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- David Longinotti (2009). Computationalism and the Locality Principle. Minds and Machines 19 (4):495-506.Computationalism, a specie of functionalism, posits that a mental state like pain is realized by a ‘core’ computational state within a particular causal network of such states. This entails that what is realized by the core state is contingent on events remote in space and time, which puts computationalism at odds with the locality principle of physics. If computationalism is amended to respect locality, then it posits that a type of phenomenal experience is determined by a single type of computational state. But a computational state, considered by itself, is of no determinate type—it has no particular symbolic content, since it could be embedded in any of an infinite number of algorithms. Hence, if locality is respected, then the type of experience that is realized by a computational state, or whether any experience at all is realized, is under-determined by the computational nature of the state. Accordingly, Block’s absent and inverted qualia arguments against functionalism find support in the locality principle of physics. If computationalism denies locality to avoid this problem, then it cannot be considered a physicalist theory since it would entail a commitment to phenomena, like teleological causation and action-at-a-distance, that have long been rejected by modern science. The remaining theoretical alternative is to accept the locality principle for macro events and deny that formal, computational operations are sufficient to realize a phenomenal mental state.
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x10.1 Locality Newton's Law of Universal Gravitation was always open to the complaint that it involved \Action at a Distance", contrary to the Principle of Locality. But it was very well established empirically, and had to be accepted. Similarly in contemporary quantum me- chanics we seem to have correlations between measurements that defy the Principle of Locality, but have to be accepted none the less.1 Although locality is a characteristic mark of causal con- nexion, it is not, as Hume supposed,2 an essential one. Nor is it merely a uniformity we have found to hold for the most part|else we should feel little compunction in accepting that in some cases it happened not to hold. It is clearly an a priori principle, though not an absolutely necessary one.
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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-Test± passing artifacts are persons, it is argued that, whether or not this objection holds, such artifacts will inevitably be persons.
Clark ends his appendix with a description of what he calls "dynamic computationalism", which he describes as an interesting hybrid between DST and GOFAI. My 'horseLISP" example could be described as an example of dynamic computationalism. It is clearly not as eliminativist as Van Gelder's computational governor example, for I am trying to come up with something like identities between computational entities and dynamic ones. Thus unlike other dynamicists, I am not doing what Clark calls "embracing a different vocabulary for the understanding and analysis of brain events". I think we probably can keep much of the computational vocabulary, although the meanings of many of its terms will probably shift as much as the meaning of 'atom' has shifted since Dalton's time. The label of "dynamic computationalism" is perhaps as good a description of my position as any, but I think I would mean something slightly different by it than Clark would. (For the following, please insert the mantra "of course, this is an empirical question" (OCTEQ) every paragraph or so.).
In this paper, I want to deal with the triviality threat to computationalism. On one hand, the controversial and vague claim that cognition involves computation is still denied. On the other, contemporary physicists and philosophers alike claim that all physical processes are indeed computational or algorithmic. This claim would justify the computationalism claim by making it utterly trivial. I will show that even if these two claims were true, computationalism would not have to be trivial.
In this paper and its sequel, I consider the significance of Jarrett's and Shimony's analyses of the so-called factorisability (Bell-locality) condition for clarifying the nature of quantum non-locality. In this paper, I focus on four types of non-locality: superluminal signalling, <span class='Hi'>action</span>-at-a-distance, non-separability and holism. In the second paper, I consider a fifth type of non-locality: superluminal causation according to 'logically weak' concepts of causation, where causal dependence requires neither <span class='Hi'>action</span> nor signalling. In this connection, I pay special attention to the difficulties that superluminal causation raises in relativistic space-time. I conclude by evaluating the relevance of Jarrett's and Shimony's analyses for clarifying the question of the compatibility of quantum non-locality with relativity theory. My main conclusions are, first: these analyses are significant for clarifying the questions of superluminal signalling in quantum phenomena and for the compatibility of these phenomena with relativity. But, second, by contrast: these analyses are not very significant for the study of <span class='Hi'>action</span>-at-a distance, superluminal causation, non-separability and holism in quantum phenomena.
Two principles of locality used in discussions about quantum mechanics are distinguished. The intuitive no-action-at-a distance requirement is called physical locality. There is also a mathematical requirement of a kind of factorizability which is referred to as "locality". It is argued in this paper that factorizability is not necessary for physical locality. Ways of producing models that are physically local although not factorizable which are concerned with correlations between the behavior of pairs of particles are suggested. These models can account for all the quantum mechanical single and joint probabilities.
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Some philosophers have conflated functionalism and computationalism. I reconstruct how this came about and uncover two assumptions that made the conflation possible. They are the assumptions that (i) psychological functional analyses are computational descriptions and (ii) everything may be described as performing computations. I argue that, if we want to improve our understanding of both the metaphysics of mental states and the functional relations between them, we should reject these assumptions. # 2004 Elsevier Ltd. All rights reserved.
Defending or attacking either functionalism or computationalism requires clarity on what they amount to and what evidence counts for or against them. My goal here is not to evaluate their plausibility. My goal is to formulate them and their relationship clearly enough that we can determine which type of evidence is relevant to them. I aim to dispel some sources of confusion that surround functionalism and computationalism, recruit recent philosophical work on mechanisms and computation to shed light on them, and clarify how functionalism and computationalism may or may not legitimately come together.
Some philosophers have conflated functionalism and computationalism. I reconstruct how this came about and uncover two assumptions that made the conflation possible. They are the assumptions that (i) psychological functional analyses are computational descriptions and (ii) everything may be described as performing computations. I argue that, if we want to improve our understanding of both the metaphysics of mental states and the functional relations between them, we should reject these assumptions.
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.
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