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The
British
Psychological
Society
British Journal of Psychology (2008), 99, 317–340
q 2008 The British Psychological Society
www.bpsjournals.co.uk
Cognitive Ethology: A new approach for studying
human cognition
Alan Kingstone1*, Daniel Smilek2 and John D. Eastwood3
1
Department of Psychology, University of British Columbia, British Columbia,
Canada
2
Department of Psychology, University of Waterloo, Ontario, Canada
3
Department of Psychology, York University, Ontario, Canada
We all share a desire to understand and predict human cognition and behaviour as
it occurs within complex real-world situations. This target article seeks to open a
dialogue with our colleagues regarding this common goal. We begin by identifying the
principles of most lab-based investigations and conclude that adhering to them will fail
to generate valid theories of human cognition and behaviour in natural settings. We
then present an alternative set of principles within a novel research framework called
‘Cognitive Ethology’. We discuss how Cognitive Ethology can complement lab-based
investigations, and we show how its levels of description and explanation are distinct
from what is typically employed in lab-based research.
The study of human cognition has been punctuated by three historical stages of advance
(Van Kleeck & Kosslyn, 1991). The first stage, beginning in the late 1950s to early 1960s
was marked by a rapid progression propelled by the methods of traditional
psychophysics and experimental psychology. The second stage, beginning by the
mid-1970s, was fuelled by computational analysis that signalled the arrival of cognitive
science. The third phase, which began in the mid-1980s, incorporated evidence from
neuropsychology and animal neurophysiology, and most recently an ever increasing
array of techniques for scanning the brain of alert participants.
In the present article, we take as our starting-point a critical problem that continues
to bedevil the study of human cognition that arose precisely from the original and
remarkably successful methods of experimental psychology. Those methods, which
involved simplifying the issue of investigation by making the experimental context both
impoverished and controlled, sought to discover causal relationships between one
factor and another. The intention was that by minimizing the complexity of the
environment and maximizing the experimental control, investigators could create
theories that would be universally valid. However, by the mid-1970s it had become very
* Correspondence should be addressed to Dr Alan Kingstone, Department of Psychology, University of British Columbia,
Vancouver, British Columbia, Canada (e-mail: [email protected]).
DOI:10.1348/000712607X251243
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318 Alan Kingstone et al.
clear that most statements were true if, and only if, particular laboratory conditions were
met. In other words, the relationship between factor A and factor B was predictable if,
and only if, specific conditions were established within the lab; the relationship
between factors became unpredictable when these laboratory situations were not met.
Thus, for example, memory experiments found that what people remembered
depended on factors such as (a) what processing they performed on the stimulus
materials; (b) what stimulus materials they expected to receive; (c) what materials were
actually presented; (d) what people were doing before their memory was measured; (e)
how their memory was measured, and so on and so forth. The take home message was
that cognitive processes vary and are affected by what is happening elsewhere within
the cognitive system, and therefore cognitive processes depend critically on the specific
situational context in which a subject is embedded.
The field’s response to the above fact has generally taken one of the two forms. One
reaction is to deny that there is a problem. This ‘response’ enables one to maintain the
initial assumption that cognitive processes are invariant and unaffected by what is
happening elsewhere, and thus allows one to continue to create and study laboratoryspecific phenomenon like ‘nonword repetition memory’ or ‘inhibition of return’. The
other reaction is to acknowledge that there is a problem, but then continue to conduct
research predicated on the assumption that cognitive processes are invariant. Both
responses are what Broadbent (1991) has called ‘pathological’.
Occasionally, investigators like Donald Broadbent and Ulric Neisser have tried a third
response. They acknowledged that cognitive processes change with situational changes
and worked hard to bring the implications of this fact to the awareness of others.
Perhaps their only mistake was to trust that the next generation of researchers would
take their words to heart and try to find a solution to the issue. In hindsight, this faith has
proven to be grossly misplaced, as the next generation of researchers have adopted one
of the pathological responses of the past and grounded their neuroimaging
investigations on the false assumption that cognitive processes are invariant across
situations. It is precisely this false assumption that allows researchers to make the
remarkable claim that the cognitive processes that they engage and measure in a simple,
artificial brain neuroimaging situation captures the same fundamental cognitive
processes and associated neural systems that are engaged in a complex natural situation.
The aim of the present paper is modest but against this historical backdrop, we
believe it is vital. We aim to initiate a dialogue among researchers regarding the fact that
cognitive processes vary substantially with changes in context. We also hope to
stimulate researchers to find a response to this issue that is not ‘pathological’. By putting
forward a possible solution of our own, a novel research approach that we call
‘Cognitive Ethology’, our intention is to encourage other researchers to develop and
advance their own positive responses. While what follows for the remainder of this
paper focuses primarily on instances of cognition as it pertains to the investigation of
human attention, we think that the issues we raise here can be readily extended to other
research domains of human cognition.
Laboratory research
Laboratory research in the field of human cognition is founded on the critical
assumption that human cognition is subserved by processes that are invariant and
regular across situations. This invariance assumption enables one to conduct a study in
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Cognitive Ethology
319
the laboratory and then to propose that the process being measured is expressed in
everyday life. Importantly, there is a second assumption that falls out of the first. Given
that processes are assumed to be invariant across situations, it follows that one can
reduce situational variability without compromising the nature of the process one is
measuring. Indeed, a basic objective of the experimental environment in the laboratory
is to gain as much control over a situation as is possible so that any change can be
attributed to the variable that is being manipulated.
Together, these assumptions provide a powerful one–two punch. The assumption of
process stability enables the scientist to be concerned with real-life situations without
ever having to leave the laboratory. In addition, the assumption of control drives the
scientist increasingly away from complex real-life situations to paradigms that are
simple, contrived, and artificial.
These assumptions are not, however, without their risks. For instance, the
assumption of invariance eliminates any need or even obligation for the scientist to
confirm that the process being manipulated and measured in the laboratory actually
expresses itself in the real world. Investigators do, of course, through the process of
replication, check that their lab-based effects are regular within the laboratory
environment. Unfortunately, a result that is invariant within the strict confines of the
laboratory does not mean that it is reproducible outside the lab. Indeed, even a cursory
examination of the literature reveals that there are many instances where even the most
minor change within a laboratory situation will compromise the replicability of an effect
(e.g. Atchley & Kramer, 2001; Berry & Klein, 1993; Bindemann, Burton, & Langton,
2008; Soto-Faraco, Morein-Zamir, & Kingstone, 2005; Wolfe & Pokorny, 1990). In
addition, as any researcher knows all too well, failed replications that are published
represent just the smallest tip of a very large iceberg of failed replications that are
obtained in the laboratory and never published.
Upon closer consideration, there is a good reason why lab-based effects should be so
remarkably fragile. After all there is a large, well established, and growing body of
literature indicating that process stability is tied intimately to the situation used to create
it, with participants’ strategies and associated brain configurations changing from one
situation to the next (see for instance Duncan & Owen, 2000 for a review). Neisser
(1976) referred to these dynamic configurations as ‘schemata’, Monsell (1996) has
spoken of ‘task-set reconfigurations’, and Di Lollo, Kawahara, Zuvic, and Visser (2001)
have referred to ‘configurable input filters’. In each case, the basic message is that
cognitive processes change with situational context; and conversely, process invariance
reflects situational stability.
