Andrew Clark

Cognitive niche construction is the process whereby organisms create and maintain cause–effect models of their niche as guides for fitness influencing behavior. Extended mind theory claims that cognitive processes extend beyond the brain to include predictable states of the world. Active inference and predictive processing in cognitive science assume that organisms embody predictive (i.e., generative) models of the world optimized by standard cognitive functions (e.g., perception, action, learning). This paper presents an active inference formulation that views cognitive niche construction as a cognitive function aimed at optimizing organisms' generative models. We call that process of optimization extended active inference.

Recent work in computational and cognitive neuroscience depicts the brain as an ever‐active prediction machine: an inner engine continuously striving to anticipate the incoming sensory barrage. I briefly introduce this class of models before contrasting two ways of understanding the implied vision of mind. One way (Conservative Predictive Processing) depicts the predictive mind as an insulated inner arena populated by representations so rich and reconstructive as to enable the organism to ‘throw away the world’. The other (Radical Predictive Processing) stresses the use of fast and frugal, action‐involving solutions of the kind highlighted by much work in robotics and embodied cognition. But it goes further, by showing how predictive schemes can combine frugal and more knowledge‐intensive strategies, switching between them fluently and continuously as task and context dictate. I end by exploring some parallels with work in enactivism, and by noting a certain ambivalence concerning internal representations and their role in the predictive mind.

Biological brains are increasingly cast as ‘prediction machines’: evolved organs whose core operating principle is to learn about the world by trying to predict their own patterns of sensory stimulation. This, some argue, should lead us to embrace a brain-bound ‘neurocentric’ vision of the mind. The mind, such views suggest, consists entirely in the skull-bound activity of the predictive brain. In this paper I reject the inference from predictive brains to skull-bound minds. Predictive brains, I hope to show, can be apt participants in larger cognitive circuits. The path is thus cleared for a new synthesis in which predictive brains act as entry-points for ‘extended minds’, and embodiment and action contribute constitutively to knowing contact with the world.

Predictive processing accounts of neural function view the brain as a kind of prediction machine that forms models of its environment in order to anticipate the upcoming stream of sensory stimulation. These models are then continuously updated in light of incoming error signals. Predictive processing has offered a powerful new perspective on cognition, action, and perception. In this chapter we apply the insights from predictive processing to the study of emotions. The upshot is a picture of emotion as inseparable from perception and cognition, and a key feature of the embodied mind.

Andy Clark is currently Professor of Philosophy and Director of the Philosophy/Neuroscience/Psychology program at Washington University in St. Louis, Missouri. He is the author of two books MICROCOGNITION (MIT Press/Bradford Books 1989) and ASSOCIATIVE ENGINES (MIT Press/Bradford Books, 1993) as well as numerous papers and four edited volumes. He is an ex- committee member of the British Society for the Philosophy of Science and of the Society for Artificial Intelligence and the Simulation of Behavior. Awards include a visiting Fellowship at the Australia National University, Canberra in 1989, and an ESRC Senior Research Leave Fellowship in 1992. He is an Associate of BEHAVIORAL AND BRAIN SCIENCES, serves on the editorial boards of the journals.

Language, according to Jackendoff, is more than just an instrument of communication and cultural transmission. It is also a tool which helps us to think. It does so, he suggests, by expanding the range of our conscious contents and hence allowing processes of attention and reflection to focus on items which would not otherwise be available for scrutiny. I applaud Jackendoff s basic vision, but raise some doubts concerning the argument. In particular, I wonder what it is about public language that uniquely fits it to play the functional role which Jackendoff isolates — why couldn't expression in a private inner code induce the same computational benefits? I suggest a weaker position in which the communicative role of public language moulds it into a suitably expressive resource, such that natural language emerges as the logically and technologically contingent filler of a functional role which could, in principle, be filled by other means. I also compare and contrast Jackendoff's position with some related ideas due to Daniel Dennett and others, concluding with a sketch of my own view of language as an external artifact whose computational properties complement those of the basic biological brain.

How does language (spoken or written) impact thought? One useful way to approach this important but elusive question may be to consider language itself as a cognition-enhancing animal-built structure. To take this perspective is to view language as a kind of self-constructed cognitive niche. These self-constructed cognitive niches play, I suggest, three distinct but deeply interlocking roles in human thought and reason. Working together, these three interlocking routines radically transform the human mind, and mark a genuine discontinuity in the space of anitnal minds