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**Ron Chrisley COGS Department of Informatics University of Sussex**

New Computationalism Ron Chrisley COGS Department of Informatics University of Sussex Thanks for coming Two ways to cram a complex idea into 20 minutes: simplify: total, clear understanding of watered-down version Or rush through the thing in its complexity, so superficial, impressionistic understanding of the thing in its complex glory. Clarify rushed parts in discussion Opt for latter! Literally have more slides than minutes, so get going! paper to Matthew Piper School of Humanities and Information, University of Skövde October 19th, 2006

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**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

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**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

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**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

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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

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**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

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**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

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**Externalist computation**

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

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**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

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**Grounded computation Alternative view: Independent motivation:**

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

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**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

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**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

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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

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**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

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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

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**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

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**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

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Thank you! Video, audio and PowerPoint files of this talk and others can be found at: Comments welcome:

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