We acknowledge that some cognitive processes are relatively regular across
situations. Some aspects of language production would seem to qualify. However,
critically, based on laboratory findings alone, it is not possible to know whether
mechanisms that appear invariant in the laboratory environment will survive outside the
lab. Thus, the principle of invariance cannot, and should not, be assumed. This point is
made most forcefully by Broadbent when he writes: ‘In light of the evidence I would feel
this [assumption of invariance] is almost pathological; it can only be preserved by
avoiding the literature produced by people who use different background conditions of
experiment’ (Broadbent, 1991, p. 874).
Ironically, any attempt to test the assumption of invariance against real-life
situations is met immediately with obstacles that arise from the second assumption of
experimental control. The first obstacle is that cognitive concepts often become defined
by the experimental controls that are used to examine them. For instance, reflexive
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320 Alan Kingstone et al.
attention is often defined as a process that benefits the detection of, and response to, a
visual target stimulus that occurs shortly after the abrupt onset of a peripheral, spatially
non-predictive, stimulus event. It is not clear whether such a sequence of events ever
occurs naturally in real life, and if it did, how this event could be measured.
Let us accept for the moment that this first obstacle is somehow overcome, and
reflexive attention as defined in the laboratory is measured in the real world.
A researcher is then immediately posed with the second obstacle of having to make the
case that the data collected in the real-life situation are, in fact, a manifestation of the
same process being measured in the lab. This is a daunting, and perhaps an ultimately
impossible, obstacle to surmount. Our reservation is derived from the very fact that
variables that are controlled in the laboratory are not controlled in real life. Therefore, a
real-world effect that appears to be the product of a controlled laboratory effect can
always be re-attributed to factors that were uncontrolled in real life. Conversely, the
failure to find evidence of a laboratory effect in the real world can be dismissed, as it is a
fallacy to conclude that something does not occur simply because one does not find
evidence for its existence. Thus, there is no direct way to demonstrate or refute that
causal factors found in a simple lab-based setting are also being expressed in a complex
real-world situation. Note that the purported real-world relevance of lab-based
findings cannot be falsified; such claims, therefore, are, in this most important regard,
unscientific.
Driving the nail further into this coffin is the fact that general systems theory (see
Ward, 2002; Weinberg, 1975) has demonstrated that tight experimental control can be
effective at revealing the basic characteristics of simple linear systems but it is
ineffective at revealing the characteristics of complex, non-linear systems, which must
surely include the human cognitive system. General systems theory holds that certain
stable characteristics of complex systems are only revealed, or emerge, when several
variables are able to vary together. Of course, this is precisely what is prohibited in
controlled laboratory situations, and it is precisely what occurs in uncontrolled natural
situations.
Cognitive Ethology
If there are both practical and principled reasons to conclude that lab-based studies
grounded on the assumptions of invariance and control are unlikely to inform us about
cognitive processes as they are expressed in real-life situations, then what are
researchers to do? Our experience, like that of Broadbent’s (1991), has been that,
whether or not researchers acknowledge that the assumptions of invariance and control
are problematic, they behave as if these assumptions are unproblematic and that they
will lead to cognitive theories that are universally valid. We sympathize with these
responses and fully acknowledge that we have indulged in them ourselves. There is
much to be said for denial. It lets one continue to do what one loves to do – to generate
questions and hypotheses, design experiments, collect data, write papers, go to
conferences, interact with colleagues, mentor students, and in general to ‘move
forward’ in one’s career as a scientist. Any and all of these items are powerful motivators
for us to look away from the basic fact that doing our simple experimental lab-based
studies is not going to enable us to develop theories that can predict and explain
cognitive processes as they are expressed in real-world situations. A second option, and
one that we explore in the remainder of this paper, is to first directly study how people
behave in their natural real-world environments before moving into the lab. That is,
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Cognitive Ethology
321
rather than being locked into a laboratory paradigm with the a priori assumption that
the paradigm or task that is being applied is tapping into processes that are expressed in
everyday life-situations, one would instead opt to explore first how people behave as
they function within a naturally occurring situation. Once this complex problem space
is identified and described then one could begin to move into the laboratory to test
hypotheses that are generated by real-world observations. We have called this approach
‘Cognitive Ethology’.
A Nature publication by Land and Lee (1994) provides a good illustration of a
research approach that is grounded in the principle of first examining performance as it
naturally occurs. These investigators were interested in understanding where people
look when they are steering a car around a corner. This simple issue had obvious
implications for human attention and action, as well as for matters as diverse as human
performance modelling, vehicle engineering, and road design. To study this issue, Land
and Lee monitored eye, head, steering wheel position, and car speed, as drivers
navigated a particularly tortuous section of road. Their study revealed the new and
important finding that drivers rely on a ‘tangent point’ on the inside of each curve,
seeking out this point 1–2 seconds before each bend and returning to it reliably.
For the present purposes, what is especially striking about the Land and Lee paper is
that it was conducted without falling into the standard experimental assumptions of
invariance and control. By stating that one is interested in understanding how one
performs in a real-world situation, like driving around a corner, one is implicitly
acknowledging that there may be no model laboratory task that can speak to the
question under consideration. In other words, this Cognitive Ethology research
approach rejects the assumption of process stability. In doing so, it assumes that
processes may be contextualized to the situation within which they occur.
The Land and Lee study is also important because by choosing to measure
performance as it naturally occurs, Land and Lee were rejecting the standard a priori
assumption that variance that is not manipulated experimentally is something to be
controlled. This alternative way to deal with variance, to let it occur naturally and
measure it, is based on the assumption that variance may reveal key characteristics of
cognitive processing. In other words, it is based on the assumption that variance is part
of the complex cognitive signal that must be understood. This is the second key
assumption underlying the Cognitive Ethology approach. It also dovetails with the basic
tenet of general systems theory that complex systems are only revealed, or emerge,
when several variables are free to co-occur.
At a first glance it may seem that Cognitive Ethology is merely espousing an ‘applied’
approach to research, that is, an approach that will result in a non-integrated collection
of insights regarding human behaviour in specific real-world contexts. While such
knowledge is of unquestionable utility, it is not our focus. We wish to make a far broader
and deeper claim. We argue that cognitive processes and behaviours that are
generalizable and meaningful are most likely to reveal themselves when people are
studied first under the real-world conditions where multiple variables are free to
co-occur. Specifically, we argue that it is by starting with real-world observations and
individual variation that one is most likely to generate subsequent research questions for
investigation that may lead to general principles of cognition that have relevance to
naturally occurring phenomena. Note that we are not stating that by studying behaviour
outside the laboratory one can assume that generalization between situations will
occur (see for instance the study by Underwood, Chapman, Crundall, Cooper, & Wallen,
1999 which suggests important limitations to the Land and Lee (1994) investigation).
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322 Alan Kingstone et al.
Rather, we are saying that by starting at this level of investigation one can begin to ask
questions that are truly relevant to the real world; and over time begin to draw out
features of behaviour that are common across natural situations by conducting studies
both inside and outside of the laboratory (see for instance Hayhoe & Ballard, 2005).
