We should probably also read this paper by Chalmers if we are to understand where his philosophy of mind is coming from and what he's been concentrating on for the last decade or two:
A Computational Foundation for the Study of Cognition
David J. Chalmers
[This paper was written in 1993 but never published (although section 2 was included in "On Implementing a Computation", published in Minds and Machines in 1994). It is now forthcoming in the Journal of Cognitive Science (2012), where there will be a special issue devoted to commentaries on it and a reply. Because the paper has been widely cited over the years, I have not made any changes to it (apart from adding one footnote), instead saving any further thoughts for my reply in the special issue. In any case I am still largely sympathetic with the views expressed here, in broad outline if not in every detail.]
ABSTRACT
Computation is central to the foundations of modern cognitive science, but its role is controversial. Questions about computation abound: What is it for a physical system to implement a computation? Is computation sufficient for thought? What is the role of computation in a theory of cognition? What is the relation between different sorts of computational theory, such as connectionism and symbolic computation? In this paper I develop a systematic framework that addresses all of these questions.
Justifying the role of computation requires analysis of implementation, the nexus between abstract computations and concrete physical systems. I give such an analysis, based on the idea that a system implements a computation if the causal structure of the system mirrors the formal structure of the computation. This account can be used to justify the central commitments of artificial intelligence and computational cognitive science: the thesis of computational sufficiency, which holds that the right kind of computational structure suffices for the possession of a mind, and the thesis of computational explanation, which holds that computation provides a general framework for the explanation of cognitive processes. The theses are consequences of the facts that (a) computation can specify general patterns of causal organization, and (b) mentality is an organizational invariant, rooted in such patterns. Along the way I answer various challenges to the computationalist position, such as those put forward by Searle. I close by advocating a kind of minimal computationalism, compatible with a very wide variety of empirical approaches to the mind. This allows computation to serve as a true foundation for cognitive science.
Keywords: computation; cognition; implementation; explanation; connectionism; computationalism; representation; artificial intelligence.
A Computational Foundation for the Study of Cognition
A Computational Foundation for the Study of Cognition
David J. Chalmers
[This paper was written in 1993 but never published (although section 2 was included in "On Implementing a Computation", published in Minds and Machines in 1994). It is now forthcoming in the Journal of Cognitive Science (2012), where there will be a special issue devoted to commentaries on it and a reply. Because the paper has been widely cited over the years, I have not made any changes to it (apart from adding one footnote), instead saving any further thoughts for my reply in the special issue. In any case I am still largely sympathetic with the views expressed here, in broad outline if not in every detail.]
ABSTRACT
Computation is central to the foundations of modern cognitive science, but its role is controversial. Questions about computation abound: What is it for a physical system to implement a computation? Is computation sufficient for thought? What is the role of computation in a theory of cognition? What is the relation between different sorts of computational theory, such as connectionism and symbolic computation? In this paper I develop a systematic framework that addresses all of these questions.
Justifying the role of computation requires analysis of implementation, the nexus between abstract computations and concrete physical systems. I give such an analysis, based on the idea that a system implements a computation if the causal structure of the system mirrors the formal structure of the computation. This account can be used to justify the central commitments of artificial intelligence and computational cognitive science: the thesis of computational sufficiency, which holds that the right kind of computational structure suffices for the possession of a mind, and the thesis of computational explanation, which holds that computation provides a general framework for the explanation of cognitive processes. The theses are consequences of the facts that (a) computation can specify general patterns of causal organization, and (b) mentality is an organizational invariant, rooted in such patterns. Along the way I answer various challenges to the computationalist position, such as those put forward by Searle. I close by advocating a kind of minimal computationalism, compatible with a very wide variety of empirical approaches to the mind. This allows computation to serve as a true foundation for cognitive science.
Keywords: computation; cognition; implementation; explanation; connectionism; computationalism; representation; artificial intelligence.
A Computational Foundation for the Study of Cognition