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Epistemic Landscapes, Optimal Search, and the Division of Cognitive Labor

Published online by Cambridge University Press:  01 January 2022

Jason McKenzie Alexander ,
Johannes Himmelreich  and
Christopher Thompson
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Abstract

This article examines two questions about scientists’ search for knowledge. First, which search strategies generate discoveries effectively? Second, is it advantageous to diversify search strategies? We argue pace Weisberg and Muldoon, “Epistemic Landscapes and the Division of Cognitive Labor” (this journal, 2009), that, on the first question, a search strategy that deliberately seeks novel research approaches need not be optimal. On the second question, we argue they have not shown epistemic reasons exist for the division of cognitive labor, identifying the errors that led to their conclusions. Furthermore, we generalize the epistemic landscape model, showing that one should be skeptical about the benefits of social learning in epistemically complex environments.

Type
Research Article
Information
Philosophy of Science , Volume 82 , Issue 3 , July 2015 , pp. 424 - 453
Copyright
Copyright © The Philosophy of Science Association

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Footnotes

†

Johannes Himmelreich is grateful for the hospitality of the School of Philosophy at the Australian National University at which a first version of this article was written.

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