In sum, the Cognitive Ethology research approach rejects the standard assumptions
of invariance and control, and in their place we find a commitment to understanding the
situation against its real-life background conditions and the variance within that
environment. According to this approach, the initial job of the researcher is simply to
observe, describe, and measure what people do and experience in the situation of
interest (see also Koch, 1999; Rosch, 1999). In this regard, description of real-world
behaviour and experience serves to define the ‘explananda’ of inquiry. Of course, such
an observation is unlikely to be of much value in artificial laboratory situations where
human behaviour is typically highly constrained. For instance, in a typical fMRI attention
experiment that measures human behaviour and brain activations, people are only
allowed to move one finger to press one key, with all other movements, including even
minor head and eye-movements prohibited.
Yet, the observation of real-world behaviour is very different. As stated by Koch
(1999, p. 27), ‘description is no lowly or easy task; it is in fact the very basis – indeed, the
flesh – of non-spurious knowledge’. Description of people’s cognitive functioning in
complex real-world situations is intrinsically valuable and meaningful because it is
grounded in reality and therefore maps out precisely what cognitive research ultimately
seeks to predict and understand.
Related to the emphasis on describing cognitive functioning in the real world is the
notion that researchers can begin their research enterprise by describing cognition in
the concepts that are used in everyday ‘folk-psychological’ language (see Prinzmetal &
Taylor, 2006; Birmingham, Bischof, & Kingstone, 2008, for recent instances of folk
psychology helping to guide research). To be clear, this approach does not entail
necessarily accepting ‘folk-psychological’ explanations of cognitive functioning, nor
does it reject the idea that important concepts should be refined and given more
technical meanings on the bases of subsequent scientific inquiry. Rather, the Cognitive
Ethology approach simply asserts that there is a potential benefit of initially grounding
our observations and concepts in real-world situations.
Just as there were practical problems for the assumptions of invariance and control
when they are applied to understanding real-world phenomena, one finds that there are
also practical problems for the assumptions of situation and variance. One key problem
is quite simply that it is very hard to do research at the real-world level. It is hard for
several reasons. First, it is difficult because there are no ‘off the shelf’ model tasks to use
when one conducts this form of research. Hence, one cannot, for instance, simply
manipulate the Posner cueing paradigm or the visual search paradigm and claim that one
is gaining new insights into how people allocate their attention in everyday life (see
Kingstone, 1992; Eastwood & Smilek, 2005 for precisely this type of claim). Instead, one
has to spend a good deal of time observing and describing what people are doing. In
addition, because one is not attempting to control what people do, there is a
tremendous amount of variation in the behaviour that people produce whether it is
different people at the same time or one person at different times. It is also difficult
because there is relatively little scientific data on how people behave in the real-world
situations rather than in artificial laboratory environments. This means that what
questions and approaches are most interesting and likely to bear fruit are largely
unknown. It also means that there may be little or no previous work performed on how
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Cognitive Ethology
323
to go about analysing the data one collects, and therefore, one may have to create new
analysis tools to gain a full understanding of the data that has been collected.
We would argue, however, that these challenges are better viewed as exciting
opportunities for researchers interested in truly discovering and understanding human
cognition. All the complex real-world data one collects, and all the questions that one
explores and answers, provide a foundation for future investigations and a benchmark
against which other studies can be measured. By beginning one’s research enterprise at
the level of natural performance rather than lab-based manipulations one sets out to
discover what really happens in the world, and in the words of Neisser ‘finding out what
really happens in the world around us : : : will be worth knowing in any imaginable
future’ (Neisser, 1976, p. 10).
Integrating Cognitive Ethology with laboratory investigations
Our position, that Cognitive Ethology and lab-based studies are founded on opposing
assumptions, raises the question as to whether these two approaches should be viewed
as competing or complementary. On the one hand, they may be seen as competing
frameworks. Informal discussions with our colleagues, as well as a historical reading of
the field (e.g. Banaji & Crowder, 1989; Neisser, 1991), indicates that real-world and labbased investigations have tended to be viewed as competitive enterprises. Our
demonstration that the two forms of research are based on opposing assumptions makes
this conflict between approaches a natural one. Yet, their goal is ultimately the same – to
predict and explain human cognition as it operates in the real world. Therefore, one
would think that the two frameworks might be able to operate in harmony rather than
opposition.
We would go one step further and suggest that only when both approaches are
rigorously pursued will it be possible to achieve the goal of understanding how
cognition operates in everyday settings. In short, we see these two research frameworks
as complementary and mutually constraining. This point is illustrated by a second
Nature paper by Land and Horwood (1995) that followed up on the original Land and
Lee (1994) investigation. Land and Horwood conducted controlled laboratory
experiments in a driving simulator to determine what kinds of cornering information
are critical to normal, and abnormal, driving performance. They did this by
systematically removing corner information that is normally present in the real-world
driving environment. The critical point that we wish to make here is that the laboratory
experiment conducted by Land and Horwood (1995) was based on a rigorous
description of driving behaviour in the real world reported by Land and Lee (1994).
Once that description was in place, then the obvious transition was to the laboratory to
recreate, control, and manipulate the effect. Notice though that without first having
discovered what people do in the real-world driving situation Land and Horwood would
be unable to identify when lab-based performance was abnormal. Thus, by starting at
the real-world level, one is grounded in what people really do when they are not in the
lab, and hence, one can determine what behaviours are, and are not, specific to the
laboratory environment.
In summary, the work by Land and colleagues provides a good example of how
complex real-world descriptions provide a series of systematically articulated observations
to which lab-based investigations can be linked and validated. Once real-world
observations are made, the laboratory-based approach can then be applied to evaluate
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324 Alan Kingstone et al.
and study real-world behaviour by systematically imposing control. In this way, it is
possible for Cognitive Ethology investigations to guide laboratory investigations. Without
such guidance, lab-based investigations run the real risk of moving further
and further away from everyday situations and studying behaviours and theoretical
conceptualizations that are meaningful only to the artificial environments that give
rise to them.
Finally, it is also worth noting that the Cognitive Ethology research approach
provides a way for the research enterprise to be immediately and effectively selfcorrecting. This is because if people begin to behave differently in the laboratory than
in real life, for instance, no longer using the ‘tangent point’ while cornering in a
simulator, the investigator is alerted to the fact that there is something in the laboratory
that fails to capture what people really do in the real world. This sensitivity to whether a
laboratory environment is, or is not, able to scale up to the natural world is absent when
one applies the current operating standard of conducting laboratory research first in
isolation from any systematic naturalistic observation.
Personal and subpersonal levels of explanation
Following Dennett (1969, 1978; see also Pessoa, Thompson, & Noe, 1998) we believe
it is important to distinguish between two levels of explanation referred to as
the personal level and the subpersonal level. Personal-level explanations focus on
describing and understanding the person as a whole organism interacting with his or
her environment. Here the focus is both on what the active, engaged person is doing in
the environment and what information is available to that person to support
purposeful, functional behaviour. In contrast, subpersonal-level explanations involve
describing and understanding the person in terms of the internal organization and
processes of the brain. Here the focus is on the brain mechanisms that subserve
cognition, what information is available to those mechanisms, and how these
mechanisms process the information.
