London Judgment & Decision Making Group
Autumn term 2013 – 2014
Organizers
Emmanouil Konstantinidis
University College London
Contact details:
Department of Cognitive, Perceptual & Brain Sciences
Room 204c, 26 Bedford Way, London, WC1H 0AP
UK
Telephone: (+44) 020 7679 5364
E-mail: emmanouil.konstantinidis.09@ucl.ac.uk
Neil Bramley
University College London
Contact details:
Department of Cognitive, Perceptual & Brain Sciences
Room 201, 26 Bedford Way, London, WC1H 0AP
UK
E-mail: neil.bramley.10@ucl.ac.uk
LJDM website
http://www.ljdm.info
Web administrator:
Dr Stian Reimers (Stian.Reimers.1@city.ac.uk)
LJDM members’ (Risk & Decision) list
Contact: Dr Marianne Promberger (marianne.promberger@kcl.ac.uk)
Seminar Schedule
October – December 2013
5:00 pm in Room 313, 26 Bedford Way, UCL Psychology
2nd October
Value-integration, intuitive computation and preference-reversal
Marius Usher
Tel Aviv University / University of Oxford
9th October
Cognitive modelling of experience-based decision-making: To generalise or
not?
Emmanouil Konstantinidis
University College London
16th October
The dark side of white lies
Lily Jampol
Cornell University
23rd October
Adaptive gain control during human perceptual choice
Sam Cheadle
University of Oxford
30th October
Modelling Interventions in Decision Analysis: Normative Foundations and a
New Probability Revision Method
Shweta Agarwal
The London School of Economics
06th November
NO SEMINAR – UCL READING WEEK
13th November
Cognitive Training with Real-Time Strategy Gaming
Brian Glass
Queen Mary University of London
20th November
tbc
Piotr Winkielman
University of California, San Diego
27th November
When and why do graphs enhance risk comprehension? Considering the
impact of graph literacy
Yasmina Okan
University of Leeds
4th December
tbc
tbc
tbc
11th December
Using less than we experience: The interplay between experience and memory
in choice and valuation
Nathan Ashby & Tim Rakow
University of Essex
Abstracts
02.10.2013
Marius Usher
Tel Aviv University / University of Oxford
Value-integration, intuitive computation and preference-reversal
Value integration is a central process, in various types of decisions, such as choosing a flatmate or
a selecting a stock on the basis of previous returns. While the classical approach to this process
involves an analytic mode of serial application of digital operations, research in numerical
cognition have indicated an intuitive/parallel stream of numerical processing, based on analogue
representations. Here I will present a number of recent studies we carried out showing that: i)
there are conditions that make intuitive computations of averages both better and faster than rule
based ones, ii) unlike analytic computations, the intuitive averaging can performed at high speed
and improves with the length of a sequence, iii) this computation is nevertheless subject to
attentional biases that can explain paradoxical preference reversal effects. The results will be
discussed in relation to the 2 system theory of decision processes.
09.10.2013
Emmanouil Konstantinidis
University College London
Cognitive modelling of experience-based decision-making: To generalise or not?
The study of experience-based decision-making has benefited from the application of cognitive
models which decompose individuals’ choice strategies and performance into latent cognitive
processes. Model predictions are dependent on each individual’s previous choice history as well
as the payoffs received from each option. The empirical validation of candidate models is usually
assessed based on two methods: the “one-step-ahead” prediction method that uses past choices
and payoffs to predict future choices and the simulation method which does not rely on any past
choice information and only uses past payoffs. However, these two methods yield inconsistent
results regarding which model should be preferred. A potential explanation of this discrepancy
refers to the reliance of each model on past choices and payoffs: because the simulation method
takes account of past payoffs but not past choices, a model which relies more on past choices will
perform worse under this method. We sought to better understand the discrepancy between the
two methods by employing the equal payoff series extraction (EPSE) technique (Yechiam & Ert,
2007) in a classical experience-based paradigm, the Iowa Gambling Task (IGT). Based on EPSE
we were able to quantify the degree to which each model relies on past choices and thus predict
which model will provide the best fit under the simulation method. In addition, we propose and
evaluate a new reinforcement-learning model for the IGT.
16.10.2013
Lily Jampol
Cornell University
The dark side of white lies? The subtle effect of biased performance feedback on inequality
in the workplace.
How we give and receive performance feedback is complexly determined by myriad factors such
as environment, social relationships, and individual characteristics. Yet little research has
explored the how inconsistency in communication about performance can be a subtle yet
important factor in the maintenance of inequality in the workplace. This project aims to expose a
covert and endemic bias in how we give feedback and why this bias may impact the advancement
of disadvantaged groups. Specifically, across several studies, we find that implicit gender
stereotypes (e.g., that women need protection) may make women the targets of white lies (more
positive but less accurate feedback) during performance evaluation. This may especially be the
case for participants who hold traditional views about women, and despite research showing that
women are traditionally evaluated as less competent then men. Collectively, the results of our
studies suggest that although seemingly an act of benevolence, differential telling of white lies
may actually undermine progress if particular groups of people are not receiving accurate
feedback needed to improve performance.
