Must Design Become ‘Scientific’?
Phoebe Sengers
Cornell Information Science and
Science & Technology Studies
Ithaca, NY 14850 USA
sengers@cs.cornell.edu
“In 1970 Imre Lakatos, one of the best friends I ever had,
cornered me at a party. ‘Paul’, he said, ‘you have such
strange ideas. Why don’t you write them down? I shall
write a reply, we publish the whole thing, and I promise you
– we shall have lots of fun.” – Paul Feyerabend [3, p. vii].
Thus began my education in design research1.
INTRODUCTION
“[A]s the accepting and rejecting of ideologies should be
left to the individual it follows that the separation of state
and church must be supplemented by the separation of state
and science, that most recent, most aggressive, and most
dogmatic religious institution.” – Paul Feyerabend [3, p.
15]
PROLOGUE
It’s 1999. The scene: a computer science research
laboratory.
Entering stage left is Phoebe, a geeky
computer scientist with no understanding of visual design.
She approaches Boris, a hip and therefore somewhat
intimidating interaction designer.
Design research occupies a dubious status in HCI. On the
one hand, we all recognize the important role creative
design can play in the development of effective
computational systems. On the other hand, design research
is often looked at as the epistemological poor cousin to
more obviously scientific or engineering approaches.
Creative design can improve an interface’s look and feel,
certainly, but, in the eyes of many in the academic HCI
community, it is suspect as a form of academic knowledge
because it does not yield measurable laws, generalized
conclusions, or reproducible procedures that will reliably
result in similar outcomes whenever – and by whomever applied.
Phoebe: Boris, sorry to bother you, but could you help me
with my interface? The emotional equalizer I’m building
looks really ugly and I can’t figure out why.
Boris: Hmmmm. Why don’t you try replacing those
straight lines that show the level of each emotion with rows
of little squares, like this:
In this position paper, I argue that design research generates
a unique form of knowledge which would be lost if it were
to become more ‘scientific’. I believe creative design has
something special to offer HCI, which it will lose if it is
mashed into a scientific/engineering approach. In this, I
follow a string of more polished papers [e.g. 2,18] which
have appeared in the HCI literature in defense of the unique
nature of creative design. Sadly, it seems that more such
papers will continue to be necessary. Previous papers have
focused on elucidating the unique perspectives and
practices of designers. The contribution I hope to make to
this discussion as a non-creative designer is to put the
arguments around design in the context of a broader set of
issues about the relationship between HCI and science: the
uncertain status of HCI itself as scientific research; how
knowledge is identified in the field as being scientific or
not; and what kinds of useful knowledge we can have in
Phoebe: That is amazing – this looks so much better! How
did you know that? Is there some rule about what shapes
you should use? Are there any books I could read to know
how to do it?
Boris: That’s the problem with you computer scientists.
You’re always looking for a rule for everything. You think
good design can be reduced to a 7 step procedure, and that
you could just read about it in a book and then know how to
do it. There are no procedures. Designers don’t write that
kind of book. You want to know how I know what to do?
Because I’ve been trained as a designer, that’s why! There
are no rules, you just get a sense for it with time and
training.
Note: despite Boris’s insightful rant I recommend [42] for
other geeks in the same situation, although no hard-and-fast
rules are found there either.
1
1
building computational systems that is not scientific
knowledge, and that would be lost if we forced design into
the straitjacket of what we call science. Inspired by Paul
Feyerabend’s Against Method, a playful attack on many
cherished assumptions about scientific method, my goal in
this paper is not to be correct, but to stimulate discussion of
how we in HCI conceive of what kinds of work are good.
