this paper I'm indebted to three anonymous referees (whose insights were especially helpful), John Searle (whose seminal discussion of zombies in his The Rediscovery of the Mind provides the first round of my ammunition), Daniel Dennett, Stevan Harnad, David Rosenthal, Robert Van Gulick (who offered particularly insightful comments on the remote ancestor presented at the 1994 Eastern APA Meeting), Peter Smith, Kieron O'Hara, Michael Zenzen, Jim Fahey, Marvin Minsky, Larry Hauser and Pat Hayes. David Chalmers provided helpful analysis of a previous draft, and I profited from reading his The Conscious Mind, wherein zombies are taken to be logically possible. Conversations with Ned Block and Bill Rapaport also proved to be valuable.

The proper treatment of computationalism, as the thesis that cognition is computable, is presented and defended. Some arguments of James H. Fetzer against computationalism are examined and found wanting, and his positive theory of minds as semiotic systems is shown to be consistent with computationalism. An objection is raised to an argument of Selmer Bringsjord against one strand of computationalism, namely, that Turing-Testfpassing artifacts are persons, it is argued that, whether or not this objection holds, such artifacts will inevitably be persons.

The dominant scientific and philosophical view of the mind --- according to which, put starkly, cognition is computation --- is refuted herein, via specification and defense of the following new argument: Computation is reversible; cognition isn't; ergo, cognition isn't computation. After presenting a sustained dialectic arising from this defense, we conclude with a brief preview of the view we would put in place of the cognition-is-computation doctrine. We are indebted to Bill Rapaport, Pat Hayes, Ken Ford, Marvin Minsky, Jim Fahey, two anonymous referees (who provided particularly insightful comments), and many Rensselaer students. These people provided trenchant objections which saw to the evolution of the present version from a rather inauspicious primogenitor. 1 Introduction The dominant scientific and philosophical view of the mind --- put starkly, that cognition is computation --- is refuted herein, via specification and defense of the following new argument: Computation is...

To a majority of the people involved in the study of expertise from a computational perspective, `expertise' tends to refer to domains such as medical diagnosis, aircraft piloting, auditing, etc. The reasoning in domains like these appears to be ready-made for computational packaging. But what if we try to cast a broader, braver net in an attempt to catch varieties of expertise out there in the real world which don't, at least at first glance, look like they can be rendered in computational terms? In particular, what about mathematical expertise? In this chapter I focus on elementary "infinitary " expertise in the domain of mathematical logic. I argue that at least some of this expertise is indeed uncomputable. I end by briefly discussing the implications of this argument for the practice of AI and expert systems.

I advocate a theory of "syntactic semantics" as a way of understanding how computers can think (and how the Chinese-Roam-Argument objection to the Turing Test can be overcome): (1) Semantics, considered as the study of relations between symbols and meanings, can be turned into syntax- a study of relations among symbols (including meanings)- and hence syntax (i.e., symbol manipulation) can suffice for the semantical enterprise (contra Searle). (2) Semantics, considered as the process of understanding one domain (by modeling it) in terms of another, can be viewed recursively: The base case of semantic understanding- understanding a domain in terms of itself- is "syntactic understanding." (3) An internal (or "narrow"), first-person point of view makes an external (or "wide"), third-person point of view otiose for purposes of understanding cognition.

9.9.05 1245am NY time Do human persons hypercompute? Or, as the doctrine of computationalism holds, are they information processors at or below the Turing Limit? If the former, given the essence of hypercomputation, persons must in some real way be capable of infinitary information processing. Using as a springboard Gödel’s little-known assertion that the human mind has a power “converging to infinity, ” and as an anchoring problem Rado’s (1963) Turing-uncomputable “busy beaver ” (or Σ) function, we present in this short paper a new argument that, in fact, human persons can hypercompute. The argument is intended to be formidable, not conclusive: it brings Gödel’s intuition to a greater level of precision, and places it within a sensible case against computationalism. 1

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In this paper I place Jim Fetzer's esemplastic burial of the computational conception of mind within the context of both my own burial and the theory of mind I would put in place of this dead doctrine. My view in a nutshell: Computationalism will yield Total Turing Test-passing zombies (in the philosopher's sense of `zombie'), but replicating persons will be unreachable for two reasons. One, persons process information at a "super"-Turing level; two, people enjoy certain properties (e.g., intentionality) beyond the reach of any mere information-processing object. Accordingly, computationalism ought to be supplanted with the engineering of "sub-person" artifacts and the irreducibly philosophical investigation of personhood. I end with nascent appraisal of Fetzer's interesting semiotic/connectionist replacement for computationalism. I'm grateful to Michael Costa for inviting Jim Fetzer to organize a symposium on whether minds are computational systems for the annual meeting of the Sout...

Most subscribers to the "Strong" AI doctrine that cognition is computation believe that even venerated attacks on this view [such as John Searle's (1980) Chinese Room Argument] are horribly obscure and fanciful. We find this attitude agreeable. But in this paper we present a genuinely formidable argument against "Strong" AI---an argument that has its roots in elementary aspects of recursion theory and quantified modal logic, two bodies of knowledge which "Strong" AI has generally embraced.