This
claim is plausible and well supported, especially given
demonstrations that overlapping neural activity in the
ESS often correlates with self-report and online measures of experience sharing (Pfeifer, Iacoboni, Mazziotta, & Dapretto, 2008; Singer et al., 2004). Second,
evidence about the neural bases of experience sharing has led to several claims that such sharing is the
primary mechanism underlying interpersonal understanding (Gallese & Goldman, 1998; Gallese, Keysers,
& Rizzolatti, 2004). This argument aligns much less
well with existing data than the first. On one hand,
it is true that shared experience provides a parsimonious, efficient way for perceivers to learn from and
learn about others’ motor intentions, affective states,
and attitudes (Dijksterhuis & Bargh, 2001; Niedenthal,
Barsalou, Winkielman, Krauth-Gruber, & Ric, 2005;
Prinz, 1997; Schippers, Gazzola, Goebel, & Keysers,
2009; Schippers, Roebroeck, Renken, Nanetti, & Keysers, 2010). On the other hand, such sharing is a much
less likely mediator of interpersonal understanding in
other situations. This is because targets’ “higher level”
intentions and beliefs often are translated only ambiguously into motor or somatic states. For example,
the identical motor program of pushing someone could
signify the very different intentions of starting a fight
or saving an inattentive commuter from an oncoming
bus (Jacob & Jeannerod, 2005).
The utility of experience sharing becomes even blurrier when one considers that nonverbal expressions of
intentions, beliefs, and emotions often fail to match
the states targets are actually experiencing. In many
cases, targets with no interest in being understood—
because they are lying to, competing with, or attempting to produce a specific impression in targets—
intentionally dissociate their nonverbal expressions
THE REINTEGRATION OF ACCURACY
from their internal states (Ansfield, 2007; Ekman,
Friesen, & O’Sullivan, 1988; Ybarra et al., 2010). The
situation improves only slightly for more forthcoming
targets: Even when earnestly expressing themselves,
these targets often produce ambiguous nonverbal cues.
This is especially prevalent in the domain of emotional
expression. Although Ekman and colleagues famously
demonstrated the ease with which posed facial expressions of canonical emotions are recognized (Ekman,
Sorenson, & Friesen, 1969), such expressions rarely
occur outside artificial contexts such as emotion studies
and tourist photos: Even while experiencing powerful
emotions, targets in naturalistic settings often produce
subtle cues that leave perceivers puzzling over what
those targets are feeling (Fernandez-Dols, Carrera, &
Russell, 2002; Russell, Bachorowski, & FernandezDols, 2003; Zaki, Bolger, & Ochsner, 2009). In such
situations (and they are common), it is unclear how perceivers’ use of experience sharing—by itself—could
guide insightful inferences about target states.
Mental State Attribution
What is a perceiver to do, given the limitations of
experience sharing? One alternative is to rely on contextually defined semantic information about targets’
likely states, which is based on what perceivers know
of the target and situation they are observing. By way of
illustration, consider encountering a friend you know,
who is grieving the recent death of a family member.
This friend displays a neutral facial expression and occasionally even smiles at you while talking about the
funeral and events since. If you were to make a judgment about his or her feelings based solely on sharing
the internal states implied by these expressions, you
may decide that your friend actually feels fine. However, it is more likely that your knowledge about your
friend’s situation will influence your judgments and
lead you to the (probably correct) hypothesis that your
friend’s outward appearance belies a more negative internal experience.
Perceivers commonly create and test such hypotheses about targets’ internal states. Although these hypotheses may be generated quickly and easily, they can
typically be represented explicitly and propositionally
within awareness as a perceiver effortfully deliberates
about a target. We refer to this form of mind perception
as mental state attribution2 to describe the process by
which perceivers tie together multiple strands of information in the service of nuanced, flexible inferences
2 This type of inference has also been described in developmental
and clinical research as, “theory of mind” or “mentalizing” (BaronCohen, Leslie, & Frith, 1985; Flavell, 1999; Leslie, Friedman, &
German, 2004; Saxe et al., 2004), whereas inferences about more
stable traits—as opposed to phasic internal states—are often grouped
under the heading “person perception.” We believe these terms refer to a highly overlapping set of computations and hence use one
unifying term to refer to all of them.
about targets’ states and dispositions (Castelli, Happe,
Frith, & Frith, 2000; Kelley, 1973; Saxe et al., 2004).
Like experience sharing, mental state attribution
also has a relatively stable neural signature, involving
multiple brain regions that support inferences about intentional states. Cognitive neuroscience research over
the last 15 years has borrowed a number of paradigms
from developmental and clinical traditions to study
mental state attribution, usually by asking perceivers
to draw inferences about the beliefs, knowledge, intentions, and emotions of others based on written vignettes, pictures, or cartoons. In a typical study, brain
activity is compared between two conditions in which
perceivers make judgments that differ only in their social or mental state content: For example, drawing inferences about the traits and states of intentional agents
(e.g., “How dependable is Tracy?” “Is Kenneth’s belief up to date?”), as opposed to inanimate objects
that nonetheless have similar characteristics (“How dependable is Tracy’s computer?” “Is Kenneth’s photograph up to date?”).
Regardless of the type of judgment being made
about others or the medium in which target cues
are presented, such comparisons produce a strikingly
consistent pattern of activation in a network that includes: Medial prefrontal cortex, temporoparietal junction, posterior cingulate cortex, and temporal poles. We
refer to this set of regions as the mental state attribution system (MSAS), again with the understanding that
this categorization is somewhat loose and functional
(for more descriptions of the MSAS and its functions,
see Baron-Cohen et al., 1999; Castelli, Frith, Happe,
& Frith, 2002; Fletcher et al., 1995; Goel, Grafman,
Sadato, & Hallett, 1995; J. P. Mitchell, Heatherton, &
Macrae, 2002; Ochsner et al., 2004; Olsson & Ochsner,
2008; Peelen, Atkinson, & Vuilleumier, 2010; Saxe &
Kanwisher, 2003). Notably, many regions within the
MSAS have been tied to humans’ more general ability
to “project” themselves into distal scenarios or points
of view (including the past, future, and uncertain or
counterfactual concepts, as well as targets’ nonobservable mental states; see Buckner, Andrews-Hanna, &
Schacter, 2008; J. P. Mitchell, 2009b; Schacter, Addis,
& Buckner, 2007; Spreng, Mar, & Kim, 2009). This
putative role for the MSAS—in lifting oneself out of
the cognitive “here and now” and simulating past and
future perspectives and states—is intriguing because it
is complementary to the assumed functional role of the
ESS in providing a basis for vicariously experiencing
the motor, sensory, and visceral states of targets. All
this being said, it is important to note that the specific
computations carried out by MSAS regions remain to
be precisely specified, and whatever they turn out to
be, they also play functional roles in behaviors not obviously related to mind perception (Corbetta, Patel, &
Shulman, 2008; Daw, Niv, & Dayan, 2005; for more on
this, see Amodio & Frith, 2006; Cavanna & Trimble,
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2006; J. P. Mitchell, 2008a, 2009a; Olsson & Ochsner,
2008; Saxe, 2006; Saxe et al., 2004; Zaki & Ochsner,
2011b).
A Tale of Two Systems
Experience sharing and mental state attribution are
functional cousins, serving the intimately related goals
of sharing and appraising targets’ internal states. As
such, one might expect them to work together often in
guiding mind perception. This makes the lack of family
resemblance in these processes—between either their
behavioral and neural correlates or the research programs that have explored them—all the more striking.
Extant data have supported a picture of these mind
perception processes as surprisingly dissociable, in at
least two ways.
First, experience sharing and mental state attribution differ in the level of effort they seem to require, as
reflected both in these processes’ developmental trajectory and in the circumstances during which they
are engaged. Developmentally, mental state attribution comes online concurrently with executive functions such as response inhibition (Carlson & Moses,
2001), and much later than behavioral signs of experience sharing (Flavell, 1999; Meltzoff & Decety, 2003;
Meltzoff & Moore, 1977; Wellman, Cross, & Watson, 2001). Mental state attribution is most common
when perceivers are given an incentive to make accurate or defensible judgments (Devine, Plant, Amodio,
Harmon-Jones, & Vance, 2002; Kunda, 1990; Tetlock
& Kim, 1987) and when they have the time and attentional firepower necessary to perform the necessary
mental state calculus (Gilbert, Pelham, & Krull, 1989;
Kruglanski & Freund, 1983). By contrast, sharing of
targets’ motor and emotional states often occurs outside of awareness (Dijksterhuis & Bargh, 2001; Neumann & Strack, 2000), and regions within the ESS—
but not the MSAS—are engaged even when perceivers’
attention to social targets is limited (Chong, Williams,
Cunnington, & Mattingley, 2008; Spunt & Lieberman,
2011).
Second, as readers may have noticed, the brain regions making up the ESS and the MSAS are almost
completely nonoverlapping. This dissociation holds up
under meta-analytic scrutiny: Studies engaging one
system rarely engage the other concurrently (Gobbini, Koralek, Bryan, Montgomery, & Haxby, 2007;
van Overwalle & Baetens, 2009). Even more strikingly, the situations and task parameters that engage
the MSAS often dampen activity in the ESS, and vice
versa, leading to suggestions that these neural systems
sometimes “compete” with each other for the guidance of behavior. For example, Brass, Ruby, and Spengler (2009) demonstrated that when participants were
asked to refrain from imitating targets’ movements,
164
they demonstrated reduced engagement in the ESS and
concurrently engaged areas within the MSAS. In another study, we (Zaki, Hennigan, Weber, & Ochsner,
2010) presented participants with nonverbal emotional
expressions of targets combined with sentences describing the situational contexts to which targets were
putatively reacting. In some cases, these two types
of information suggested incongruent affective states
(e.g., a happy-looking target paired with a contextual
sentence stating that the target’s dog just died). Perceivers then were asked to judge how they believed
targets felt. As perceivers relied more on target nonverbal behavior when making judgments, they increased
engagement of their ESS and dampened engagement of
the MSAS; the opposite pattern emerged as perceivers
relied more on contextual cues.
The impressive dissociations between the cognitive and neural signatures of experience sharing and
mental state attribution have sometimes motivated an
“either/or” approach to mind perception, in which researchers focus on one process while ignoring—or dismissing the importance of—the other. As we see next,
this view proves an ill fit for existing and emerging data
(Apperly, 2008; J. P. Mitchell, 2005), and reintegrating
accuracy into the study of mind perception provides
a way to move past such assumptions in favor of potentially richer questions about how mind perception
operates.
Accuracy Returns
As just described, a process-oriented approach to
mind perception has been both generative—in its ability to produce robust, replicable findings and relatively
lean theoretical accounts of processes—and potentially
limiting—in its tendency to isolate the study of single processes and ignore (or remain agnostic about)
their relationship to behavioral outcomes such as accuracy. If process- and accuracy-related research programs are to make mutually beneficial contact, however, the question naturally arises as to what has
become of accuracy research while the processoriented approach has dominated research on mind perception, and on social cognition more broadly. After
suffering a 25-year dry spell following the critiques
of Cronbach and others, interpersonal accuracy research has regrouped and grown steadily over recent
decades. Existing reviews provide excellent and detailed descriptions of current approaches to accuracy
research (Funder, 1995; Ickes, 1997; Jussim, 2005;
Kenny & Albright, 1987; Swann, 1984). As such,
we describe only four of these very briefly, with the
goal of laying out the basics of the most common
approaches so that in later sections we can explore
their integration with process-oriented work. The first
three of these accuracy types (pragmatic, realistic, and
THE REINTEGRATION OF ACCURACY
componential) focus inferences about dispositions,
whereas the fourth (empathic) directly addresses mind
perception.
Pragmatic Accuracy
One approach to accuracy has overcome problems
in measurement and validity by circumventing them
entirely. Instead of attempting to establish a criterion representing the “true” state or trait of targets
and measuring interpersonal accuracy as the ability
of perceivers’ inferences to approach that truth, the
pragmatic approach focuses on the utility of social
inferences for negotiating social relationships (Fiske,
1992, 1993; Jussim, 1991; E. R. Smith & Collins, 2009;
Swann, 1984). Following Mischel’s interactionist approach to personality, if targets’ behavior varies stably
across situations, then a perceiver’s accuracy for a target need not (and potentially cannot) encompass all
of that target’s behavior. Rather, perceivers need only
predict behavior relevant to domains in which they interact with a target (e.g., to successfully interact with
John, his students need to accurately assess how hard
a grader he is but not how much he loves banjo music). There is evidence that perceivers do achieve such
“circumscribed accuracy” (Swann, 1984) and that they
constrain their predictions about targets to situations
relevant to their basis for judgment (Idson & Mischel,
2001; Noordewier & Stapel, 2009).
focus on the mix of sources that influence interpersonal
judgments.
Empathic Accuracy
Pragmatic, realistic, and componential approaches
to accuracy all share a focus on perceivers’ ability
to gauge targets’ stable dispositions, but often, perceivers are more concerned with a target’s transient
states (How does Frank feel right now? Is Jenna
flirting with me?). Work on empathic accuracy examines interpersonal consensus about such states using paradigms in which perceivers’ rating of targets’
thoughts and feelings are compared with targets’ reports on their own states (Ickes, 1997; Ickes, Stinson, Bissonnette, & Garcia, 1990; Levenson & Ruef,
1992). Such paradigms have been used to examine the
situational and individual-difference predictors of accuracy for emotions (Klein & Hodges, 2001; Pickett,
Gardner, & Knowles, 2004; Simpson, Ickes, & Blackstone, 1995; Simpson, Orina, & Ickes, 2003; Stinson &
Ickes, 1992). Similar approaches in nonverbal behavior
also have examined the types of emotional cues (e.g.,
visual, prosodic) that predict accuracy, and in which
circumstances they do so (Costanzo & Archer, 1989;
Hall & Schmid Mast, 2007; Nowicki & Duke, 1994;
Rosenthal, Hall, DiMatteo, Rogers, & Archer, 1979;
Russell et al., 2003).
Where Do We Go From Here? Integrating
Process and Accuracy
Realistic Accuracy
In contrast to pragmatic accuracy, the realistic accuracy approach takes as a starting point the idea that
targets’ dispositions (e.g., a target’s level of extraversion) are real: that is, they exist independently of target
and perceiver opinions. Thus, accuracy can be studied
using methods used for construct validation by first
identifying traits that are consensually perceived by
others, predictive of behavior, and stable across time,
and then examining how accurate perceivers are in perceiving such traits (Funder, 1995).
Componential Accuracy
Componential accuracy is embodied by Kenny and
colleagues’ work (Kenny & Albright, 1987; Malloy &
Kenny, 2006), which statistically disentangles multiple
potential sources of interpersonal consensus in a manner similar to that suggested by Cronbach’s original
critiques. Especially interesting for current purposes,
component models provide behavioral cues about the
processes that perceivers employ in drawing inferences
about targets (e.g., projection or stereotyping). Unlike
the realistic approach, however, component models remain agnostic about targets’ “real” traits and instead
The process- and accuracy-oriented approaches described here ostensibly study two sides of the same
social cognitive coin: How people go about attempting
to understand each other and how well their attempts
fare. As such, the relative lack of crosstalk between
these approaches is at least somewhat surprising. In
some cases, this disconnect may stem from perceptions that processes and accuracy are orthogonal and
do not impact each other in lawful ways. If this were
true, it would be unclear how single studies or research
programs could meaningfully tie these phenomena together. In other cases, researchers may believe that
processes and accuracy are related but that the structure of these relationships is obvious (e.g., the more
a perceiver applies a given process, the more accurate their inferences will be), and therefore the explicit
study of their connection offers little new insight about
mind perception. If this were true, it would be unclear why examining process–accuracy relationships is
a meaningful endeavor. In this section we address the
first of these issues (how processes and outcomes can
be brought together). In the third section we address
the second (why bringing these phenomena together is
important to the future of mind perception research).
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A Framework for Integration
A Social Cognitive Neuroscience Approach
In building a framework for integrating research on
process and accuracy, it should be highlighted that we
adopt a social cognitive neuroscience (SCN) approach
(Lieberman, 2007; J. P. Mitchell, 2006; Ochsner, 2007;
Ochsner & Lieberman, 2001) that combines the theory
and methods of cognitive neuroscience and social psychology. Two key ideas are embodied by this approach.
The first idea is that behavior can be explained usefully
at multiple levels of analysis, including (a) the social
level describing behaviors and experience in their interpersonal context, (b) the cognitive level specifying
underlying information processing mechanisms, and
(c) the neural level specifying the neural systems that
implement these processes. Whereas social psychology traditionally has been concerned primarily with
the first two of these levels, and cognitive neuroscience
primarily concerned with the latter two, SCN (or social
neuroscience more broadly; see Cacioppo & Bernston,
1992) seeks to connect all three.
The second idea concerns the way in which we draw
inferences about the relationships between these levels. In any given experiment we can manipulate and/or
measure variables at the social (e.g., accurate vs. inaccurate inference) and neural (e.g., activity in specific
brain systems) levels. By contrast, cognitive processes
such as experience sharing and mental state attribution
cannot be directly measured; their operation must be
inferred from patterns we observe in social- and neurallevel variables. For this reason, the SCN approach emphasizes the use of converging evidence from the social and neural levels to triangulate on psychological
processes. This can provide greater leverage for testing
psychological theories than approaches that emphasize
only the social and cognitive, or cognitive and neural
levels, respectively.
Applying SCN to Process-Accuracy Relationships
The SCN approach can be used to build a framework that uses behavioral (including self-report) and
neuroscientific measures to draw inferences about how
interpersonal accuracy is related to the underlying processes of experience sharing and mental state attribution. Although no one technique taken alone is sufficient to document the presence of a given cognitive
process—or its effect on accuracy—the hope is that
combining data from varying levels of analysis will
afford us more traction in examining mind perception
in a way that speaks to multiple domains of research.
Figure 1 illustrates this framework, using experience sharing as an example process. Cognitive/processlevel phenomena—for example, a perceiver’s deployment of experience sharing—are impossible to
observe directly. Even defining them requires wading
into murky phenomenological terrain (e.g., “How can
we really know what emotion a target is experiencing?”). However, each of these phenomena involves
multiple measurable variables at the social/behavioral
and neural levels. By way of comparison, consider that
the study of affective experience (the leftmost phenomenon in Figure 1) has been well served by seeking out converging evidence from self-report, neural
activity, and other domains (Barrett, 2009; Barrett,
Mesquita, Ochsner, & Gross, 2007; Kober et al., 2008;
Lindquist & Barrett, 2008). Similarly, we believe that
the operation of mind perception processes and their
effect on accuracy can be inferred best from the many
measurable signs that these cognitive-level phenomena
leave in their wake. These include activity in relevant
neural systems, convergence between targets’ and perceivers’ reports of their own affect (a social/behavioral
level sign of experience sharing), convergence between
targets’ and perceivers’ reports on targets’ affect (a social/behavioral level sign of interpersonal accuracy),
and correlations between target and perceiver neural or
physiological activity over time (Marci & Orr, 2006;
Schippers et al., 2009; Stephens, Silbert, & Hasson,
2010; Vaughan & Lanzetta, 1980). It is important to
note that connections between phenomena can also be
effectively interrogated by sampling evidence at multiple levels of observation. For example, a strong case for
Figure 1. A framework for combining neural and behavioral observations to gain traction on how and when mind
perception processes produce accurate inferences. Note. ESS = experience sharing systems.
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THE REINTEGRATION OF ACCURACY
the idea that experience sharing contributes to interpersonal accuracy can be made by marshalling evidence
that these phenomena are related at behavioral, experiential, and neural levels (Cacioppo & Bernston, 1992;
Ochsner & Lieberman, 2001).
Modeling Context Dependency
As Lieberman (2005) pointed out, if a social psychologist was stranded on a desert island and given the
choice of one idea to bring with her, a likely candidate would be “the power of the situation.” The SCN
approach expands this “situationalist” focus to neuroscience research as well. Does Jack’s high score on a
conscientiousness scale mean he won’t be found playing air guitar while standing precariously on a barstool
this weekend? Will viewing a surprised face engage
participants’ amygdala or not? The likely answer to
these (and myriad other questions) is, It depends on
the contexts in which behaviors and brain activity are
embedded. Our own work and our examination of others’ work suggest that process-outcome relationships
in mind perception are no exception to this trend. That
is, asking whether experience sharing or mental state
attribution (or any other mind perception process) produces accuracy is a conceptual nonstarter. Instead, researchers should focus on when these processes produce accuracy. This requires “zooming out” from a
focus on processes or accuracy in isolation, to achieve
a broader focus on contextual factors that determine
their connection to each other.
Figure 2 displays such a broad view of accuracy,
with an emphasis on the many moving parts that determine the course of a mind perception episode. In this
model, both the cues produced by a target and those
received by a perceiver constrain (a) the likelihood that
a perceiver will engage a given mind perception pro-
cess, and (b) the effect that process can be expected
to have on accuracy. Zooming out also makes clear
that neither cognitive processes nor accuracy are mind
perception’s endgame. Both of these phenomena serve
the more “downstream” goal of supporting adaptive
social behavior and fostering positive social ties. Researchers often labor under the assumption that mind
perception processes and interpersonal accuracy allow
perceivers to “navigate,” “maneuver,” or otherwise locomote adeptly through their social world. However,
there are likely cases in which a given process, or even
accuracy, are not social interaction’s power steering.
Processes and accuracy sometimes have no effect on
social well-being, and can even reduce perceivers’ ability to connect fruitfully with others. Our approach emphasizes the need to model situational factors that determine when a process (or accuracy) helps—and when
it harms—perceivers’ social interactions.
Thus, central to this model is a focus on two ways
in which the relationship between cognitive processes
and later outcomes are mediated by other factors. First,
there is an emphasis on understanding the situational
factors that determine whether a given process will produce accurate inferences. Second, there is an emphasis
on understanding how accuracy itself can serve as a
mediator between the use of a mind perception process
and adaptive social outcomes.
It is worth noting that connections between mind
perception phenomena are bidirectional and that the
left–right direction in Figure 2 is not a timeline demarcating sequentially completed steps. Perceivers do
not encounter targets, deploy a mind perception process, draw an (in)accurate inference, produce a socially (mal)adaptive behavior, and call it a day. Instead, social interactions are dynamic and dense with
feedback loops (Freeman & Ambady, 2011; Kunda
& Thagard, 1996). For example, learning that she is
Figure 2. An illustration of some of the many contextual factors constraining the relationship between mind perception phenomena.
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mistaken or has behaved inappropriately, a perceiver
may alter the way she engages during subsequent
interactions with a target. Perceivers can shift their
mind perception in multiple ways, including changing the content that they focus on when employing
mental state attribution (such as the level at which
they construe a target’s behavior; see Spunt, Satpute,
& Lieberman, 2010; Vallacher & Wegner, 1987), or
altogether changing the process they employ in perceiving that target (e.g., “turning up” one’s shared experience through perspective taking; see Batson, 1991;
Lamm, Batson, & Decety, 2007). These adaptations
can, in turn, serve perceivers’ goals of better understanding targets (Eyal & Epley, 2010). Such feedback
processes are not limited to perceivers’ information
processing; targets also may change the social cues
they produce to clarify their internal states after learning that a perceiver has misjudged them (Swann & Ely,
1984; Swann, Hixon, Stein-Seroussi, & Gilbert, 1990),
or (even more interesting) may change their self-view
to match a perceiver’s initially erroneous judgment of
them (Turner, 1991). The role of such feedback loops
in mind perception is an emerging topic of enormous
interest. However, because relatively little is known
about how such feedback works—and to constrain
the scope of this article—we focus predominantly on
“left to right” relationships between the phenomena in
Figure 2.
What Does This Buy Us? The (Basic and
Applied) Fruits of Integration
Thus far, we have outlined a framework for integrating processes and accuracy in the study of mind
perception. We now broaden our focus to suggest ways
in which this integrative approach can foster novel insights and influence the way observations are made
in behavioral, neuroscientific, and clinical mind perception research. We describe separately the potential
advances that could be made for our understanding
of mind perception in each of these domains, but we
emphasize at the outset that a major advantage of integrating the study of processes and accuracy emerges
specifically from bridging data gleaned from different
approaches (e.g., neural and clinical) that too often are
isolated from each other.
Specifically, we discuss five advantages an integration of process and accuracy have over the study of either in isolation: (a) overturning incorrect but pervasive
assumptions about mind perception, (b) delineating the
situation-specific relationships between processes and
accuracy, (c) tying data about information processing
more directly to evidence about social well-being, (d)
drawing parallels between mind perception and other
domains of cognition, and (e) mapping the domains
168
in which social cognitive abnormalities in psychiatric
disorders lead to functional impairments.
As previously mentioned, the majority of examples we discuss focus on mind perception accuracy for
transient affective states (i.e., empathic accuracy) and
not on inferences about other aspects of individuals,
such as their stable dispositions. Beyond the pragmatic
limitations of space, this narrowing of scope is motivated by two principled factors. First, empathic accuracy paradigms enjoy some psychometric strengths
that obviate some of the early concerns leveled against
accuracy research more generally. Historically, accuracy has been calculated as the simple difference between a perceiver’s rating of a target state or trait
relative to some criterion measure (e.g., the target’s
self-report). This approach is intended to index accuracy about the overall level of some attribute, has
been common to many forms of accuracy research,
and has been roundly criticized as statistically problematic (see earlier and see Cronbach, 1955; Kenny,
1991). By contrast, contemporary empathic accuracy
paradigms record perceivers’ inferences, as well as targets’ self-report, at multiple timepoints. This allows
researchers to compute a measure of accuracy for the
time-varying dynamics of a target’s state, not just the
overall average level of that state. For example, one
can calculate the correlation between a perceiver’s inferences about a target’s affect and a target’s self-rating
as they both vary across time. The resulting correlations reflect target–perceiver agreement about when a
target felt relatively negative. It is important to note that
such correlations are independent of the overall level
of some state that perceivers infer that targets are experiencing and that targets assign to themselves. As such,
dynamic measures are robust to many of the biases—
including stereotype application, assumed similarity,
or scale usage tendencies—that can inflate empathic
accuracy measures defined as the difference between
two global assessments.
Second, for reasons explained above (see Where
Do We Go From Here?), we are especially interested
in connecting measures of cognitive processes such as
shared experience and mental state attribution to measures/correlates of interpersonal accuracy at the behavioral and neuroscientific levels. Because almost all neuroscience research on process use concerns the sharing
and inferring of transient states (beliefs, emotions, intentions), and not static traits, empathic accuracy is a
natural candidate for exploring process-accuracy relationships across multiple levels of analysis. This does
not mean that this measure of accuracy is the only one
that can be used to examine the connections we describe next. In fact, it is our hope that future researchers
will be motivated to explore similar connections—
at both the neural and behavioral levels—between
mind perception processes and other forms of
accuracy.
THE REINTEGRATION OF ACCURACY
Contributions to Behavioral Approaches
Perceivers’ Mind Perception Abilities: Half Full or
Half Empty?
Imagine an extraterrestrial preparing to make first
contact with Earth. In advance of meeting humans,
she decides to do research on our behavior, taps into
PsycINFO, and reads all the work she can find on
mind perception. She is disappointed to learn that people are, by and large, inept at understanding each other:
They ascribe traits to each other based on demonstrably nondiagnostic behaviors (Gilbert & Malone, 1995;
Jones & Harris, 1967); erroneously impute their knowledge, beliefs, and preferences onto others (Epley et al.,
2004; Gilovich, Medvec, & Savitsky, 2000; Gilovich,
Savitsky, & Medvec, 1998; Ross, Greene, & House,
1977); and carelessly apply stereotypes (Fiske, 1998).