BACKGROUND
"[G]iven any rule, however `fundamental' or `necessary'
for science, there are always circumstances when it is
advisable not only to ignore the rule, but to adopt its
opposite." – Paul Feyerabend [3, p. 23]
I have been working for an apparently interminable period
of time in the interdisciplinary area between computer
science and cultural studies. One of the goals of my work
is to develop methods for building computational systems
that are nonscientific in nature, and, in the process, to
demonstrate that other forms of knowledge, for example
from the humanities, can be useful as part of technology
design. The point is not so much to use insights from the
humanities as input to technology design, as to demonstrate
that technology design itself can be a form of humanist
practice [see e.g. 11,12,14], i.e. that creating useful
knowledge through building technology does not need to
proceed in a scientific or engineering manner (although, of
course, it can do so).
In the process, I have been repeatedly struck against folk
philosophies of science that apparently underly HCI
practice and structure what is considered to be good work.
By a ‘folk philosophy of science’ I mean something
analogous to folk psychology – an everyday way of
understanding what science is and how it works that is used
to make decisions about how work should be done,
understood, and evaluated.
These folk philosophies of
science therefore police and shape what work can be done,
often without their holders’ conscious awareness.
The pleasure of my life (and, I have noticed, of some of my
colleagues as well), is to demonstrate the fallacy of various
folk philosophies of science by demonstrating that the
opposite of these folk philosophies can be taken and one
can still generate useful results. For example, in HCI
science is generally taken to be ideally quantitative and
based on a large sample size, while O’Brien and Rodden
argue that only qualitative, small-scale, detailed studies of
domestic environments will lead to good domestic
applications [8]. Science is generally considered to focus
on clear, well-defined results, while Gaver, Beaver, and
Benford argue that ambiguity is an important part of the
technology design arsenal [6]. Science is considered to be
ideally impersonal and objective, while I argue that in some
instances a personal, autobiographical approach to design is
more effective [13].
Admittedly, it is fun to publish papers that upset the
applecart of expectations in HCI, but there is a more serious
business underlying these papers. These papers raise
awareness of opportunities for building systems and
understanding how they work that become lost when we
place too-strong strictures on the kinds of knowledge that
are acceptable in CHI. This is, in my opinion, especially
the case when we maintain a gold standard of science and
engineering as the ultimate goal of HCI knowledge,
particularly when this gold standard is animated by ideas of
what it means to do science that the history and philosophy
of science demonstrate to be false.
TRUTH AND METHOD
“[T]here is only one principle that can be defended under
all circumstances and in all stages of human development.
It is the principle: anything goes.” – Paul Feyerabend [3, p.
28]
Where exactly is the mismatch between science and
creative design? Two recent meta-papers at CHI suggest its
nature.
Gaver’s CHI workshop paper [5] argues that the
relationship between theory and practice is different in
creative design – or what he denotes practice-based
research – than is generally assumed in HCI. Gaver argues
that in HCI, the gold standard for knowledge is theory,
particularly the notion that a design will implement and test
a particular, well-defined theory or method. In contrast,
Gaver outlines his experiences of the History Tablecloth, a
table cover for the home that ostensibly denotes the
movement of objects across its surface. He argues that the
relationship between theory and practice in this case study
is not that of a theory directly driving design decisions, but
of a variety of theories at different scales (including
ethnographic research, random ideas about home life,
technological possibilities, and personal experience) all
combine to inform the design process in a rich variety of
ways.
Evaluation of the History Tablecloth, also,
demonstrated that the Tablecloth was meaningful in a large
variety of ways, which could only partially be led from the
conceptual work that had gone into its design. Rather than
demonstrating a general theory or method, for example of
ludic design, the knowledge used in and generated by the
case study were more of a “wide palette of orienting
concepts … that can be used opportunistically and
integrated in an ad hoc fashion.”