Laboratory studies of cognition typically focus on explaining behaviour at the
subpersonal level in terms of the mind/brain mechanisms that underlie cognition.
A good example of attention studies aimed at a subpersonal level of explanation is
provided by studies of covert attention (e.g. Posner, 1978). Covert visual attention refers
to the selection that occurs without movement of the eyes. In other words, covert
attention is a selection mechanism within the mind/brain and it is often believed to be
subsumed by several neural networks (e.g. Posner & Raichle, 1998), with the midbrain
responsible for the movement of attention, the thalamus controlling the engagement of
attention, and the parietal lobe managing the disengagement of covert spatial attention.
Similarly, the standard box and arrow diagrams that identify attention as a stage or
process in an information-processing framework (see Pashler, 1998) and the various
brain areas that have been identified in neuroimaging studies as being relevant to
attention (Corbetta & Shulman, 2002) are all explanations of attention at a subpersonal
level. Subpersonal explanations often aim to explain cognitive behaviour by assuming
that cognitive processes and their associated neural activations are relatively invariant
across different background conditions.
Though most studies of cognition focus on uncovering subpersonal explanations of
human cognition and performance, there are good reasons to believe that such a level of
explanation is not sufficient. First, subpersonal explanations often do not provide a
satisfying answer as to why cognitive performance is how it is. Second, subpersonal
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Cognitive Ethology
325
explanations fail to explain how cognitive performance relates to other cognitive
systems. Third, subpersonal explanation fails to recognize that cognition is inherently
distributed among multiple individuals (e.g. shared attention during reading or problem
solving) and the environmental context (e.g. use of memory aids like a personal digital
assistant (PDA) or a pilot’s use of cockpit gauges). In each case, the shortcomings of the
subpersonal account are addressed by a personal-level explanation. We illustrate these
points below.
Visual search asymmetry refers to the finding that looking for an object is not equally
efficient when the role of target and distractor is reversed in a search display. For
example, in Figure 1 search is less efficient when the white-topped item is the target and
the black-topped items are distractors (as shown) than when this relation is reversed.
To experience this effect, simply turn Figure 1 upside down and look for the target. The
target is now the black-topped item and it stands out conspicuously among whitetopped distractors.
Why should an apparently trivial feature difference between target and distractors,
such as which is white on top and black on the bottom, have such a profound effect on
search performance? A subpersonal explanation will typically sidestep this larger
question and point to a different neural pattern of activation for the two different search
conditions or propose a mechanism at some level of the information-processing
highway. Yet, such explanations do not provide an answer to the original and bigger
question of ‘why?’.
To provide this answer, researchers reach out to a personal level of explanation,
grounding their account on how people interact with their everyday environments.
Thus, they propose that human vision is biased to expect a scene to be lit from overhead
because in the real world there is a single sun that shines overhead illuminating objects
from the top (Ramachandran, 1988; van Zoest, Giesbrecht, Enns, & Kingstone, 2006).
Specifically, the effect of such lighting in a three-dimensional environment is to produce
shading gradients in the resulting image. Objects that are uniform in their surface
coloration and generally convex will tend to be lighter at the top, where the surfaces
have a more direct access to the light source, and darker at the bottom, where light is
less able to reach the surface. A bias to interpret the meaning of these patterns of
luminance is thus used to explain why search difficulty varies in Figure 1, where the
items can be interpreted as being influenced by overhead lighting. It also explains why
the search asymmetry in Figure 1 favoured the black-topped target, as this runs against
the standard expectation of scene shading. Thus, one finds that the personal-level
explanation complements, and ultimately grounds, the subpersonal explanation.
A second example is simpler, but no less compelling. It is well accepted that
attention can be drawn to many different changes to stimulus features – colour, shape,
motion, luminance, and presentation of a new object in the visual field. Importantly,
some of these features are more effective than others at attracting attention, for example
a luminance change is generally more effective than a colour change in attracting
attention. One explanation, a subpersonal account, would interpret these differences in
terms of inherent differences in neural signal properties. For instance, light or motion
changes are more effective in attracting attention than colour or form change because
the magnocellular visual pathway (which is concerned with processing luminance and
motion) is more rapid than the parvocellular visual pathway (which is concerned with
processing colour and form). According to this subpersonal viewpoint, a new object
should have no privileged influence on attentional orienting, over and above the
influence of its constituent features. However, this is not the case. The presence of a
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326 Alan Kingstone et al.
Figure 1. Search is harder when the white-topped item is the target and the black-topped items are
distractors (as shown) than when this relation is reversed. This effect can be experienced by turning the
figure upside down and looking for the black-topped target which stands out conspicuously among
white-topped distractors. This black-topped target is thought to be easy to find because it runs against
our everyday expectation of scene shading where items are normally lit from the top, for example, by a
single sun overhead.
new object is more effective in attracting attention than any other feature change
(Yantis, 1993).
Why do new objects exert such a powerful influence? To answer this question
investigators have again gone beyond the subpersonal level of explanation and provided
a personal-level account that is based on the relevance that different features play in
an individual’s everyday life (Enns, Austen, Di Lollo, Rauschenberger, & Yantis, 2001).
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327
They note that while feature changes like colour and shape are important, they are not
as fundamentally important to an individual as is the appearance of a new object. Why?
Because feature changes may be considered as updates to a known stimulus object,
whereas the appearance of a new object introduces an unknown item into the scene,
one which must first be identified, for example, as a predator or a prey. Thus, one finds
again that subpersonal explanations do not provide a compelling understanding of why
a cognitive process operates as it does. That account is provided by a complementary
personal-level explanation.
Subpersonal explanations of cognition, for instance ones which identify cognitive
processes solely as information-processing mechanisms within the brain, also fail to
provide a satisfactory explanation of more systemic aspects of cognition such as the
sorts of attentional behaviour that emerge when two or more individuals are
communicating or are engaged in a common task. Yet, such collaborative attention is
critical in our everyday lives, particularly in safety critical sectors such as aviation.
In December 1972, Eastern Airlines Flight 401 crashed into the Florida Everglades. The
reason: Three experienced professional pilots simultaneously focused their attention on
a small malfunctioning indicator light and no one was paying attention to the fact that
the autopilot had disengaged. As a result of this catastrophic failure of collaborative
attention, no one was flying the plane (Vicente, 2003). The important point of this
example for present purposes is that the cognitive dynamics that ultimately led to the
crash of Flight 401 are difficult to explain based on subpersonal mechanisms that are
localized within the mind/brain of an individual. The clear failure of attention occurred
as a result of the interaction between individuals and was therefore distributed among
individuals and their immediate environment. Such distributed cognition (see Hutchins,
1995) requires a different level of explanation, a personal-level account that includes a
consideration of multiple individuals, their current goals, abilities, and beliefs, as well as
their specific situational demands.