They can correct these mistakes, but only through
slow, labor-intensive application of rules, and in the
absence of such efforts, they “default” to error and
bias (Devine, 1989; Devine et al., 2002; Gilbert, Pinel,
Wilson, Blumberg, & Wheatley, 1989).
Why has existing research equipped our interplanetary traveler with such underwhelming expectations?
Because accuracy is hard to define, and the faults
and foibles of mind perception have proved comparatively easier to uncover and eye-catching to boot, the
process-oriented approach tends toward a potentially
disheartening view of mind perceivers as “faulty computers,” running mind perception software that is often situation inappropriate (Higgins & Bargh, 1987;
Krueger & Funder, 2004). This outlook gains further
momentum from its contact with a historically popular
view of decision making, which suggests that people—
instead of optimizing their decisions based on all the
information available to them—rely on simple judgmental heuristics that lead them toward a host of incorrect decisions about the outside world (Kahneman
& Tversky, 1996; Tversky & Kahneman, 1974), the
sources of their own behaviors and abilities (Nisbett
& Wilson, 1977), and even the nature of those behaviors and abilities (Kruger, 1999; Kruger & Dunning,
1999).3
Is such a pessimistic attitude about mind perception warranted? Granted, perceivers can be induced
into committing lawful, compelling errors when judging targets’ states and traits. However, studies of these
effects often use statistically perfect judgments as a
criterion against which to define social cognitive error
(e.g., completely discounting nondiagnostic information when making preference judgments, see Jones &
Harris, 1967). Further, studies of social cognitive error typically use highly superficial and nonnaturalistic
tasks that—in a manner analogous to visual illusions—
3 Nonetheless, heuristics offer efficient decisions that are often as
accurate—and sometimes more accurate—than exhaustive problemsolving strategies (Gigerenzer, 1999; Rieskamp & Otto, 2006).
are designed to create the errors they document
(Funder, 1987) and may overlook the ways these errors
actually reflect generally adaptive processing. These
factors result in a “half-empty glass” view of perceivers
who are seen in light of their errors and not their accomplishments (Krueger & Funder, 2004).
Traditionally, accuracy research has taken a much
different tack: Comparing judgments made in more
naturalistic settings (i.e., judgments made about actual social targets on the basis of complex behavior)
to targets’ own self-perceptions. Further, accuracy in
these studies is typically measured against a baseline
of chance, as opposed to an assumption of perfect (and
often perfectly rational) performance. This approach
produces a more optimistic view of mind perceivers,
who are shown to excel in a number of ways. First,
perceivers largely agree with each other and establish
impressive consensus about the states and traits of social targets, even when they have access only to “thin
slices” of target behavior (Ambady & Rosenthal, 1992,
1993; but see also Ames, Kammrath, Suppes, & Bolger,
2010), or impoverished target cues (North, Todorov, &
Osherson, 2010; Zaki, Bolger, et al., 2009). Second,
perceivers’ inferences are impressive predictors of target behavior (Funder, 1991; Moskowitz & Schwarz,
1982), even decades after perceivers’ from their initial impressions (Nave, Sherman, Funder, Hampson,
& Goldberg, 2010). Third, perceivers achieve consensus with targets themselves (Ickes, 1997; Kenny &
Albright, 1987; Levenson & Ruef, 1992; Zaki, Bolger,
& Ochsner, 2008). Finally, emerging evidence suggests
that, at least in certain situations, perceivers have a
well-calibrated understanding of when they are likely
to be accurate, versus inaccurate, about target states
(Kelly & Metcalfe, in press).
An integration of processes and accuracy can combine the strengths of each of these approaches in balancing views about perceivers’ skills in understanding
targets. Specifically, not only can we document that
perceivers fare pretty well in their endeavors (the conclusion of extant accuracy research) or that a given
process sometimes fails them (the conclusion of extant
process research), but we can more specifically chart
the landscape of process-accuracy relationships to describe when a given process supports accuracy. We turn
to this issue now.
Processes’ Situation-Specific Utility
When humans are equipped with more than one tool
for completing a single task, a few questions naturally
arise. One could ask which tool is better for completing
that task (e.g., “Should I use the hammer or screwdriver
for hanging this painting?”). However, a deeper question may be, Why would nature equip us with more
than one tool for a single task? The answer is often
that what appears to be a single task (e.g., hanging a
painting), upon closer inspection, ends up splintering
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into multiple, independent tasks each suited to different tools (e.g., hanging frames held up by screws vs.
nails).
Perceivers’ repertoire of mind perception processes
suggests just such a state of affairs: Shared experience,
mental state attribution, and other processes likely exist in tandem because they each support accurate interpersonal understanding under differing circumstances.
This perspective can clear up confusion in the extant
literature on the process-accuracy relationship.
Consider the age-old search for the “good perceiver.” Popular intuition has long held that some
individuals—specifically, those who tend to share others’ experiences— also should be adept at understanding those experiences (Allport & Allport, 1921). However, attempts to relate accuracy and experience sharing
have fared surprisingly poorly (Hall, 1979; Ickes et al.,
1990; Levenson & Ruef, 1992), leading modern accuracy research to largely abandon the search for “good
perceivers” (Ickes et al., 2000). The model described
in the Modeling Context Dependency section suggests
a way out of this counterintuitive null finding: Lawful
features of social situations may determine when experience sharing will come in handy to mind perceivers.
Following this logic, we recently tested the idea
that a critical feature of a perceiver’s situation is the
type of target they encounter. Our premise was that
mind perception, as a fundamentally interpersonal process, should depend both on a perceiver’s tendencies
to deploy specific kinds of processes—such as experience sharing—and features of targets that influence
how easily they can be perceived—such as their trait
levels of emotional expressivity (Gross & John, 1997;
Zaki, Bolger, et al., 2009). Specifically, we predicted
that perceivers high on the tendency to use experience
sharing would be more accurate in judging the emotions of a target to the extent that the target sends strong
expressive signals to their internal emotional state that
the perceivers could share. In line with this prediction,
we found that perceivers’ trait-level experience sharing
predicted accuracy as a function of a target’s tendency
to be emotionally expressive (Zaki et al., 2008). Findings like this both flesh out situation-specific utility
of mind perception processes and highlight the importance of moving beyond the “perceiver-centric” view
that has dominated process-oriented research for half
a century.
Linking Processes to Social Well-Being and
Dysfunction
Whereas the proximal goal of mind perception processes is forming an accurate impression of targets,
the ultimate goal of such processes is to allow perceivers to function adaptively in the social world, by
forming and maintaining social bonds with others.
Positive social relationships are a central human need
(Baumeister & Leary, 1995) that provides both psycho170
logical and physical protection against environmental
stressors (Bolger & Eckenrode, 1991; Cohen, Doyle,
Skoner, Rabin, & Gwaltney, 1997; Hawkley, Burleson,
Berntson, & Cacioppo, 2003). Indeed, discussions of
mind perception often begin with the idea that processes such as experience sharing and mental state attribution are important because those processes support
adaptive social behavior.
But do they? Perhaps only sometimes. On one hand,
individual differences in experience sharing sometimes
are associated with adaptive social behaviors, such
as cooperation, altruism (Eisenberg & Miller, 1987;
Johnson, 1975), or some measures of social skills (Bailey, Henry, & Von Hippel, 2008; Pfeifer et al., 2008;
Riggio, Tucker, & Coffaro, 1989), and individual differences in the tendency to employ mental state attribution may track with accommodating behavior during conflict in close relationships (Arriaga & Rusbult,
1998; Long & Andrews, 1990). On the other hand,
some studies have found no relationship between these
processes and social skills, adjustment, or integration
(Cliffordson, 2002; McWirther, Besett-Alesch, Horibata, & Gat, 2002).
The integrative approach we advocate suggests a
novel prediction: Accuracy may serve as a “middleman” mediating the relationship between deployment
of a process and its ultimate adaptive goal of promoting
social well-being. Support for this comes from the finding that interpersonal accuracy (especially concerning
transient states such as thoughts and emotions) predicts adaptive relationship behavior, such as skillful
social support (Verhofstadt, Buysse, Ickes, Davis, &
Devoldre, 2008); lower relationship abuse (Clements,
Holtzworth-Munroe, Schweinle, & Ickes, 2007); and
social adjustment in adolescents (Edwards, Manstead,
& MacDonald, 1984; Gleason, Jensen-Campbell, &
Ickes, 2009; Spence, 1987), college students (Carton,
Kessler, & Pape, 1999; Zaki & Ochsner, 2011a), and
adults (Bartz et al., 2010).
Of course, the idea that accuracy supports adaptive
social function is nothing new (for a review of nearly
100 studies on this topic, see Hall, Andrzejewski, &
Yopchick, 2009) and was, in fact, part of the impetus for the original accuracy movement described earlier. Today, well-known theories incorporate decoding
of others’ states into larger constructs, such as emotional intelligence (Lopes, Grewal, Kadis, Gall, & Salovey, 2006; Mayer, DiPaolo, & Salovey, 1990; Mayer,
Salovey, & Caruso, 2008; Mayer, Salovey, Caruso,
& Sitarenios, 2001) or affective social competence
(Halberstadt, Denham, & Dunsmore, 2001). However,
these frameworks often view accuracy as a precursor, or “lower level, fundamental skill” (Mayer et al.,
2008, p. 506) that combines with other skills such as
affect management and communication ability to produce a higher level set of abilities that support social
function.
THE REINTEGRATION OF ACCURACY
In contrast, mind perception researchers view accuracy itself as a complex outcome dependent on a suite
of flexibly deployed cognitive processes. As such, research tying health and well-being to accuracy often
makes little contact with work on the cognitive processes that produce accuracy. This is unfortunate, given
that social cognitive work has begun to suggest that
empathic accuracy does not always promote adaptive
behavior. In fact, in some cases accuracy can be maladaptive, as when perceivers correctly intuit a target’s
negative or relationship-damaging thoughts and feelings (Simpson et al., 1995; Simpson et al., 2003) or
when accuracy prevents the application of (presumably adaptive) positive biases in self-perception that
are characteristic of most individuals (Taylor & Brown,
1988).
Integrating processes and outcomes suggests ways
to address these seemingly conflicting relationships between mind perception processes, accuracy, and adaptive social behavior by reframing the questions we ask.
Instead of asking whether a given mind perception process promotes adaptive behavior, we might ask when
its use is adaptive by virtue of producing accurate inferences, and when does that process motivate adaptive
behaviors irrespective of (or even by reducing) accuracy?
Following a social cognitive neuroscience approach, both behavioral and neural correlates of mind
perception processes and accuracy can be brought to
bear in answering such questions, and testing models
in which accuracy mediates the relationship between
mind perception processes and social function. The use
of brain activity to predict outcomes in the field is only
now taking hold (cf. the “brain as predictor” model employed by Berkman, Falk, & Lieberman, 2011; Falk,
Berkman, Mann, Harrison, & Lieberman, 2010) and
stands to make headway in linking information processing to adaptive behavior in the social domain.
Contributions to Neuroscientific Approaches
Fleshing Out Single-Process Models
Dissociations between the neural systems supporting experience sharing and mental state attribution
have prompted a curious debate among neuroscientists about which system is primarily responsible for
mind perceivers’ abilities (Apperly, 2008). Some, following so-called simulation theory (Heal, 1996), have
cited the role of the ESS as evidence that shared experience is the royal road to interpersonal understanding
(e.g., Gallese & Goldman, 1998; Gallese et al., 2004).
Others, following the tongue-twistingly named “theory
theory” (Gopnik & Wellman, 1992), argue that mental
state attribution, supported by the MSAS, is central to
understanding targets (e.g., Saxe, 2005).
We believed such theories lack two features critical
to forming a more complete theory of mind percep-
tion’s neural bases. First, in focusing on single neural
systems, it is easy to forget that processing the complex
social cues perceivers most often encounter in daily life
typically draws on both the MSAS and ESS (among
other regions). Second, MSAS and ESS-based theories
of interpersonal understanding have proceeded largely
in the absence of direct evidence about whether either
neural system supports accuracy about actual social
targets. This is because tasks engaging the ESS rarely
require perceivers to infer targets’ internal states, and
tasks tapping the MSAS typically employ extremely
easy, simplified social tasks that produce ceiling effects. In each case, the ability to directly measure the
neural systems supporting accurate, as opposed to inaccurate, social inferences is limited at best (Zaki &
Ochsner, 2009). We now discuss each of these weaknesses in the literature—and how we believe they can
be overcome—in turn.
Moving from single to multiple-process models.
In our view, nominating single processes or neural systems as supporting interpersonal understanding likely
reflects a lack of contact between cognitive neuroscientific and behavioral approaches to mind perception.
A major aim of cognitive neuroscience is using brain
activity as a guide for interpreting multiple cognitive
processes as either distinct (based on separable neural
circuitry) or functionally related (based on overlapping
neural circuitry; see Henson, 2005). This approach has
helped to resolve a number debates about cognition, for
example, providing evidence that visual imagery and
visual perception are highly similar (Kosslyn et al.,
1997), or that declarative and procedural memory are
not (Buckner et al., 1995; Schacter, 1997).
However, such an approach also encourages researchers to emphasize single patches of neural real
estate and to focus on tasks that excite their particular
neural neighborhood. For example, a researcher examining the role of the ESS may be more interested in
tasks tapping the ESS, such as perceivers’ sharing of
targets motor intentions, disgust, or pain, and may pay
less attention to false belief tasks that do not engage the
ESS. Similarly, such a researcher may pay more attention to data demonstrating that damage to the ESS impairs emotion perception (Adolphs, Damasio, Tranel,
Cooper, & Damasio, 2000; Shamay-Tsoory, Tomer,
Berger, Goldsher, & Aharon-Peretz, 2005) than to similar lesion data suggesting that the MSAS is necessary
for making judgments about many forms of beliefs and
intentions (Shamay-Tsoory, Aharon-Peretz, & Perry,
2009).
Nonetheless, the fact that neural systems can be
dissociated does not imply that they are necessarily
or even usually dissociated during social inferences,
especially those based on the kinds of complex social
information that we encounter in everyday situations
(Keysers & Gazzola, 2007; Shamay-Tsoory, 2010;
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ZAKI AND OCHSNER
Singer, 2006; Uddin, Iacoboni, Lange, & Keenan,
2007; Zaki & Ochsner, 2009). Consistent with this,
both the ESS and MSAS are concurrently engaged by
“naturalistic” mind perception tasks, such as viewing
videos of complex social cues (Brass, Schmitt, Spengler, & Gergely, 2007; de Lange, Spronk, Willems,
Toni, & Bekkering, 2008; Spunt et al., 2010; Wolf,
Dziobek, & Heekeren, 2010).
The second weakness in the cognitive neuroscience
literature on mind perception is the absence of direct
data on the neural sources of accuracy, which renders
any claim about the neural bases of interpersonal understanding more speculative than is typically recognized. In some ways, this is similar to the state of memory research in the mid-1990s. At that time, a few key
brain regions had been linked to memory performance
through lesion studies, and in the first wave of neuroimaging studies of memory these same regions were
engaged during encoding tasks. The extent to which
any given region was critical for successful encoding
was not yet known, however, because the issue had yet
to be assessed directly. This changed with the advent
of the subsequent memory paradigm, in which brain
activity during a given encoding trial was related to
veridical recollection of a memorandum on a later test.
This approach confirmed that activity in the medial
temporal lobe and inferior frontal gyrus was related
to later performance, cemented their functional importance to memory formation, and provided a critical
methodological tool for probing the neural correlates
of memory more generally (Brewer, Zhao, Desmond,
Glover, & Gabrieli, 1998; Wagner et al., 1998).
We believe that integrating a focus on accuracy into
neuroimaging studies of mind perception can play a
similar role, by providing novel, direct evidence about
the role of the ESS and MSAS in producing interpersonal accuracy. To take a step in that direction, we
identified brain regions the activity of which increased
as perceivers became more accurate about the emotions
expressed by targets shown on videotapes talking about
autobiographical emotional experiences. This analysis
revealed that activity in several regions within both the
MSAS and ESS (especially the putative mirror neuron
system engaged by observing and performing actions;
see Zaki, Weber, Bolger, & Ochsner, 2009) predicted
accuracy. Dovetailing with this initial finding, a subsequent study demonstrated that functional coupling
between target brain activity and perceiver brain activity in both ESS and MSAS predicts perceivers’ comprehension of stories told by targets (Stephens et al.,
2010).
This type of data is critical in that it can help move
past the prevalent yet ultimately unproductive debate
as to whether interpersonal understanding is supported
by the MSAS or ESS, by demonstrating that both
systems—and, it stands to reason, their related cognitive processes—support accuracy.
172
The suggestion here is that future work could move
toward asking more nuanced questions about when a
given system is most important to fostering accuracy.
Again, consider memory research, where the neural
bases of successful encoding have been shown to differ
critically depending on the type of information being
encoded (e.g., social vs. nonsocial; see Macrae, Moran,
Heatherton, Banfield, & Kelley, 2004; J. P. Mitchell,
Macrae, & Banaji, 2004). In like fashion, the MSAS
and ESS may turn out to be variably useful in producing accurate inferences, depending on types of social
cues perceivers encounter and the inferences they are
asked to make. Specifically—although direct evidence
is still lacking—extant data suggest that the MSAS
may support accurate inferences about complex, contextualized internal states (i.e., those that require understanding the source of a belief or emotion), whereas
the ESS may support accuracy about states with more
prominent bodily components, such as disgust or pain
(Keysers & Gazzola, 2009; Lamm & Singer, 2010;
Saarela et al., 2007; Zaki, Davis, & Ochsner, 2011;
Zaki et al., 2010). Future work should investigate such
possibilities.
Drawing Parallels With Other Phenomena
As previously described, a major aim of cognitive
neuroscience is to “carve nature at its joints” by using
imaging data to inform questions about the distinct
or overlapping processing systems underlying various
behaviors. In this regard, imaging data have proven to
be particular useful in addressing particular kinds of
questions about processing mechanisms. One question
ideally suited for imaging data is whether two different
behavioral phenomena depend on common or distinct
processing systems. By determining whether the two
behaviors recruit similar or different neural systems
one gains purchase on this question.
In the last decade, this approach has been applied
to the study of social cognition to demonstrate that
encountering, drawing inferences about, and responding to social information recruits brain regions largely
distinct from those supporting processing of nonsocial
information. Consider the example of cognitive control. Tasks requiring the engagement of control processes such as response inhibition or working memory engage lateral prefrontal and cingulate regions
but seldom if ever activate regions within the MSAS
(Botvinick, Braver, Barch, Carter, & Cohen, 2001;
Wager, Jonides, & Reading, 2004). In fact, cognitively demanding tasks deactivate several MSAS regions, and activity in regions associated with social
and nonsocial task types demonstrates negative, reciprocal relationships (Drevets & Raichle, 1998; Fox
et al., 2005). At first these findings were taken to mean
that thinking about animate agents requires a discrete
form of information processing unique to the social
domain (J. P. Mitchell, 2008b) and that cognition and
THE REINTEGRATION OF ACCURACY
socioemotional processes might be antagonistic to one
another (Drevets & Raichle, 1998). More recent models have focused on the specific computations that may
differentiate the demands of social versus nonsocial
inference (Buckner & Carroll, 2007; J. P. Mitchell,
2009b).
Although useful for clarifying the boundaries between social and nonsocial cognition, a strong focus on
dissociating their underlying processing systems may
miss ways in which the two kinds of systems collaborate in everyday social interactions that demand more
than one kind of process come into play. This bears on
the previous discussion of cognitive control. Behavioral work suggests that mind perception—and specifically mental state attribution—is highly demanding,
and succeeding in it depends on the availability of executive control resources (Apperly & Butterfill, 2009;
Carlson & Moses, 2001). At first blush, this finding
seems to clash with evidence that executive control
and social cognition rely on different neural systems.
This confusion is partially cleared up, however, when
we consider that neuroimaging studies of mind perception often employ social tasks with limited or no
executive demands (e.g., passive viewing of social targets), and when they do employ more difficult social
tasks (e.g., some studies of mental state attribution),
cognitive control demands are typically equated across
the critical mind perception and baseline control conditions so as to isolate the neural correlates of mental
state attribution.
As such, distinctions between neural systems involved in social and nonsocial information processing
may not reflect “deep” dissociations between the computations underlying these phenomena. Instead, they
may reflect the simple fact that, to date, extant work has
largely focused on a particular question: Is mind perception different from other cognitive abilities? This
question is addressed by attempting to isolate neural
systems preferentially engaged by the presentation of,
and judgments about, social cues. Typically, this is accomplished by stripping away the complexities of everyday social interaction to devise tasks simple enough
that they depend most critically on only the specific
mind perception process(es) of interest in a given study.
Asking a different question—for example, What
do social and nonsocial information processing have
in common?— suggests focusing on tasks that more
closely match the complex processing demands of “everyday” social cognition where cognitive control processes might be important. For example, targets often
produce unclear or contradictory feedback about their
internal states, which perceivers must sort through or
choose between in order to be accurate. In such cases,
drawing accurate interpersonal inferences requires adjudication between multiple sources of social information (e.g., a target who looks sad but sounds happy). It
is likely that these requirements functionally resemble
other forms of response conflict that engage executive
control centers in the brain. Studies of the neural correlates of perceiving conflicting social cues bear out
this parallel by showing engagement of domain general control systems (Decety & Chaminade, 2003; R.
L. Mitchell, 2006; Wittfoth et al., 2009) that interact
with regions in the ESS and MSAS to guide attention to
the cues that perceivers find most relevant to deciding
how targets feel (Zaki et al., 2010).
Thus, although the neural systems involved in mind
perception and nonsocial cognition can be dissociated,
exploring their common reliance on domain-general
control systems can illuminate some of their similarities as well. Future work employing naturalistic social
tasks in combination with measures of accuracy may
serve to further characterize the links between mind
perception processes and other cognitive abilities.
Contributions to Clinical Approaches
Finally, an integration of processes and accuracy
has the potential to reframe thinking about clinical disorders characterized by social cognitive deficits. As
with the study of healthy perceivers, this approach allows for a shift away from viewing these disorders as
representing disruptions of single processes that invariably cause social symptoms and toward a focus on (a)
seeing disorders as arising from abnormal profiles of
function in multiple processes and their interrelationships and (b) examining the situation-specific effects
of these processing abnormalities on social symptoms.
Here we consider autism spectrum disorders (ASD) as
an example case.
Processes and Accuracy in Autism
Individuals with ASD famously fail to engage in
typical forms of interpersonal interactions (Lord et al.,
1997; Lord, Rutter, & Le Couteur, 1994; Wing &
Gould, 1979) and to normatively deploy mental state
attribution and experience sharing or engage the neural systems underlying these processes (Baron-Cohen
et al., 1985; Dapretto et al., 2006; Kennedy, Redcay, & Courchesne, 2006; Oberman, Ramachandran,
& Pineda, 2008; Rogers, Hepburn, Stackhouse, &
Wehner, 2003). The observed covariance between a
specific kind of processing dysfunction (e.g., experience sharing) and abnormal social function in ASD
is sometimes used as evidence that abnormalities
in single mind perception processes underlie social
deficits in autism (Baron-Cohen, 1994; Oberman &
Ramachandran, 2007). On this view, abnormalities in
either mental state attribution or experience sharing
lead, more or less directly, to the complex social symptoms evinced by ASD.
Although processes such as those supporting experience sharing no doubt play some role in ASD, single
173
ZAKI AND OCHSNER
process models fail to square with several lines of evidence (Happe, Ronald, & Plomin, 2006). For example,
not all studies of ASD document problems in mind perception tasks or their neural bases (Bird et al., 2010;
Bowler, 1992; Castelli, 2005; Fan, Decety, Yang, Liu,
& Cheng, 2010). Further, the few studies attempting
to directly link deficits in mind perception processes
with social symptom severity have yielded inconsistent results (Dapretto et al., 2006; Fombonne, Siddons,
Achard, Frith, & Happe, 1994; Lombardo, Barnes,
Wheelwright, & Baron-Cohen, 2007; Rogers et al.,
2003; Tager-Flusberg, 2007). What’s more, interventions aimed at encouraging the use of mind perception
processes (e.g., training in recognizing photographed
emotional faces) often produce improvements on these
tasks without causing any parallel improvements in
clinically assessed social deficits (Gevers, Clifford,
Mager, & Boer, 2006; Golan & Baron-Cohen, 2006;
Hadwin, Baron-Cohen, Howlin, & Hill, 1996, 1997;
Ozonoff & Miller, 1995). These disparities underscore
the gap between successfully deploying a particular
cognitive process and successfully interacting with others.
The model we are advocating here suggests that two
conceptual shifts could better link information processing to social function in ASD. First is the proposition
that adaptive social functioning depends on the simultaneous and concerted use of multiple processes to
support accurate understanding of the complex social
cues perceivers typically encounter. Extant tasks used
to assess impairments in ASD (such as motor imitation
or emotion identification using pictures) are ill suited
to capturing such deficits, because they are aimed at
assessing the deployment of single processes using
highly simplified stimuli. Second, abnormalities in the
operation of mind perception processes likely interact
with features of a situation (e.g., the target to which a
perceiver is paying attention), affecting social function
more in some situations and less so or not at all in
others. As such, moving beyond a “perceiver-centric”
take on mind perception could allow for mapping the
specific contextual domains in which the processing
deficits characterizing ASD are most damaging to patients.
Although there are only three extant studies of empathic accuracy in ASD, they provide promising initial
support for the more nuanced view we are advocating here. For example, individuals with ASD demonstrate more consistent impairments in empathic accuracy than in simpler, more canonical theory of mind
tasks (Demurie, De Corel, & Roeyers, 2011; Roeyers,
Buysse, Ponnet, & Pichal, 2001). Second, the one study
examining contextual effects on accuracy deficits suggests that ASD individuals’ social cognitive problems
are indeed selective and related to the types of cues they
encounter. Specifically, ASD status predicted reduced
accuracy when perceivers observed unstructured inter174
actions between targets but not when they observed
targets interviewing each other in a structured format
(asking each other questions, such as “What do you
like to do in your spare time?”; see Ponnet, Buysse,
Roeyers, & De Clercq, 2008). These data suggest that
examining context-dependent deficits in accuracy can
help researchers map the domains in which individuals with ASD are likely to be more or less impaired
and how these impairments evolve out of mind perception processes that support greater or lesser accuracy. Such an approach also suggests potential novel
interventions based not on erasing cognitive deficits
but rather on placing individuals in contexts/situations
where those cognitive deficits are less likely to
matter.
Consider anecdotal reports (Grandin & Barron,
2004) and empirical studies (Baron-Cohen, 2009;
Baron-Cohen, Richler, Bisarya, Gurunathan, & Wheelwright, 2003) suggesting that individuals with ASD often compensate for mind perception deficits by using
systemized rules to elaboratively “work out” the likely
experiences of social targets. Such a compensatory
strategy could be most useful when targets are producing clear and structured cues about their internal states
(as in the interview condition previously described)
of the type produced by emotionally expressive targets (Zaki et al., 2008; Zaki, Bolger, et al., 2009).