Similar issues arise in Dourish’s critique of the uptake of
ethnography in HCI [1]. Dourish argues that ethnography
as an epistemological form is badly mangled when the
knowledge it produces is reduced to a bulleted list of design
implications at the end of a paper. While it is possible that
ethnography can lead to design implications, it can also, for
example, identify things that cannot be designed for, or
simply demonstrate vividly the complexity of the situation
of design and the social factors at play in the situation that
may be designed for. These aspects of ethnographic
knowledge are lost in the simple list of design
recommendations. Here, again, we see a mismatch between
the depth and situatedness of ethnographic knowledge and
the simplified, relatively general rules for design that are
required to make an ethnography paper feel to many
reviewers like a real contribution to the science of HCI.
argues that classical AI sees "[a]n adequate account of any
phenomenon... [as] a formal theory that represents just
those aspects of the phenomenon that are true regardless of
particular circumstances" [17, p. 178]. Yet, she argues, this
is a false view of theory, since it is precisely the
particularities of the situation that enable action to happen.
Plans – i.e. formal theories – are useful for action, not
because they drive action, but rather because they act as
resources for and explanations of action which can be used,
adapted, and re-interpreted on the fly.
What both of these critiques speak to is a particular aspect
of the folk philosophy of science that underlies HCI: the
assumption that knowledge ideally should be representable
as laws, methods, or theories that are relatively independent
of context. Fitt’s Law often appears to be the gold standard
by which contributions to HCI are judged – although,
admittedly, few, if any, other contributions have lived up to
its neat succinctness.
This model of knowledge would be substantially more
adequate to creative design research practices. In fact, this
model would be more appropriate for understanding how
science itself works. As Polanyi argues [9,10], science is
informed not only by explicit theories and methods, but
equally by tacit knowledge, i.e. personal, unarticulated and
largely unarticulable knowledge such as exactly how and
when those theories and methods should be applied.
Creative design is sometimes criticized in HCI as being too
personal and subjective, yet science and engineering have
similar personal and subjective dimensions, although they
are not as well-documented within scientific circles [see
also 7]. Not everyone can learn to build a good bridge, and
few can do it simply from recipes in a textbook. As
Suchman argues, "While scientific reasoning consists in
negotiating practical contingencies of shop talk and its
technologies, those practices are notably absent from the
scientific outcomes and artifacts produced…. Just as
instructions presuppose the work of 'carrying them out', so
representational devices assume the local practice of their
production and use. Such situated practice is the taken-forgranted foundation of scientific reasoning." [16, p. 318]
As Gaver and Dourish argue, neither practice-based
research nor ethnography, properly understood, yield this
kind of knowledge. This is not to be understood as a
negative limitation of these methods, but to acknowledge
the positive alternative epistemologies that underly these
practices: small, local forms of knowledge that are
unevenly but richly true in particular, local circumstances –
‘humble’ theory, as Gaver puts it.
The goal with these approaches is, to paraphrase Gadamer,
truth, not method [4]. It is not to find relatively general
principles and theories that can be seen to hold regardless of
context. This is not because the approaches are
epistemologically weak, but because such generalized
principles and theories negate the richness of the
phenomena that the researcher is attempting to understand
and engage with. The theory or abstract knowledge alone is
not the point – the point is to engage with the social and
material circumstances of the situation, with abstract
knowledge as one – valued, but not solely determinant –
resource and output, and to report what happened in ways
that allow others to draw from them in specific, material
situations. Forcing creative design to be scientific would
mean precisely to do away with one of its central and most
useful features: rich, local, situated knowledge.
This paper, then, is a plea for a recognition of creative
design’s unique epistemological status. That which appears
to make design ‘unscientific’ – its focus on situated,
improvisational forms of knowledge – is precisely its
strength. Design does not need to be ‘cleaned up,’
systematized, and turned into routine procedures. Its forms
of knowledge can remain as stimulating design
opportunities, and need not be turned into general theories
of how the world works. This, it turns out, is not so
different from scientific practice, though it is far from the
folk philosophies of science operative in HCI. In the end,
perhaps, it is not design that should become scientific, but
science that should learn from the epistemological forms of
design.