Collaborative attention has already been established as a critical factor for child learning
and development (e.g. Tomasello, 1995; Dunham & Moore, 1995). For instance, numerous
studies of joint attention in human infants has shown that 1-year old infants are able to
follow the direction of gaze of others (e.g. Butterworth & Corchran, 1980; for a review see
Tomasello, 1995) and that children as young as 2 years make inferences about where a
parent is attending when acquiring language skills (Tomasello & Todd, 1983). Such joint
attention has even been linked to development of theory-of-mind in children (e.g. Charman
et al., 2000), arguably one of the more critical characteristics of well-adjusted adults. As with
the crew members of Flight 401, the cognitive dynamics that underlie joint attention in
children and their parents, or any two or more individuals for that matter, cannot be
satisfactorily explained solely with reference to subpersonal mind/brain mechanisms
within an individual. A personal level of explanation is again required.
To reiterate, the personal level of explanation focuses on understanding human
cognition as operating in service of individuals as they interact with an ever-changing
real-world environment. The specific focus is on explaining cognition in terms of (a) the
behaviour of whole embodied people and their interaction with their environment and
others around them (Pessoa et al., 1998) and (b) people’s subjective experiences, goals,
and beliefs (see Jack & Roepstorff, 2003). Rather than solely construing cognition as a
neural or information-processing system, explanations of cognitive performance at the
personal level construe cognition as an overt system involving an embodied individual,
an environment (which includes other people), and the person’s goals, purposes,
and beliefs.
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328 Alan Kingstone et al.
Although the personal and subpersonal are two distinct ways of describing and
understanding human cognition, they are clearly related and can, in a complementary
manner, enrich our overall understanding of human cognition. For instance, a personallevel approach to the study of attention can assist the subpersonal approach reach its
goal of understanding how attention operates in everyday settings. Specifically, by
concretely describing how cognition functions at the personal level it can become clear
which situations and variables are important to study at a subpersonal level.
We do not mean to suggest that in the past subpersonal studies have been conducted
completely without any guidance from personal-level observations. Indeed, most
researchers use their own informal personal-level observations to guide their research to
some extent. However, this is certainly not the kind of personal-level guidance that we
are suggesting here. In fact, there are several reasons to believe that this type of informal
guidance has led subpersonal investigations further away from the real world rather
than closer to it. First, a researcher’s informal observations are often guided primarily by
the constraints of their laboratory paradigm or a particular theoretical framework to
which they adhere. Such observations are inherently biased and serve to further
perpetuate the existing views (Kingstone, Smilek, Ristic, Friesen, & Eastwood, 2003).
Thus, while such informal observations give the appearance that subpersonal research
is being guided by real-world descriptions, in actuality, the subpersonal framework may
be constraining and overly determining personal-level observations. In addition,
informal observations may not be representative of many of the possible outcomes in
the real world and therefore can generate laboratory paradigms that reflect and entrench
these limitations. Without a systematic, clear, and extensive articulation of how
individuals behave in the real world, it is unclear how one can evaluate the merit of
either the informal observations made by researchers or, more importantly, whether the
laboratory findings are consistent with how people behave in the real world. For these
reasons we propose that informal personal-level observations are not sufficient to guide
subpersonal research and that personal-level descriptions of attention are necessary. It is
precisely this systematic articulation of cognition at the personal level that is currently
lacking.
In addition to guiding subpersonal studies, personal-level explanations can also
reveal the reasons why subpersonal mechanisms function as they do. Consider the
search asymmetry and attention capture by new objects examples discussed earlier.
Though, of course, there must be some subpersonal brain mechanisms that underlie
these behaviours, the reasons why those mechanisms function the way that they do only
becomes apparent when one considers the behaviour of the individual at the personal
level.
A similar argument has recently been made by Findlay and Gilchrist (2003) regarding
the function of covert attention. They argue that covert attention, as it is understood in
the lab-based settings (i.e. orienting without any concomitant eye-movements), does not
seem to serve any important purpose. They give several reasons. First, spatial cueing
leads to relatively small increases in the speed of responses to a cued target, being often
less than 40 ms. Second, the speed with which covert attention is shifted is not
substantially faster than overt shifts of attention. And third, covert attention is not a
necessary explanation of the apparent limitations in capacity because selection can
occur at many levels of the system. According to Findlay and Gilchrist (2003), the
purpose and function of covert attention becomes clear only when covert attention is
considered as part of a larger attention system which involves the act of overt eyemovements as individuals select information from their environment.
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Cognitive Ethology
329
Collectively, the ideas presented in this section suggest the assertion that cognitive
processes, like covert attention, cannot be fully understood at the subpersonal level
unless the explanation is grounded in a personal-level understanding of peoples’ overt
cognitive behaviour and their experiences, beliefs, and intentions as they select
information in their everyday environments. We explore this proposal in the next
section.
Cognitive Ethology and subjective experience
Consistent with our position that a personal-level description and explanation is
critically important to scientific investigations, we suggest that it is essential that one
seek to observe and describe the subjective experiences of individuals as well as their
overtly observable (objective) experiences. It should go without saying that subjective
experience is at the heart of cognitive performance in complex natural settings. For
instance, we select objects in our environment to become conscious of them and then
to flexibly interact with them. Yet, laboratory studies of cognition rely heavily on
measures of objective behaviour and often ignore subjective experience. For example,
studies of attention using the Posner cueing paradigm measure spatial attention by
measuring peoples’ objective response time and accuracy as they detect a target
stimulus. In fact, measuring people’s reaction time and accuracy as they detect, identify,
or localize simple stimuli constitutes one of the primary measures used in studies of
attention. Other objective measures range from monitoring eye-movements to recording
brain activations. We refer to these objective measures of behaviour as third-person
measures because they can be observed by someone other than the individual involved
in the behaviour (see Varela & Shear, 1999).
Subjective reports, that is, first-person measures of personal experiences and beliefs,
are largely ignored in cognition for several reasons. First, there is the general belief,
which appears to be a remnant of behaviourism’s objection to the way that structuralists
used introspection, that subjective reports are not reliable and replicable across
individuals. Second, it is thought that introspecting about subjective experience might
change and bias subjective experience (see Lutz & Thomas, 2003). Third, subjective
reports are often believed to be vulnerable to experimenter demands. Fourth,
subpersonal mechanisms of cognitive performance, which are the primary interest of
experimental psychologists, are assumed to operate below conscious awareness. Finally,
on occasion, even when peoples’ subjective reports agree across individuals, they may
be inconsistent with their behaviour (Hurlbert & Heavey, 2001; Nisbett & Wilson, 1977).
For this impressive list of reasons, subjective reports have fallen by the wayside.
However, perhaps these concerns are not as compelling as they first appear to be.
After all, many of the criticisms levelled against the use of subjective reports are general
experimental problems that also apply to objective measures of performance. Consider
the first criticism above, that subjective reports are unreliable. In actuality, perceived
unreliability of subjective reports in the ‘structuralist’ research programme was due
primarily to ‘the problem of inducing the same mental states in many observers where
the states were sufficiently stable to allow consistent judgments across observers’
(Ericsson, 2003, p. 5, italics added). Therefore, the problem was not in the method of
introspection but rather with the stability of the experience. The reader will notice, as
we have noted in the first section of this paper, that this same issue of
stability/invariance also plagues objective third-person laboratory studies of cognitive
performance.
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330 Alan Kingstone et al.
