David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
Studies in History and Philosophy of Science Part A 41 (3):223-226 (2010)
Nowadays, it has become almost a matter of course to say that human mind is like a computer. Folks in all walks of life talk of ‘programming’ themselves, ‘multi-tasking’, running different ‘operating systems’, and sometimes of ‘crashing’ and being ‘rebooted’. Few who have used computers have not been touched by the appeal of the idea that our inner workings somehow resemble computing machines. The success of modern day computational psychology appears to bears witness to the explanatory and predictive pay-off in positing a connection between computers and minds. Among its other virtues, the computational framework has rendered theorising about inner processes respectable, it has provided a unified and naturalistic arena in which to conduct debates about psychological models, and it provides the tantalising possibility of accurately simulating and reproducing psychological processes. There is almost universal agreement that the mind is in some sense like a computer. But consensus quickly ends once we ask how the mind is supposed to be like a computer. Even after more than thirty years of model building, and a wealth of empirical work, surprisingly little consensus exists in cognitive science on the correct answer to this question. What is more, disagreement tends to lie at a relatively deep level. There is little agreement about the content of the notion of computation, what it means for a physical system, like the brain, to implement a computation, the broad-brush computational architecture of the mind, or how computational models fit with other models of the mind, such as control theoretic models, statistical models, or dynamical systems theory
|Keywords||No keywords specified (fix it)|
|Categories||categorize this paper)|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library|
References found in this work BETA
No references found.
Citations of this work BETA
Raymond Turner (2014). Programming Languages as Technical Artifacts. Philosophy and Technology 27 (3):377-397.
Similar books and articles
Subrata Dasgupta (2008). Shedding Computational Light on Human Creativity. Perspectives on Science 16 (2):pp. 121-136.
Valerie Gray Hardcastle (1995). Computationalism. Synthese 105 (3):303-17.
James H. Fetzer (1997). Thinking and Computing: Computers as Special Kinds of Signs. [REVIEW] Minds and Machines 7 (3):345-364.
Gordana Dodig-Crnkovic (2011). Significance of Models of Computation, From Turing Model to Natural Computation. Minds and Machines 21 (2):301-322.
Bruce J. MacLennan (1994). Words Lie in Our Way. Minds and Machines 4 (4):421-37.
Mary Litch (1997). Computation, Connectionism and Modelling the Mind. Philosophical Psychology 10 (3):357-364.
Margaret A. Boden (1988). Computer Models On Mind: Computational Approaches In Theoretical Psychology. Cambridge University Press.
Paul R. Thagard (2002). How Molecules Matter to Mental Computation. Philosophy of Science 69 (3):497-518.
David J. Chalmers (2011). A Computational Foundation for the Study of Cognition. Journal of Cognitive Science 12 (4):323-357.
Mark Sprevak (2010). Computation and Cognitive Science. Studies in History and Philosophy of Science Part A 41 (3):223-226.
Added to index2010-04-08
Total downloads31 ( #63,581 of 1,413,330 )
Recent downloads (6 months)3 ( #67,208 of 1,413,330 )
How can I increase my downloads?