SITUATED KNOWLEDGES
"It is often taken for granted that a clear and distinct
understanding of new ideas precedes, and should precede,
their formulation and their institutional expression… First,
we have an idea, or problem, then we act, i.e. either speak,
or build, or destroy…Creation of a thing, and creation plus
full understanding of the correct idea of the thing, are very
often parts of one and the same indivisible process and
cannot be separated without bringing the process to a stop.
The process itself is not guided by a well-defined
programme.... The passion gives rise to specific behaviours
which in turn creates the circumstances and the ideas
necessary for analyzing and explaining the process, for
making it `rational.'”– Paul Feyerabend [3, p. 23]
ACKNOWLEDGMENTS
Thanks to Boris Müller for starting my design education
and to Bill Gaver for continuing it. This work is sponsored
by NSF Award # IIS-0238132.
REFERENCES
This argument may sound disturbing and unfamiliar to
those versed in scientific traditions within HCI. But it is
analogous to Suchman’s discussions of the role of abstract
knowledge in Plans and Situated Actions [16]. Suchman
1.
3
Dourish, P. (2006). Implications for design. Proc.
CHI ’06. NY: ACM Press, 541-550.
2.
Fallman, D. (2003). Design-oriented human-computer
interaction. Proc. CHI 2003, 225-32.
3.
Feyerabend, P. (1973). Against Method: Outline of an
Anarchistic Theory of Knowledge. London: NLB.
4.
Gadamer, H.-G. (1986). Truth and Method. NY:
Crossroad.
5.
Gaver, W. (2006). Learning from Experience: The
Humble Role of Theory in Practice-Based Research.
CHI 2006 Workshop on Theory and Methods for
Experience-Centered Design.
6.
7.
8.
9.
Gaver, W., Beaver, J., & Benford, S. (2003).
Ambiguity as a resource for design. Proceedings of
CHI'03. NY: ACM Press, 233-240.
Haraway, D. J. (1991) Situated Knowledges: The
Science Question in Feminism and the Privilege of
Partial Perspective. Simians, Cyborgs, and Women:
The Reinvention of Nature. Routledge: New York, 183201.
O'Brien, J. & Tom Rodden (1997). Interactive Systems
in Domestic Environments. Proceedings of the 1997
Conference on Designing Interactive Systems. ACM
Press.
Polanyi, M. (1974). Personal Knowledge. Chicago: U
Chicago Press.
10. Polanyi, M. (1983). The Tacit Dimension. Peter Smith
Publisher.
11. Sengers, P. (1999). Practices for Machine Culture: A
Case Study of Integrating Artificial Intelligence and
Cultural Theory. Surfaces. Volume VIII.
12. Sengers, P. (2003). The Engineering of Experience. In
M. Blythe, A. Monk, K. Overbeeke, and P. Wright, ed.,
Funology: From Usability to Enjoyment. Kluwer.
13. Sengers, P. (2006). Autobiographical Design. In CHI
2006 Workshop on Theory and Method for Experience
Design.
14. Sengers, P., Boehner, K., David, S., & Kaye, J. (2005).
Reflective Design. Proc. Critical Computing, 49-58.
15. Simon, H. (1995). Literary Criticism: A Cognitive
Approach. Stanford Electronic Humanities Review,
vol 4, no 1, http://www.stanford.edu/group/SHR/41/text/simon1.html.
16. Suchman, L. (1990). Representing practice in
cognitive science. In M. Lynch and S. Woolgar, eds.,
Representation in Scientific Practice. Cambridge, MA:
MIT Press, 301-321.
17. Suchman, L. (1987). Plans and situated actions.
Cambridge: Cambridge UP.
18. Wolf, T. V., J. Rode, J. Sussman, and W. Kellogg
(2006). Dispelling "design" as the black art of CHI.
Proc. CHI 2006, 521-530.
19. Williams, R. (2003). The Non-Designer’s Design
Book, 2nd ed., Peachpit Press.