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50 Years of Successful Predictive Modeling Should Be Enough: Lessons for Philosophy of Science

Published online by Cambridge University Press:  01 January 2022

Michael A. Bishop  and
J. D. Trout
J. D. Trout*
Affiliation:
Iowa State University and Loyola University, Chicago
*
Send requests for reprints to the authors. Bishop: Department of Philosophy and Religious Studies, 402 Catt Hall, Iowa State University, Ames, IA 50011; mikebish@iastate.edu; Trout: Department of Philosophy, 6525 N. Sheridan Rd., Loyola University, Chicago, IL 60626; email: jtrout@orion.it.luc.edu.
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Abstract

Our aim in this paper is to bring the woefully neglected literature on predictive modeling to bear on some central questions in the philosophy of science. The lesson of this literature is straightforward: For a very wide range of prediction problems, statistical prediction rules (SPRs), often rules that are very easy to implement, make predictions than are as reliable as, and typically more reliable than, human experts. We will argue that the success of SPRs forces us to reconsider our views about what is involved in understanding, explanation, good reasoning, and about how we ought to do philosophy of science.

Type
Research Article
Information
Philosophy of Science , Volume 69 , Issue S3 , September 2002 , pp. S197 - S208
Copyright
Copyright © The Philosophy of Science Association

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