The superb Rob Rupert contribution to the superb Byron Kaldis edited volume.
It may seem natural to think of the mind as a stream of conscious experience occurring squarely behind the eyes, or perhaps as some single, persisting subject of these experiences, hovering in the center of the skull. The past hundred years of scientific thinking about the mind have challenged this view in a variety of ways. The most recent challenge, and the most striking to date, rests partly on the distributed nature of cognition – the fact that intelligent behavior emerges from the interaction of a variety of elements, some of which may be spatially removed from the locus of behavior. From such distributed models of cognition, many authors have inferred the extended-mind thesis, the claim that the mind itself spreads into the world beyond the boundary of the human organism. Distributed cognitive models have had direct impact on, and to some extent have been inspired by, research in the social sciences. Studies of insect behavior, for instance, form a bridge between the interests of cognitive scientists and matters to do with group-level behavior: large numbers of social insects, each of which “mindlessly” follows such simple information-processing rules as “drop my ball of mud where the pheromonal concentration is the strongest,” design elaborate nests. This illustrates both how intelligent-looking results can arise from a distributed – and one might think fairly unintelligent – process and also how their emergence might be social in nature: environmental conditions induce various sub-populations to play different roles in the life of the insect colony. Some robustly cognitive, human social processes also seem amenable to distributed theorizing: contemporary scientific results, in particle physics, for 2 example, often involve the contribution of hundreds, or even thousands, of individuals and instruments; here, each individual exercises a rich set of her own cognitive resources while playing a role in a much larger, highly structured enterprise. An intermediate case might be the modeling of traffic patterns: individual humans can reason in flexible and complex ways about driving and routes of travel, but, constrained by the presence of other automobiles and surrounding infrastructure, drivers’ contributions to traffic flow, and the resulting traffic patterns, have much in common with large-scale behavioral patterns of social insects. The remainder of this entry consists of three sections. Section II describes distributed cognitive modeling and the extended-mind thesis in more detail. Section III reviews critical reactions to the extended-mind thesis. Finally, Section IV briefly discusses fruitful areas of ongoing research on distributed cognition and the extended mind.