Richard S. Marken
The RAND Corporation
The year 2003 is the 30th anniversary of the publication of William T. Powers’ Behavior: The control of perception (B: CP), the first book to describe the theory of behavior that has come to be known as Perceptual Control Theory or PCT. It is also, as stated in the request for contributions to this volume, the 50th anniversary of Powers' "initial steps in the research that has led to PCT". I might add that it is also the 25th anniversary of my own involvement with PCT, which began in earnest in 1978. So now seems like a nice time to take stock of the state of PCT. And we are doing this with this well deserved Festschrift in honor of William T. Powers. I would like to contribute to this Festschrift by looking forward rather than backward. I have done my share of reminiscing about the past history of PCT, so far as I am familiar with it. I have lamented, in private and in print, the failure of PCT to attract the interest of behavioral scientists over the last 30 years, since the publication of B: CP made the PCT perspective readily accessible to the behavioral science community. What I would rather do now is look back on the future of PCT by taking an imaginary look at what I think the next 50 years of PCT will have been like.
Looking back over the next fifty years I see that PCT has become the dominant perspective in the behavioral sciences, having replaced behaviorism, cognitive science and evolutionism. I see this because to see anything else would be foolish. If PCT has not become dominant then this essay, and the Festschrift for which it was composed, will have been completely forgotten. So what do the behavioral sciences look like now that they are based on PCT? Perhaps what is most obvious to this visitor from 50 years in the past is the almost complete absence of statistical analysis in behavioral research. Research aimed at testing theories of individual behavior is now based on control models of individuals rather than statistical models of aggregates. Researchers no longer report statistical significance but real significance, in terms of how well the behavior of the model matches the behavior they have observed.
Modeling is now the basis of behavioral science research. Modeling tools are available which make it easy for the researcher to quickly build a model of the behaving system that includes an accurate model of the physical environment in which the system’s behavior is produced. These modeling tools take advantage of the ever-increasing power of digital technology to produce real-time digital simulations of dynamic interactions between system and environment. Behavioral research, like physics and chemistry, is now a science based on modeling rather than a guessing game based on statistical significance testing.
Behavioral science is based on modeling because behavioral research methods are now based on testing for controlled variables (Marken, 1997). Behavioral scientists now understand that the apparent randomness of behavior was an illusion created by ignoring the variables that organisms control. What behavioral scientists had called "responses" are now understood to be actions that protect controlled variables from disturbances. Disturbances correspond to what behavioral scientists had called "stimuli". When many disturbances affect the state of a controlled variable, actions will appear to be randomly related to any one of those disturbances (stimuli). PCT has moved the focus of behavioral science from the randomly-noticed stimulus-response relationships that were the subject of statistical studies of behavior to the consistently controlled perceptions that are now the centerpiece of models of behavior (Marken, 2001).
Research in all areas of behavioral science is now organized around testing for controlled variables. Behavioral scientists no longer ask, “What is the cause of the organism’s behavior?” They now ask, “What perceptual variable(s), if controlled by the organism, would lead me to see the organism behaving in this way?” This emphasis on testing for controlled perceptual variables has led to a new style of research in which the subjects of behavior studies are allowed to have better control over variables in their environment. The style of research which was aimed at measuring an organism’s “responses” to the presentation of discrete “stimuli” has been replaced by research aimed at measuring an organism’s ability to control perceptual variables that are being influenced by smooth variations in environmental variables that are disturbances to these variables.
Ingenious new experimental techniques have been developed that allow researchers to observe the state of hypothetical controlled variables while the variables are being disturbed. These techniques are similar to those developed long ago in the study of the perceptions controlled by baseball outfielders when they catch a fly ball. For example, McBeath, et al (1995) used a video camera attached to a fielder’s shoulder to observe the state of optical variables, such as the optical trajectory and acceleration of the ball, that the fielder might be controlling while catching fly balls. These early efforts were often limited by the failure of the researchers to record disturbances, such as the actual trajectory of the ball, to these hypothetical controlled variables. But these studies were important precursors to current PCT-based research inasmuch as they focused the attention of researchers on the importance of monitoring the state of possible controlled variables.
Research aimed at the identification of the perceptual variables controlled by humans and other organisms has been going on for several decades and the catalog of controlled variables continues to grow. Much of the research effort these days is aimed at classifying controlled variables and studying the relationship between systems controlling different types of perceptual variables. Much of this work supports the basic framework of a hierarchy of perceptual control systems that was originally proposed by Powers (1973, 1998). In particular, the research results are consistent with Powers’ brilliant suggestion, based at the time only on subjective experience, that the hierarchy of control is organized around a limited number of different classes of perceptual variables. Although these perceptual classes are not precisely the same as those suggested by Powers it is now clear that there are a limited number of different kinds of perceptual variable. The research is also consistent with Powers’ suggestion that lower level classes of perceptual variables are used as the means of controlling higher level classes of perceptual variables. It is a testament to the scientific depth of Powers’ work that this hierarchical relationship between perceptual classes was suggested well before there was any significant objective data to support it.