Also not unique to subjective reports is the second concern noted above, namely
that introspection might change or bias subjective experience. The fact that studying a
factor might change that factor is true of laboratory studies of mechanisms as well. In
fact, this idea forms a core reason to our claim that mechanisms studied in the laboratory
might not operate in the same way in the real world. Most generally, this is an instance of
the well-established Heisenberg Uncertainty Principle, an epistemological limitation
that plagues many scientific enterprises and is certainly not unique to reports of
subjective experience. Similarly, the third objection, that subjective reports are easily
biased by experimenter demands, can also apply to objective measures of performance,
for instance studies of cognitive processes of race (e.g. Gehring, Karpinski, & Hilton,
2003). Therefore, in these regards, subjective reports and objective measures are
vulnerable to the same possible shortcomings. It is also worth noting that over the past
several decades, there have been considerable advances in the development of firstperson methodologies that minimize the extent to which introspective reports bias
conscious experience and the extent to which they are susceptible to experimenter
demands (see Dennett, 2003; Ericsson, 2003; Ericsson & Simon, 1980; Lutz &
Thompson, 2003).
The latter two criticisms of subjective reports are also not as problematic as one
might first be led to believe. The fourth concern was that subjective reports are not
useful for studying cognition because people do not have conscious access to
subpersonal mechanisms, which likely operate below conscious awareness. This seems
reasonable and true. But, as we have noted above, a subpersonal level of explanation
alone cannot be expected to provide a meaningful explanation of cognitive performance
in complex real-world settings. At a personal level of explanation, subjective reports can
be extremely useful because they can provide direct access to peoples’ beliefs,
intentions, goal, and actions, which are critical for that level of explanation (see Lutz &
Thompson, 2003). Finally, the fact that subjective reports and objective behaviour
disagree with each other (see Nisbett & Wilson, 1977) occurs only in specific situations
and is certainly not the rule across all situations (see Lutz & Thompson, 2003; Smilek,
Eastwood, Reynolds, & Kingstone, 2007, In press; Wilson, 2003).
Thus, under closer consideration, it appears that subjective and objective reports
may share a common and imperfect foundation. In fact, it could be argued that
subjective reports are in some ways ‘more primary’ than indirect objective measures of
cognition. Indeed, some form of introspective methodology is an integral part of all
‘objective’ methods (Jack & Ropstroff, 2002, 2003). For instance, experiments are often
designed based on the subjective experience of the experimenter. Most of us have been
trained to consider our preferred paradigms and tasks in a manner that enables us to
introspect on how one might behave and to make predictions and gain insights about
the resulting data. Similarly, experimental instructions involve an interpersonal
exchange between experimenter and subject in which the experimenter provides the
participant with ‘a model of how they should carry out the experimental task’ (Jack &
Roepstorff, 2003, p. vii). Data are also sometimes understood or validated on the basis of
informal interviews following an experiment, such as whether a stimulus was
consciously experienced or not. Subjective experiences are, therefore, inherent to
objective experimental studies of cognition.
Our position is that subjective reports represent an extremely powerful and valid
tool for exploring personal-level explanations of cognitive performance. First, they can
provide direct access to participants’ explicit goals, intentions, and behaviour in
everyday situations. Reason’s (e.g., 1979, 1984) exploration of people’s slips of attention
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Cognitive Ethology
331
is a good example of this use of subjective reports. Reason conducted several diary
studies in which large groups of participants provided detailed reports of their everyday
slips of attention (e.g. putting the milk in the cupboard and the cereal in the fridge).
Reason provides many examples of reports of such attentions slips that simply could not
be measured using objective methods; only the subjective reports clearly captured an
individual’s goals and intention as well as the details of the events that occurred at
unexpected and relatively infrequent times in everyday life (which is when attention
slips often occur). Based on his analysis of these subjective reports of attention slips,
Reason was able to create a classification system for ‘actions not as planned’ and also put
forth a compelling theory about how such slips come about. Surprisingly little has been
done to follow up this interesting work on attention slips (for exceptions see Cheyne,
Carriere, & Smilek, 2006; Robertson, 2003; Robertson, Manly, Andrade, Baddeley, &
Yiend, 1997).
Second, subjective reports are useful in that they can provide important insights into
differences in cognitive behaviour across individuals. A good example of this use of
subjective reports is provided by the pioneering work of Broadbent and colleagues
(Broadbent, Cooper, FitzGerald, & Parkes, 1982). Broadbent et al. developed the
Cognitive Failures Questionnaire (CFQ) to measure individual differences in failures of
perception, memory, and attention. They found that the peoples’ CFQ scores are
relatively stable over long periods of time and that people with high CFQ scores
(i.e. highly prone to cognitive failures) are more vulnerable to showing negative effects
in stressful situations.
Third, subjective reports can reveal the types of cognitive strategies people
are trying to implement in various situations. This can help investigators gain
insight into how participants may be performing their tasks and, in doing so,
gain new insights into their data. A good example appears in Marcel’s (1983) classic
exploration of unconscious influences of briefly presented stimuli. Based on the
subjective reports of his participants, Marcel was able to divide his participants into
those that were passive viewers and those that used active strategies. The results
showed that the strength of the unconscious influence of a briefly presented
stimulus was greater when the participants passively view the displays, as opposed
to when they actively looked for the stimulus (for similar demonstrations see Smilek,
Enns, Eastwood, & Merikle, 2006; Snodgrass, Shevrin, & Kopka, 1993; Van Selst &
Merikle, 1993).
Finally, subjective reports can be useful for helping to generate experimental
hypotheses. Consider, for instance, recent studies of grapheme-colour synaesthesia, a
condition in which achromatic letters and numbers automatically elicit specific and
consistent colour experiences (Dixon, Smilek, Cudahy, & Merikle, 2000; Mattingley,
Rich, Yelland, & Bradshaw, 2001). Because synaesthesia is principally a subjective
condition, defined by an unusual conscious experience, the majority of the studies
investigating this condition are motivated or based on the subjective reports of the
synaesthetes (see Smilek & Dixon, 2002).
In addition to noting the utility of measuring subjective experience, we wish to
highlight that first-person reports of subjective experience and third-person measures of
object behaviour can be integrated in a complementary fashion, dovetailing with the
personal and subpersonal levels of explanation outlined previously. In this way, first- and
third-person measures can be combined in a synergistic way so that they mutually
constrain and support our understandings of cognitive performance both in real-world
and lab-based settings.
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332 Alan Kingstone et al.
Cognitive Ethology and the future
Based on the foregoing considerations, we wish to make several recommendations for
future studies of cognition. We formulate these recommendations as an alternative
approach to the study of cognition; we have referred to this alternative as Cognitive
Ethology. The primary goal of this approach is to understand the functioning of human
cognition in the real world. This approach is based on the following important assumptions:
(1)
(2)
(3)
(4)
Invariance: The dynamics of cognition are, at least in part, contextualized. Variability
in cognitive processing that arises from contextual differences is important to
understand. Only by explaining such variability will meaningful and stable cognitive
processes be discovered.
Control: Important insights into cognition will be gained when individuals behave in
an unconstrained and uncontrolled manner in their natural environments. The goal is
to measure naturally occurring variance rather than the variance that emerges from
controlling the system.
Cognition as a distributed system: Cognition is a non-linear systemic process.
Important aspects of cognition will only emerge when embodied individuals are
considered as a part of a system that involves their natural environment (including
other individuals).
