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Epistemic Landscapes and the Division of Cognitive Labor

Published online by Cambridge University Press:  01 January 2022

Michael Weisberg  and
Ryan Muldoon
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Abstract

Because contemporary scientific research is conducted by groups of scientists, understanding scientific progress requires understanding this division of cognitive labor. We present a novel agent-based model of scientific research in which scientists divide their labor to explore an unknown epistemic landscape. Scientists aim to find the most epistemically significant research approaches. We consider three different search strategies that scientists can adopt for exploring the landscape. In the first, scientists work alone and do not let the discoveries of the community influence their actions. This is compared with two social research strategies: Followers are biased toward what others have already discovered, and we find that pure populations of these scientists do less well than scientists acting independently. However, pure populations of mavericks, who try to avoid research approaches that have already been taken, vastly outperform the other strategies. Finally, we show that, in mixed populations, mavericks stimulate followers to greater levels of epistemic production, making polymorphic populations of mavericks and followers ideal in many research domains.

Type
Research Article
Information
Philosophy of Science , Volume 76 , Issue 2 , April 2009 , pp. 225 - 252
Copyright
Copyright © The Philosophy of Science Association

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Footnotes

‡

We are grateful for the research assistance of Daniel Singer and Anna Tuchman. Many thanks to Michael Dickson, Tania Lombrozo, Edouard Machery, Brian Skyrms, Michael Strevens, J. D. Trout, and Deena Skolnick Weisberg for helpful comments on earlier versions of this article.

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