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Why Wundt?

The development of psychology as a science has tended to buy into and to reinforce the dichotomy of mind and matter. In most histories of psychology, Wilhelm Wundt's lab is identified as the first experimental psychology lab - as the birthplace of a scientific psychology. However, certainly there were others who had experimental programs before Wundt (e.g., Fechner and Helmholtz).

Perhaps the reason is that whereas Fechner and Helmholtz were studying relations between mind and matter (i.e., psychophysics), Wundt, with the emphasis on introspection, framed psychology as mental chemistry.  This methodology emphasized the distinction between the stimulus as an object in the ecology and the stimulus as a property of mind. And there was a clear understanding that it was only the properties of mind that were of interest to the 'science' of psychology. In fact, Titchener would characterize associations between introspections and the ecological object as 'stimulus errors.' And Ebbinghaus would focus on nonsense syllables in an attempt to isolate the mental chemistry of memory from experiences outside the experimental context.

Of course, not everyone bought into this. William James characterized the experimental work of Wundt and Titchener as 'brass instrument psychology.' In framing a functionalist psychology, James was particularly interested in mind as a capacity for adaptation in relation to the dynamics of natural selection.  In this context, the pragmatic relations between mind and matter (satisfying the demands of survival) were a central concern.

Note that Wundt's research program was very broad, particularly if you consider his Volkerpsychologie. Thus, the key point is not to criticize his choice of focus or specialization. Rather, it is the later field of psychology that choses this focus as the 'birthplace' of the science that reinforces the idea that the science of psychology should be framed exclusively in terms of the mind, in isolation from matter (e.g., a physical ecology).

While Behaviorism brought the methodology of introspection under suspicion, and shifted attention to 'behavior,' the idea of 'stimulus' remained psychological (if not mentalistic) in that the nature of the stimulus (e.g., reinforcement versus punishment) was derived from the impact on behavior (e.g., increasing or reducing its likelihood), rather than as a consequence of its physical attributes. Thus, the Laws of learning could be pursued independently from any physical principles (e.g., the Laws of Motion).

The Computer Metaphor and Symbol Processing

With the development of information technologies, the mind again became a legitimate object of study. However, now the topic was not mental chemistry, but mental computation. The computer metaphor added new legitimacy to the separation of mind (i.e., software) from matter (i.e., hardware). And the new science of linguistics, with its basis in a dyadic model of semiotics (Saussure) shifted the focus to symbol processing in a way that made the link between the symbol and the ecology completely arbitrary.  The focus was on the internal computations - the rules of grammar, the 'interpretation' that resulted from the mental computations.  It became apparent to many that the stimuli for mental computations were arbitrary signs (e.g. C-A-T) and that the 'meanings' of these arbitrary signs were constructed through mental computations.

In this climate, people such as James Gibson, who followed the Functionalist traditions of William James in pursuing the significance of mind for adapting to an ecology, were marginalized. The field of psychology became the study of internal computational mechanisms for processing arbitrary signs. The focus of psychology was to identify the internal constraints of the computational mechanisms. In this context, the most interesting phenomena were errors, illusions, and biases, because these might give hints to the internal constraints of the computations.  A mind that was successful or situations where people behaved skillfully tended to be ignored - because the internal constraints were not salient when the mind worked well.


Ironically, in linking mental computations to brain structures, the dichotomy between mind and matter continues to be reinforced, at least to the extent that 'matter' reflects the physical constraints in an ecology.  While neuroscience involves the admission that the hardware matters, by isolating the computation to the 'brain' there remains a strong tendency for psychology to ignore the role of other physical properties of the body and ecology in shaping human experience.  For many, neuroscience effectively reduces psychology and cognition back to a mental chemistry or to brain mechanisms that can be understood independently  from the pragmatic aspects of experience in a complex ecology.  In this regard, I fear that increased enthusiasm for neuroscience is a backward step or an obstacle to progress toward a science of human experience.



A division or contrast between two things that are or are represented as being opposed or entirely different.  Either/Or


Consisting of two parts, elements, or aspects. Both/And

Mind and Matter

In Western culture there is a tendency to think about Mind and Matter as dichotomous. That is, mind is considered to be a different kind of thing than matter (e.g. physical bodies). For example, the objects of mind (e.g., ideas) are considered to be massless and are not subject to physical laws (e.g. Laws of Motion). Rather, mental objects are typically associated with the laws of logic or more generally computation (e.g., information theory). This leads to a natural division between the physical sciences (e.g., physics, chemistry, and biology) and the social sciences (e.g., psychology, sociology, economics). Although both groups tend to aspire to similar methodological standards (e.g., well-designed experiments), there is an assumption that the objects of study and the natural laws constraining the behavior of the objects may be fundamentally different kinds of things. This also leads naturally to an assumption that, beyond methodology, there is little that one type of science can learn from the other. That is, there is an implication that each of the two types of sciences can be complete without considering objects of the other type. In other words, there is an assumption that the software can be understood independently from the hardware, and vice versa. The soft sciences study the software and the hard sciences study the hardware.

As the old saw goes: What is mind, never matter. What is matter, never mind.