This suggests a form of intervention in which caregivers and family members of individuals with ASD
could restructure their behavior to provide clear, readable cues about their internal states, thereby rendering
the information-processing issues inherent to ASD less
debilitating.
Although speculative, ideas like this one highlight
a broader point: Integrating measures of mind perception processes, accuracy, and adaptive functioning can
produce novel predictions about the domains in which
information-processing deficits lead to clinical dysfunction, and suggest situation-specific interventions
to alleviate such dysfunction.
Conclusions
Mind perception research has a long and sometimes rocky past. The early years were defined by
the hunt for accuracy. This hunt never captured its
quarry, which led researchers to focus almost exclusively on the information-processing steps underpinning social cognition—independent of accuracy. This
shift has been enormously successful in characterizing
the separable mechanisms through which perceivers
try to understand targets, and recent work identifying
neural signatures of these processes has made the endeavor even more compelling.
We have argued that mind perception research—
in focusing almost exclusively on process—has
THE REINTEGRATION OF ACCURACY
often chosen to ignore its past, and as a consequence
has been limited in some important ways. The majority of current mind perception research is concerned
with determining whether and when a given cognitive
processes is in play—and neural correlates of these
processes are—in many cases without reference to
whether or to what extent one’s resulting understanding
of another person is accurate. Or put another way, we
know a lot about what processes people engage when
they try to make sense of others minds but less about
what determines whether they are accurate. This matters because in actual social encounters, a perceiver’s
goal is not simply to draw any old inference about
their social partners but (usually) to draw an accurate
one.
There seem to be two main reasons that the process approach has failed to make contact with the accuracy approach. First, researchers may believe that
accuracy is too difficult to quantify. Luckily, this concern is outdated. Following a 25-year hibernation,
accuracy research has surged, producing a novel and
varied approaches to quantifying accuracy and identifying its predictors. Second, even if process-oriented
researchers believe that accuracy can be quantified,
they may not believe doing so is relevant to their work.
Here, we hope to have shown that this view may be
shortsighted insofar as integration can provide several
novel insights, predictions, and lines of research. Following the framework previously outlined, the strength
of this approach comes from directly linking (either
behavioral or neural) signs that a process has been
deployed with signs that a perceiver has accurately decoded a target’s internal states, and in turn relating both
of these constructs to adaptive outcomes in the social
world. Critical to all of these connections is identifying
first the contextual boundaries that determine when a
process supports accuracy and, second, when accuracy
predicts social well-being.
In elaborating this approach, we have purposefully
constrained our focus to two processes—mental state
attribution and experience sharing—and on one form
of accuracy—the ability to correctly judge a target’s
dynamic emotional experience—because we considered a limited focus to be necessary for fully fleshing
out and illustrating the value of a process-accuracy
integration in a single article. However, we hope that
future work will port this approach to the study of other
processes, such as stereotyping and projection (Hoch,
1987; Judd & Park, 1993; Jussim, 1991; Neyer, Banse,
& Asendorpf, 1999); other forms of accuracy, such as
predictions of one’s own future experiences (Gilbert
et al., 1998; Kermer, Driver-Linn, Wilson, & Gilbert,
2006; Wilson, Wheatley, Meyers, Gilbert, & Axsom,
2000); and other forms of adaptive behavior, such as
successful negotiation, cooperation, and accurate prediction about others’ actions (Coricelli & Nagel, 2009;
Galinsky, Maddux, Gilin, & White, 2008; Hampton,
Bossaerts, & O’Doherty, 2008; Valdesolo, Ouyang, &
DeSteno, 2010).
Overall, we believe that this approach can reframe
current data concerning mind perception processes,
prompt richer questions about how people understand
each other, and suggest new ways of testing these questions. The sorts of changes motivated by this approach
will vary depending on the phenomenon being studied and level of analysis being employed. In some
cases, questions will be refined from the categorical
(“Which process leads to accuracy?”) to the conditional (“When will this process produce accuracy?). In
other cases, neuroscientists could shift away from characterizing single systems (“What processing steps are
instantiated in the MSAS or ESS?”) and toward more
holistically viewing these systems’ role in naturalistic
situations (“How do the MSAS and ESS interact with
each other and with other systems—like those involve
in domain general cognitive control—to produce accurate inferences?”). Finally, in clinical settings, this
could mean moving beyond characterizing psychiatric
disorders as arising from deficits in single processes
(“Do individuals with ASD fail to normatively employ mental state inference?”) to examining profiles of
information-processing abnormalities across multiple
processes in a broader social-cognitive context (“Under which situations will failing to employ mental state
attribution most affect an ASD individual’s abilities to
interact with others, and is there a way to attenuate this
effect?”).
Let us end by saying that in no way do we wish
to suggest that the current, process-focused approach
dominating social cognition should be replaced by the
one described here. That would be as counterproductive as the screeching halt of accuracy research half a
century ago. Instead, we are making the simple point
that—as so often is the case when two approaches provide different angles on the same, complex question—
joining forces can be beneficial to everyone.
Note
Address correspondence to Jamil Zaki, Department
of Psychology, Harvard University, Northwest Science
Building, 52 Oxford Street, Cambridge, MA 02138.
E-mail: zaki@wjh.harvard.edu
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Psychological Inquiry, 22: 183–186, 2011
C Taylor & Francis Group, LLC
Copyright ISSN: 1047-840X print / 1532-7965 online
DOI: 10.1080/1047840X.2011.573767
COMMENTARIES
Interacting Minds: A Framework for Combining Process- and
Accuracy-Oriented Social Cognitive Research
Bahador Bahrami
UCL Institute of Cognitive Neuroscience, University College London, London, England; Institute of Anthropology,
Archaeology, Linguistics, Aarhus University, Aarhus, Denmark; and Centre of Functionally Integrative
Neuroscience, Aarhus University Hospital, Aarhus, Denmark
Chris D. Frith
Institute of Anthropology, Archaeology, Linguistics, Aarhus University, Aarhus, Denmark; Centre of Functionally
Integrative Neuroscience, Aarhus University Hospital, Aarhus, Denmark; and Wellcome Trust Centre for
Neuroimaging, University College London, London, England
Zaki and Ochsner underscore the importance of
combining two different viewpoints in social cognition: a currently popular, process-oriented approach
that is concerned with how we come to understand
others’ mental states. The main insights from this mind
perception research come from the ideas of theory of
mind and understanding by simulation. Another, rather
older approach focused on what enables human agents
to understand others’ mental states better. The latter approach is motivated by the assumption that there must
be some survival value in higher accuracy and reliability of our internal mental models of others’ intentions
and beliefs. Accuracy research has been thwarted, Zaki
and Ochsner argue, by a lack of principled theoretical approach leading to research programs plagued by
a plethora of scattered and often difficult-to-replicate
cross-correlations between multiple arbitrary dependent variables.
Both approaches are admittedly concerned with social interaction. However, both also address social interaction as yet another cognitive faculty serving the
isolated agent. For example, in a game of poker, the
accuracy approach may seek to understand who is better at calling bluffs. The process approach, on the other
hand, may ask what happens in the poker player’s brain
that enables him to call the bluff and raise the stakes as
opposed to fold. But whether these findings will be essentially different from the work of a psychophysicist
who investigates the object recognition that happens
when the player reads his cards is far from decided
(Frith & Frith, 2010).
Social interaction also allows agents to share information and make decisions together. This function is
directly relevant to the accuracy and the process of social perception but is qualitatively different from what
helps our poker player win the game. Every social agent
is continuously sampling information and making
judgments and inferences about her or his surrounding
environment. These inferences are always corrupted
by (extrinsic environmental as well as intrinsic neural)
noise and therefore have limited reliability (Green &
Swets, 1966). By interacting with other social agents
who have obtained their own samples of information,
individuals can benefit from the increased reliability
of joint decisions (Nitzan & Paroush, 1985). Information sharing through interaction can lead to emergent
forms of collective wisdom that could serve all members of a group. Indeed, such collective wisdom that
arises from efficient near-optimal democratic decisionmaking strategies are amply observed in social animals
such as bees and deer (Conradt & Roper, 2005, 2007;
Seeley & Visscher, 2004a, 2004b) and has been the
topic of much interest in humans (Surowiecki, 2004).
The research on collective wisdom asks what constitutes efficient social interaction. We are often told that
“two heads are better than one.” But what are the minimum necessary or sufficient conditions for two heads
together to excel better than one in isolation? Are there
any limiting conditions to group benefit accrued by interaction? Are there any conditions where interaction is
counterproductive and not advisable? These questions
rephrase the Zaki and Ochsner’s idea of “accuracy of
social perception” in the context of collective decision
making.
The brain is a highly efficient information integration device that adeptly integrates information from
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COMMENTARIES
Figure 1. Leili and Majnun make joint decisions about where the ball landed.
(A) The ball’s trajectory. (B) Leili and Majnun’s individual decisions are based
their respective noisy perceptual representation conceptualized here as Gaussian
distributions. The figure was inspired by Ernst (2010).
multiple sensory channels. A prominent example of
such highly efficient integration is speech perception:
Noisy visual and auditory information are efficiently
and quickly combined almost as perfectly as mathematically possible (given their own inherent noise
level) to maximize understanding (Ernst & Bulthoff,
2004). One brain can combine information optimally
from multiple modalities. But can two different brains
integrate information about the same modality? If
yes, how does the integration happen? The answer to
this question entails rephrasing Zaki and Ochsner’s
process-oriented mind perception in terms of collective
decision making: What is the nature of the shared
information that contributes to making joint decisions?
It is interesting to note that these questions—which
relate critically to the accuracy limit and the process of
collective decisions—date back to (at least) the French
revolution (Condorcet, 1785). However, it is only recently that they have been formally and rigorously addressed in humans (Bahrami et al., 2010; Sorkin, Hays,
& West, 2001). The conceptual basis of this new approach to collective decision making is described next
in the context of a game of tennis (see Figure 1).
Leili and Majnun—our two protagonists from here
on—are watching a game of tennis (Figure 1). The ball
has just landed very close to the line (Figure 1A, white
184
arrow), and they disagree about whether it landed in
or outside the court (Figure 1B). They will consult
each other and arrive at a joint decision about the ball,
and the game will then carry on. But let’s stop here
and consider the situation. Each observer’s visual perception of what happened can be conceptualized as a
normal distribution1 with a mean (dL for Leili and dM
for Majnun) and a standard deviation (σL and σM ). The
mean identifies the observer’s decision about whether
the ball fell above (e.g., Leili) or below (e.g., Majnun)
the thick black line that marks the border of the tennis court. The standard deviation of each distribution
quantifies the amount of noise in the observer’s sensory
representation and is inversely related to the observer’s
perceptual sensitivity. A reliable percept would therefore be characterized by a mean with large magnitude
(greater distance from the boundary, e.g., Majnun) and
a small standard deviation (sharper, less noisy distribution, e.g., Leili).
This formulation is useful in many respects. First,
a large body of literature in sensory psychophysics
gives us reliable tools to empirically identify these parameters underlying the decisions made by Leili and
1 This normal distribution could represent, for example, the activity pattern of neurons in the observer’s primary visual cortex.
COMMENTARIES
Majnun in isolation and for the group (Green & Swets,
1966). Second, and more important, one could use this
formulation to construct different models of collective
decision making (Bahrami et al., 2010; Sorkin et al.,
2001). Such models explicitly define a communication
strategy in terms of which parameters Leili and Majnun share with each other and what decision rule they
employ to combine the communicated parameters. The
model takes (dL , dM ) and (σL , σM )—which have been
empirically determined (see previously)—and makes
exact, specific predictions about the corresponding parameters for the joint performance.
By comparing the empirical and predicted parameters of the group’s performance, one could distinguish
between alternative models of communication—thus
addressing the “process” question proposed by Zaki
and Ochsner (this issue). Once a winning model of
communication is identified, one could then explore
that model’s predictions for conditions under which
two heads are expected to do better than one and when
they are expected to do worse—thus addressing the
“accuracy” question proposed by Zaki and Ochsner
(this issue).
Take the simplest possible case: If all Leili and Majnun could communicate to each other was their disagreement (i.e., that dL × dM < 0), then their joint
sensitivity will be no better than the average of their
individual sensitivities (Bahrami et al., 2010). A number of studies have shown that groups of two or more
observers can achieve greater perceptual sensitivity
than their respective individual members in isolation
(Bahrami et al., 2010; Green & Swets, 1966; Sorkin
et al., 2001). Clearly the content of communication is
richer than just signifying disagreement.
On the other hand, what would happen if Leili and
Majnun were so good at communicating that each
could fully reconstruct the other’s internal sensory representation? The normal distribution is fully described
by its mean and standard deviation. So, perfect communication would require Leili and Majnun to exchange
the mean and the standard deviation of their respective
internal normal distribution distinctly and accurately.
The group’s sensitivity, SLM (i.e., sharpness of the normal distribution) is then expected to be
SLM =
2
SL2 + SM
.
(1)
It turns out that this is quite a tall order to fill for
collective decision making. Sorkin et al. (2001) and
Bahrami et al. (2010) have shown that group performance falls markedly short of this expectation. That
complete and exact communication of sensory representations between separate brains is not possible is
hardly surprising. Previous research in multisensory
perception has shown that this model is a good predictor of how information from different sensory modali-
ties, such as touch and vision are combined within the
brain of the same observer (Alais & Burr, 2004; Ernst &
Banks, 2002). Communication between brains is not
as reliable or high-fidelity as communication within
the same brain. Neither “just disagreement” nor “fullfledged communication” captures the characteristics of
human collective decision making. A middle ground
should be sought.
A useful clue about the likely strategy for collective decision may be obtained by noting that Leili and
Majnun’s conversations leading to their joint decision
are mostly about how confident they are about their
decisions. Remember that a reliable decision is the
one based a large mean and a small standard deviation. Therefore, the observer’s confidence in her or his
decision could be conceptualized as the ratio of the
observer’s mean to her or his standard deviation (dL /
σL for Leili and dM / σM for Majnun). The sign of this
ratio would indicate the observer’s decision (e.g., positive indicating “in” for Leili and negative indicating
“out” for Majnun). The magnitude of this ratio would
correlate with the probability that the observer believes
she or he has made the right decision. Once confidences
are communicated, joint decision could be simply defined as the sign of the sum of confidences (Bahrami
et al., 2010). This confidence sharing model predicts
a more modest benefit from information sharing. The
group’s sensitivity will be
SLM =
SL + SM
.
√
2
(2)
We have recently shown that this model captures
group performance in collective decision making over
a wide variety of experimental conditions (Bahrami
et al., 2010; see the upcoming discussion for more details). As such, the confidence-sharing model provides
an example for Zaki and Ochsner’s proposition for
process-oriented understanding of social interaction.
This model is based on a set of explicit and simple assumptions and offers a powerfully predictive account
of the likely nature of communicated information and
rules of interaction in collective decision making.
This model gives a markedly better fit to the data
than the direct sharing model (Equation 1) when Leili
and Majnun have very different sensitivities. If Leili
is a much better tennis observer (i.e., more sensitive)
than Majnun—specifically, if SM / SL < 0.4—then the
confidence-sharing model predicts that the joint decisions will be less accurate than Leili’s individual decisions (i.e., SLM < SL ). In contrast, the direct-sharing
model predicts that the group will never do worse
than the better member (see Bahrami et al., 2010,
for details of calculations2 ). Empirical results from
2 It is easy and quite fun to derive both of these predictions from
Equations 1 and 2.
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COMMENTARIES
multiple experiments support the confidence-sharing
model (Bahrami et al., 2011; Bahrami et al., 2010)
indicating that a major determinant of the outcome of
social interaction is the similarity in interacting agents’
competence (in our case captured empirically by perceptual sensitivity).
The relevance of these latter findings to addressing
what Zaki and Ochsner proposed as a dearth of principled approaches to accuracy-oriented social cognitive
research cannot be overstated. The confidence-sharing
model offers specific predictions for when social interaction is accurate and group members benefit from
cooperation/communication and for when it is not accurate and groups members suffer from being subjected
to cooperation, for example, by the compulsion to comply with social/political correctness.
Current research in social cognitive neuroscience
has already taken on board the notion that a comprehensive understanding of the social brain can happen
only in an interactive context. It is in this context that
combining accuracy-oriented and process-oriented
social research can be most useful. Research in this
area could benefit from scrutinizing examples such
as the confidence-sharing model recounted here and
exploring the conditions and situations where such
models fail to account for social interactive behavior.
For example, how is social learning incorporated in
collective decision making? The confidence-sharing
model assumes that human observer’s behavior in
collective decision making is stationary and stable
over time. But it is more than clear that social
learning plays an important role in communication
and collaboration. How and where such models will
fail to explain social learning would be immensely
instructive for social cognitive research.
Acknowledgments
This work was supported by a British Academy
postdoctoral fellowship to Bahador Bahrami, the Danish National Research Foundation and the Danish
Research Council for Culture and Communication,
the European Union MindBridge project (Bahador
Bahrami, Chris D. Frith), and the Wellcome Trust
(Chris D. Frith). Support from the MINDLab UNIK
initiative at Aarhus University was funded by the Danish Ministry of Science, Technology and Innovation.
186
Note
Address correspondence to Bahador Bahrami, Institute of Cognitive Neuroscience, University College
London, 17 Queen Square, London, United Kingdom
WC1N 3AR. E-mail: bbahrami@gmail.com
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Psychological Inquiry, 22: 187–192, 2011
C Taylor & Francis Group, LLC
Copyright ISSN: 1047-840X print / 1532-7965 online
DOI: 10.1080/1047840X.2011.567961
Integrations Need Both Breadth and Depth: Commentary on Zaki and
Ochsner
Nicholas Epley
Booth School of Business, University of Chicago, Chicago, Illinois
Tal Eyal
Department of Psychology, Ben Gurion University of the Negev, Beer Sheva, Israel
Zaki and Ochsner (this issue) put out a call for social cognition researchers to integrate work on the processes that enable mind perception with work on the
accuracy with which people reason about other minds.
We welcome this call and believe it is long overdue. Indeed, the main reason that psychologists are interested
in underlying psychological processes at all is because
they give insight into how effectively these processes
are likely to function in everyday life. Understanding
how people reason about the minds of others is interesting mainly because it provides insight into how well
they are likely to do so.
Zaki and Ochsner echo the arguments that process
researchers have been making for many years—that
people rely on multiple processes and cognitive tools
to reason about the minds of others. We agree with
Zaki and Ochnser that neuroscience may aid process
researchers in understanding exactly how these different processes operate in any given social judgment
given that these underlying processes cannot be observed directly. We also agree that neuroscience has
the potential to provide a more concrete understanding
of exactly when different processes are utilized to make
inferences about the minds of others. And we therefore
agree that neuroscience may help to integrate the processes that guide mind perception to the accuracy that
those processes produce.
Although we found much to like in this target article, we also found three points that could count as disagreement. First, we are concerned that an increased
focus on accuracy inevitably leads to useless and misleading arguments about how good people really are
at judging the minds of others. Oversimplified statements that people are “consummate experts” or amateurs at judging the minds of others are a waste of time
and reflect opinions from authors more than facts from
experiments. Second, we think that Zaki and Ochsner
have overlooked, or at least underemphasized, the main
benefit of linking process to accuracy. This benefit is
that understanding process enables researchers to predict when people are likely to be accurate and when
they are not. This, in turn, also enables researchers
to predict the systematic mistakes that people might
make and provides insight into how to systematically
increase or decrease accuracy. Finally, Zaki and
Ochsner suggest focusing on the adaptive consequences of accuracy rather than simply on accuracy
as an end goal in itself. We think that research area is
already getting considerable attention, and instead we
suggest zooming out to the beginning of the mind perception process to understand the factors that trigger
people to think about the minds of others in the first
place.
Oversimplifying Accuracy
Bernard Madoff ran an investment securities firm
for nearly 50 years that defrauded its investors of billions of dollars. The magnitude of Madoff’s fraud appears unprecedented. More amazing, however, was that
Madoff’s lies went undetected by his closest friends,
and apparently even his family members, for well over
20 years. Day after day, year after year, one dinner party
and lunch meeting after another, Madoff sat across the
table from friends and family members and other close
investors telling lies that nobody seemed able to detect.
It is hard to fault Madoff’s investors. Detecting whether
people are lying or telling the truth appears, based on
experiment after experiment, with both novices and
experts, to be a very difficult task. A recent metaanalysis of 206 lie detection experiments found that
people could accurately distinguish between lies and
truths 54% of the time, on average, when chance accuracy was 50% (Bond & DePaulo, 2006).
We were therefore rather surprised to read in the
opening paragraphs of Zaki and Ochsner’s article that
whether we’re sniffing out the intentions of a used
car salesman or figuring out the right thing to say
to an upset friend . . . we are consummate experts at
this task, accurately reading the internal mental states
that guide other’s behavior with an ease and skill that
would be shocking if it wasn’t so universal. (p. 159)
Really? Lies and truths, remember, are detected accurately only 54% of the time. People do indeed find it
easy to reason about the minds of others, but you have
to evaluate the scientific evidence for accuracy with at
187
COMMENTARIES
least one eye closed in order to conclude that “we are
consummate experts.”
Our concern with this opening emphasis, revisited
again later in the article in caricatured descriptions of
the heuristics and biases research tradition, is important, because all calls to consider accuracy in social
cognition seem to start out the same way, whether
it is a call from a reporter or a call by researchers
to study accuracy. These calls almost inevitably seek
some statistics, ideally a single statistic, that will tell us
how good people “really are” at whatever we are trying to measure accurately. The problem with a simple
answer to these calls, such as the “consummate expert”
characterization offered by Zaki and Ochsner, is that it
is misleading to readers and unhelpful to psychological
science.
It is misleading to readers because there is simply
no general statement that can be made about how good
people really are at understanding the minds of others.
People are relatively good at some tasks, such as knowing how they will be judged by others in general, and
relatively bad at more challenging versions of the same
task, such as knowing how specific individuals within
a group will judge them (Kenny & DePaulo, 1993).
Some traits (e.g., extraversion) are easier to judge
than others (e.g., neuroticism; Funder & Dobroth,
1987; Hall, Andrzejewski, Murphy, Schmid Mast, &
Feinstein, 2008). Some people (e.g., high in intelligence) are better mind readers than others (Callaghan
et al., 2005; Davis & Kraus, 1997; Realo et al., 2003).
Some cultures (e.g., collectivistic) seem to foster capacities that would enable better mind reading than others (Cohen & Gunz, 2002; Wu & Keysar, 2007). Some
people, such as our friends, are easier to read than others (Stinson & Ickes, 1992) but still not as easy to read
as we might think (Savitsky, Keysar, Epley, Carter, &
Swanson, 2011; Swann & Gill, 1997). Finally, trying
harder to be accurate appears to improve accuracy in
some domains (Epley, Keysar, Van Boven, & Gilovich,
2004) but has no effect in others (Hall et al., 2009; Myers & Hodges, 2009). The only general thing that can
be said about mind perception is that it is sometimes
better than chance, almost never perfect, and leaves
plenty of opportunity for improvement.
Instead of noting the enormous variability in accuracy observed in both process- and accuracy-oriented
research, Zaki and Ochsner (this issue) repeat a common (but empirically unsubstantiated) claim of critics that studies of social cognitive error “typically
use highly superficial and nonnaturalistic tasks that
. . . are designed to create the errors they document”
(p. 169). We wonder what the actual evidence is for
such a claim. For instance, process researchers study
how partisans on opposite sides of the abortion debate
(Chambers, Baron, & Inman, 2006), an educational
dispute (Robinson, Keltner, Ward, & Ross, 1995), or
a labor/management conflict (Robinson & Friedman,
188
1995) view each other’s attitudes and beliefs. Process
researchers ask people to predict if someone else can
detect when they are lying or telling the truth (Gilovich,
Medvec, & Savitsky, 2000), predict how attractively
they will be judged by a member of the opposite sex
based on a photograph (Eyal & Epley, 2010), or predict
when another person will be able to detect that they are
“only teasing” when they poke fun at someone versus
when they are actually intending to be critical (Kruger,
Gordan, & Kuban, 2006). We are curious to know how
these experiments count as “superficial” or “nonnaturalistic.”
Accuracy researchers, in contrast, take posed photographs of people pretending to experience an emotion and ask people to report what the person is “really
feeling” (Nowicki & Carton, 1993). Or they clip out
faces from advertisements, get consensus judgments
from a small number of raters about what mental state
that person is probably feeling or thinking, call those
consensus judgments a measure of accuracy, and then
measure how well people can predict those consensus
judgments looking at only a cutout of the target’s eyes
(Baron-Cohen, Wheelwright, Hill, Raste, & Plumb,
2001). Or they ask people to interact with each other,
go back and watch a videotape of that interaction trying
to remember every point at which they had a thought,
and then measure how well the interaction partner can
predict the other person’s recalled thought after the
interaction (Ickes, 2003). We are curious to know in
what way these studies are somehow deeper and more
naturalistic.
Zaki and Ochsner are, however, absolutely right that
accuracy researchers typically use chance as the baseline of comparison. Doing better than chance is therefore counted as evidence of accuracy, no matter how
slight. Process researchers, in contrast, typically use
perfect accuracy as the baseline, and any deviation is
therefore counted as error, again no matter how slight.
Whether people look like “consummate experts” or not
therefore depends on the researcher’s basis of comparison rather than on people’s actual ability. We wish
that researchers would stop making such claims. Accuracy research will benefit markedly, we think, when
researchers get beyond overly simplistic statements
about people’s true ability and instead attend to how
the processes underlying mind perception can predict
variability.
Process Predicts Accuracy
Accuracy researchers “crowded the exits” (Gilbert,
1998) after Cronbach’s critique and started studying
more basic psychological processes because, at least
in part, researchers had gotten ahead of themselves.
Understanding the processes that enable mind perception is the first necessary step in understanding
when those processes are going to produce accurate
COMMENTARIES
judgments and when they are not. Early researchers
had overlooked this first step altogether. With 30 years
of subsequent process research, psychologists are now
better positioned to understand when people are likely
to be more or less accurate and how to increase accuracy systematically. The real benefit that we think
comes from linking process to accuracy is the ability
for underlying processes to predict accuracy. Zaki and
Ochsner describe this possibility in their Processes’
Situation-Specific Utility section but underemphasize
the value of this benefit.
One concrete example of how understanding process can both predict and enable accuracy comes from
our own research (Eyal & Epley, 2010) examining how
well people can intuit the impressions they are conveying to others. This is not an easy mind perception task.
Other people’s impressions are not written on their
faces in the same way that a simple emotion might
be. In this case, people reason about the minds of others by using their own mental states—their own attitudes, beliefs, or impressions—as an initial starting
point (Alicke, Dunning, & Krueger, 2005; Epley et al.,
2004; Flavell, 1986; Keysar, Barr, Balin, & Brauner,
2000; Nickerson, 1999; Piaget, 1929; Smith, Coats, &
Walling, 1999). This egocentric strategy enables accuracy when two people share the same psychological
perspective but produces errors when perspectives differ (e.g., Gilovich et al., 2000; Gilovich, Savitsky, &
Medvec, 1998; Keysar, 1994; Nickerson, 1999; Ross
& Ward, 1996; Van Boven, Dunning, & Loewenstein,
2000).
