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New Computationalism

This talk explores the concept of transparent computationalism and challenges the Church-Turing thesis, pan-computationalism, and the idea that cognition is strictly computation. It presents alternative views of computation to address critiques and discusses the possibility of strong AI even if computationalism is false.

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New Computationalism

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  1. New Computationalism Ron Chrisley COGS Department of Informatics University of Sussex School of Humanities and Information, University of Skövde October 19th, 2006

  2. Overview Will discuss four related claims/ideas: • "Transparent" defense of computationalism • Falsity of the Church-Turing thesis • Falsity of pan-computationalism • Even if computationalism is false, strong AI is possible

  3. Transparent computationalism • The claim that cognition is computation can be construed opaquely or transparently • Opaque construal: The mind is best understood in terms of the concepts from current (or past!) computational theory • Transparent construal: The mind is best understood in terms of whatever concepts, it turns out, best explain what computers do • Many critiques of computationalism succeed only on the opaque construal • Thus, transparent computationalism is not threatened

  4. The transparent strategy • For each critique, present: • A current (opaque) view of computation • The critique based on that view • An alternative view of computation that avoids the criticism • Independent motivation for that view of computation

  5. Critique 1: Dynamics • Opaque view: Discrete steps in an algorithm essential to computation • van Gelder: • Cognition isn't discrete, but fundamentally dynamical • Therefore, cognition isn't computation

  6. Dynamical computation • Alternative view: Generalise notion of an effective procedure to include any physically realisable and exploitable process, even dynamical ones • Independent motivation: Real-time computational control of an airplane wing

  7. Critique 2: Externalism • Opaque view: Computational properties are syntactic and local • Fodor: • Psychological properties are semantic and relational/external/non-local • Therefore, there can't be a computational psychology

  8. Externalist computation • Alternative view: Even computational explanations are external/relational (cf Peacocke's "Content, computation and externalism", 1994) • Independent motivation: Embedded computational systems

  9. Critique 3: The Chinese Room • Opaque view: • All essential computational properties are formal • Non-formal properties of a computation are mere implementation detail • Searle: • Formal properties are insufficient for mind • Therefore, there can't be a computational psychology

  10. Grounded computation • Alternative view: • Having a semantics is crucial to computation • Some properties that current formal theory takes to be irrelevant play a constitutive role in determining computational state • Independent motivation: • Not every process is a computation • Real-time computational control of an airplane wing

  11. The Church-Turing thesis • An example of an explicit acknowledgment of the distinction and relation between informal and formal (theoretical and pre- theoretical) notions • Diagonal arguments (Gödel, Lucas, Penrose) do not show what they purport to: falsity of Strong or even weak AI

  12. The Church-Turing thesis • Diagonal arguments highlight a special case of a general property: • For any set of things that can answer questions, one can construct a question that no member of that set can answer, even though some things outside the set can. • Implies, e.g., that odd-numbered TMs can compute functions that even-numbered TMs cannot • And that TMs can compute functions we cannot

  13. Universality • One might think this violates Turing's famous result, that there exist universal machines • But no conflict, since Turing's universality result is about simulation, not computation

  14. Against pan-computationalism • Putnam's sense: Everything instantiates every computation • fails because of the causal aspect of causation (cf, e.g., Chalmers 1994, Chrisley 1994) • More plausible sense: Everything has some computational desciption • Yes, but still too broad: IBM vs BMW • Suggests that we need to do more work to capture real computation: Semantics

  15. Computation and mind • Traditionally, two ways computation is relevant to understanding or replicating mind: • Weak AI: Computational simulation of mind • Strong AI: Cognition is computation

  16. Strong AI without Computationalism • Even if cognition is not computation, does not imply falsity of strong AI • Not because of pan-computationalism • Third way: computation as the ultimate plastic • Computation is a convenient way to configure a system's causal/dynamical profile • In between identity and mere simulation

  17. Strong AI without Computationalism • E.g. Suppose life is crucial for mind; and (e.g.) Boden is right that life is non-functional • Does not imply that one cannot program a system to be alive • Falsity of (even transparent) computationalism does not imply Strong AI is impossible

  18. Thank you! Video, audio and PowerPoint files of this talk and others can be found at: http://e-asterisk.blogspot.com Comments welcome: ronc@sussex.ac.uk

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