Subjective reports: Subjective reports provide a direct measure of people’s conscious
experiences, goals, intentions, and beliefs pertaining to their attentional behaviour in
everyday environments.
The Cognitive Ethology approach also makes the following recommendations for future
studies of cognition:
(1)
(2)
(3)
The initial job of the researcher is to observe and describe what people do in the
real world in order to specify the domain of inquiry. Such observation should be
undertaken in a systematic empirical manner – rather than ‘arm chair observing’.
These observations will form a much needed description of cognition as it
operates in real-world settings.
The conceptual language used to describe human cognition should, initially, be
grounded in the concepts and language that are used by people in their everyday life.
Studies of human cognition should integrate measures of both objective (thirdperson) behaviour as well as subjective (first-person) experiences. First-person
subjective reports should be combined in a mutually constraining fashion with
third-person objective observations of behaviour.
Ultimately, Cognitive Ethology should be combined with other empirical approaches
(e.g. laboratory-based neuroscience) in order to arrive at a fuller understanding of the
functioning of human cognition.
On the first glance, it might appear to some that what we are proposing is simply a
rehashing of older ideas. While we fully acknowledge that our notion of Cognitive
Ethology is grounded in earlier thinking, we nevertheless believe that Cognitive
Ethology represents a unique and critically important synthesis of previous ideas.
To appreciate the uniqueness of what we call the Cognitive Ethology approach, it is
helpful to contrast this approach with other research approaches that have emerged
throughout the history of psychology, including: (a) information processing and
cognitive neuroscience (Miller, 1956), (b) the ethological approach (e.g. Carthy, 1966;
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Cognitive Ethology
333
Hutt & Hutt, 1970), (c) the ecological approach (e.g. Barker & Wright, 1955; Wright,
1967), and (d) Gibson’s (1950, 1979) ecological optics.
Information processing and cognitive neuroscience
In the forgoing discussion, we have articulated how our Cognitive Ethology approach
differs and is complementary with the common laboratory-based approach to studying
cognition. This common approach to which we have been referring is a combination of
the information-processing approach and the cognitive neuroscience approach. These
approaches share in common with Cognitive Ethology the general goal of understanding
human cognition and behaviour as it occurs in the real world. The difference between
approaches arises when one considers the assumptions underlying the research
strategies used to achieve this goal. At the heart of information processing and cognitive
neuroscience are the assumptions of invariance and control that we have articulated
earlier. As noted above, the Cognitive Ethology approach rejects these assumptions. The
information-processing and cognitive neuroscience approaches seek to provide a
subpersonal explanation of behaviour, whereas Cognitive Ethology seeks to also provide
an explanation of behaviour at the personal level. Finally, unlike information processing
and cognitive neuroscience, Cognitive Ethology places a strong emphasis on peoples’
subjective reports and personal insights into their performance.
The ethological approach
This approach, which gained prominence during the 1960s, focuses on describing
behaviour patterns of humans and animals in their natural contexts (e.g. Carthy, 1966;
see Hutt & Hutt, 1970 for a review). The focus on behaviour patterns in natural contexts
gained prominence because it became apparent that classical behaviourism failed
miserably in certain instances when applied beyond the laboratory (see Breland &
Breland, 1961). Our approach and the classic ethological approach are similar in that
they both seek to provide a detailed description of behaviour as organisms interact with
and in their natural environment. Furthermore, both approaches consider it essential
that natural behaviour be observed and described as it normally occurs rather than being
modified or probed in artificially controlled settings. In fact, these similarities are what
prompted us to include the term ‘ethology’ when giving a name to our approach.
There are, however, several critical differences between the two approaches. The
first and primary difference concerns one goal of our approach, which is to relate the
observations to classically cognitive concepts such as attention and memory. Our
approach views these cognitive concepts as being contextualized processes revealed by
the interaction of an individual with his or her environment. In contrast, classical
ethology focuses on overt behaviour (i.e. generating an ethogram as a starting-point)
and does not seek to draw inferences about cognition. The second difference between
the approaches concerns the role of subjective reports. An important defining
characteristic of the ethological approach it that it rejects inferences about subjective
experience as well as the validity of subjective reports, insisting that behaviour be
described without inferring intention, motivation, and cognition to an animal (Carthy,
1966; Hutt & Hutt, 1970). In contrast, our approach considers participants’ subjective
reports and beliefs to be critical for understanding cognition and behaviour. The third
difference between the approaches concerns the balance in emphasis between the
behaviour on the one hand and the environment on the other. Unlike the ethological
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334 Alan Kingstone et al.
emphasis on behaviour over environmental situation, our approach seeks to take a
more balanced focus on individual behaviour and situational factors. Finally, our
approach is not committed to several issues central to classical ethology, such as how
behaviour might be shaped by evolutionary pressures and whether behaviours are
innate or learned.
The ecological approach
Another approach which bears some similarity to Cognitive Ethology is the ecological
approach (e.g. Barker & Wright, 1955; Wright, 1967; see Hutt & Hutt, 1970 for a
review). This approach seeks to understand how the environment (i.e. ‘habitat’) relates
to, or determines, behaviour. The critical similarity between the ecological approach
and Cognitive Ethology pertains to the idea that characterizing situations is essential for
understanding human behaviour. However, there are several important differences. One
important difference between approaches involves the relative amount of emphasis
placed on the environment and individual (see Hutt & Hutt, 1970). Specifically, the
ecological approach emphasizes the role of the environment over the role of the
individual. In contrast, our approach does not wish to allow the environment to
overshadow either the individual or his/her behaviour. Another important difference
between approaches pertains to the role of subjective reports and personal insights of
the participants. In particular, the ecological approach limits the discussion of mental
states (or ‘attitudes’) to those inferred from observable behaviour and does not
recognize subjective reports as important and valid data. In contrast, Cognitive Ethology
considers subjective reports and observable behaviour to be equally important.
Ecological optics
Gibson’s (1950, 1979) ecological optics is based on the idea that perception is driven
by the structure of the environment. According to Gibson (1959, p. 459), ‘perception is
a function of stimulation and stimulation is a function of the environment’. This implies
that perception is directly a function of the environment. Because of this strong
emphasis on the environment as a determinant of perception, the framework is
essentially ecological.
The similarities between Cognitive Ethology and Gibson’s ecological optics are
many. First, both approaches agree that cognitive concepts cannot be properly
understood without considering the fact that participants are embedded in an
environment and that cognition is not independent of the environment. Second, both
approaches reject the assumption of stability. Gibson believed that the problem with
traditional psychophysics was that it focused on how the sensory receptors respond to
discreet stable stimulation. Gibson observed that ‘the stimulation of receptors and the
presumed sensations : : : are variable and changing in the extreme, unless they are
controlled in the laboratory’ (Gibson, 1966, p. 3). This keen observation, which also
implied a limitation of laboratory studies, formed the basis for the critical idea that
change across time and situations must be understood and integrated within a
theoretical framework (see Gibson, 1959, p. 464–465). We agree with Gibson that the
initial research focus should be on naturally occurring variability rather than variability
that is controlled, eliminated, manipulated, or created in the laboratory.