Progress in research and modeling has gone hand in hand ever since scientists started looking at behavior through PCT glasses (Marken, 2002). This is because research and modeling are inextricably interrelated in the PCT approach to behavior. Progress in research depends on the development of models that explain the research results. Similarly, progress in the development of models of behavior depends on research aimed at testing the predictions of these models. This tight interrelationship between research and modeling has resulted in the development of models that produce behavior that is remarkably realistic. Some early models based on PCT (Powers, 1999; Marken 2001) hinted at the kind of realism that could be produced by models based on PCT. Current models benefit from many years of research into the variables that organisms actually control while carrying out various behaviors. They also benefit from the realism that can now be achieved in terms of simulation of the physical environment in which behavior actually occurs.
The science of PCT has not only increased our understanding of behavior, it has also contributed to developments in many areas of practical endeavor. For example, PCT-based models of behavior have paved the way for the development of robots that can perform very complex and dangerous tasks in highly unpredictable, disturbance-prone environments. PCT models of economic behavior have made it possible for policy experts to design economic policies that preserve the best results of capitalism, in terms of the production of wealth, while eliminating its worst wrongs, such as the maintenance of egregious wealth inequality. World population is stabilizing near zero population growth, poverty has now been largely eliminated and sustainable, prosperous no-growth economies are now a feature of nearly all world societies. The new economic model has resulted in the development of economic systems that depend more on reuse of existing resources than depletion of natural resources so that environmental pollution has been reduced to very low levels.
PCT has also become part of the popular understanding of "how people work". This means that people in general now have a better understanding of how to deal with each other on an everyday basis. In particular, people are better able to deal with the inevitable conflicts that arise between themselves and others. People now understand conflicts to be the result of conflicting goals rather than conflicting actions. They also understand that the solution to conflict does not lie in pushing harder against it. When they find themselves in conflict, people are now more apt to look at themselves and ask, "What do I really want?" rather than look at their adversary and ask, "How can I get them to change?" The prevalence of the PCT has not turned the world into utopia but it has reduced the level of violence in the world considerably since violence is now understood be the cause of rather than the solution to interpersonal (and international) conflict.
Looking back over the next 50 years I see that perhaps the greatest legacy of PCT is a change in the tone of the conversation regarding the nature of human nature. The argument between liberals who believed that all human ills were caused by society and conservatives who believed that all human ills were the result of freely made bad choices has become more nuanced. PCT shows that the difference between liberals and conservatives was simply a difference in the part of the control loop at which one focused their attention. The liberals saw disturbance resistance as evidence of social control of behavior while conservatives saw the existence of a higher level goal as evidence of free choice. The liberal/conservative argument has largely disappeared with the realization that both points of view were correct. We can reduce social ills by reducing social disturbances, such as poverty, so that people can control more effectively. But we can also reduce social ills by freely choosing goals, such as moderation and kindness, that reduce conflict by reducing the degree to which we, ourselves, are social disturbances to others.
Thirty years before the beginning of these next 50 years, William T. Powers' introduced an exciting and revolutionary new view of behavior to the scientific establishment of the day. The new view was that behavior is the control of perception. Powers proposed this view at a time when the prevailing view was that behavior is controlled by perception. Thus, when Powers' introduced his new view of behavior it was rarely understood, often ignored and sometimes angrily rejected. Now the idea that behavior is the control of perception is taken for granted. This Festschrift is a long overdue celebration of the work and person of William T. Powers', who first presented the perceptual control view of behavior to a skeptical and often hostile audience.
Marken, R. S. (1997) The dancer and the dance: Methods in the study of living control systems, Psychological Methods, 2 (4), 436-446
Marken, R. S. (2001) Controlled variables: Psychology as the center fielder views it, American Journal of Psychology, 114, 259-281
Marken, R. S. (2002) Looking at behavior through control theory glasses, Review of General Psychology, 6, 260–270
McBeath, M. K., Shaffer, D. M, and Kaiser, M. K. (1995) How baseball outfielders determine where to run to catch fly balls, Science, 268, 569-573.
Powers, W. T. (1973). Behavior: The control of perception. Hawthorne, NY: Aldine DeGruyter.
Powers, W. T. (1998). Making sense of behavior. New Canaan, CT: Benchmark.
Powers, W. T. (1999) A model of kinesthetically and visually controlled arm movement, International Journal of Human-Computer Studies, 50 (6), 463-581