This view that Mind and Matter are dichotomous is reflected in the parsing of the puzzle shown on the left of the figure below. The challenge for such a perspective is how to address properties of human experience that depend on relationships between mental things (e.g., desires, sensitivity, capability) and physical things (consequences, appearances, physical layout). The challenge is how to add two fundamentally different kinds of things together into a coherent narrative with respect to human experience that reflects properties such as satisfying (e.g., whether a particular type of food will satisfy the desire for healthy nourishment), specifying (e.g., whether a particular pattern in a visual flow field will specify a safe separation from the car ahead of you), or affording (e.g., whether an object requires a one-handed or two-handed grasp).

In fact, one might ask which of the two sciences (i.e., physical or social) owns the phenomenon of human experience? Which science determines whether something is satisfying, whether something is specified, or whether something is afforded? Or do these aspects of experience fall into the gap between the two distinct sciences.

Satisfying, Specifying, Affording

The puzzle diagram on the right suggests a different framework for a single science, where experience is considered to be a joint function of mind and matter. In this perspective, satisfying, specifying, and affording become the objects of study - where these objects are considered to be duals. That is, they reflect relations spanning mind and matter. Thus, each object is ill-defined without specification of both aspects. Thus, the affordance of graspable reflects a relation between the size of an object (e.g., a basketball) and the size of a hand. The specificity depends on a relation between structure in an optical array (e.g., patterns of angular expansion) and an appropriately tuned sensor (e.g., a well-tuned, attentive eye). The satisfying attribute depends on the relation between intentions, needs, or desires (desire for nutrition) and the actual physical consequences (e.g. the digestibility of an object).

The duals of affording, specifying, and satisfying are suggested as the fundamental objects of study for a unified science of experience. These objects are duals in the sense that they refer to relations over mind and matter.

In a recent article on new approaches to designing human experiences, Sanders and Stappers (2008) write "We are heading into a world where experience trumps reality." I think that perhaps William James and Robert Pirsig might suggest something even more drastic.  They would perhaps argue that - experience is reality!

This is a major theme developed in our book What Matters. The claim is that the parsing in the left puzzle diagram that treats mind and matter as independent objects of study, breaks human experience into pieces that will never add up to a coherent narrative. On the other hand, we argue that the parsing represented in the right puzzle diagram is a parsing that may be a first step toward a unified science of human experience that spans mind and matter.


Keenness of mental perception and understanding; discernment; penetration.

Knowing versus Seeing

In studying human performance, I have been most curious about expertise or skill; and my original intuitions came from my own experiences in sports. My initial motivation was to discover the 'magical' attribute that separated me from the really excellent athletes. At the start I tended to frame the questions as "What do they know that I don't know?"  But as I began to explore deeper, I quickly reframed the question to "What do they see that I don't see?" Or more generally, "what do they sense; or what are they attuned to that I am not sensitive to?"  This change of perspective was strongly influenced by Eleanor Gibson's work on perceptual learning and de Groot's work on expertise in chess.

I don't think it is necessarily an either/or proposition with respect to knowing versus seeing. I expect that both knowing and seeing are involved, but there is an important difference between these two ways of framing the research question. Approaches focused on knowing tend to see expertise as a result of accrual of knowledge that can be 'added to' the information available through perception that allows better mental computations.  The general implication is that experts have a more extensive data base to tap into.

However, approaches based on seeing, tend to see expertise as reflecting something akin to a coordinate transformation in mathematics (for example a log transform). The benefits of coordinate transformations are that they can make certain patterns easier to pick-up.  A good example is work on visual skill involved in avoiding collisions, landing aircraft, or catching baseballs. This work illustrates that when you look at visual perception in terms of angular coordinates (angles and expansion rates), rather than Euclidean (x,y,z) coordinates then the computations needed to brake, land or catch a ball become relatively simple.

This is why I have chosen to title this blog Perspicacity. As a scientist, the focus of my work is to discover how the underlying coordinate systems or representations that experts use are different from those of non-experts. As a designer, the focus of my work is to create representations (i.e., interfaces) that help people to see phenomena in ways that are more similar to what the experts are seeing. The design goal is to create perspicacious systems.

The other reason that I like the term is that perspicacity suggests an intimacy between perception and cognition (between seeing and knowing) that I think has been lost in a reductionist cognitive science where perception and cognition are seen as independent or at least loosely coupled modules in an information processing system. I believe that a parsing that treats perception and cognition as different phenomena breaks the system in such a way that it will not be possible to put the pieces back together again to achieve a complete understanding of human experience.



Keenness of mental perception and understanding; discernment; penetration.

About Me: John Flach


Hello! My name is John Flach and I am currently a Professor of Psychology at Wright State University in Dayton, OH. For more than 30 years I have been exploring human performance in the context of sociotechnical systems. My work has involved collaborations with engineers, designers, and domain experts in such fields as aviation, healthcare, highway safety, military command and control, and process control. The focus of this work is to explore the capabilities of smart humans and how they are able to succeed (and occasionally fail) in managing complex work.

My explorations have been guided by a hope to better understand everyday human experience and to apply this understanding to the design of technologies that will enhance the quality of human experiences. As a result of these explorations I have developed rather unconventional views about the nature of human experience that I believe have implications for both cognitive science and for design.

I recently teamed with Fred Voorhorst to write a book to introduce our unconventional ideas about What Matters. This book is currently available as a free download through Core Scholar:

The intent of this blog is to continue the narrative begun in our book and to share our experiences with others who are searching for answers to the question: What Matters?