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Compressibility and the Reality of Patterns

Published online by Cambridge University Press:  01 January 2022

Tyler Millhouse
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Abstract

Daniel Dennett distinguishes real patterns from bogus patterns by appeal to compressibility. As information theorists have shown, data are compressible if and only if those data exhibit a pattern. Noting that high-level models are much simpler than their low-level counterparts, Dennett interprets high-level models as compressed representations of the fine-grained behavior of their target system. As such, he argues that high-level models depend on patterns in this behavior. Unfortunately, data scientific practice complicates Dennett’s interpretation, undermining the traditional justification for real patterns and suggesting a revised research program for its defenders.

Type
Research Article
Information
Philosophy of Science , Volume 88 , Issue 1 , January 2021 , pp. 22 - 43
Copyright
Copyright © The Philosophy of Science Association

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Footnotes

†

I am indebted to Shaun Nichols, Daniel Dennett, Terry Horgan, Brandon Ashby, Caroline King, Rhys Borchert, and Amanda Romaine for their comments, conversation, and encouragement on this article. Any remaining errors or omissions are entirely my own.

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