1. 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

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: 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

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:
Comments welcome: