Brains, it has recently been argued, are essentially prediction machines. They are bundles of cells that support perception and action by constantly attempting to match incoming sensory inputs with top-down expectations or predictions. This is achieved using a hierarchical generative model that aims to minimize prediction error within a bidirectional cascade of cortical processing. Such accounts offer a unifying model of perception and action, illuminate the functional role of attention, and may neatly capture the special contribution of cortical processing to adaptive success. This target article critically examines this “hierarchical prediction machine” approach, concluding that it offers the best clue yet to the shape of a unified science of mind and action. Sections 1 and 2 lay out the key elements and implications of the approach. Section 3 explores a variety of pitfalls and challenges, spanning the evidential, the methodological, and the more properly conceptual. The paper ends (sections 4 and 5) by asking how such approaches might impact our more general vision of mind, experience, and agency.
The problem with brain GUTs: Conflation of different senses of “prediction” threatens metaphysical disaster
Andy Clark is Professor of Logic and Metaphysics in the School of Philosophy, Psychology, and Language Sciences at the University of Edinburgh in Scotland. He is the author of six monographs, including Being There: Putting Brain, Body and World Together Aga in (MIT Press, 1997), Mindware (Oxford University Press, 2001), Natural-Born Cyborgs: Minds, Technologies and the Future of Human Intelligence (Oxford University Press, 2003), and Supersizing the Mind: Embodiment, Action, and Cognitive Extension (Oxford University Press, 2008). In 2006 he was elected Fellow of the Royal Society of Edinburgh.