Online research in philosophy

Harnad defines computation to mean the manipulation of physical symbol tokens on the basis of syntactic rules defined over the shapes of the symbols, independent of what, if anything, those symbols represent. He is, of course, free to define terms in any way that he chooses, and he is very clear about what he means by computation, but I am uncomfortable with this definition. It excludes, at least at a functional level of description, much of what a computer is actually (...) used for, and much of what the brain/mind does. When I toss a Frisbee to the neighbor's dog, the dog does not, I think, engage in a symbolic soliloquy about the trajectory of the disc, the wind's effects on it, and formulas for including lift and the acceleration due to gravity. There are symbolic formulas for each of these relations, but the dog insofar as I can tell, does not use any of these formulas. Nevertheless, it computes these factors in order to intercept the disc in the air. I argue that determining the solution to a differential equation is at least as much computation as is processing symbols. The disagreement is over what counts as computation, I think that Harnad and I both agree that the dog solves the trajectory problem implicitly. This definition is important, because, although Harnad offers a technical definition for what he means by computation, the folk- definition of the term is probably interpreted differently, and I believe this leads to trouble. (shrink)

Stevan Harnad correctly perceives a deep problem in computationalism, the hypothesis that cognition is computation, namely, that the symbols manipulated by a computational entity do not automatically mean anything. Perhaps, he proposes, transducers and neural nets will not have this problem. His analysis goes wrong from the start, because computationalism is not as rigid a set of theories as he thinks. Transducers and neural nets are just two kinds of computational system, among many, and any solution to the semantic problem (...) that works for them will work for most other computational systems. (shrink)

While I agree in general with Stevan Harnad's symbol grounding proposal, I do not believe "transduction" (or "analog process") PER SE is useful in distinguishing between what might best be described as different "degrees" of grounding and, hence, for determining whether a particular system might be capable of cognition. By 'degrees of grounding' I mean whether the effects of grounding go "all the way through" or not. Why is transduction limited in this regard? Because transduction is a physical process which (...) does not speak to the issue of representation, and, therefore, does not explain HOW the informational aspects of signals impinging on sensory surfaces become embodied as symbols or HOW those symbols subsequently cause behavior, both of which, I believe, are important to grounding and to a system's cognitive capacity. Immunity to Searle's Chinese Room (CR) argument does not ensure that a particular system is cognitive, and whether or not a particular degree of groundedness enables a system to pass the Total Turing Test (TTT) may never be determined. (shrink)