Complex and flexible behavior is a major mark of intelligence. But does complex behavior necessarily require a complex brain? The basic goal of the psychologist Louise Barrett’s engaging new book, Beyond the Brain: How Body and Environment Shape Animal and Human Minds (Princeton University Press, 2011), is to get us to rethink this common assumption. Using a wide array of examples of non-human intelligence, as well as studies of infant cognition and development, Barrett shows how behavioral flexibility, when viewed within a larger system that includes body and environment, can arise without a big, fancy, and concept savvy brain.
Perhaps the most fascinating example of small-brain intelligence that Barrett offers for consideration is the Portia spider, a well-studied genus of the salticidae, or jumping spider, family (see pp. 57-70). Portia display a startling variety of flexible, context-dependent hunting behaviors, including mimicry, stalking, and “smoke-screen behavior” (that is, taking advantage of disturbances to advance undetected), all with very little brainpower. Perhaps most surprising, from a cognitive standpoint, is their ability negotiate obstacles when stalking, sometimes taking detours that cause them to lose sight of their prey. How could they do this without planning a route, or holding in mind some concept of the prey’s location? Experiments on Portia spiders indicate that this complex and seemingly representation-dependent behavior can be explained in terms of perceptual skills: if patterns of scanning and fixating with their powerful eyes (the best among invertebrates) are governed by a few simple “rules” – like a preference for uninterrupted horizontal edges leading to the prey – the spider may be able to improvise a detour without any “inner” map or plan.
By itself the Portia example may not seem that revolutionary, but together with other examples from robotics and animal cognition, Barrett’s book steadily undermines the assumption that intelligent behavior requires complex reasoning based on an “inner world” of concepts. Barrett does not deny that planning and other concept- or representation-heavy kinds of thought play an important role in human cognition. She merely wishes to question the anthropocentric bias that sees all intelligence in these terms. However, through her extensive considerations of small-brained intelligence, Barrett also raises questions about instances of “higher” primate and human infant intelligence that we more confidently presume to explain with concepts (for example, the recognition of familiar others such as relatives). And this leads to questions about the very nature and function of conceptual intelligence.
Thus, while Barrett is exploring intelligence “beyond the brain,” she is also pursuing a deeper issue: how do complex brains like ours contribute to intelligent behavior? Mainstream cognitive science of the last fifty years has defined intelligence as inferential problem solving; accordingly, cognitive neuroscience has pictured the human brain as a massive, hierarchically organized information processor, and has focused on describing the computational (that is, algorithmic) processes of the brain that support this kind of problem solving. In Artificial Intelligence (AI), the “intellectual” bias of this computational approach has succeeded best in abstract domains like chess, while the basic motor skills of the average two-year-old have remained largely beyond reach. Although cognitive science has become increasingly focused on contributions of body and environment to intelligent behavior in the last two decades, the basic computational picture of intelligence remains dominant.
In contrast, one of the many virtues of Barrett’s book – and what sets it apart from many other endorsements of the turn toward “embodied” and “extended” views of cognition – is the clarity with which she shows that moving beyond the brain is not just a matter of lessening its computational burden: it also entails a radically different view of the kinds of problems for which big brains are needed, and a corresponding picture of how brains might function as non-computational organs of intelligence. Although Barrett herself does not announce the arrival of a new paradigm in cognitive and behavioral science, her book brings together an impressive collection of dissenting viewpoints that together pose, at the very least, a major challenge to the reigning computational approach: these include the action-oriented view of perception and cognition common to pragmatism (for example, John Dewey), phenomenology (Maurice Merleau-Ponty), and ecological psychology (James Gibson); the dynamical systems approach to brain function developed by Walter J. Freeman and others (J.A.S. Kelso); and the body- and world-dependent approach within AI (Rodney Brooks).
Barrett’s book is therefore an ideal introduction for philosophers, historians, and scientists to the main figures and ideas of non-computational cognitive science. Especially for philosophers, her book is worth considering as a bellwether of current and future trends, including the possibility that cognitive science and philosophy of mind might be entering a new “behaviorist” phase. Is this simply another swing of the pendulum, a reaction against the excesses – or perhaps the exhaustion – of the computational view, which itself was partly a reaction against the behaviorist paradigm that preceded it? Or is the S-R model that underlies both classical behaviorism and computational theory finally being overturned? Are we entering another “anti-mentalist” phase in which philosophers and scientists become allergic to any and all discussions of representation or “inner life?” Or might we find ways to understand representational, introspective, and imaginative dimensions of human thought that do not sneak in a homunculus?