Perspectives between two people may differ for
many reasons. One of these differences is that people have much more information about themselves
than others do (Jones & Nisbett, 1971). People are experts about themselves. Experts in any domain are able
to notice fine-grained details and subtle distinctions
that novices cannot even notice. People are therefore
likely to think about themselves in much more lowlevel detail than others are (Chambers, Epley, Savitsky, & Windschitl, 2008; Eyal & Epley, 2010; Jones &
Nisbett, 1971; Pronin, Gilovich, & Ross, 2004; Semin,
2004; Trope & Liberman, 2010). Others, in contrast,
are relative novices and are therefore likely to think
of the self in much more abstract, general, and highlevel terms (Trope & Liberman, 2010). A professor,
for instance, might evaluate the quality of her own lecture by thinking about low-level details of words and
phrases in the lecture, whereas students are likely to
evaluate the lecture in terms of its overall content and
general interest. If people evaluate themselves under
a microscope but are evaluated by others at the level
of the naked eye, then people are likely to have some
difficulty intuiting how they are viewed by others.
This insight from the process that guides mind perception suggests that aligning the level at which people
construe themselves and others may increase accuracy.
In a recent series of experiments we conducted to test
this hypothesis (Eyal & Epley, 2010), participants anticipated how attractive they would be evaluated by another participant on the basis of a photograph. Half of
the participants anticipated how they would be judged
by someone looking at their picture later that day. The
other half of participants anticipated how they would
be judged by someone 3 months from now. The latter
condition encourages a higher level self-construal than
the former (Trope & Liberman, 2010). As predicted,
participants were significantly more accurate, both in
the correlation between predicted and actual evaluations and the absolute difference between them, when
predicting how they would be evaluated 3 months from
now than when intuiting how they would be judged
right now. These differences were substantial. Participants were no better than chance at predicting how
attractively they would be judged later that day (r =
–.24) but were impressively accurate when predicting
how they would be judged 3 months from now (r =
.55).
Not only does understanding process identify how
to increase accuracy for everyone but it also predicts
which individuals are likely to be consistently more
accurate than others. In particular, those who are particularly likely to think of themselves in high-level
details should be more accurate predicting how they
are evaluated by others than those who tend to think
of themselves in low-level details. We measured this
tendency using Vallacher and Wegner’s (1989) Action
Identification Scale. In this version, people imagined
themselves performing a variety of different activities
(such as voting) and then indicated which description
of the event they preferred, either a low-level description (marking a ballot) or a high-level description (influencing the election). As predicted, those who tended
to describe their own behavior in high-level terms were
more accurate predicting how attractive they would be
rated by a member of the opposite sex (r = .38). The
real benefit from integrating process and accuracy in
mind perception, we believe, is that only an understanding of the former can provide systematic insight
into the latter.
Triggering Mind Perception
Zaki and Ochsner suggest that mind perception
researchers should “zoom out” to consider the relation not only between psychological processes and
their downstream consequences for accuracy but also
between accuracy and their yet further downstream
consequences for adaptive outcomes. Although the
outcomes of accuracy for adaptive functioning are interesting and important, considerable attention is already being paid to these outcomes. Less attention
is being paid, we think, to the activation of mind
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COMMENTARIES
perception processes in the first place. What triggers
people to think about, or activate, their capacity to reason about the minds of others? Understanding these
factors would require zooming out to consider the very
beginning of mind perception processes rather than the
outcomes that emerge at the end.
A complete understanding of mind perception, we
suggest, would then consider four critical components:
activation (when mind perception is triggered), application (how people reason about the minds of others),
accuracy (how well mind perception processes predict others’ mental states), and adaptive functioning (in
what way is accuracy is related to outcomes). We think
that research on mind perception is in a similar position as research on stereotyping was roughly 20 years
ago. At that time, psychologists considered stereotypes
to be used almost inevitably in any social interaction.
The only questions were how these stereotypes were
applied to targets, how well these stereotypes actually
predicted a target person’s behavior, and how much
these stereotypes led to discriminatory outcomes. Real
progress was made in understanding how stereotypes
function in everyday life, however, by considering the
upstream question of when stereotypes were activated
in social interaction and when they were not. Although
it is relatively easy to activate stereotypes in social interaction (Devine, 1989), it is not inevitable. Activating
a stereotype from memory requires attentional effort
(Gilbert & Hixon, 1991; Macrae, Milne, & Bodenhausen, 1994) and is driven by the situational cues in
one’s environment (Wittenbrink, Judd, & Park, 2001).
Knowing how stereotypes influence social life requires
understanding when these processes are triggered in
the first place.
Like stereotypes, mind perception processes are often considered to be activated almost inevitably whenever a person is in the midst of a social interaction. The
ability to reason about the minds of others has been hypothesized to be a distinct neural module that is “rapid
. . . automatic, requiring no effortful attention . . . and
universal” (Stone, Baron-Cohen, & Knight, 1998, p.
640). People even find it relatively easy under the right
circumstances to attribute minds to nonhuman agents,
ranging from pets to gods to geometric shapes (Heider & Simmel, 1944; see Guthrie, 1993, and Epley,
Waytz, & Cacioppo, 2007, for reviews). Mind perception is one of the capacities that make human beings
especially intelligent compared to our nearest primate
relatives (Herrmann, Call, Hernández-Lloreda, Hare,
& Tomasello, 2007). It stands to reason that we would
therefore make rampant use of our brain’s most prized
possession.
Although people have the capacity to imagine the
minds of others, just as they also have the capacity to
use stereotypes when evaluating others, emerging research makes it clear that mind perception is not necessarily an automatically activated process and instead
190
can be triggered by the individual or the situational
context (for reviews, see Epley & Waytz, 2010; Waytz,
Klein, & Epley, in press). These triggers matter because
they not only help to explain when people are likely
to reason about other minds relatively rampantly, such
as when they anthropomorphize nonhuman agents, but
also when people are likely to fail to consider the minds
of other humans, behaving either completely egocentrically or treating other people as mindless animals
or objects (Bandura, Underwood, & Fromson, 1975;
Haslam, 2006; Leyens et al., 2003). The accuracy and
adaptive outcomes of mind perception processes matter nothing for people’s behavior in everyday life if
they are not activated in the first place.
Although still very much in the early stages of development, mind perception appears to be triggered by
both motivational and cognitive factors. For example,
thinking about the minds of others helps to explain their
behavior and enables a closer personal connection with
others, and people who are motivated either to explain
another’s actions or to connect with another person
are also more likely to activate their mind perception
capacities (Epley, Akalis, Waytz, & Cacioppo, 2008;
Waytz et al., 2010). Thinking about the minds of others
is also triggered by the degree to which one is connected to, or engaged with, another person. Such connection and engagement is increased by feeling similar to another person, and similarity therefore seems to
engage both the experience sharing (Avenanti, Sirigu,
& Aglioti, 2010; Batson, 1994) as well as the mental
state attribution processes involved in mind perception
(Harris & Fiske, 2006). These triggers are often easy
to miss in the empirical literature because researchers
often put people into the very contexts where those
triggers are already present, making mind perception
seem more automatic than it may actually be. For instance, in the widely cited Heider and Simmel (1947)
study that is commonly used to show how easily people attribute minds to almost anything (i.e., geometrical
shapes), participants were asked to explain the behavior of the shapes, a powerful trigger for mind perception. We think that an increased focus on the triggers
of mind perception processes is every bit as important as focusing on the outcomes that these processes
produce.
Completely in line with the main arguments of Zaki
and Ochsner, we think that neuroscience is uniquely
positioned to reveal these triggers. Activation of mind
perception processes can be detected especially well
using neuroscientific methods compared to behavioral
methods, even though neuroscientific methods to date
have typically been applied in understanding which
type of mind perception processes are utilized once
someone has already been triggered to think about
the mind of another person. We are, like Zaki and
Ochsner, optimistic about the advances that may come
from these methods if researchers begin studying not
COMMENTARIES
only how mind perception processes are used but also
when they are activated.
Conclusion
Much of everyday life involves interacting with, or
thinking about interactions with, other minds. Those
minds most commonly come wrapped within a human body, but minds also appear in other animals,
imagined supernatural agents, or even in one’s car
or computer. Understanding how people act as intuitive psychologists to understand these other minds,
and understanding how accurately we function as intuitive psychologists in everyday life, is therefore one
of the most central issues in all of psychological science. We agree wholeheartedly with Zaki and Ocshner
that psychological science will benefit from integrating
mind perception processes with the accuracy of those
processes, and we hope this general call will be both
heard and accepted. We also agree with the bulk of
their target article, particularly the benefit that could
come from neuroscientific methods. We think, however, that psychological science will benefit particularly if researchers could set aside overly simplistic
attempts to characterize and caricature both the processes that enable mind perception and the overall accuracy it produces, focus instead on using mind perception processes to predict both impressive cases of
accuracy and error, and broaden their focus on mind
perception processes even further to understand the
triggers of mind perception.
Note
Address correspondence to Nicholas Epley, The
University of Chicago, Booth School of Business,
5807 South Woodlawn Avenue, Chicago, IL 60637.
E-mail: epley@chicagobooth.edu or Tal Eyal, Department of Psychology, Ben-Gurion University, Beer
Sheva 43210, Israel. E-mail: taleyal@bgu.ac.il
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Psychological Inquiry, 22: 193–199, 2011
C Taylor & Francis Group, LLC
Copyright ISSN: 1047-840X print / 1532-7965 online
DOI: 10.1080/1047840X.2011.573765
On Making a Thriving Field Even Better: Acknowledging the Past
and Looking to the Future
Judith A. Hall and C. Randall Colvin
Department of Psychology, Northeastern University, Boston, Massachusetts
It is very exciting that research on interpersonal
accuracy has gained such keen interest in psychology and in adjacent fields. And well it should
have, because social life depends on the ability to
draw accurate interpersonal inferences of many sorts.
In any interaction, and perhaps without even trying, a person makes judgments about some, maybe
even all, of the following states and traits of other
people: emotions; intentions; desires; needs; motives; interpersonal attitudes such as attraction or liking; personality; truthfulness; intelligence; thoughts;
values; physical states; and social categorical attributes such as social class, occupation, status, ethnicity, national origin, sex, sexual orientation, and
age.
Zaki and Ochsner (this issue) make a valuable
contribution to understanding this important phenomenon by proposing ways in which accuracy
can be related to neuropsychological and other social processes, especially ways that individual differences in accuracy might be explicable in terms
of what is happening in the physical body, notably
the brain. Attempts to understand the process of
accurate judgment—not just judgment, but accurate
judgment—are very much needed. How do people
achieve accuracy? If we can unlock that mystery, we
can progress toward understanding why some people are more accurate than others and how to maximize the chance that people will be accurate, by
altering elements of the situation that help or hinder accuracy or by training people to enhance accuracy.
In the present commentary we wish to contribute
additional ideas that may be useful for understanding the field and future research. First, we address
the authors’ assertion that research on accuracy was
moribund for many years prior to its recent rediscovery by a new generation of investigators. Then, we
discuss the “process” concept and how it might most
fruitfully be examined for understanding accuracy; we
discuss choices among different accuracy tasks and
paradigms; we discuss the different, possibly incommensurable, assumptions and goals held by researchers
of process and researchers of accuracy; and finally, we
ask, What is the final goal of process-accuracy integration?
Saying Something Does Not Make It So
It is common to read that research on accuracy
died after Cronbach’s (1955) psychometric critique,
and Zaki and Ochsner repeat this many times. They
quote earlier writers who proclaimed that accuracy researchers “crowded the exits,” to the point that accuracy
research “all but faded from view” (p. 160–161). They
assert that researchers “eagerly jumped ship,” creating
what they call a “25-year dry spell” (p. 164) and a “25year hibernation” (p. 175). They say that the question
of how well perceivers make their judgments was “relatively neglected” compared to research on how such
judgments are made; even stronger is their statement
that accuracy research experienced “‘abandonment’ in
favor of a ‘near monopoly”’ of process-oriented research (p. 160).
In addition to this claim that accuracy research in
general died, they also say that researchers gave up
looking for individual differences in accuracy because
such individual differences could not be found. According to Zaki and Ochsner, empirical disappointments led modern accuracy research to largely abandon
the search for “good perceivers.” And they conclude
that “no matter how organized accuracy researchers
might have made their search for good judges, those
judges—at least in the way researchers conceived
of them—may have been more myth than reality”
(p. 161).
These are sweeping assertions. One source of difficulty in evaluating them is their breadth in terms of
domains of accuracy research. Although Funder and
West (1993) stated that researchers gave up doing research on accuracy of personality judgment for two
decades after Cronbach, Zaki and Ochsner do not limit
their “hibernation” claim to the topic of personality
judgment. Personality judgment is only one, and not
the most prevalent, domain in which accuracy has been
investigated. Relatedly, it is unclear what domains of
accuracy are relevant when Zaki and Ochsner discuss
research on personal correlates of accuracy (i.e., the
search for the “good judge”). Second, the years marking the onset and offset of the “hibernation” are unclear.
By focusing their discussion on very recent work, Zaki
and Ochsner imply that the dark ages of accuracy research persisted for a very long time.
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COMMENTARIES
In this section we argue that Zaki and Ochsner’s
characterizations of accuracy research and its findings
could create misleading impressions in readers.
Zaki and Ochsner (appropriately) consider interpersonal accuracy to encompass many content domains,
and we do too. The first question we take up is whether
researchers gave up studying accuracy of interpersonal
judgment and whether there was ever a long period of
demoralization.
Prominent programs of research were begun in the
1970s and continued strong in ensuing years. Ekman’s
Pictures of Facial Affect were developed in that decade
(Ekman, 1976) and were used in highly influential research on accuracy in emotion judgment by Ekman
and by many other investigators. Both Ekman’s facial
stimuli and others developed by Izard were used in
seminal cross-cultural research on accuracy (Ekman &
Friesen, 1971; Izard, 1971). The Profile of Nonverbal
Sensitivity, a test of accuracy in decoding nonverbal
cues, was developed in 1971 (Rosenthal, Hall, DiMatteo, Rogers, & Archer, 1979) and formed the basis of
extensive research by its developers and others.
Not being sure exactly when the “25-year hibernation” began and ended, we might also include the extensive research of Nowicki and colleagues using the Diagnostic Analysis of Nonverbal Accuracy tests, begun
in the 1980s and expanding quickly in the early 1990s
(Nowicki & Duke, 1994). The Interpersonal Perception
Task of Costanzo and Archer, another test of decoding
interpersonal cues, was published in 1989. Reviews of
standardized tests for measuring interpersonal accuracy and the research that uses them (Hall & Bernieri,
2001; Hall, Bernieri, & Carney, 2005) gives a glimpse
into the large amount of research on accuracy that
has been done continuously with these tests and many
others—often systematically and programmatically—
for many decades. Accuracy has not been recently discovered or rediscovered.
Furthermore, accuracy research was not done by obscure investigators who published in unimportant journals. In the 1970s, accuracy research was conducted
by mainstream, and often highly visible, people such
as Robert Rosenthal, Paul Ekman, Klaus Scherer, Ross
Buck, Miron Zuckerman, Bella DePaulo, Carroll Izard,
Douglas Jackson, and Lee Sechrest. Entering the field
in the 1980s were David Funder, David Matsumoto,
Patricia Noller, Frank Bernieri, Stephen Nowicki, and
many others. These researchers would have been surprised to hear that their field was in “hibernation.” Furthermore, the journals were often mainstream. This
list of names is not meant to be exhaustive—only illustrative of some nonobscure people who worked on
accuracy during the years that Zaki and Ochsner might
be considering inactive.
Further evidence against the “hibernation” claim is
the existence of numerous meta-analyses, encompassing more than 50 years of research, that evaluated ei194
ther overall levels of accuracy or correlates of accuracy.
Consider the following meta-analyses:
Gender differences in accuracy of decoding nonverbal
cues: 75 studies (Hall, 1978), and 50 additional studies
(Hall, 1984)
Accuracy in detecting anxiety: 80 studies (Harrigan,
Wilson, & Rosenthal, 2004)
Accuracy in detecting deception: 206 studies (Bond
& DePaulo, 2006)
Cultural in-group advantage in interpersonal accuracy:
168 studies (Elfenbein & Ambady, 2002)
Comparison of accuracy levels between tests and content domains: 108 studies (Hall, Andrzejewski, Murphy, Schmid Mast, & Feinstein, 2008)
Psychosocial correlates of interpersonal accuracy: 215
studies (Hall, Andrzejewski, & Yopchick, 2009); 36
studies (Davis & Kraus, 1997)
Relation of encoding accuracy to decoding accuracy:
40 studies (Elfenbein & Eisenkraft, 2010)
Accuracy of judging personality: 199 studies (Connelly & Ones, 2010)
Relation of intelligence to interpersonal accuracy: 38
studies (Murphy & Hall, 2011); 21 studies (Davis &
Kraus, 1997)
Not only are the studies in these meta-analyses numerous, they also span a very wide range of years and
give no evidence (to our eyes) that researchers “jumped
ship” from this important topic. Connelly and Ones’s
(2010) meta-analysis of studies reporting on accuracy
of personality judgment using self-other agreement located one study in the 1950s, four in the 1960s, 15
in the 1970s, and 44 in the 1980s (B. Connelly, personal communication, February 20, 2011). Elfenbein
and Ambady’s (2002) meta-analysis of accuracy across
cultures found three studies before 1959, three in the
1960s, 18 in the 1970s, and 31 in the 1980s. In Bond
and DePaulo’s (2006) meta-analysis of lie detection
accuracy, it is stated that the articles dated from 1941
to 2005, with 103 studies published before 1995 (suggesting that many likely appeared in the 1970s and
1980s) and 103 after 1995. Instead of jumping ship or
going into hibernation, many researchers seem to have
pursued the topic of accuracy. It is unclear whether
the trends indicate that research was once actively pursued, then stopped, and then started again, or whether
it is rather a case of the field simply gaining steady
momentum. We think the latter is more likely.
Zaki and Ochsner’s conclusion that researchers
failed to find evidence for the “good judge” must also
COMMENTARIES
be challenged. Many studies, conducted over many
years, have found individual differences in accuracy
and correlates of those individual differences. These
correlates include personality, psychopathology, empathy, relationship quality, gender, dominance, workplace effectiveness, and intelligence (based on metaanalyses: Davis & Kraus, 1997; Elfenbein, Foo, White,
Tan, & Aik, 2007; Hall, 1978, 1984; Hall, Halberstadt,
& O’Brien, 1997; Hall, Andrzejewski, et al., 2009;
Marsh & Blair, 2008; Murphy & Hall, 2011). These
effects are sometimes rather small, but they are real
and therefore support the validity of the “good judge”
construct. With correlational studies, of course, it is
often not clear whether accuracy is the cause of, consequence of, or epiphenomenal to the correlated variable. But, still, it is clear that good and poor judges
do differ in identifiable ways. There may be domains
in which there is no reliable individual variation in accuracy (as indeed seems to be the case for accuracy
of detecting deception; Bond & DePaulo, 2008), but
a sweeping conclusion that individual differences and
personal correlates do not exist cannot be supported.
Thus, we think it is quite possible that accuracy
research did not die, and it is certainly the case that the
search for the “good judge” did not fail. Although Zaki
and Ochsner make occasional mention of this topic’s
long tradition, their article is imbued with the general
notion that research was rare or feeble for a long time
and needed new, recent thinking to be reclaimed as
a fruitful research direction. Although it may be true
that recent researchers are asking new questions (let
us hope they are), this can be acknowledged without
dismissing or ignoring what came before. Awareness
of past research might also reveal that some of the
“new” questions are not so new after all.
What Is a Fruitful Way to Relate Process to
Accuracy?
The concept of process is central to Zaki and
Ochsner’s article, but it is not well defined by the authors. In theory, process could include what is happening while someone is making interpersonal judgments,
what is happening while someone is making accurate
interpersonal judgments, or what is happening before
one makes such judgments that determines whether
the judgments are accurate or not. We learn different
things from these different definitions of “process.”
Thus, for example, if we can see what brain regions
are activated during a given accuracy task, this sheds
light on process in the sense that we can see what is happening concurrently with the judgments, but it may not
be informative about how accuracy is achieved. Alternatively, understanding antecedent factors that predict
accuracy may shed light on how accuracy is maximized
without revealing what parts of the brain are doing the
work.
For many purposes, the approach that identifies
“process” as something causally antecedent to accuracy is likely to be the most useful. One category of proximal causes is psychological states or actions that precede the judgments, such as the stimulus
features perceivers attend to (Murphy & Isaacowitz,
2010; Schmid, Schmid Mast, Bombari, Mast, & Lobmaier, 2011), whether they carefully analyze the stimulus versus trust their first impression (Patterson &
Stockbridge, 1998), what emotional state they are in
(Ambady & Gray, 2002), how motivated they are to be
accurate (Hall, Blanch, et al., 2009), and whether they
are distracted by competing cognitive tasks (Phillips,
Tunstall, & Channon, 2007). Of course, factors such as
these may themselves be in a causal ordering with respect to each other. Research on such factors is, in fact,
very unclear and contradictory, and there is evidence
that the results depend on what kind of accuracy task
is used (e.g., Hall, Blanch, et al., 1990; Phillips et al.,
2007). Thus there is much room for fruitful research
on proximal determinants of accuracy.
More distal, yet still context-specific, factors could
influence the ones just identified. For example, one’s
role-based power, one’s personal relationship to the
person being judged (romantic partner vs. stranger),
or the quality of one’s relationship with that person
(happy vs. unhappy marriage partners) could influence judgment strategies, emotions, attention, cognitive load, and so forth.
Lest the reader come away thinking that accuracy
depends only on locally varying factors, the large literature on personal correlates of accuracy alluded to
in the preceding section demonstrates that accuracy
has traitlike properties, which implies distal causation
stemming from formative experiences. Many authors
have suggested what some of those might be, with
candidates as diverse as early relations with parents,
family expressive style, the experience of being a parent, dance or athletic training, occupational demands,
gender socialization, and personality traits that are associated with certain social learning experiences and
motivations (for review, see Hall, Andrzejewski, et al.,
2009). As stated earlier, ambiguity about causation is
a weakness in this literature; researchers should work
harder to study putative formative experiences in a way
that permits causal inference.
A truly general trait of accuracy has eluded demonstration; different accuracy tasks are typically poorly
correlated with each other (Hall, 2001) or have unknown relations to each other. Thus, a person may
be consistent for a given kind of accuracy task without much generalization across tasks. When consistent accuracy does exist, it could be due to consistencies in proximal process variables (e.g., the person
consistently applies the optimal judgment strategy).
195
COMMENTARIES
But accuracy could also be the product of knowledge
about the accuracy domain in question, which has accumulated over time—a possibility not explicitly discussed in Zaki and Ochsner’s article. The possibility
that knowledge (either implicit or explicit) is a contributor to accuracy has both commonsense appeal and
empirical support. Empirical support comes from lensmodel studies that reveal which target behavioral cues
are appropriately utilized by perceivers in making accurate judgments (Gifford, 1994; Scherer, 1978); appropriate use of a given cue implies knowledge about
its relevance for the judgment in question. Support for
knowledge as a determinant of accuracy also comes
from studies where knowledge of nonverbal cue meanings was separately tested using a paper-and-pencil test
and then correlated with accuracy of judging people in
audiovisual tests (Davitz et al., 1964; Rosip & Hall,
2004). A balanced consideration of sources of accuracy should therefore include knowledge along with
more transient and proximal factors.
How Should Accuracy Be Measured?
It is wonderful that many methods and instruments
exist for assessing accuracy, and more appear all the
time. Different approaches provide different windows
into accuracy. It is important to discover the limitations and advantages of different approaches, how they
relate to each other, and what each means. An arithmetic or absolute difference between judgment and
criterion means something different from a correlation
across items between judgment and criterion, which
is different from a correlation across targets between
judgment and criterion, which is different from a correlation across time between judgment and criterion,
all of which are different from whether the judgment
matches the specific content of the criterion. These
are all examples of approaches to accuracy. Which approach is chosen should depend on the question being
asked and what operational definition best maps on
to the construct of interest, not on any predetermined
notion of what is the right or best way to measure
accuracy. Not only is there no best way in the abstract; we also know very little about which methods
are best suited for different research goals and what
answers different methods would yield if compared
against each other. When testing their hypotheses, researchers tend to choose a method based on habit or
familiarity rather than on empirical grounds, and they
can hardly be blamed, because comparative research is
lacking.
No method is perfect. One method may be especially vulnerable to response biases, while another
method may be especially plagued by low variance between perceivers. Some methods are more vulnerable
to stereotype accuracy than others; profile correlations
196
across items are very vulnerable, whereas item-level
correlations across targets are much less so, often not
at all. The across-time correlational method of Zaki
and Ochsner is vulnerable to a stereotype element, too,
if the perceiver’s preconceived notion of how the rated
construct varies over time happens to match the pattern rated by the target. It is also vulnerable to an
assumed similarity artifact if the perceiver responds
according to how he or she would have felt in the
observed situation. Methods for separately measuring
distinctive and stereotype components of accuracy allow for many interesting questions to be asked, but
such methods are not always needed or applicable.
Our goal as researchers is not to find the measure that
is beyond reproach or that is right in a general sense,
but rather to choose the measure that is right for our
purposes.
Sometimes, researchers debate whether accuracy
that draws on stereotype knowledge deserves to be
called accuracy. However, they should not forget that
any time perceivers apply a correct judgment heuristic, such as “wrinkled corrugator muscle means distress” or “loud voice means extraversion,” they are
using information based on prior experience in a probabilistic way to guide their answers—in other words,
they are applying stereotypes. Those wishing to banish
stereotype-based accuracy from the list of true accuracies might be hard-pressed to justify giving credit to
knowledge of what cues generally mean while discrediting knowledge of what people are generally like.
Process and Accuracy, and the Assumptions
That Guide Them
We appreciate Zaki and Ochsner’s efforts to bring
research on mind perception processes and accuracy
under one unifying umbrella. In this section, we discuss meta-theoretical issues that researchers confront,
explicitly or implicitly, when attempting to integrate
two disparate research areas. In their abstract, the authors state, “Although in principle both the accuracyand process-oriented approaches study related aspects
of the same phenomena [emphasis added], in practice they have made strikingly little contact with each
other” (p. 159). Integration of this sort might appear
to be straightforward when compared with attempts at
integrating two independent theories, such as Dollard
and Miller’s (1950) efforts to integrate psychoanalysis
and learning theory. Nevertheless, Zaki and Ochsner’s
proposal for integration faces several stubborn challenges of its own.
To highlight issues associated with integration, we
present a hypothetical example. Consider the research
topic “Driving to Fenway Park,” the home of the
Boston Red Sox. In this example, process-oriented researchers are interested in the routes selected by drivers
COMMENTARIES
traveling from their residences to Fenway Park. The
researchers determine optimal driving routes and compare them to the routes selected by drivers. Consistent with their meta-theoretical beliefs, the processoriented researchers evaluate the degree to which
average drivers deviate from the experimenter-defined
optimal route and manipulate situational factors to determine their effect on drivers’ route selection to Fenway Park. In general, process-oriented researchers seek
general laws that describe the inner workings of the
human mind, focus on external factors that influence
it, and are concerned with efficient causation (e.g., an
event or action responsible for an effect; manipulation of independent variable responsible for effect on
dependent variable).
