The Causal and Explanatory Role of Information Stored in Connectionist Networks

  • Authors:
  • Daniel M. Haybron

  • Affiliations:
  • Department of Philosophy, Rutgers University, New Brunswick, NJ 08903, USA (E-mail: haybron@ibm.net)

  • Venue:
  • Minds and Machines
  • Year:
  • 2000

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Abstract

In this paper I defend the propriety of explaining the behavior of distributed connectionist networks by appeal to selected data stored therein. In particular, I argue that if there is a problem with such explanations, it is a consequence of the fact that information storage in networks is superpositional, and not because it is distributed. I then develop a ``proto-account'' of causation for networks, based on an account of Andy Clark's, that shows even superpositionality does not undermine information-based explanation. Finally, I argue that the resulting explanations are genuinely informative and not vacuous.