23.10.2013
Sam Cheadle
University of Oxford
Adaptive gain control during human perceptual choice
Neural systems adapt to background levels of stimulation. Adaptive gain control has been
extensively studied in sensory systems, but overlooked in decision-theoretic models.
I will
describe evidence for adaptive gain control during the serial integration of decision-relevant
information. Human observers judged the average information provided by a rapid stream of
visual events (samples). The impact that each sample wielded over choices depended on its
consistency with the previous sample, with more consistent or expected samples carrying greater
weight. This bias was also visible in the encoding of decision information in pupillometric
signals, and in cortical responses measured with functional neuroimaging. These data can be
accounted for with a new serial sampling model in which the gain of information processing
adapts rapidly to reflect the average of the available evidence.
30.10.2013
Shweta Agarwal
The London School of Economics
Modelling Interventions in Decision Analysis: Normative Foundations and a New
Probability Revision Method
One of the key challenges in decision analysis is modelling decision makers’ beliefs about the
world in a way which is both manageable in terms of judgmental burden and natural for the
decision makers themselves. The problem context explored in this project is one where actions
can affect the probability of one or more uncertain events (for instance advertisers designing
marketing campaigns to improve the chance of success of a new product or operational risk
mitigations). A convenient modelling tool of choice for such decisions is the influence diagram.
We address the normative foundation of influence diagrams where probabilities of a chance
variable depend on a decision and argue that a general foundation for influence diagram
modelling is provided by Causal Decision Theory (CDT). Then we show that generalizations of
existing probability revision methods to model interventions in decision analysis (generic
controller of Matheson and Matheson), coincides with a class of linear probability revision
rules—‘imaging’—and expose the theoretic advantages of the linearity property. We also propose
a convenient method to operationalize the concept of linear probability revision rules and illustrate
its application using a real world case study conducted for a leading insurance company.
06.11.2013
UCL READING WEEK – NO SEMINAR
13.11.2013
Brian Glass
Queen Mary University of London
Cognitive Training with Real-Time Strategy Gaming
Training in action video games can increase the speed of perceptual processing. Additionally, we
find that video-game training can lead to broad-based changes in higher-level competencies such
as cognitive flexibility, a core and neurally distributed component of cognition. Two versions of a
real-time strategy (RTS) game are compared to determine which video gaming characteristics can
enhance cognitive flexibility and why these changes occur. Using a meta-analytic Bayes factor
approach, we found that the gaming condition that emphasized maintenance and rapid switching
between multiple information and action sources led to a large increase in cognitive flexibility as
measured by a wide array of non-video gaming tasks. Theoretically, the results suggest that the
distributed brain networks supporting cognitive flexibility can be tuned by engrossing video game
experience that stresses maintenance and rapid manipulation of multiple information sources.
Practically, these results suggest avenues for increasing cognitive function.
20.11.2013
Piotr Winkielman
University of California San Diego
tbc
tbc
27.11.2013
Yasmina Okan
University of Leeds
When and why do graphs enhance risk comprehension? Considering the impact of graph
literacy
In order to make informed medical decisions people need to understand information about risks,
benefits, and drawbacks of different treatments. Graphical displays—including bar charts, icon
arrays or line plots—are powerful tools that can facilitate the communication and comprehension
of such information. However, inadequately designed graphs may not only be unhelpful, but can
also lead to errors in comprehension and mislead decision makers. Individuals with low graph
literacy (i.e., the ability to understand graphically presented information) can be at a higher risk of
misinterpreting the data depicted. I will present results of a series of experiments designed to (1)
identify the errors that are most prominent among individuals with low graph literacy, (2) uncover
the cognitive processes underlying such errors, and (3) test graphical design features (i.e.,
dynamic displays) that can reduce errors and foster informed medical decision making.
Experiments included web questionnaires as well as laboratory-based studies involving process
tracing methodologies (i.e., eye-tracking). Results revealed that graph literacy affected allocation
of attention to regions of graphs containing essential information for accurate interpretations. I
will discuss implications of our results for the design of graphical risk communications, including
the customization of health-related decision-support systems.
04.12.2013
tbc
tbc
tbc
tbc
11.12.2013
Nathan Ashby & Tim Rakow
University of Essex
Using less than we experience: The interplay between experience and memory in choice and
valuation
Recent research investigating decisions from experience suggests that not all information is
treated equally with more recently encountered information being weighted heavier in the
decision process (Hertwig, Barron, Weber, & Erev, 2004). We report three studies investigating
how this differential treatment of information affects subjective valuations of and choices between
risky prospects and what role individual differences in working memory play. In Study 1 we find
that a model averaging only a subset of the most recently encountered outcomes fits the data best.
In Study 2 and 3 we replicate and expand on this finding by showing that the amount of
information used to form valuations and choices varies between individuals and that digit span
explains a significant portion of this variation. Combined, these results indicate a direct link
between cognitive capacity and information usage, providing further insight into the processes
involved in the construction of value.