In contrast, accuracy-oriented researchers determine driver accuracy by calculating how close each
driver comes to locating the designated parking lot for
participants at Fenway Park. Drivers are ranked according to their accuracy scores, and individual characteristics are sought that statistically predict drivers’
rank order. Consistent with their meta-theoretical assumptions, accuracy-oriented researchers often focus
on individual differences in judgment accuracy and use
accuracy correlates as clues for enhancing accuracy
and making inferences about underlying processes. In
general, accuracy-oriented researchers study individual variation in human behavior, identify predictor and
outcome variables, and are concerned both with efficient and teleological causation (i.e., people develop
and mature toward desired end state; examples include
Maslow’s need hierarchy and Loevinger’s, 1976, EgoDevelopment).
Although our Fenway Park studies were fictitious,
they encapsulate real differences between process
and accuracy researchers. As a result, we disagree
with Zaki and Ochsner that process and accuracy researchers seek answers to the “same, complex question” (p. 175). For several decades, philosophers of
science have argued that researchers’ epistemological assumptions or “worldviews” may be so different
that there is little or no basis for theoretical or empirical integration (Laudan, 1977; Overton & Reese,
1973; Pepper, 1942). Process-oriented researchers, according to contemporary philosophy of science, subscribe to a mechanistic worldview in which scientific
knowledge is advanced by studying basic elements,
behavior is a function of situational press, and causation is determined by antecedent–consequent relations (i.e., efficient causation). Accuracy researchers,
in contrast, often subscribe to an “organismic” worldview in which scientific knowledge is advanced by
studying the organization of structures within organisms, behavior is a function of organism–environment
interaction, and causation is both quantitative (i.e.,
efficient causation) and qualitative (i.e., teleological
causation).
Overton and Reese (1973) characterized mechanistic and organismic research programs as “incommensurable” due to their distinct meta-theoretical assumptions. And despite the proposal by Overton and Ennis
(2006) to soften the strong stance taken by Overton and
Reese, researchers who seek to integrate process and
accuracy research will confront competing desiderata
relating to priority (e.g., should research study route
selected or successful arrival at Fenway Park), pragmatism (e.g., should research focus on training to enhance
perceiver accuracy vs. process research to advance basic knowledge), and causation (e.g., experimental manipulations that cause selection of mind perception processes vs. practice and feedback to facilitate enhanced
performance), among others. As a result, it behooves
researchers to evaluate the potential benefits of integration compared with its numerous challenges. One
might start this evaluation by elaborating the intermediate and terminal goals of the research; for example,
the intermediate goal might be to implement an interdisciplinary multimethod approach (which the authors
do), and the terminal goal might be to develop theory
that encompasses empirical results from process and
accuracy research (which the authors do not do).
What Is to be Gained by Integrating Process
and Accuracy Research?
In the second section of their article, the authors
purport to lay the conceptual foundation for integrating process and accuracy research. Given the authors’
overarching goal to integrate these two research areas,
the details for achieving it are rather sparse. The first
three paragraphs make the important point that successful integration requires multimethod research. We
agree, and encourage all psychological researchers to
use multiple methods. In the remaining five paragraphs,
the authors describe their preferred social cognitive
neuroscience approach for integrating process and accuracy. The approach involves three key components:
situationally induced cognitive processes, neuroimaging analysis of the experience sharing and mental state
attribution systems, and assessment of mind perception
accuracy. Because participants’ mind perception processes produce “measurable signs that these cognitive
level phenomena leave in their wake” (p. 166), inferences about process usage can be derived from the
observed convergence among external data sources.
Subsequently, integration of process and accuracy is
achieved, according to the authors, by demonstrating
empirical relations between process usage and mind
perception accuracy.
Can Zaki and Ochsner’s proposed strategy successfully integrate two research traditions whose metatheoretical beliefs are considered incommensurable? Has
the process-accuracy conundrum been solved? The
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COMMENTARIES
answer may be yes to both, but questions remain. In
the Where Do We Go From Here? section of their
article, one could construe the authors’ examples as
a recommendation to set aside extant research findings and start a new line of integrated research that is
relatively narrow in scope and relates experience sharing and mental state attribution processes to accuracy.
On the other hand, the authors’ call for integration
could be interpreted by readers as encouragement for
process-oriented and accuracy-oriented researchers to
reconcile and combine their independent research programs. Given the decades of research by process and
accuracy researchers, we hope the intent of Zaki and
Ochsner’s proposal is to integrate extant research findings and develop new research approaches that include
both process and accuracy.
The authors argue that process-oriented and
accuracy-oriented researchers study similar phenomena but that their respective findings have little impact
on each other. Furthermore, they state that combining
the two approaches “could expand our understanding
of social cognition” (p. 159). Although this may be
true, researchers who attempt to integrate theory and
data derived from mechanistic and organismic worldviews may find it difficult to reconcile the differences
in belief systems.
If the authors’ prescription for integrating process
and accuracy is followed, can the two areas be united?
Process- and accuracy-oriented approaches, and the
theory, research, and methods uniquely associated with
them, are not separate Lego structures easily united by
a few common pieces. Instead, the two approaches
are like combining Legos and wooden blocks. Unfortunately, Zaki and Ochsner do not consider the
metatheoretical differences that may hinder integration, and they suggest that researchers will easily integrate the two approaches if given the right tools.
We have not formally surveyed researchers’ opinions
on this topic. However, over the years we have encountered process researchers who either are uninterested in the accuracy question or doubt that it can
be empirically studied. Likewise, we have encountered accuracy researchers who see little relevance
in experimental process research for judgments about
real human beings in naturally occurring social situations.
Consistent with Overton and Reese (1973), the
two approaches might very well be incommensurable;
process-oriented researchers may remain largely uninterested in accuracy, and many accuracy-oriented researchers may view results from experimental research
on process to be uninformative. Despite the possibility
that these two approaches may not be good candidates
for integration, there remains the possibility of an integrated program of research. As previously described,
accuracy research often examines both the extent to
which perceivers accurately judge others and corre198
lates of judgmental accuracy, the latter of which may
suggest processes that influence accuracy. We encourage accuracy researchers to give process issues more
consideration in their own research. Despite questioning the viability of Zaki and Ochsner’s framework for
integration, we congratulate them on their thoughtful
article and acknowledge that it stimulated considerable
thought among the present authors.
Note
Address correspondence to Judith A. Hall, Department of Psychology, Northeastern University, Boston,
MA 02115. E-mail: j.hall@neu.edu or C. Randall
Colvin, Department of Psychology, Northeastern University, Boston, MA 02115. E-mail: r.colvin@neu.edu
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Psychological Inquiry, 22: 200–206, 2011
C Taylor & Francis Group, LLC
Copyright ISSN: 1047-840X print / 1532-7965 online
DOI: 10.1080/1047840X.2011.561133
Everyday Mind Reading Is Driven by Motives and Goals
William Ickes
Department of Psychology, University of Texas–Arlington, Arlington, Texas
The target article by Zaki and Ochsner (this issue)
is an ambitious attempt to provide an overarching conceptual framework for the study of “everyday mind
reading.” This conceptual framework is intended to address two major goals: (a) the integration of research on
the processes by which everyday mind reading occurs
with research on the accuracy of everyday mind reading, and (b) the triangulated integration of all relevant
research findings across three levels of analysis: social behavior, cognitive/affective processes, and neural
engagement.
At the risk of sounding like one of the blind men
who is providing his own limited view of the elephant,
I won’t attempt to evaluate Zaki and Ochsner’s organizational framework in toto. Instead, I limit my commentary to six issues that I hope both the authors and
the readers of this exchange in Psychological Inquiry
will find of interest. These issues concern (a) terminology, (b) the question of whether we humans are
“consummate experts” at everyday mind reading, (c)
the pitfalls of “perceiver-centric research,” (d) the importance of the motivation to be accurate or inaccurate,
(e) linking accuracy/inaccuracy to adaptation, and (f)
linking accuracy/inaccuracy to clinical problems.
the less helpful usages, let’s consider the term mind
perception. The authors like this term because it is
broadly inclusive; I am more critical because I think it
is too broadly inclusive. On the face of it, the term mind
perception could refer to any number of things, some
of which—such as introspection, the Turing test, and
telepathy—don’t seem to fit well beneath the target
article’s current meaning-umbrella. In short, I think
that the term mind perception carries too much surplus
meaning.
With regard to a contrasting example, I noticed that
Zaki and Ochsner sometimes refer to my own term,
empathic accuracy, in an overly restrictive way. After
initially acknowledging that this term refers to a perceiver’s accuracy in inferring a target person’s thoughts
and feelings, they later narrow its meaning to the accurate inference of feelings (i.e., affective states) only.
I object. Empathic accuracy for thoughts is extremely
important, and it should not be ignored or overlooked.
In fact, the results of more than 20 years of research
have shown that (a) people typically report about 67%
more thoughts than feelings (Ickes & Cheng, 2011)
and (b) the distinction between accuracy-for-thoughts
and accuracy-for-feelings can sometimes, though not
often, be important empirically as well as conceptually
(e.g., see Barone et al., 2005).
On the other hand, I am pleased by other terms that
Zaki and Ochsner have chosen to use, and by the way
they have chosen to use them. To be specific, I applaud
and endorse their proposal that we move away from
such perpetually ambiguous and confusing terms as
mentalizing, theory of mind, simulation, and (my nominee for the least felicitous term in this area of research)
theory theory, and instead move toward the wide-scale
adoption of their own preferred substitutes—mental
state attribution (MSA) and experience sharing (ES).
In my opinion, mental state attribution is less ambiguous, less cryptic, more accurately descriptive, and more
heuristic than mentalizing, theory of mind, or theory
theory. Similarly, I believe that experience sharing is
better—on all of these same dimensions—than simulation or simulation theory. (As a quick example of why
experience sharing is less ambiguous than simulation,
note that the authors use the word simulation near the
end of their Mental State Attribution section to refer to
simulating a hypothetical reality through the process
of mental state attribution—a meaning that is easily
Terminology
People are always going to disagree about terminology. I was acutely aware of that when I decided to
reverse the word order in Carl Rogers’s (1957) term accurate empathy in order to emphasize the accuracy portion of the term empathic accuracy. Both elements of
this term have been argued about for decades: empathy
because, from the word’s inception, different people
have used it to refer to (at least) seven or eight different
things (see Ickes, 2003, pp. 61–65; also see Batson,
2009) and accuracy because of its different sources,
which are often confounded and are sometimes artifact
inducing (Cronbach, 1955; Gage & Cronbach, 1955;
Kenny, West, Malloy, & Albright, 2006). Having been
down that road myself, I am quite sensitive to people’s
disagreements regarding terminology.
It’s not surprising, then, that with regard to the target
article I find some of the terms that Zaki and Ochsner
have used (or some of the ways they have used them)
to be more problematic than others. Turning first to
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COMMENTARIES
justified but is ironically quite at odds with its usual
one in this area of research.)
I further applaud and endorse Zaki and Ochsner’s
proposal to extend their preferred terms by adding the
word system to each. This felicitous convention enables us to talk about a mental state attribution system
(MSAS) and an experience sharing system (ESS) in
ways that are not purely hypothetical but instead have
the support of a developing body of neuroscience research findings. Although these terms may eventually
prove to have their own limitations, and although there
is always the possibility that even better terminology
might come along later, I think that the MSA, MSAS,
ES, and ESS neologisms are—for the present at least—
clearly better than the more traditional but also more
problematic terms they are intended to replace. Other
people, of course, may (and, let’s face it, probably will)
disagree.
Are We “Consummate Experts”?
Beginning in their abstract, Zaki and Ochsner (this
issue) state that “accurately understanding the contents
of other minds is a . . . task that humans perform with
impressive skill” (p. 159). Similarly, in the first paragraph of their introduction, they go on to describe us
humans as “consummate experts at this task, accurately
reading the internal mental states that guide other’s behavior with . . . ease” (p. 159).
Sorry, but in my opinion this is sheer hyperbole.
The research on empathic accuracy reveals that we
are substantially better than chance would predict at
accurately inferring the specific content of other people’s thoughts and feelings. However, I believe that
a phrase such as “consummate experts” is unjustified
and misapplied. Instead, I would characterize human
mind-readers as being “as good as we need to be, but
not better than it’s good for us to be.”
This conclusion is based on the insights provided
by empathic accuracy research, in which the empathic
accuracy measure is computed as a ratio of the “total
accuracy points earned” to the “total accuracy points
possible” (Ickes, 2001, 2003). Baseline or chance-level
accuracy typically averages about 5% in this research
(Ickes, Stinson, Bissonnette, & Garcia, 1990; Stinson & Ickes, 1992). The empathic accuracy achieved
by total strangers is substantially better than this 5%
baseline, averaging about 20%. The empathic accuracy achieved by close friends is about 30%—notably
better, but still far from perfect (100%). The average
empathic accuracy of marriage partners is a little higher
yet (30–35%), but again still very far from 100%. The
highest individual scores my colleagues and I see in
our research usually fall in the range of 50 to 60%.
After more than 20 years of research, we have yet to
see any empathic superstars who score in the higher
percentages—the upper 70s, the 80s, or the 90s.
Perhaps, compared to other species on this planet,
we humans are indeed the greatest mind readers that
evolutionary pressures have yet produced. I would hesitate to draw that conclusion because of its sheer presumptiveness, but I suppose it is possible. Before we
congratulate ourselves too much, however, consider the
possibility that it might not be to our advantage to be
“consummately expert” mind readers but that it might
instead be to our advantage to be “good enough, but
not too good” at performing this task.
Biologists tell us that if there is a prime directive in
nature, it is to ensure the survival of one’s own genes
so they can be transmitted to one’s offspring and then
protected until these offspring are able to mate and pass
them on again. In other words, the prime directive is
“Put yourself and your closest kin first—ahead of all
others.” Consider, however, what would happen if we
were so “consummately expert” as mind readers that
we perceived the pain and need of everyone else we
met as acutely and accurately as if it were our own. The
likely outcome of this state of affairs is that the prime
directive would no longer apply: we would repeatedly
sacrifice our own interests for the sake of all others and
put our own genes, and those of our descendants, at
grave risk.
Because the empathic accuracy data suggest an apparent “ceiling” of approximately 60% on our ability
to read other people’s minds, I am inclined to think that
evolutionary pressures worked to calibrate this ceiling
at that particular level. I suggest that these evolutionary
pressures operated over countless generations to eventually optimize the effective range of empathic accuracy in humans so that it was high enough to enable us
to deal effectively with others but was not so high that
we put our genetic futures at grave risk by weighting
everyone else’s interests as heavily as our own.1 I’m
not sure how one would go about testing this hypothesis, but I think it’s a highly plausible one in light of the
available data. So, in response to Zaki and Ochsner’s
later question (Perceivers’ Abilities: Half Full or Half
Empty? section) about whether the accuracy glass is
“half full or half empty,” I suggest that Nature might
reply, “It’s just right.”
On the Pitfalls of “Perceiver-centric Research”
Zaki and Ochsner (this issue) correctly note that the
considerable body of research that has sought to determine the personality traits of “good” versus “poor”
perceivers has generally failed to achieve this goal (for
1 By “us,” I mean to refer to typically developing humans—not
those with a clinically significant organic or functional impairment
of the mind-reading system.
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COMMENTARIES
reviews, see Davis & Kraus, 1997, and Ickes, 2003,
chap. 7). In their The Rise and Fall of Accuracy Research section, Zaki and Ochsner suggest that this failure occurred because personality traits might not be related to perceiver accuracy as “main effect” predictors
but only as components of Trait × Situation interaction
effects.
Although there might be some truth in this speculation (I think more data are needed to make a good case
for it), a more obvious reason for the failure to find
replicable personality predictors of perceiver accuracy
is that the variance in perceivers’ inferential accuracy
scores appears to be quite small in comparison to the
variance in target persons’ “readability” scores. This
was the conclusion my colleagues and I reached when
we applied Kenny’s (1994) social relations model to
the empathic accuracy data in multiple data sets and
found that the average amount of “perceiver variance”
was surprisingly small (Ickes et al., 2000). It is a fundamental tenet of statistics that correlations are smaller
(and therefore less likely to be significant) to the extent
that the range (or variance) of the outcome variable is
restricted. That’s what we have in this case. So a simpler explanation of the failure to find replicable “main
effects” of personality variables predicting inferential
accuracy scores is that there just isn’t much interperceiver variation in these scores for personality trait
measures to account for. (For a related perspective on
this issue, see Hodges, Laurent, & Lewis, 2011.)
There is an important qualification that applies to
these findings. The research just described used only
college students as the participants—a subject selection bias that might well have resulted in a relatively
narrow range of perceiver ability. To counter this problem, we could do what autism researchers do and expand the range of perceiver ability scores by including
in our sample individuals who are known to be exceptionally poor “everyday mind readers.” Perhaps with a
wider range of perceiver ability available to study, the
search for replicable personality predictors of inferential accuracy scores might prove to be more successful.
The Importance of Motivation
People who propose box models have to worry
about the number of boxes they include. If they include too many boxes, their model may get criticized
for failing to achieve theoretical parsimony; if they include too few boxes, their model may get criticized
for failing to include some variable or process that is
crucially important.
With regard to the box model depicted in Figure
2 of the target article and its accompanying elaboration in the text, I find much in this model to admire.
One of its virtues is that it acknowledges the importance of both ES and MSA as potential determinants
202
of inferential accuracy, rather than touting one process
at the expense of the other (for a complementary perspective, see Hodges & Wegner, 1997). Another of its
virtues is that it aspires to achieve a “triangulated” integration of all relevant research findings across three
levels of analysis: social behavior, cognitive/affective
processes, and neural engagement. Time will tell how
successful the model will be in these respects, but there
is no doubting its impressive scope or the high level of
ambition that such an effort represents.
On the other hand, I also find that something crucially important is missing from Figure 2, and that
missing element is the motivation to be either accurate
or inaccurate in one’s inferences about another person’s
current experience.2
The importance of the perceiver’s motivation was
suggested in the very first of our empathic accuracy
studies, when we found that people were more accurate at “reading” the thoughts and feelings of oppositesex strangers who were physically attractive than those
who were less attractive (Ickes et al., 1990). Still, it
wasn’t until several years had passed and the accumulating data had basically beat us over the head with the
importance of the perceiver’s motivation that we began
to give it the theoretical and research attention it deserved (e.g., Ickes & Simpson, 1997, 2001; Simpson,
Ickes, & Blackstone, 1995; Simpson, Ickes, & Grich,
1999; Simpson, Kim, et al., 2011; Simpson, Oriña, &
Ickes, 2003).
Some motives are externally induced (e.g., by a
stranger’s physical attractiveness) and can therefore
be addressed, as Zaki and Ochsner propose, under the
general rubric of “context effects.” However, other motives are carried around inside the perceiver, sometimes
interacting with relevant context variables and sometimes operating independent of them. For example,
there is accumulating evidence that individuals who
score high in anxious attachment become “hypervigilant” (and therefore more accurate) in regard to their
romantic partner’s thoughts and feelings in contexts
in which their relationship appears to be threatened
(Dugosh, Cheng, & Park, 2011; Simpson et al., 1999;
Simpson et al., 2011). This is a case in which the perceiver’s mind-reading motive interacts with a relevant
context variable (perceived relationship threat) to affect
the perceiver’s inferential accuracy. On the other hand,
there is also accumulating evidence that individuals
who score high in avoidant attachment are generally
less motivated to learn what their partners are thinking and feeling (Rholes, Simpson, Trans, McLeish, &
Friedman, 2007; Simpson et al., 1999; Simpson et al.,
2011), an effect that appears to be relatively independent of context.
2 In fact, although the word motivation appears three times in the
reference list of Zaki and Ochsner’s target article, it does not appear
even a single time in the text!
COMMENTARIES
In most of the laboratory research on inferential accuracy, the researcher takes great pains to ensure that
all participants will be comparably motivated to make
correct inferences, accomplishing this goal either by
means of the task instructions, by presenting the task as
a kind of “test,” or even by offering a financial incentive
for good performance (Klein & Hodges, 2001). However, in people’s everyday lives, their motivation to be
accurate or not is far more complicated and variable,
stemming both from people’s long-standing motives
and from the more transient, situationally induced motives that can quickly appear and then, just as quickly,
vanish.
Imagine, for example, that a young man sees a beautiful woman sitting across the room in his local Starbucks. He asks if he can join her and is motivated by
her beauty to hang on her every word, track her every
facial expression, and decode every gesture and bit of
body language in an attempt to understand her better.
Two minutes later, however, he has already lost all of
his patience with her annoying, insistent voice and her
drama-queen attitude, and he is now actively “tuning
her out.”
This is not just a fanciful example. There is accumulating evidence that perceivers can “dial down” or
“dial up” their inferential accuracy skills virtually at
will, in the service of their current motivations3,4 (for
a recent summary of this work, see Smith, Ickes, Hall,
& Hodges, 2011). Consider the following examples.
First, maritally aggressive men are not only more likely
to disattend (i.e., “tune out”) a woman’s complaints
(Schweinle & Ickes, 2007), but the resulting “motivated inaccuracy” predicts their likelihood of abusing their wives (Schweinle & Ickes, 2007; Schweinle,
Ickes, & Bernstein, 2002). Second, anxiously attached
women who listen to their male dating partners being interviewed by an attractive female interviewer are
more likely than less anxious women to closely monitor
(i.e., “tune in” to) their partner’s behavior and correctly
predict his answers to the interview questions (Dugosh
et al., 2011). Third, men who expect to get paid for
greater empathic accuracy appear to exert more effort
to (successfully) achieve it than men who don’t expect
to get paid (Klein & Hodges, 2001). Fourth, studies
by Thomas and Maio (2008) and by Smith and Lewis
(2009) have shown that men dial up or dial down their
interpersonal sensitivity depending on whether they
believe that being sensitive or being insensitive is associated with a socially desirable male gender role.
3 See
Ickes, Smith, Hall, and Hodges (2011).
the motivator tends to affect the group of participants who
have it in a fairly uniform way—leading them to either dial up
or dial down their empathic accuracy more or less in unison—its
influence can be sufficient to produce an effect that is statistically
significant when tested in comparison to the group of participants
who don’t have the motivator.
4 If
After resisting the importance of mind-reading motivation for several years and eventually being forced
by the data to acknowledge its pervasive effects, I can’t
regard any theoretical model of the inferential accuracy
process as complete unless it explicitly addresses the
perceiver’s motivational concerns. In fact, it was this
grudging admission that eventually led Jeffry Simpson
and me to propose our empathic accuracy model, in
which the perceiver’s motivation to be accurate or inaccurate plays a central theoretical role (Ickes & Simpson, 1997, 2001). So, although motivation is an “extra
box” that can’t be neatly and easily integrated into Zaki
and Ochsner’s Figure 2 model, I think they are well advised to try to figure out how to incorporate it. As we
have seen, it is not just a matter of assuring the reader
that “context” makes a difference.
Linking Accuracy/Inaccuracy to Adaptation
Zaki and Ochsner (this issue) are correct in calling for more attention to the links between inferential
accuracy and adaptation (Linking Processes to Social
Well-Being section). To put it simply, if evolutionary
pressures have operated to promote our ES and MSA
capabilities, we should expect that there are adaptive
advantages associated with these capabilities.
As Zaki and Ochsner note, these capabilities are
organized within a dynamic system. As Ickes et al.
(2011) have noted, this system enables us not only to
understand others but to modulate the degree of our
empathic insight, dialing it up or dialing it down to fit
the demands of the situation as well as our own personal
needs and motives. According to Ickes and Decety
(2009), current neuroscience views of this system
challenge . . . the notion that there are domain-specific
“theory of mind” modules in the brain. Alternative
accounts (Decety & Lamm, 2007; Stone & Gerrans,
2007) argue that (a) elementary computational operations have evolved to perform social functions, and
(b) evolution has constructed layers of increasing complexity, from nonrepresentational to representational
and meta-representational mechanisms, which may be
sufficient to provide a complete understanding of human social cognition. (Ickes & Decety, 2009, p. viii)
Given the vast reach and flexibility of this system, our personal adaptation will on most occasions
be served by achieving greater accuracy in our understanding of others but will on other occasions be served
by our becoming less accurate (or even willfully inaccurate). Consider, for example, the plight of certain dating couples who participated in the study by Simpson
et al. (1995). The members of these couples reported
that they were highly dependent on each other, yet they
were also afraid that their relationship might not last.
When they were put into an experimental situation in
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COMMENTARIES
which they had good reason to believe that they were
each harboring disloyal thoughts and feelings (about
their attraction to alternative partners), they did a remarkably poor job of inferring each other’s thoughts
and feelings. In fact, their empathic accuracy scores
were found to be at chance-baseline levels (significantly below the average level that even total strangers
typically achieve).
And was this a bad thing? No. As it turned out,
the motivated inaccuracy displayed by these couples
proved to be highly adaptive. These highly threatened,
highly inaccurate couples were all still together several
months later, whereas close to 30% of the less threatened but more accurate couples in the study had broken
up by then. As this finding illustrates, sometimes our
most adaptive response is to “not go there”—to stay out
of our partner’s head and to not know because we do
not want to know what he or she is currently thinking or
feeling. The fact that such “motivated inaccuracy” can
occur—and can help to sustain the relationship in the
face of a rather intense short-term threat—suggests that
the cognitive system that underlies our mind-reading
skills is sufficiently flexible to enable us to adaptively
dial down these skills as well as to dial them up.
In most situations, of course, our motive is to be
more accurate—not less. For example, increased accuracy is an adaptive response when your romantic partner needs help and support, and it’s your job to figure
out what kind of support is most needed. In this case,
the available research shows that the more empathically
accurate perceivers provide the most helpful instrumental support, presumably because these perceivers
can read their partner’s mind well enough to know exactly what he or she needs (Verhofstadt, Buysse, Ickes,
Davis, & Devoldre, 2008; Verhofstadt, Davis, & Ickes,
2011).
Finally, consider the problem faced by young adolescents who must deal with the stresses of poor peer
relationships: experiencing social rejection and victimization and having relatively few friends. When Gleason, Jensen-Campbell, and Ickes (2009) examined how
well young adolescents coped with this problem, they
found that those with a high level of empathic accuracy coped the best. These adolescents were relatively
unaffected by their poor peer relationships, whereas
their less accurate counterparts wound up depressed
and anxious, and were more likely to “act out.”
In summary, the empathic accuracy literature already provides compelling examples of the kind of
research that Zaki and Ochsner have called for more
of: research that links empathic accuracy to the important adaptations that individuals make in their everyday lives. Most of the time, such adaptations require us
to dial up our everyday mind-reading skills. There are
some occasions, however, when the adaptations require
us to dial down our everyday mind-reading skills—to
204
keep ourselves from not knowing things that do not
appear to be in our current interest to know.