There are, however, at least three critical differences between Cognitive Ethology
and Gibson’s ecological optics. First, whereas Gibson’s framework emphasizes the
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Cognitive Ethology
335
role of environment with minimal or no consideration of the characteristics of the
individual, Cognitive Ethology places equal emphasis on the characteristics of the
individual and those of the situation. A second difference pertains to the use of
introspection and participants’ subjective reports. Consistent with a greater focus
on the environment than the individual, Gibson believed that introspection is only a
means of generating hypotheses and did not consider subjective reports to be
important data in their own right. Gibson writes: ‘introspection, however unbiased,
is no more than a guide to the study of perception’ (Gibson, 1959, p. 461). In
contrast, and as we have emphasized, Cognitive Ethology considers subjective
insights as important data in their own right and seeks to ground cognitive concepts
in people’s everyday understanding of those concepts. The third important difference
between the approaches concerns the types of cognitive phenomena they seek to
explain. Gibson’s theory provides a theory about the point of ‘contact’ between the
sense organs and an ‘energy flux’ in the world. Thus, perception was explained in
terms of a basic stimulus structure such as the ‘optical texture in the array of light’.
It is difficult to see how such a level of explanation could ever provide insights
into more complex human behaviour. Cognitive Ethology, on the other hand, seeks
to directly address the ‘higher level’ aspects of cognition that are beyond the scope
of Gibson’s ecological optics. In some sense, Cognitive Ethology takes off where
Gibson’s theory ends.
Common objections to Cognitive Ethology
When discussing Cognitive Ethology with our colleagues, we have noticed several
common issues or objections that have been raised. Here we address four main
concerns that have been brought to our attention.
(1) How does Cognitive Ethology go beyond previous calls for more ecologically
valid research?
Cognitive Ethology extends previous calls for ecological validity in at least two
important ways. First, by articulating the principles of lab-based research and their
alternatives (e.g. laboratory vs. naturalistic research, personal vs. subpersonal levels
of explanation, subjective vs. objective measures, experiment vs. folk grounding of
concepts) we have gone substantially beyond previous calls for more ecological
validity in psychological research (Neisser, 1976; Kingstone et al., 2003). Indeed, our
discussion of the principles underlying laboratory studies and their alternatives
suggests a possible reason why previous exhortations for ecological validity have not
taken hold. Our speculation is that, while seeking to be more ecological, researchers
have maintained a laboratory-based subpersonal focus. In doing so, they adhered to
assumptions (e.g. invariance and control) that are, at the core, incompatible with the
ecological goal. This has resulted in the general view that ecological validity is
something that cannot be attained and has created a degree of resignation to, and
comfort with, artificial laboratory studies. We believe that the incompatibility between
ecological goals and the underlying research assumptions may have gone largely
unnoticed because the assumptions and their implications for ecological validity have
not been clearly articulated. We hope that this paper will help to provide some clarity
in this regard and also affirm that ecological validity can, and indeed should, be
attained using the personal-level real-world approach that we outlined.
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336 Alan Kingstone et al.
(2) Does the Cognitive Ethology framework suggest that cognition should not be
studied in laboratory settings?
The short answer to this question is ‘no’. Laboratory studies of cognition can certainly
contribute to our understanding of human cognition. However, it is our proposal that
laboratory studies are not likely to provide accurate understandings unless they are first
grounded in systematic observations of how cognition operates in real-world settings.
The goal of Cognitive Ethology is to provide the much needed body of observations on
the basis of which existing laboratory findings can be validated and future laboratory
experiments can be grounded. Ultimately, we believe that studies based on the Cognitive
Ethology approach, and laboratory studies ranging from psychophysics to the cognitive
neuroscience, can be combined in a complementary fashion and, in doing so, will lead to
a much clearer and accurate understanding of human cognition in the real world.
(3) Is Cognitive Ethology just another name for human factors engineering or applied
psychology?
Cognitive Ethology is related yet distinct from human factors engineering and applied
psychology. The primary goal of human factors engineering is to create or spawn new
technology (see Vicente, 2003). Similarly, applied psychology seeks to solve specific
real-world problems. In contrast to these approaches, Cognitive Ethology is not directly
interested in solving a problem in the real world or in generating new technological
innovations, though one would hope that such innovations would certainly emerge
from this line of research. Rather, Cognitive Ethology focuses on what is typically
referred to as ‘basic research’ in that it seeks to understand human behaviour for the
sake of having a better understanding and not for a direct application or technological
innovation. Thus, as opposed to human factors engineering and applied research, at
times Cognitive Ethology investigations might focus on issues that do not have an
immediately apparent or direct application.
(4) The Cognitive Ethology approach will not work because it is impossible to
sufficiently control all extraneous variables in real-world settings
This is perhaps the most common objection raised against studying cognition in the
real world. And, it is a main reason why researchers have gone further and further
into their laboratories and have studied cognition in highly controlled paradigms
(e.g. Broadbent, 1971; Posner, 1978). We argue, however, that the concern that human
cognition cannot be studied in real-world settings, because it is not possible to control
naturally occurring variability, is misguided. Though it is clearly the case that it is
difficult (if not impossible) to run a controlled experiment in natural settings, it is
worth noting that such controlled experiments are only one part of the whole
scientific enterprise. Many branches of science, such as biology and physics, have been
based on decades, if not centuries, of systematic observation and description of
naturally occurring events. In these sciences, experimentation may only occur after
years of systematic observation. And, in some sciences, such as astronomy, observation
and description remain the only way of doing research. Placed in the context of other
research domains, it seems rather absurd that experimental psychology in general, and
cognitive research in particular, has not conducted systematic observations or
descriptions of their area of inquiry (see Koch, 1999). Psychology is unique in that it
has, almost from its inception, been handed the experimental method without a clear
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Cognitive Ethology
337
description of its subject matter. It is precisely this void in observation and description
of naturally occurring cognitive phenomena that Cognitive Ethology can fill. Cognitive
Ethology seeks to observe and measure the naturally occurring variability related to
cognition in real-world settings in order to lay the foundational observations on which
theories and experimentation can be built.
Concluding comments
Given the many considerations that have been presented in this paper, some
conclusions are obvious. First, experimental simplification of a real-world situation is a
reasonable research tactic when it follows careful real-world investigation.
Second, real-world and lab-based investigations are complementary, not competing,
research approaches. Each offers a level of explanation that is outside the realm of the
other, with personal-level explanations, including subjective reports, often providing
the foundational answers to the big ‘why’ and ‘how’ questions that are central to
investigations of cognitive phenomena. We have also noted that personal-level
explanations also explain cognition as operating in service of an individual’s goals and
needs as they interact with a continually changing environment.
Third, the field needs fresh data that is drawn from real-world experiences and
phenomena. We have identified research assumptions that embrace the principles of
variance and situation, which we propose will help advance the field in its quest to
understand and predict real-world cognition and behaviour.
Fourth, and finally, we have outlined a new research approach, called Cognitive
Ethology, that makes concrete our ideas and which we hope will serve as a useful tool
for our colleagues’ future research efforts. We look forward to the constructive dialogue
that this article will stimulate and the other novel research approaches that will be
borne from these efforts.
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Received 12 March 2007; revised version received 9 October 2007