Linking Accuracy/Inaccuracy to Clinical
Problems
The empathic accuracy literature has also addressed
Zaki and Ochsner’s call for more research that links
people’s accuracy or inaccuracy to various clinical
problems (Contributions to Clinical Approaches section). As my colleagues and I have noted elsewhere
(Ickes, 2009; Rollings, Cuperman, & Ickes, 2010;
Schmid Mast & Ickes, 2007), researchers have already
examined the role of empathic accuracy in
r autism and Asperger syndrome (Demurie, De Corel,
r
r
r
r
r
& Roeyers, 2011; Ponnet, Buysse, Roeyers, & De
Clerq, 2008; Ponnet, Buysse, Roeyers, & De Corte,
2005; Ponnet, Roeyers, Buysse, De Clerq, & Van
Der Heyden, 2004; Roeyers, Buysse, Ponnet, &
Pichal, 2001)
attention-deficit/hyperactivity disorder (Demurie
et al., 2011)
borderline personality disorder (Flury, Ickes, &
Schweinle, 2008)
marital conflict interactions (Simpson et al., 2011;
Simpson et al., 2003)
the social cognition of maritally aggressive/abusive
men (Clements, Holzworth-Munroe, Schweinle, &
Ickes, 2007; Robillard & Noller, 2011; Schweinle
& Ickes, 2007; Schweinle et al., 2002; Schweinle,
Ickes, Rollings, & Jacquot, 2010)
the training of student therapists (Barone et al.,
2005; Marangoni, Garcia, Ickes, & Teng, 1995).
Because the empathic accuracy paradigm is still
relatively young, I have been impressed by how quickly
all of this clinical/applied research has been done. The
rapid progress of this work leads me to believe that it is
only a matter of time until researchers who study other
forms of inferential accuracy will begin to follow this
lead.
Conclusion
In summary, I regard Zaki and Ochsner’s target article as an ambitious, worthy, and even heroic effort
to bring about an overarching conceptual organization
that is long overdue. These authors have my sincere
admiration for what they have already achieved. Their
general model of the mind-reading process is incomplete, however, because it leaves out the crucial element of the perceiver’s motivation—the element that
20 years’ worth of research on empathic accuracy has
consistently (and insistently) emphasized.
COMMENTARIES
Note
Address correspondence to William Ickes, Department of Psychology, University of Texas at Arlington, Box 19528, Arlington, TX 76019. E-mail:
ickes@uta.edu
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Psychological Inquiry, 22: 207–209, 2011
C Taylor & Francis Group, LLC
Copyright ISSN: 1047-840X print / 1532-7965 online
DOI: 10.1080/1047840X.2011.568266
History, Dialectics, and Dynamics
David A. Kenny
Department of Psychology, University of Connecticut, Storrs, Connecticut
My commentary more elaborates on the Zaki and
Ochsner (Z&O; this issue) target article than critiques
it. Before I begin, the reader should be warned that
I make no claims of being a neuroscientist or for that
matter even a social-cognitive researcher. I do not know
the difference between the somatosensory and the anterior cingulated cortex. “Cytoarchitectonic properties
of anatomical connectivity” is something I gladly know
nothing about. For those sections of the article that are
neuroscientific, I offer no commentary. I do comment
on history, the dialectical dance between accuracy and
bias, and the dynamics of social perception. Not very
surprisingly, I view their work through the lens of my
own work.
were practicing researchers to know what to do? Part of
the demise of accuracy was due to the great uncertainty
as to how to analyze accuracy data.
Third, I think that Cronbach and others thought that
researchers should not be studying accuracy. They believed that people were not really very accurate, or if
they were accurate, it was because they were biased.
It is perhaps ironic that I am now engaging in mind
reading of Cronbach and others, but I raise this issue
because at the time many came away from reading
Cronbach believing that people were not accurate. For
example, Gage and Cronbach (1955) stated that “social perception . . . is dominated . . . by what the Judge
brings to it than by what he takes in during it” (p. 420).
Clearly they are suggesting that if we are to understand social perception, we would be much better off
in studying biases than accuracy. Social psychologists
were very eager to document these biases (Krueger &
Funder, 2004).
Fourth, I think too it is important to realize that accuracy researchers did not all of sudden become cognitive
scientists. Rather the movement in social psychology
was to study attitude change, and eventually when it
returned to the study of person perception the focus
was on attribution theory. One of the early pioneers
in attribution research was Daryl Bem (1967), who
described himself at that time as a radical behaviorist, which is hardly social cognitive. Moreover, neither
of the two major theoretical contributors to attribution theory, Edward “Ned” Jones and Harold Kelley, to
my knowledge ever described themselves as “socialcognitive researchers.” Jones was downright dubious
about social cognition, more for methodological than
theoretical reasons, and Kelley viewed himself more
as a relationship researcher than as a social cognitive
researcher. All of which is not to say that eventually
the successor to accuracy research was the social cognitive approach. However, their triumph occurred more
than 25 years after the Cronbach critique.
History
My first set of comments concern history. Although
Z&O do make clear that earlier accuracy research focused on individual differences, I do not think that they
emphasize enough that this is at the heart of reason for
the demise of interest in accuracy research. That is, if
it is the case that in normal populations there are very
small differences between people in their skill to read
others, then measuring those individual differences and
their correlates is very difficult. As we argued in Kenny
and Albright (1987), researchers in the late 1950s inappropriately concluded that because individual differences in accuracy were weak, people were inaccurate.
Obviously, such reasoning is fallacious, but it is what
happened. To see that individual differences are weak
in normal populations, consider, for example, the rather
extensive analysis of individual differences in lie detection by Bond and DePaulo (2008), who found that
a good lie detector (someone who is 1 SD above the
mean) has only about a 1.5% chance more of being
right than a poor lie detector (someone who is 1 SD
below the mean). They state, “Lie detection accuracy
is not a reliable individual difference” (p. 486). One
of the key ideas in Z&O is that by looking at clinical
populations, we have a much better chance of finding
individual differences.
A second point is that although Cronbach laid out a
clear way to study accuracy in 1955, just 3 years later
(Cronbach, 1958) he said it was all wrong. If an expert
like Cronbach might change his whole approach, how
The Dance Between Bias and Accuracy
The Z&O article emphasizes two very different
lines of work on social perception. One is work on
the process of judgment, and the other is work on
whether those judgments are accurate. Z&O nicely
document how these two lines of work have operated
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COMMENTARIES
independently. However, as they correctly argue, a
complete analysis requires their simultaneous study.
Bias (what is essentially what Z&O call process)
and accuracy are usually thought of as polar opposites.
One can be biased or accurate, but one cannot be both.
It might be better to think about bias and accuracy
dialectically and allow for the two opposites to simultaneously exist. Echoing a point made by Cronbach
(1955), bias, that is, assumed similarity, can lead to accuracy. Moreover we can, by having a biased and therefore incorrect view of reality, create that reality through
the self-fulfilling prophecy. Bias and accuracy are not
so much opposites, but they are dialectical dance partners.
I have been grappling with these issues for nearly 40
years. In my very first empirical publication (Curry &
Kenny, 1974), I examined how perceived similarity and
understanding one’s roommate’s personality and values relate to interpersonal attraction. In Berman and
Kenny (1976), we examined how perceivers were able
to recognize the true correlation in traits, as well as be
biased by the halo effect. In the 1980s, I finally figured out how I should have done the analyses in Curry
and Kenny (1974) and I wrote with Albright (1987;
what I think is the best paper I have ever written) a
post-Cronbachian approach to accuracy research. In
Levesque and Kenny (1993), we took that approach
and placed people in a situation in which presumably
they were totally biased (i.e., zero acquaintance), but
they achieved impressive accuracy. In Kenny, Bond,
Mohr, and Horn (1996), we were able to show that
perceivers were able to know how much two people
like one another while they were biased by assumptions of balance, reciprocity, and agreement with self.
Kenny and Acitelli (2001) highlighted the interplay
between bias and accuracy and showed that romantic
partners could be both biased and accurate in their perceptions of their partner; moreover, we showed how
they were accurate by being biased. Finally, in Kenny
(1991, 2004) I discussed a theoretical model of person perception which discusses the interplay between
accuracy and bias.
I can remember in the 1990s discussing these issues with Ziva Kunda, and she suggested that I should
try to investigate how both biases and truth can simultaneously influence judgments. Nearly 20 years later,
Tessa West and I (West & Kenny, 2011) have undertaken this very project. We have created the truth and
bias model (T&B). Z&O suggest that multiple processes simultaneously operate, and T&B allows for
multiple biases and the truth to determine judgment.
The T&B model complements rather than provides an
alternative to the Gibsonian, Brunswikian, and Signal Detection Theory approaches. It also can, given
the proper measurements, design, and analysis, measure individual differences in bias and accuracy and
the correlation between bias and accuracy. It is very
208
much in the spirit of Z&O’s call for uniting process
and outcome research.
Dynamics of Perception
There is one point in Z&O to which I want to call
special attention: “time-varying dynamics of the target’s state” (p. 168). Classically, most accuracy researchers used a standard set of judgments: All perceivers are given the same questions, and the issue is
whether the perceiver is right or wrong on those questions. However, although it might be useful to know
that my boss is generally an angry person, it is much
more important for me to know when she is angry and
when she is not. In particular, it is important for me
to be sensitive to the transition from happy to angry
and vice versa. Being sensitive to changes is what is
important. As Z&O state (harkening back to Cronbach
and Gage), if you just look at any one time to see if
I know how angry she is, my accuracy will be largely
be due to my tendency to see her as angry (i.e., what is
called in T&B directional bias).
T&B emphasize the procedure used by Levenson
and Ruef (1992) of a perceiver viewing a target and
continuously rating the target’s emotions. One nice feature of this approach is that it can be tailored to different
populations. So, for instance, autistic children can try
to read the emotions of their parent. Another nice feature is that the approach focuses on change. We should
take a lesson from research on the unitization of events.
Observers agree hardly at all in terms of parsing events
into units (Newtson & Engquist, 1976). However, what
they do agree on is “when something happens,” or what
are called break points. The Levenson and Ruef procedure can be used to determine whether people can
recognize when a significant change occurs.
Methodologically, Cronbach (1955) was multivariate, but he looked at different variables, not the same
variable moving trough time. My two major publications on the measurement of accuracy (Kenny &
Albright, 1987; Kenny & Winquist, 2001) focused too
much on the snapshot of one point in time and not on
the dynamics of social perception. Fortunately, using
T&B (West & Kenny, 2011), we outline a method of
the dynamic study of accuracy. I would think T&B
could be adapted for the analysis of the Levenson and
Ruef (1992) procedure.
Conclusion
Much of the discussion about accuracy research
in social and personality psychology over the last 25
years is much like the discussion of sex by adolescent
boys: They like to talk about why it is good to do, but
they hardly ever actually do it. I think we have finally
COMMENTARIES
turned a corner in accuracy research where we now
have groups of researchers who have been studying
accuracy, not just talking about it. What I find most
refreshing about Z&O is that they are actually doing
it, not just talking about doing it.
Acknowledgments
I thank Tessa V. West who provided with comments
on an earlier version of this article.
Note
Address correspondence to David A. Kenny, University of Connecticut, Department of Psychology, 406
Babbidge Road, Unit 1020, Storrs, CT 06269–1020. Email: david.kenny@uconn.edu
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Psychological Inquiry, 22: 210–216, 2011
C Taylor & Francis Group, LLC
Copyright ISSN: 1047-840X print / 1532-7965 online
DOI: 10.1080/1047840X.2011.567960
How to Make Social Neuroscience Social
Christian Keysers
Social Brain Lab, Netherlands Institute for Neuroscience, Amsterdam the Netherlands; and Department of
Neuroscience, University Medical Center Groningen, Groningen, the Netherlands
Lawrie S. McKay
Social Brain Lab, Netherlands Institute for Neuroscience, Amsterdam, the Netherlands
Social neuroscience has had a boost over the last
two decades. There have been a number of dominant
themes in the course of this research, two of which are
(a) the identification of systems involved in attributing beliefs, true or false, to others (e.g., Amodio &
Frith, 2006; Ochsner et al., 2004; Saxe, Carey, & Kanwisher, 2004) and (b) the discovery that brain regions
involved in our own actions, emotions, and sensations
are recruited while we witness those of others (e.g.,
Iacoboni, 2009; Keysers & Gazzola, 2006; Keysers &
Gazzola, 2009; Rizzolatti & Craighero, 2004). As Zaki
and Ochsner (this issue) correctly conclude, the lion’s
share of this research has focused on characterizing the
cognitive and neural processes perceivers engage when
encountering other minds. This approach has two conceptual limitations. First, it typically ignores whether
the engagement of these processes leads to accurate
inferences about those minds. Second, it is not social
in the strong sense, as experiments typically only measured the brain activity and social perception of one
isolated individual (the observer) while ignoring the relationship between that individual’s brain activity and
perception and those of the target or other individuals.
In their target article, Zaki and Ochsner (this issue)
advocate a refreshingly new perspective. They argue
that the goal of mind perception is (a) to accurately
perceive what goes on in others and (b) to ultimately
help us interact better with others and be happier. Accordingly, one should ask not only what brain regions
are recruited during mind perception, but also which
of them lead to an accurate perception of what is on
the mind of others and, to a lesser extent, which of
them promote social functioning and happiness. Surprisingly, except for Zaki and Ochsner’s own work,
there is indeed very little empirical work addressing
these utilitarian questions.
In the field of social neuroscience, it is rare to find
publications that propose profoundly novel approaches
to the study of the social brain. We think that this is
one of those rare articles that inspire us to look at the
entire enterprise of social neuroscience from a novel
angle. In what follows, we discuss four issues inspired
by the target article that we hope extend and refine
the ideas that Zaki and Ochsner have seeded. First, we
argue that systematically inaccurate mind perception
can be highly instructive about how people understand
the minds of others. Second, we offer some examples
where experience sharing is perhaps a more useful resource than Zaki and Ochsner presume. Third, we look
at some limitations of measuring accuracy based on
the reports of targets and observers, paying particular
attention to “insight.” Finally, and most important, we
look at three alternative approaches that are conceptually different but related to the accuracy research of
Zaki and Ochsner. All of these issues help to make
social neuroscience social again, by directly studying
the relationship between multiple individuals—be it
by comparing the brain activity of multiple individuals
or by comparing brain activity with the quality of the
individuals’ social relationships.
Understanding Is Understanding—Even if
Inaccurate
A key point made in the target article is that mind
perception has the aim of being accurate and that investigating regions of the brain in which activity correlates with accuracy is a way to focus in on the brain
mechanisms that underlie our understanding of other
people’s minds. We fully agree that this is a legitimate and understudied question. However, we believe
it would be misleading to state that a brain region contributes to our understanding of other people’s minds
only if its activity is correlated with an accurate report
of the intentions or motivations of the observed agent.
For example, while viewing a science fiction movie,
we spontaneously attribute intentions and emotions to
robots. Brain imaging has shown that when we observe
the actions of a human (Figure 1a), the brain activity of
the agent and the observer resemble each other in the
mirror neuron system. Of interest, when we observe
the actions of a robot, our brain activity looks very
similar to the activity while observing a human perform similar actions (Figure 1b, right). However, this
activity is now very dissimilar from that of the robotic
agent. Hence, activity in the mirror neuron system of
the observer can be said to be an accurate mirror of the
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COMMENTARIES
Figure 1. (Mis-)understanding robotic actions. Note. a. When subjects watch a human grasping a cocktail glass (left), the brain
activity of the agent (middle) resembles that triggered in the mirror neuron system of the observer (right). Hence, the brain activity
in the observer is a relatively accurate mirror of the state of the brain of the agent. b. When observing a robot grasp a glass (left),
the “brain” activity of the robotic agent (middle) looks rather different than that of the observer (right). The brain activity of the
observer is thus an inaccurate mirror of the state of mind of the agent, which is likely to underlie the anthropomorphic attribution
of humanlike intentions and emotions to robots. We argue that this inaccurate brain activity contributes to our (false) understanding
of robots just as much as the accurate mirroring of the human agent contributed to our understanding of humans. Brain activity was
drawn on outlines of the brain based on the findings of Gazzola et al. (2007).
activity in the human (Figure 1a) but an inaccurate mirror of the activity in the robot (Figure 1b). If we follow
the logic of Zaki and Ochsner, activity while observing
the human action would contribute to the understanding of the agent, because accurate, whereas the same
activity while observing the robot would not, because
it is inaccurate. Indeed, if one were to ask the robot how
it felt during the actions for the purpose of correlating
its report with that of the observing human, one has
reason to doubt that the report (if one were even to get
one) would closely match that of the human observer.
We would argue, however, that the same brain activity would trigger a similar understanding of both agents
and that this similarity tells us a lot about how we understand the actions of humans and robots, namely,
by anthropomorphizing—that is, assuming that their
states are similar to ours (Gazzola, Rizzolatti, Wicker,
& Keysers, 2007; and see our Figure 1a). Although
there is thus a place for the identification of accurate
mind perception, we would argue there is also a place
for investigating inaccurate mind perception.
Experience Sharing and the Gut Feeling of
Deception
Zaki and Ochsner suggest that experience sharing is
a limited resource in accurately decoding the internal
states of others. The reasons they cite are that people
often attempt to conceal their internal states from observers for a variety of reasons, and that even when
they do not, the cues presented to the observer are
ambiguous. Is it really the case that deception is not
accompanied by observable and diagnostic behaviors
that can be shared to detect deception? Posed emotions
differ in subtle but detectable ways from true emotions (e.g., McLellan, Johnston, Dalrymple-Alford, &
Porter, 2009), and deceit is accompanied by subtle cues
(e.g., fleeting gaze, etc.; Burns & Kintz, 1976). We
would argue that sharing these behaviors might trigger
a feeling of unease that could evoke a “gut feeling” of
mistrust in the sharing observer. Our point is, therefore, as argued previously (Keysers & Gazzola, 2007),
that discussing whether theory or simulation are better routes to mind perception is rather sterile. A more
fertile approach might be to investigate how these two
processes integrate to generate an understanding—or
misunderstanding—of the mind of others.
Self-Report and the Bottleneck of Insight
Zaki and Ochsner (this issue) propose a technique
to measure empathic accuracy. A target is filmed for
a while and later asked to give a moment-to-moment
report of how she felt. An observer then views this
film and reports, on a moment-to-moment basis, how
she thought the target had felt. Empathic accuracy is
then simply the correlation between the two time series of moment-to-moment reports. To apply this measure to neuroscientific data, one then shows many such
movies and examines if brain activity in certain regions
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COMMENTARIES
is higher during the movies where accuracy is higher.
This technique indeed represents an original and innovative approach to correlating two different and important levels of investigation: behavior and brain activity.
As highlighted by Zaki and Ochsner, the ability of an
observer to make accurate judgments about an actor’s
emotions is influenced by the expressivity of the actor
and the empathic abilities of the observer (Gross &
John, 1997; Zaki, Bolger, & Ochsner, 2009). However,
given that the accuracy measure depends on the correlation of reports, there is another factor that influences
both sides of the measurement, namely, alexithymia,
which is the capacity of both parties to obtain insights
into their own inner states, or its reverse.
Figure 2 shows how this can influence the reports
of both the actor and observer, and hence the correlation between their reports. In essence, the self-report
of actors is limited by their insight into their own emotions, such that even if they are highly expressive, they
may be inaccurate in reporting their own internal state.
Furthermore, if the observer has a well-tuned internal simulation/mirroring system, she might be able to
generate inner states that are a highly accurate mirror
of the inner states of the target. But if her insight is
poor, she may inaccurately report the content of these
simulations and generate low interreport accuracy. It is
important to note that an observer’s behavioral reaction
to a target is determined by many levels of representation of the feelings of the target. It is well known that
observers sometimes unconsciously mimic the posture
and tone of voice of a target, showing that nonconscious
shared representations of the behavior of the target actually influence the behavior of the observer. At the
same time, we have all experienced internal discourses
in which we reason, “She doesn’t know that I know
that Bob has left her, so I had better find an indirect
way to ask her how she feels about that.” Finally, verbal
reports are sometimes a direct component of our behavioral reaction to others: “You obviously look sad,
what happened?” Hence, in the situated perspective
adopted by Zaki and Ochsner, where what matters is
ultimately to generate the most appropriate behavioral
reaction, focusing on interreport correlation might underestimate the overall empathic accuracy because insight will act as a bottleneck, through which potentially
more accurate and behaviorally relevant nonconscious
representations of the targets feelings are filtered out.
Similarly, and perhaps more important, in the case in
which the target has poor insight whereas the observer
has a finely tuned simulation system and good insight,
the report of the observer may actually be a more accurate representation of the target’s inner states than
the target’s self-report. This possibility is arguably the
main motivation to seek the help of psychotherapists
or friends in moments of great emotional turmoil: We
intuitively feel that an external observer can sometimes
gain insights into our own feelings that are more accurate than our own insights.
Figure 2. Empathic accuracy, as measured by the correspondence in time between two reports (how the target feels and how the
observer thinks the target feels), is influenced by many variables. In addition to the expressivity and empathy of target and observers,
the insight that both parties have in the hidden internal states of their own brains and body also limits the final measured accuracy.
Investigators should therefore keep in mind that an observer might generate a very accurate simulation of the targets feelings, and
hence react appropriately to the targets emotions, while still generating comparatively low measured empathic accuracy if one or
both of the individuals have poor insight. A direct brain-to-brain approach, however, can provide different insights into the accuracy
with which the covert neural states of the two participants resonate with each other.
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COMMENTARIES
A key point here is, thus, that although Zaki and
Ochsner’s approach is an original and inspiring one to
start shedding light on the neural basis of accurate mind
reading, one needs to be aware that it is limited or filtered by insight. Of importance, the approach does not
allow for a direct quantification of the distorting effect
of a lack of insight because it has no access to the hidden mental states that the observer is actually trying to
read or the hidden mental states that observing the target has triggered in the observer. One of the great values
of neuroscience in the social and cognitive domains is
that it can provide insights into the mind without the
filtering effect of self-reports. Next we describe three
emerging new ways to look at neuroimaging data. Just
as the approach of Zaki and Ochsner is inherently social because it analyzes neuroimaging data based on
the correlation between the self-reports of a target and
an observer, these new approaches make social neuroscience truly social. But unlike the former, they do not
suffer from the filtering effect of self-report. We believe that combining all four approaches paves the way
to a profoundly new way of doing social neuroscience.
Inherently Social Neuroscience Techniques
Directly Comparing the Brain Activity of
Target and Observer
When the first publications on hyperscanning came
out (Montague et al., 2002), people were excited about
the technical prowess of scanning two people simultaneously. However, although many felt that hyperscanning was going to be the answer to important neuroscientific questions, people failed to deduce quite what
these questions were going to be.
In recent articles, we examined the relationship
between the brain activity of an observer and a target while they were trying to read each other’s mind
(Schippers, Gazzola, Goebel, & Keysers, 2009; Schippers, Roebroeck, Renken, Nanetti, & Keysers, 2010).
For this experiment, we used the game of charades,
in which one partner is given a word and the instruction to use gestures to convey the meaning of the word
to the other partner. If the other partner guesses the
word correctly, the team wins a point. Because we
could measure the brain activity of the gesturing partner while generating the gestures and of the observing
partner while trying to guess the word, we could use a
novel approach to examine social interactions. Rather
than asking, like Zaki and Ochnser, whether activity
in a certain brain region predicts how accurately the
observer can guess the word that is on the mind of the
gesturer (a correlation between interpersonal agreement and neural activity), we could directly ask which
brain regions contained accurate information about the
state of the other person’s brain.
Social interactions often introduce significant delays between the minds of two people. Imagine having
to gesture “violin player” to your partner. The brain
activity representing the verbal description will be the
first thing generated in your brain. You will then generate a plan of how to gesture it in your motor cortices.
Finally you will execute the gesture. Your partner will
see the gesture unfold over 1 or 2 s and integrate that
visual information into a motor representation of the
act of playing the violin in her motor system. She will
finally transform this motor description into a verbal
one. The corresponding motor and verbal descriptions
in the two brains will thus occur seconds apart. We,
therefore, needed to develop a technique that can detect corresponding neural representations in the two
brains without knowing exactly when they will occur relative to each other. Granger causality provides
a method suitable for such analyses (Schippers et al.,
2010). When applied to data across two brains, it essentially asks whether activity in the recent past of the
target’s brain can predict the present brain activity of
the observer or, seen the other way around, whether the
brain activity of the observer contains accurate information about the recent past of the brain activity of the
target. How many seconds of brain activity are considered the “recent past” of the target’s brain activity is a
free parameter of this approach. We found that looking
about 4 s into the past of the target was appropriate for
the kind of gestures we examined.
As previously mentioned, we had argued a number
of years ago—without relating to accuracy—that it was
futile to discuss whether the mirror neuron system or
mentalizing brain regions are more important for understanding others (Keysers & Gazzola, 2007) and that
the two systems probably work together whenever we
have to deduce thoughts from actions. Surprisingly,
traditional analyses methods found that while trying
to read what word was on the mind of the target in
the game of charades, only regions of the mirror neuron system augmented their activity compared to a
baseline—mentalizing brain regions had activity that
was no larger than during the baseline (Schippers et
al., 2009). However, directly comparing the brain activity between the target and observer, as previously
explained, revealed that both mirror neuron system regions and mentalizing regions had activity in the observer that contained information about the state of the
motor cortex of the target (Schippers et al., 2010). This
finding has four implications. It confirms our idea that
the mirror neuron system and mentalizing brain regions
both contain accurate information about the content of
a target’s brain/mind. It shows that it is possible to identify which parts of an observer’s brain contain accurate
information about the brain/mind of a target, without
needing to rely on self-reports that are potentially filtered by a lack of insight. It also affords the neuroscientist with another truly social method, by showing that
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COMMENTARIES
in addition to the between-report-accuracy approach
of Zaki and Ochsner, another viable method exists that
does not study brains in isolation. Finally, betweenbrain analyses like ours depend not on the overall level
of brain activity in a region but on the pattern of temporal fluctuations around this overall level. This gives
these methods the power to detect the involvement
of mentalizing regions in the medial prefrontal cortex
during communication that, as they are part of the default network, classical methods failed to identify due
to their tendency to reduce their activity during a task
rather than increasing it. Making social neuroscience
truly social using between brain analyses is thus not
only conceptually elegant, it generates new insights
into the working of the social brain.
At least two other publications have since followed a
similar route to examining the neural basis of mind perception. Stephens and collaborators (Stephens, Silbert,
& Hasson, 2010) have elegantly shown that the neural
basis of speech perception can be identified by comparing the brain activity of the speaker and the listener.
Anders and collaborators (Anders, Heinzle, Weiskopf,
Ethofer, & Haynes, 2010) have shown that the patterns
of activation in regions of an observer’s brain contain
information about the activity in the corresponding regions of the brain of a target who is expressing emotion
through facial expressions.
Directly Comparing the Brain Activity of
Multiple Observers
Although the aforementioned approach looks directly at the concordance between the brain activity of
an observer and a target, another successful approach
has been to examine the concordance between the brain
activity of multiple observers. The rationale behind the
two approaches differs significantly. The former directly examines what brain activity in an observer is
an accurate representation of that of the target. In this
way it is social and similar to the approach of Zaki and
Ochsner in its concentration on accurate representations of other people’s minds. As previously discussed
in the example of robotic mind perception, one might
argue that neural processes that systematically lead
to the misunderstanding of other people’s minds are
as much a part of mind perception as those that lead
to accurate understanding. Examining the concordance
between the brain activity of many observers of a target
allows us to identify regions generating both accurate
and inaccurate perceptions of other people’s minds.
In a seminal article, Hasson and collaborators (Hasson, Nir, Levy, Fuhrmann, & Malach, 2004) have pioneered this approach. They showed the Sergio Leone
movie The Good, the Bad and the Ugly to five viewers while measuring their brain activity. The authors
then looked for voxels in the brain in which the brain
activity, during the vision of certain scenes, went up
214
and down in synchrony. This approach identified a
number of brain regions that were synchronous across
viewers at certain points in the movie. The investigators then looked at the content of the movie at the
time these regions became synchronized across viewers to determine the content of the representations that
were being systematically generated in these regions
across viewers. One of the regions showing this property was the fusiform face area, which synchronized
across viewers when scenes including faces were being watched, elegantly confirming what we already
knew about this region from more classical experiments. More important, however, they also found that
the somatosensory cortices synchronized across viewers while watching actors manipulate objects in their
hands. As such, this social technique unravelled the
involvement of somatosensory regions in social perception without directly aiming to do so. As in the
aforementioned case of observer-target comparisons,
performing truly social neuroscience hence not only
confirms what we know from studying brains in isolation but also generates new knowledge. Unaware of
their findings, we were performing, in parallel, a study
that directly tested our hunch that somatosensory regions might be important in social perception (Keysers
et al., 2004): We touched participants on their legs
and showed them movies of other individuals being
touched. By comparing the location of activation in
viewers of touch and in people experiencing touch, we
could show that somatosensory cortices were activated
in both, confirming (without aiming to do so) the validity of Hasson et al.’s interviewer correlation approach.
Thanks to these experiments, we finally realize how
important somatosensory regions are in mind perception (Keysers, Kaas, & Gazzola, 2010).
Relating Brain Activity to Levels of Social
Functioning
A fundamentally different way to make neuroscience social is to relate brain activity not to accuracy or the brain activity of others, but to the level
of social functioning of participants. Are people with
more activity in a certain region better in the real social situations that we face in the world “out there”
but that are hard to simulate in the scanner environment? In a recent study we showed that activity in the
inferior frontal gyrus (thought to form a critical part
of the mirror neuron system) of autistic individuals
increases with age (Bastiaansen et al., 2011). To examine whether this change of activity was meaningful for
real social life out there, we asked the participants and
a close relative of each participant to judge the level
of functioning of each participant in the social world.
Questions included how many hours participants spend
alone, how many friends they have, how often they go
to parties, and whether they have regular employment.
COMMENTARIES
By relating brain activity to the responses of the participant and a close relative (to overcome the problem
of self-report), we could show that increased activity
in the inferior frontal gyrus indeed went along with
better social functioning where it really matters: out
there in the real social world. Looking at brain activity
and social functioning in this way confirmed what people had hypothesized for a long while: that activity in
the mirror neuron system is socially adaptive. Pfeifer
and her collaborators have also shown that increased
activity in this region goes hand-in-hand with higher
interpersonal competence in typically developing children (Pfeifer, Iacoboni, Mazziotta, & Dapretto, 2008).
Summary and Conclusion
Social neuroscience used to be a rather unsocial enterprise. The brain activity of observers was measured
in isolation while viewing a variety of stimuli. The only
social aspect was that the stimuli happened to involve
other human beings. Over the last few years, social neuroscience has seen the emergence of a number of truly
novel approaches. One of these is excellently described
in the inspiring target article of Zaki and Ochsner. In
this commentary, we point out a number of issues that
arise when using this approach: first, that they may
have underestimated the utility of experience sharing;
second, that inaccurate understanding can shed light on
mind perception; and third, that this approach is sensitive to the degree of insight the target and observer
have into their own inner states. Most important, however, we hope to have shown that three other truly
social approaches have emerged in the recent past: direct comparisons of the brain activity of the observer
and target, direct comparisons of the brain activity of
many observers and comparisons between brain activity in the lab, and social competence in the real world.
Together, these four approaches come close to what
one might call a “paradigm shift” in neuroscience. The
brain is no longer an isolated stimulus-processing machine, with social stimuli just being another type of
sensory input. The brain is seen as a device that resonates with the brain of other individuals to allow us
to interact effectively with them. Understanding their
minds is no longer an end to itself but a means to
successful social interactions. In this approach, social
neuroscience becomes truly different from other forms
of neuroscience. Social neuroscience becomes truly
social.
Note
Address correspondence to Christian Keysers, Social Brain Lab, Netherlands Institute for Neuroscience,
an Institute of the Royal Netherlands Academy of Arts
and Sciences, 1105 BA Amsterdam, the Netherlands.
E-mail: c.keysers@nin.knaw.nl
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Psychological Inquiry, 22: 217–218, 2011
C Taylor & Francis Group, LLC
Copyright ISSN: 1047-840X print / 1532-7965 online
DOI: 10.1080/1047840X.2011.559629
Social Cognition, Accuracy, and Physiology
Marco Iacoboni
Department of Psychiatry and Biobehavioral Sciences, Ahmanson-Lovelace Brain Mapping Center, University of
California, Los Angeles, California
Zaki and Ochsner (this issue) make an important
point regarding the integration of process-oriented research with accuracy-oriented research in social cognition. This position is valid and desirable. One issue that does not emerge very clearly from Zaki and
Ochsner’s proposal, though, is that some processes in
social cognition are dedicated to solving relatively simple problems and that the accuracy expected for these
problems, at least in the healthy brain, should be 100%,
thus making accuracy research for such processes less
crucial.
Zaki and Ochsner describe the process-oriented research on the Experience Sharing System (ESS) and
the Mental State Attribution System (MSAS). They
point out that one of the problems of the ESS in mediating interpersonal understanding is that “‘higher level’ ”
“intentions and beliefs often are not unambiguously
translated into motor and somatic states” (p. 162). I
couldn’t agree more.
The problem with the process-oriented research on
ESS and MSAS is that it often assumes that these
two systems compete for interpersonal understanding.
There is little competition, however, between these two
systems. The ESS and the phenomena of mirroring associated with it are very good at dealing with relatively
simple actions that are the fabric of our everyday existence. I am reaching for a glass of wine at dinner.
What can I do with it? Well, in principle I could pour
the wine on the table, just to see what kind of color the
tablecloth would get, or I could splash the wine on the
face of the person I am having dinner with. I could also
violently smash the glass on the wall. I could do all
these things. However, I have reached for and grasped
a glass of wine at a dinner table probably thousands
of times in my life, and I invariably drank the wine.
Or, at the end of the dinner, put the empty glass in the
dishwasher.
When I see somebody grasping a cup of coffee,
when one of my trainees enters my office for a meeting
and I look at her face, when I go around the city and
watch people smiling at me, or hugging each other,
when I am in line in a movie theatre, I am surrounded
by people who are busy making very predictable actions that express relatively simple intentions. The ESS
is really good at effortlessly facilitating interpersonal
understanding for these simple scenarios. These sce-
narios, however, although simple, are also very important, because they are the overwhelming majority
of the kind of things we deal with in our social life.
We all understand these situations 100% of the time.
Indeed, if we fail to grasp the meaning of these very
simple situations, it most likely means that something
is wrong with our brain. Thus, although I applaud
Zaki and Ochsner call for the integration of processoriented and accuracy-oriented research, I also think
that accuracy-oriented research is less crucial in the
field of ESS research.
The MSAS plays an important role in more complex
situations, and for those situations accuracy-oriented
research is certainly valuable, because our accuracy at
interpersonal understanding for those situations is far
below 100%.
Zaki and Ochsner (this issue) argue that “both the
ESS and the MSAS are concurrently engaged by ‘naturalistic’ mind perception tasks” (p. 172). This statement clearly relies on the assumption that we know
how to identify ESS and MSAS. I argue next that this
is not as simple as it may seem.
The brain imaging literature has consistently associated a set of cortical brain areas with MSAS, as Zaki
and Ochsner point out. There is a problem, however,
with the interpretation of the physiological response
of this set of areas (or at least with the most prominent ones). Many studies have reported “activation”
for mental state attribution tasks compared to control
tasks in these areas. The problem, however, is that plotting the activity of these areas reveals almost invariably
reduced activity for both mental state attribution tasks
and control tasks. Control tasks simply show a consistently higher reduction of activity, compared to the
mental state attribution tasks (Mitchell, Heatherton,
& Macrae, 2002). Thus, the subtraction of the control task activity to the mental state attribution task
activity yields a positive value but only because both
values are negative values and the absolute value of
the control task is higher than the absolute value of the
“experimental” task (the mental state attribution task).
The common practice in neurophysiology, however,
is to consider the response with the highest absolute
value the most important for neural coding. That is,
when a neuron increases its baseline firing rate to the
presentation of two stimuli, the stimulus yielding the
217
COMMENTARIES
highest increase in firing rate is considered preferentially coded by that neuron. Using the same logic, when
a neuron decreases its baseline firing rate in response to
two stimuli, the stimulus with the highest decrease in
firing rate (highest absolute value) is considered preferentially coded by that neuron. The same logic applies
to the local field potential, an electrical parameter of
neural activity that correlates with the BOLD fMRI
signal even better than the spiking activity of neurons.
Mysteriously, the set of areas associated with MSAS
have been exempted from this typical neurophysiological interpretation. Indeed, the opposite logic is applied to them, on the basis that they have high baseline
activity during rest (Mitchell et al., 2002). However,
neurons also have different baseline firing rates. Neurons with extremely high baseline firing rate tend to
code stimuli with reduction of the firing rate (inhibition). Nevertheless, the traditional interpretive logic in
neurophysiology that looks at absolute amount of deviation from baseline activity has been always applied
to the responses of these neurons.
There is no solid rationale for applying this
“reversed” interpretive logic to the cortical areas
associated with MSAS. There are, however, historical
reasons. Many fMRI studies on MSAS have been performed with no resting conditions, on the account that
the resting condition cannot be controlled. Furthermore, for many years there has been little awareness of
the unusually high baseline activity in the areas associated with MSAS and of the task-induced reduction of
activity in these areas. When this issue emerged, there
was already a literature linking that set of areas to
MSAS. Rather than revising the thinking about the processes in those areas, the community revised its own
thinking on how to interpret activity changes, but only
when applied to the areas associated with MSAS. This
is clearly irrational. It’s also problematic, because there
are studies showing increased activity in these areas
during mental state attribution tasks (Iacoboni et al.,
2004; Mitchell, Macrae, & Banaji, 2004). At this point,
the social cognitive neuroscience community simply
ignores this issue, and I doubt that my comments
here will produce any change. Eventually, however,
this illogical practice will have to be faced and
resolved.
A final comment on autism. Autism spectrum disorder has a very complex phenotype, most likely due
to multiple factors. Autistic traits also vary in the neurotypical population. Some of the inconsistencies in
the literature are likely due to recruitment issues. If
my control group has subjects that are high in autistic
traits and my autism spectrum disorder group is high
functioning, it is not unlikely that group differences
218
cannot be demonstrated. Furthermore, in studies looking at linking deficits in mind perception with social
symptom severity, the choice of the bio-marker is critical. Good bio-markers will succeed (Dapretto et al.,
2006), not so good ones may fail.
Although it is true that some interventions show
only task-specific improvements, others show promising preliminary results that generalize beyond the intervention (Ingersoll, 2010; Ingersoll & Lalonde, 2010;
Ingersoll & Schreibman, 2006). This is probably because the intervention acts on and improves a core
functional deficit associated with the condition.
Note
Address correspondence to Marco Iacoboni,
Ahmanson-Lovelace Brain Mapping Center, 660
Charles E. Young Drive South, Los Angeles, CA
90095. E-mail: iacoboni@ucla.edu
References
Dapretto, M., Davies, M. S., Pfeifer, J. H., Scott, A. A., Sigman,
M., Bookheimer, S. Y., & Iacoboni, M. (2006). Understanding
emotions in others: Mirror neuron dysfunction in children with
autism spectrum disorders. Nature Neuroscience, 9(1), 28–30.
doi:10.1038/nn1611
Iacoboni, M., Lieberman, M. D., Knowlton, B. J., MolnarSzakacs, I., Moritz, M., Throop, C. J., & Fiske, A. P.
(2004). Watching social interactions produces dorsomedial
prefrontal and medial parietal BOLD fmri signal increases
compared to a resting baseline. Neuroimage, 21, 1167–1173.
doi:10.1016/j.neuroimage.2003.11.013
Ingersoll, B. (2010). Brief report: Pilot randomized controlled
trial of reciprocal imitation training for teaching elicited
and spontaneous imitation to children with autism. Journal of Autism and Developmental Disorders, 40, 1154–1160.
doi:10.1007/s10803-010-0966-2
Ingersoll, B., & Lalonde, K. (2010). The impact of object and gesture imitation training on language use in children with autism
spectrum disorder. Journal of Speech, Language, and Hearing
Research, 53, 1040–1051. doi:10.1044/1092-4388(2009/090043)
Ingersoll, B., & Schreibman, L. (2006). Teaching reciprocal imitation skills to young children with autism using a naturalistic
behavioral approach: Effects on language, pretend play, and
joint attention. Journal of Autism and Developmental Disorders, 36, 487–505. doi:10.1007/s10803-006-0089-y
Mitchell, J. P., Heatherton, T. F., & Macrae, C. N. (2002). Distinct
neural systems subserve person and object knowledge. Proceedings of the National Academy of Sciences U. S. A., 99,
15238–15243. doi:10.1073/pnas.232395699
Mitchell, J. P., Macrae, C. N., & Banaji, M. R. (2004). EncodingSpecific effects of social cognition on the neural correlates of
subsequent memory. Journal of Neuroscience, 24, 4912–4917.
doi:10.1523/JNEUROSCI.0481-04.2004
Psychological Inquiry, 22: 219–220, 2011
C Taylor & Francis Group, LLC
Copyright ISSN: 1047-840X print / 1532-7965 online
DOI: 10.1080/1047840X.2011.573766
Organizing Interactions in the Study of Judgmental Accuracy
Elysia R. Todd and David C. Funder
Department of Psychology, University of California, Riverside, California
Zaki and Ochsner join the long line of commentators urging scientists in cognitive psychology and
neuroscience to draw from research in social and personality psychology and vice versa (e.g., Banaji, 2010;
Cacioppo & Berntson, 1992; Heatherton, Macrae, &
Kelley, 2004). The particular contribution of Zaki and
Ochsner is to emphasize the integration of personality/social research on the accuracy of social judgments
into investigations of cognitive processes illuminated
by neuroscience.
Those of us already on the front lines of accuracy research (e.g., Funder, 1980, 1982, 1995; Letzring, Wells,
& Funder, 2006) do not need to be convinced of its
utility. However, the authors of the target article appear to believe that some psychologists still need to
be convinced that the study of accuracy is important.
The purpose of our comment is to support their efforts
and to discuss further how the integration they suggest
might be organized.
The most interesting part of the target article might
be its demonstration of how findings from the study of
cognition and neuroscience suggest theoretical insights
for personality and social psychology. Using their own
work as an illustration (Zaki, Bolger, & Ochsner, 2008;
section 3.1.2), Zaki and Ochsner report that accuracy
depends not only on the type of information one receives but also on the particular mental process used
to interpret that information. To reach this conclusion,
the authors assume that a person’s tendency to use a
particular mental process (experience sharing) can be
tapped by his or her self-report of an individual difference variable (empathy). However, empathy could
be associated with any number of different mental processes, attitudes, or patterns of emotional response. For
the argument that the authors are making, more direct
indicators of mental process would provide stronger
support. Still, if their implication is valid, a judge who
uses experience sharing to infer a target’s current psychological state will be accurate only to the degree to
which the target is expressive, or provides information
that is emotional in nature. In short, the authors argue,
the target information must match up with the judge’s
process if accuracy is to be achieved.
The Realistic Accuracy Model (RAM; Funder,
1995) organizes four moderators of accuracy and the
interactions among those moderators. The interaction
identified by Zaki et al. (2008) exemplifies what RAM
refers to as “sensitivity,” the interaction between characteristics of the judge and specific aspects of relevant
information (see Funder, 1995, Table 2). Because RAM
offers a potentially useful rubric for organizing interactions such as those studied by Zaki et al., we offer a
brief summary.
RAM
The RAM focuses on judgments made about traits
rather than current thoughts and feelings (the focus of
Zaki and Ochsner), but we would suggest the basic
processes are similar. RAM begins with the premise
that traits are real properties of target persons. It further presumes that people sometimes make judgments
about traits and that sometimes the judgments are accurate. For an accurate judgment to be accomplished,
four things must happen. First, the target person must
emit behaviors that are relevant to the trait in question.
Second, these behaviors must be available to the judge
(e.g., emitted in his or her presence). Third, the judge
must detect and, finally, correctly utilize these relevant, available, behavioral cues in order to produce a
correct judgment. If one simply substitutes “psychological state” for “trait” in the preceding description,
we believe exactly the same sequence applies. Either
way, unless relevant information is available to a judge
who detects and utilizes it correctly, accurate judgment
simply cannot happen.
A central purpose of RAM is to account for the four
basic moderators of accuracy identified by decades of
research by many investigators. When phrased in terms
of the circumstances that make accurate judgment more
likely, the moderators are good target, good trait, good
information, and good judge. Each of these moderators has received empirical investigation. For example,
Colvin (1993) painted a picture of a good target as a
person with a coherent personality who is psychologically well adjusted. Moreover, some traits are more
easily judged than others. “Good traits” are related to
behaviors that are visible and readily expressed (Funder & Dobroth, 1987). “Good information” can be
thought of in terms of quantity (more information is
generally better; Blackman & Funder, 1988) and quality (behavioral observations in unstructured situations
yield more accurate judgments of personality than do
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COMMENTARIES
Table 1. Interactions among Moderators of Accuracy in
Personality Judgment.
Moderator
Judge
Trait
Target
Judge
Trait
Target
Information
—
—
—
—
Expertise
—
—
—
Relationship
Palpability
—
—
Information
Sensitivity
Diagnosticity
Divulgence
—
Note. From “On the Accuracy of Personality Judgment: A Realistic Approach,” by Funder (1995, p. 663). Copyright 1995 by the
American Psychological Association. Reprinted with permission.
observations in highly structured ones; Letzring et al.,
2006).
The remaining moderator has a more checkered
past. Zaki and Ochsner relate the history of the search
for the “good judge” in the traditional fashion. Although plenty of interesting findings about the good
judge can be found in the contemporary literature (see
Letzring, 2008), the nature of some of the historically
long-standing problems in that area of research illustrate the value of the points raised by the target article. One reason why the search for the good judge has
proven so difficult is that properties of the judge, target,
trait, and information on which the judgment is based
all might interact in the determination of accuracy. This
fact presents a daunting and potentially disorganized
research agenda.
One way to bring order to the research enterprise
is through the use of theory. For example, the individual difference (judge) variable studied by Zaki et al.
(2008) was conceptualized as the tendency to utilize a
particular cognitive system (experience sharing). This
is an excellent start. The identification of stable neurological and cognitive systems specialized for person
perception promises to fill a theoretical void by identifying the potential characteristics of the good judge
that are the most promising to study.
A portion of the RAM presented by Funder (1995,
Table 2), reproduced here as Table 1, can also be useful. The table labels each of the six interactions among
the four basic moderators of accuracy (see Funder,
1999, for a detailed treatment of each). One of them is
“sensitivity,” which, as mentioned, encompasses Zaki
et al.’s (2008) assertion that the accuracy of particular judges depends on the type of information that
is available. The remaining five interactions also deserve research attention. More generally, this table
can organize and suggest future research on moderators of accuracy and their interactions and tie new
research to existing findings in the literature of person
perception.
220
Acknowledgments
Preparation of this commentary was assisted by National Science Foundation Grant BNS BCS-0642243
(David C. Funder, Principal Investigator). Any opinions, findings, and conclusions or recommendations
expressed in this commentary are those of the individual researchers and do not necessarily reflect the views
of the National Science Foundation. We thank Esther
Guillaume for comments on an earlier draft.
Note
Address correspondence to Elysia R. Todd, Department of Psychology, University of California, Riverside, Riverside, CA 92521. E-mail: elysia.todd@email.
ucr.edu
References
Banaji, M. (2010). Letter to a young social cognitionist. Social Cognition, 28, 667–674.
Blackman, M. C., & Funder, D. C. (1998). The effect of information
on consensus and accuracy in personality judgment. Journal of
Experimental Social Psychology, 34, 164–181.
Cacioppo, J. T., & Berntson, G. G. (1992). Social psychological
contributions to the decade of the brain: Doctrine of multilevel
analysis. American Psychologist, 47, 1019–1028.
Colvin, C. R. (1993). Judgable people: Personality, behavior, and
competing explanations. Journal of Personality and Social Psychology, 64, 861–873.
Funder, D. C. (1980). On seeing ourselves as others see us: Self-other
agreement and discrepancy in personality ratings. Journal of
Personality, 48, 473–493.
Funder, D. C. (1982). On the accuracy of dispositional vs. situational
attributions. Social Cognition, 1, 205–222.
Funder, D. C. (1995). On the accuracy of personality judgment: A
realistic approach. Psychological Review, 102, 652–670.
Funder, D. C. (1999). Personality judgment: A realistic approach to
person perception. San Diego, CA: Academic Press.
Funder, D. C., & Dobroth, K. M. (1987). Differences between traits:
Properties associated with inter-judge agreement. Journal of
Personality and Social Psychology, 52, 409–418.
Heatherton, T. F., Macrae, C. N., & Kelley, W. M. (2004). What
the social brain sciences can tell us about the self. Current
Directions in Psychological Science, 13, 190–193.
Letzring, T. D. (2008). The good judge of personality: Characteristics, behaviors, and observer accuracy. Journal of Research in
Personality, 42, 914–932.
Letzring, T. D., Wells, S. M., & Funder, D. C. (2006). Quantity
and quality of available information affect the realistic accuracy of personality judgment. Journal of Personality and Social
Psychology, 91, 111–123.
Zaki, J., Bolger, N., & Ochsner, K. (2008). It takes two: The interpersonal nature of empathic accuracy. Psychological Science,
19, 399–404.
Psychological Inquiry, 22: 221–230, 2011
C Taylor & Francis Group, LLC
Copyright ISSN: 1047-840X print / 1532-7965 online
DOI: 10.1080/1047840X.2011.599107
REPLY
On the Reintegration of Accuracy in Social Cognition Research: Let Us
Count the Ways
Jamil Zaki
Department of Psychology, Harvard University, Cambridge, Massachusetts
Kevin Ochsner
Department of Psychology, Columbia University, New York, New York
When we set out to write this review, both of us
were a bit apprehensive about the responses we would
receive. This anxiety was driven not just by our imaginations but also by colleagues who often seemed to
take a hostile stance toward the very idea of studying interpersonal accuracy. While discussing the troubles of
accuracy research following Cronbach’s (1955) complaint, and our recent forays into this area of research,
one senior colleague told us that the entire endeavor
“should have stayed dead.” Another colleague encouraged us to reconsider using the “toxic” term accuracy
if we wanted anyone to listen to us.
As such, we were thrilled (and a touch relieved) to
find, instead, an enormously generative set of responses
to our article, which—although sometimes taking issue with the details of our approach and framework—
rarely challenged the notion of accuracy as a meaningful or measurable construct. Perhaps the deck was
stacked; many of the commentators are accuracy researchers whose work has inspired much of our own.
However, even among more “process-oriented” researchers, and across behavioral and neuroscientific
perspectives, the commentaries broadly converged on
the idea that integrating accuracy and process in social
cognition is desirable and feasible.
We like consensus, but we love new ideas, and that’s
what these commentaries contain in abundance. Many
provide particular visions about how process- and
accuracy-oriented research can and should be brought
together, and indeed, how they already are being integrated. Although the landscapes each commentator
sees for the future of the field often differ from each
other, and from our own, in important ways, there also
were commonalities in their content and architecture.
Above all else, we are heartened by the sheer number of novel and innovative approaches to these issues
embodied in these commentaries. It has become almost canonical for psychologists to dismiss accuracy
research as anemic or anachronistic, and the idea of
integrating accuracy- and process-based approaches to
social cognition is sometimes seen as too complex or
vague an endeavor to be worth pursuing. By our count,
this pessimism clashes with key ideas expressed by
virtually every commentator.
We see these commentaries as coalescing around a
set of core questions that the field of accuracy research
needs to answer—and in many cases already has begun to answer. Next we describe five such questions.
Between the commentators, others, and ourselves, a
growing number of researchers are not only posing
these questions but also producing creative new ways to
answer them. Although much work obviously remains
to be done, counting the ways research is moving forward leaves us optimistic about the future of accuracy
as an integrated part of social cognition research.
How Accurate Are Perceivers, and How
Accurate Do They Want to Be?
Epley and Eyal (this issue) and Ickes (this issue) take
issue with our characterization of perceivers as “consummate experts” at mind perception, and we agree
that this term lacks precision. On one hand, perceivers’
skills are impressive in a number of ways. Especially
in the domain of emotion perception, the fact that we
can so quickly combine myriad informational sources
together into any coherent inferences about targets is
nontrivial. Further, judging performance on many emotion perception tasks is problematic because so many
individuals often perform at ceiling when identifying
affective states. Thus, even if perceivers fail to attain
accuracy in some task types (lie detection is a prime
example), they are quite accurate in others.
On the other hand, we agree with both commentaries
that the only broad statement about accuracy that rests
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ZAKI AND OCHSNER
entirely on solid empirical ground is that perceivers are
better than chance, and worse than perfect, at judging
social targets. We do believe that—at least in processoriented research—the “worse than perfect” side of
that equation has held too much sway in the literature (perhaps because this domain of research typically
uses perfect accuracy as a baseline; see also Krueger
& Funder, 2004). That said, we agree with Epley and
Eyal and with Ickes that emphasizing the other side of
the equation is not as useful as balancing the two. In
fact, we believe that the integrative approach we advocate assumes this balanced view of perceivers’ skills.
Specifically, we suggest that more attention should be
paid to shifts in accuracy that result from alterations in
social context and process use. Such shifts could not
occur if perceivers were always perfect—or always
terrible—at drawing inferences about targets. Thus,
even if our use of the term “expert” was a bit cavalier,
we believe our approach emphasizes the variance between perfection and chance that actually characterizes
perceivers.
Perhaps a deeper and more interesting question is,
“How accurate do perceivers want to be?” One might
imagine that even if humans are not always consummate mind perception experts, we should always strive
toward perfect accuracy. Such expertise would save
us from Ponzi schemes, unfaithful spouses, and other
inaccuracy-related pitfalls. Ickes, however, points out
that—in many cases—perceivers have other motives
and may sometimes avoid the very information they
could use to accurately assess targets (Kunda, 1990).
We strongly agree that variance in motivation powerfully affects accuracy and could play out across contexts (e.g., the same individual may be motivated to be
accurate in the face of positive information and inaccurate in the face of threatening information) or across
individuals (e.g., someone high in the need to belong
or low in socioeconomic status may chronically strive
to accurately assess others’ views of him, in order to
tailor his behavior to interaction partners). This variance can importantly play into a discussion of when
accuracy is highest and what accurate perceivers look
like (see next).
How Should Accuracy Be Measured?
If psychology were to be compared to physics,
interpersonal accuracy might be seen as a kind of
quantum phenomenon: Just as measuring one feature
of a particle’s state introduces uncertainty about its
other features, accuracy can also change—sometimes
dramatically—as a function of how it is measured and
who is doing the measuring. As a result, there sometimes seem to be almost as many accuracy measurements as there are accuracy researchers (as noted by
many commentators, and especially Hall & Colvin,
this issue).
222
At first blush, this variance seems problematic. After all, methodological inconsistency was one of the
primary charges leveled at the “first wave” of accuracy researchers (Gage & Cronbach, 1955). Especially
troubling are the theoretical pitfalls inherent to operationalizing accuracy. The slipperiness of the concept
requires any researcher to make some a priori assumptions about what counts as accuracy, which can be
dangerous. This is known as the “criterion question”:
Who or what is the authority on a social target’s traits
or states? If Liz says she is nervous, is she right? What
if her friends—or FACS coders, who know more about
her facial expressions than she does (Ekman & Friesen,
1975/2003)—disagree? If she is not experiencing physiological arousal, is she calmer than she believes? If we
were to measure activity in her insula, would it “know”
more than she does about her current levels of disgust?
Defining a criterion requires a researcher to decide
which of these noisy, often contradictory, signals to
trust. That researcher’s definition of accuracy (and its
legitimacy) will, from that point on, be constrained by
her criterion assumptions, any of which is necessarily
imperfect.
Our own work and that of the commentators illustrate a wide range of such criteria, and a range
of resulting issues. As noted by Keysers and McKay
(this issue), our own choice of a criterion (a target’s self-reported emotion) is not without problems:
If a target is incorrect about his own emotions, then
a perceiver who agrees with him is only dubiously
accurate. Keysers and McKay argue that neural engagement does not suffer from this bias, and as such
shared patterns of engagement across perceivers and
targets (Schippers, Gazzola, Goebel, & Keysers, 2009;
Schippers, Roebroeck, Renken, Nanetti, & Keysers,
2010), or across multiple perceivers viewing the same
target (Stephens, Silbert, & Hasson, 2010) may provide a purer measure of accuracy than any based on
self-report.
We find this idea intriguing and think that studies
of brain–brain correspondence are a vital new source
of data in this domain. At the same time, we caution
that shared neural states are not necessarily indicative of correspondence between psychological states
or meaningful interpersonal understanding. For example, two people looking at each other’s faces will almost certainly coengage striate and extrastriate cortex
involved in perceiving complex visual stimuli, but all
this coactivation tells us is that they have simultaneously seen something (likely each other), not that they
have understood each other’s states or traits.
Keysers and McKay (this issue) and Iacoboni (this
issue) suggest that “resonance” between the mirror
neuron systems (MNS) of two individuals more deeply
connects to empathic understanding. To a certain extent, we agree, especially when perceivers are attempting to accurately understand relatively “low-”level
AUTHORS’ REPLY
motor or communicative intentions, such as a target
reaching for a glass or playing charades. However,
even coactivation of regions in this system could reflect a “shallow” level of accuracy that would leave
most perceivers unsatisfied. This is because—contra
Iacoboni’s view—we think that many important psychological states are not mapped in any direct way to
motor acts that can be represented in the mirror neuron
system (cf. Hickok, 2009).
Consider the example from our target article: A perceiver witnesses a target shoving someone else. Coengagement of the MNS could theoretically provide a
measure of how much the perceiver understands the
target’s “low-level” intention (i.e., to push), and (even
better) a measure not limited by the target’s own insights about her behavior. However, as is the case with
facial expressions of emotion (Aviezer et al., 2009;
Carroll & Russell, 1996; Kim et al., 2004; Russell,
Bachorowski, & Fernandez-Dols, 2003; Zaki, Hennigan, Weber, & Ochsner, 2010), the meaning of nonfacial motor acts also vary significantly depending on
the context in which they are embedded. Thus, simply understanding that a target wishes to push an unsuspecting person—and the neural resonance that can
index such understanding—provide little insight about
whether a perceiver correctly gauged the deeper meaning of a target’s internal states (e.g., shoving the person
to start a fight vs. attempting to save him from an oncoming bus).
Iacoboni has previously demonstrated that the MNS
is sensitive to the presence or absence of contextual
cues surrounding a movement (Iacoboni et al., 2005),
suggesting that this system may incorporate contextual
information about a target’s intention as well as their
motor acts. Be that as it may, we are more convinced by
data suggesting that attention to context and “deeper”
internal states (e.g., why someone is performing an
action as opposed to how they are performing it) engages the mental state attribution system in addition to
the mirror neuron system (de Lange, Spronk, Willems,
Toni, & Bekkering, 2008; Spunt & Lieberman, 2011;
Spunt, Satpute, & Lieberman, 2010). Further, engagement of both systems tracks with accuracy as measured by multiple criteria, including agreement with
targets themselves (Zaki, Weber, Bolger, & Ochsner,
2009) and objective memory for the content of targets’ anecdotes (Stephens et al., 2010). Together, these
data strongly suggest that coengagement of the MNS
across target and perceiver cannot tell the whole story
of interpersonal accuracy.
Finally, although Iacoboni (this issue) believes that
interpreting brain activity related to mental state attribution is complicated by the fact that some key regions
related to this process (e.g., the medial prefrontal cortex) are tonically active at rest, researchers have taken
this issue to heart for almost a decade. In fact, the striking overlap between areas related to mental state attri-
bution and the brain’s “default network” now guides
thinking about the ubiquity and centrality of social
information processing to the human mind (Buckner,
Andrews-Hanna, & Schacter, 2008; Buckner & Carroll, 2007; Mitchell, 2009; Wagner, Kelley, & Heatherton, 2011). For example, research on mindwandering
and stimulus-independent thought suggest that when
in a “default,” non-task-oriented mode, what people
do much of the time is make attributions about their
feelings and thoughts concerning things that are personally relevant to them, like their goals and interpersonal relationships (Christoff, Gordon, Smallwood,
Smith, & Schooler, 2009; Mason et al., 2007). More
broadly, organs that are tonically active at rest are not
precluded from tracking subjective or psychological
states in important and tractable ways. For example,
though everyone hopes that their heart remains tonically active, variance in heart rate (and even second
derivatives describing variance in heart rate variance)
are reliable, meaningful correlates of internal subjective states (Berntson et al., 1997).
Thus, although we strongly agree that shared
perceiver-target neural activity should join the cadre
of criteria that can be used to assess interpersonal accuracy, we do not believe that neural resonance merits
a privileged ranking as less biased or more informative
than other criterion measures. Like examination of behavior and self-report, the utility of neural resonance
lies in adding to a broader triangulation—based on aggregation of multiple types of data that are relevant to
multiple criteria—on when and how perceivers achieve
accuracy.
Thus, we propose settling our differences over the
quality of any one criterion by instead focusing on aggregating data gleaned from the use of multiple criteria
(in fact, as many criteria as possible). Before we can
do so, however, it is worth asking the question, Why is
such aggregation worthwhile? More specifically, what
does the whole (aggregation across criteria) provide
that is greater than the sum of its parts (separate lines
of data from separate criteria)? We believe there are at
least two answers to this question, which couldn’t be
more different from each other.
Convergence Across Criteria
Measuring emotional states ranks among the oldest and most Herculean challenges in psychological
research. This endeavor spans a number of qualitatively different problems. Intuitively, researchers wish
to understand the psychological ingredients—such as
perception of bodily states and contextually driven
appraisals—that constitute emotional states (Cannon,
1927; Forgas, 1995; James, 1884; Schachter & Singer,
1962; Scherer, Schorr, & Johnstone, 2001; Storbeck
& Clore, 2007). In attempting to understand these
ingredients, they run into another thorny question:
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ZAKI AND OCHSNER
Which levels of analysis—for example, behavioral
(self-reports & expressions) or physiological arousal
(e.g., heart rate)—provide valid information about
when an emotion is occurring (Ekman, Levenson, &
Friesen, 1983; Ekman, Sorenson, & Friesen, 1969;
Robinson & Clore, 2002)? Note that this second issue eerily resembles the criterion question just described. As such, these questions can be thought of
as independent and sequential: Before delving into the
components (independent variables) that produce and
track emotion, one must identify the measurements
(dependent variables) that signify that an emotion has
occurred.
As it turned out, this sequence is not nearly as tidy
as one might have imagined. Researchers argue about
the relative validity of different criteria, and—even
worse—self-reported, behavioral, and physiological
measurements of emotion often misbehave by failing
to track with each other (Mauss, Levenson, McCarter,
Wilhelm, & Gross, 2005), especially in some circumstances and for some individuals (Ansfield, 2007;
Gross, John, & Richards, 2000). However, emotion research’s melee of operationalizations gave way to a
deeper insight about emotion: The psychological ingredients and levels of analysis questions surrounding
it are not at all independent. Instead, to validly identify the independent variables that produce emotion,
one must demonstrate that they do so across a range
of criteria. This “meta-criterion” produced a generative, qualitatively novel approach to defining emotion
that brought research above the fray of argumentation
over any one criterion’s validity (Barrett, 2009; Barrett,
Mesquita, Ochsner, & Gross, 2007; Gross & Barrett,
2011; Russell & Barrett, 1999).
Social cognitive research is approaching a similar moment, when convergence across criteria can be
used as its own metacriterion to validate the role of
predictors (such as cognitive processes) in producing interpersonal accuracy. At least some predictors
do produce such cross-criterion consistency. For example, experience sharing and mental state attribution
predict accuracy across a number of criteria. These
relationships are relatively robust to differences in
how processes are measured—through developmental trajectories (Eisenberg, 1989), self-report (Hall &
Colvin, this issue) physiological arousal (Levenson
& Ruef, 1992), motor mimicry (Dimberg, Thunberg,
& Elmehed, 2000; Stel & van Knippenberg, 2008),
neural activity (Zaki et al., 2009; Stephens et al.,
2010), and its absence in neuropsychiatric patients
(Fernandez-Duque, Hodges, Baird, & Black, 2010;
Goodkind et al., 2011)—and differences in how accuracy is measured—through memory for target behavior (Hastie & Kumar, 1979; Mitchell, Macrae, &
Banaji, 2004; Stephens et al., 2010), agreement across
perceivers (Kenny et al., 2007), agreement with targets
themselves (Ickes, 1997), and response latency (Stel &
224
van Knippenberg, 2008). Perhaps more important, the
moderators that determine when these processes will
produce accuracy (e.g., target expressivity, perceiver
motivation) hold relatively constant across domains
of study and criteria. For example, although knowing
what someone is feeling and what that person is like in
general may seem quite different, Funder (this issue)
points out (and we agree) that there is impressive consistency between the factors that determine whether
individuals’ traits and states will be successfully transmitted by targets and received by perceivers.
Divergence Between Criteria
Disagreement is often as generative as agreement,
and we think the “noise” created by the use of multiple criteria of accuracy is no exception. In many cases,
apparent confounds between accuracy, on one hand,
and the criteria used to define it, on the other, might
turn out to not be confounds at all but rather clues about
systematic moderators of accuracy. Consider the examples described by Epley and Eyal (this issue) in which
perceivers are relatively inaccurate. These inaccuracyproducing situations cluster around two types of social
tasks: (a) drawing inferences about opponents in a debate or negotiation, and (b) understanding how one will
be perceived by others. Epley and Eyal claim that such
situations provide accuracy criteria that are as valid
(or more valid) as (or than) those produced by tasks
in which perceivers are relatively accurate (e.g., rating
pictures of faces or videotaped interactions). Thus, on
the face of it, Epley and Eyal’s examples suggest that
optimism about perceivers’ accuracy is driven by the
use of unrealistic criteria, and altering these criteria
overturns this rosy viewpoint.
Does this mean that accuracy is impossible to measure consistently or that perceivers are prone to failure
when measured in the most realistic way? We don’t
think so, and instead find the divergent levels of accuracy produced by these measures deeply informative.
Ickes (this issue) and Epley and colleagues (Epley,
Keysar, Van Boven, & Gilovich, 2004; Gilovich,
Medvec, & Savitsky, 2000) have documented two particularly strong forces that can influence accuracy.
First, people are accurate when motivated to be so—
for example, when targets are attractive (Ickes, Stinson,
Bissonnette, & Garcia, 1990), or when perceivers have
been rejected (Pickett, Gardner, & Knowles, 2004) or
feel a lack of power (Kraus, Cote, & Keltner, 2010)—
and inaccurate when motivated to be so—for example,
when accuracy is self-threatening (Simpson, Ickes, &
Blackstone, 1995; Simpson, Orina, & Ickes, 2003) or
when inaccuracy can bolster one’s self-image (Kruger,
1999; Taylor & Brown, 1988). Second, perceivers have
an especially difficult time overcoming the curse of
their own knowledge in understanding what targets do
AUTHORS’ REPLY
not know (Gilovich et al., 2000; Gilovich, Savitsky, &
Medvec, 1998), even when such knowledge objectively
harms perceivers’ accuracy (Epley et al., 2004) and
their ability to optimally interact with targets (Camerer,
Loewenstein, & Weber, 1989).
These two forces reframe the difference between
methods used by process and accuracy researchers and
make it unsurprising that these two groups reached
different conclusions about perceivers’ skills. Specifically, the examples of (in)accurate social perception
highlighted by Epley and Eyal (this issue) are those in
which people are (a) unmotivated to be accurate and
(b) most cursed with their own knowledge when trying
to be accurate. Anyone who has watched cable news in
the last few years likely understands that people with
strong opinions often have little interest in taking the
perspective of those on the other side. This disinterest
may be well guided, because perspective taking in contentious situations can sometimes produce dissonance
and even worsen the outcome of intergroup interactions
(Cikara, Bruneau, & Saxe, 2011; Vorauer, Martens, &
Sasaki, 2009; Vorauer & Sasaki, 2009). Similarly, people are least likely to be accurate when accuracy requires them to overcome intimate self-knowledge (i.e.,
rate how they will be perceived by targets), especially
when such ratings are further tangled with motivational
forces (e.g., rating how attractive one will be rated by
others compounds self-knowledge and motivated reasoning).
Eyal and Epley (2010, this issue) leverage these
well-known biases to produce an intervention for improving accuracy (see ‘manipulating process use can
alter accuracy’ below), and we commend this step in
merging information about processes and accuracy.
However, it is worth noting that they begin with situations in which accuracy is most likely to be poor
(i.e., classes of judgment that are most loaded with
motivational biases and the curse of knowledge) and in
greatest need of improvement. Accuracy researchers in
many other domains have, instead, sought to describe
the performance of perceivers in more “neutral” settings where, in fact, accuracy can be a good bit better.
For example, there is no clear reason that rating the
emotions of a stranger or the traits of someone described in a vignette would systematically draw out
inaccuracy related to the curse of knowledge or selfserving biases.
Which criterion, then, should we trust more: the
one that pinpoints our biases and inaccuracies, or the
one that does not? Our point here is that neither is
more “naturalistic” or important than the other. Instead,
these criteria differ in some of the very psychological
ingredients that produce (in)accuracy in the first place,
and this difference—in and of itself—uncovers some
deeper information about when perceivers are likely to
be most (in)accurate. In other words, when there is a
divergence in accuracy across criteria, the deeper ques-
tion might not be “which criterion is better?” but rather
“what does this divergence tell us about the contexts in
which perceivers are most likely to be accurate?”
What Does a “Good Perceiver” Look Like?
A perennial goal of accuracy research is to identify the dispositions that track stably with interpersonal
acuity. How has this search for “good judges” fared?
This depends on whom you ask. Our initial article (as
well as Ickes, Kenny, and Funder’s commentaries in
this issue) described the good judge as elusive at best,
and imaginary at worst, and claim that stable correlates
of accuracy are hard to come by. Hall and Colvin (this
issue) provide a valuable counterpoint to this view by
presenting a wealth of data demonstrating that a number of dispositional features (e.g., intelligence, Big Five
personality scores, and gender) do predict interpersonal
accuracy.
What underlies this disparity? One possibility is
that researchers’ ability to identify trait-level predictors
of accuracy—like the overall levels of accuracy they
document—depend on the criteria they employ. For the
most part, the literature Hall and Colvin describe uses
standardized tests of interpersonal sensitivity, such as
the Profile of Nonverbal Sensitivity (Rosenthal, Hall,
DiMatteo, Rogers, & Archer, 1979), Interpersonal Perception Test (Costanzo & Archer, 1989), or identification of emotions from canonically posed facial expressions (Ekman & Friesen, 1975/2003). In almost
all cases, accuracy in these tests is defined as a convergence between perceivers’ inferences about social
cues prepared by researchers (i.e., designed to represent a given internal state) and the normative response
to those cues (i.e., the state they are designed to represent). In other words, these tasks provide stable and
structural “right answers” about target states, which
perceivers either tap into or not.
These relatively standardized tests advance accuracy research in at least two ways: (a) by allowing for
comparability across numerous studies, and (b) providing the power to detect small but consistent signatures of good perceivers. They also differ consequentially from “idiosyncratic” accuracy measures, in
which the critical stimuli are not standardized or designed by researchers but rather are produced spontaneously by targets. It is this latter accuracy criterion that was most hamstrung by the methodological critiques of Cronbach and others: Idiosyncratic
accuracy measures often required a “subtraction” between perceiver inferences and target self reports, and
issues with this measurement produced deep problems for early accuracy researchers. Standardized accuracy tests at least partly overcome this problem
by replacing such subtractions with more tractable
measures of whether perceivers produce correct
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ZAKI AND OCHSNER
(i.e., normative) judgments about experimenterdesigned social cues. This may partially explain why—
as Hall and Colvin note—standardized tests (largely in
the domain of nonverbal sensitivity) did not suffer the
slowdown that idiosyncratic accuracy measures did in
the post-Cronbach age.
However, the advantages of standardizing accuracy
measures comes—we think—at a real cost. This is because posed and acted expressions of emotions and
social relationships necessarily diverge from “real”
behavior produced by targets. This divergence may
shed some light on disparities between the picture of
accuracy, and accurate judges, that standardized and
idiosyncratic approaches produce. For example, gender and self-reported empathy predict accuracy as defined by standardized measures (Hall, Andrzejewski,
& Yopchick, 2009) but not as defined idiosyncratically
(Ickes, 2003; Levenson & Ruef, 1992; Zaki, Bolger, &
Ochsner, 2008).
Our explanation for this disparity tracks closely with
Ickes’s (this issue): standardized measures partial out
much of the variance that ends up being most important to idiosyncratic measures of accuracy and, most
likely, to accuracy outside of the lab. Specifically, standardized measures rarely account for the broad disparities between how different targets translate their states
and traits into perceptible cues. In many naturalistic
situations, it is these differences, more than perceiver
traits, that drive accuracy (Ickes et al., 2000; Snodgrass,
Hecht, & Ploutz-Snyder, 1998; Zaki et al., 2008). In
other words, perceiver traits may predict accuracy but
only when other, potentially stronger predictors (e.g.,
variance in targets’ expressivity) are removed from the
equation.
Does this mean that including target variance in a
predictive model destroys any prospects of identifying
good judges? We don’t think so; in fact, we think it will
enrich our understanding of differences between perceivers by affording a more nuanced, conditionalized
view of interperceiver differences. Specifically, people
may differ not in how accurate they are, full stop, but
rather in when or for whom they are relatively accurate
or inaccurate. This interactionist approach reframes
individual differences as dependent on context, and
specifically the social contexts provided by the targets
with whom perceivers interact (Mischel, 1973; Mischel
& Shoda, 1995; Zayas, Shoda, & Ayduk, 2002). Such
an approach can open numerous avenues for incorporating the situational forces that powerfully affect
accuracy and examine their interaction with individual differences in perceivers’ motivational and cognitive tendencies (or cognitive and affective “units”; see
Mischel & Shoda, 1995). For example, if perceivers are
more accurate when in a position of low social power,
then we might ask which perceivers are most sensitive
to that effect. We continue to feel that such an approach
can refine the study of good perceivers and produce sta226
ble predictors of accuracy that generalize across many
different contexts (e.g., different social targets).
How Can Processes and Accuracy Be
Integrated Best?
The central aim of our target article was to provide a
framework for systematically relating social cognitive
processes and measures of interpersonal accuracy to
one another. Our hope was to promote thinking about
the ways in which research focusing on these two domains could inform each other rather than continue in
isolation. The data presented and arguments made in
the commentaries suggest at least three ways in which
processes and accuracy can be fruitfully related to each
other, which we consider in turn.
Manipulating Process Use Can Alter
Accuracy
Epley and Eyal (this issue) demonstrate one way in
which process-based research can make direct predictions about when perceivers are likely to be more or
less accurate. They draw on the idea that individuals
tend to construe their own experiences and behaviors
at a fine-grained, detailed level but think about others at a coarser, more global level. This asymmetry in
construal levels lawfully produces two errors: A perceiver will often underascribe fine-grained detail to
others’ experience while considering too many such
details when guessing how others will view the perceiver herself. Although this bias has been characterized across many studies (Gilovich, et al., 1998), Eyal
and Epley (2010) went one step further by showing
how manipulated shifts in construal level can alter accuracy. In a simple paradigm, they induced perceivers
to be more detailed when thinking about others and
more global when thinking about themselves. By going
against their baseline tendencies, this exercise heightened perceivers’ accuracy, both about others’ experiences and how others’ would view perceivers themselves. Other process-based approaches can similarly
increase accuracy. For example, building on evidence
that perceivers tend to overascribe their own internal
states onto targets, Todd, Hanko, Galinsky, and Mussweiler (2011) demonstrated that inducing a “difference
mindset” (priming people to think of disparities between themselves and others) improved accuracy in a
number of domains.
Accuracy Can Tell Us About Process Use
The strategy of converting well-known processing
biases into prescriptions for improving accuracy epitomizes the integrative style of research we hope to see
AUTHORS’ REPLY
much more of in the future. However, like social cognitive biases themselves, these improvements may be
local to particular classes of inferences. For example,
differences in perceivers’ construal levels when drawing inferences about themselves and others are likely
most pronounced in when perceivers are drawing inferences about stable, traitlike attributes (e.g., how attractive a perceiver thinks others will find him or how
conscientious he believes a target to be). When drawing other types of inferences—critically including inferences about how others are feeling—perceivers may
naturally “match” construal levels with targets; indeed,
the phenomenon of experience sharing suggests such
matching. More important, strategies that produce accuracy in some contexts can reduce accuracy in others.
For example, although assuming similarity with targets is often bad for accuracy, it can also often improve
accuracy (Hoch, 1987; Neyer, Banse, & Asendorpf,
1999).
Such complexities do more than provide boundary
conditions on the utility of process-based techniques
for improving accuracy. They also demonstrate the utility of accuracy-based research to circle back and inform our understanding of social cognitive processing.
Biases such as assumptions of self-other similarity may
not exist solely because they such assumptions are cost
little in information-processing terms but also because
they work (i.e., produce accuracy) in some cases. As
such, measuring accuracy can help researchers understand the nature and utility of the processes they study.
West and Kenny’s Truth and Bias Model (Kenny, this
issue; West & Kenny, 2011) provides a method for
gathering just such information. The strength of its
contribution comes from quantifying the role of multiple processes in producing accuracy across different
contexts. This approach could enrich the new tack being taken by Epley, Eyal, Todd, and others: In addition
to trying to improve accuracy by reducing well-known
processing biases, these researchers could ask when
reducing a given bias should be expected to help accuracy, and when it might be expected to hurt it.
Comparison With Other Domains Can Shed
Light on Processes and Accuracy
A third way to unite processes and accuracy is by
way of analogy to other domains in which these phenomena are already more intertwined than they are in
social cognition research. Bahrami and Frith (this issue; Bahrami et al., 2010) offer a compelling example
of such a parallel in their model of social decision
making. This model quantitatively captures the rules
by which two observer’s individual perceptions of the
outside world aggregate into a joint, multiperson perceptual judgment.
Of course, Bahrami and Frith’s approach does not
tackle mind perception proper, in that it models two
perceivers’ cooperative attempts to understand physical events, not perceivers’ attempts to understand each
other’s internal state. However, their model nonetheless lays a rich groundwork for integrating social cognition and decision-making research. For example, we
would expect the quality of joint decisions to be critically limited not only by the judgments and confidence
of each interlocutor but also by each person’s ability to
accurately understand their interaction partner’s confidence. As Bahrami and Frith point out, this ability will
be shaped importantly by the motives of each individual. To follow Bahrami and Frith’s athletics example
(but in a context more familiar to us), two individuals
watching a basketball go out of bounds at an NBA game
not only perceive a sensory event but also imbue the
simple physics of that event with deep affective significance. A Boston Celtics fan’s motivation for her team
to keep the ball can not only influence her willingness
to say that it was last touched by the opposing team
from Los Angeles but can also shift her private perception of what occurred (Balcetis & Dunning, 2006,
2010) and her confidence in that percept. This same
fan may be highly motivated to accurately understand
and integrate another Celtics fan’s perception into her
final judgment of the event but much less motivated
to understand what a Lakers fan witnessed. As anyone familiar with a contentious sports rivalry knows,
such motivations can produce extremely noisy perceptions of physical events across fans of different teams.
Thus, models of multiperson decision making should
incorporate roles for affect and motivation in shaping
the interpersonal judgment steps Bahrami and Frith
describe so nicely.
That said, a broader point that we see in Bahrami
and Frith’s commentary is that considering the cognitive “building blocks” underlying mind perception
can provide important clues about the structure of
social cognitive processes and their relation to accuracy. Oftentimes, this requires incorporating models
and paradigms inspired by research outside of mind
perception (and social psychology altogether). In our
target article, we mentioned executive function as one
such building block that supports accurate perception
of complex social cues (Davis & Kraus, 1997). Another
domain we feel can connect well with research on mind
perception is the study of reward processing and feedback learning. People find being accurate rewarding
(Tricomi, Delgado, McCandliss, McClelland, & Fiez,
2006; Tricomi & Fiez, 2008), and we expect that being
accurate about other people also would be perceived
as rewarding. If—like other rewards—accuracy feedback motivates changes in behavior, this could provide a mechanism for understanding the origins of
(and a possible means for changing) perceivers’ cognitive biases when encountering targets. For example,
if the strategic bias to assume self-other similarity has
been reinforced over time (by affording an accurate
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ZAKI AND OCHSNER
inference about a target), then perceivers’ continued
use of that strategy becomes easier to understand.
Can Processes and Accuracy Be Integrated
at All?
Our article was meant as a call for researchers to
spend a lot of time attempting to explicitly integrate
process and accuracy measures in single research programs and to taxonomize the relationships between
these phenomena. But the very act of making that request begs the question of whether such an integration
is even possible. If the answer to that question is no,
then this endeavor is in trouble from the get-go. Hall
and Colvin (this issue) caution that such trouble may be
on the horizon. They argue that process- and accuracyoriented researchers begin with different metatheoretical points of view (in Kuhn’s, 1962, terms: “mutually
incommensurable paradigms”) that could hamper our
ability to fruitfully compare notes or combine forces.
We find this argument interesting but believe that
these theoretical differences are more historical than
intrinsic, and offer—by way of counterpoint—an existence proof that integration across process- and
accuracy-oriented research is both possible and currently thriving. A number of the commentaries in this
issue not only argue for cross-talk between these domains but also, more important, exemplify the fact that
such integration is already occurring and can continue
to expand. In counting the ways that such progress is
being made across just this small sample of researchers,
we feel more confident than ever that the future of this
endeavor is bright.
Acknowledgments
We thank Adam Waytz for helpful comments on a
manuscript version of this response.
Note
Address correspondence to Jamil Zaki, Department
of Psychology, Harvard University, Northwest Science
Building, 52 Oxford Street, Cambridge, MA 02138.
E-mail: zaki@wjh.harvard.edu
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