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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.

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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.

References

Arrow, Kenneth J., Forsythe, Robert, Gorham, Michael, Hahn, Robert, Hanson, Robin, Ledyard, John O., Levmore, Saul, Litan, Robert, Milgrom, Paul, and Nelson, Forrest D.. 2008. “The Promise of Prediction Markets.” Science 320 (5878): 877–78.CrossRefGoogle ScholarPubMed
Bonabeu, Eric, Dorigo, Marco, and Theraulaz, Guy. 1999. Swarm Intelligence: From Natural to Artificial Systems. Oxford: Oxford University Press.CrossRefGoogle Scholar
Clearwater, Scott H., Huberman, Bernardo A., and Hogg, Tad. 1991. “Cooperative Solution of Constraint Satisfaction Problems.” Science 254 (5035): 1181–83.CrossRefGoogle ScholarPubMed
Couzin, Iain D., Krause, Jens, Franks, Nigel R., and Levin, Simon A.. 2005. “Effective Leadership and Decision-Making in Animal Groups on the Move.” Nature 433 (7025): 513–16.CrossRefGoogle ScholarPubMed
Hong, Lu, and Page, Scott E.. 2004. “Groups of Diverse Problem Solvers Can Outperform Groups of High-Ability Problem Solvers.” Proceedings of the National Academy of Sciences of the USA 101 (46): 16385–389.CrossRefGoogle ScholarPubMed
Jackson, Susan E., Joshi, Aparna, and Erhardt, Niclas L.. 2003. “Recent Research on Team and Organizational Diversity: SWOT Analysis and Implications.” Journal of Management 29 (6): 801–30.CrossRefGoogle Scholar
Kauffman, Stuart, and Levin, Simon. 1987. “Towards a General Theory of Adaptive Walks on Rugged Landscapes.” Journal of Theoretical Biology 128 (1): 11–45.CrossRefGoogle ScholarPubMed
Kauffman, Stuart, and Weinberger, Edward D.. 1989. “The NK Model of Rugged Fitness Landscapes and Its Application to Maturation of the Immune Response.” Journal of Theoretical Biology 141 (2): 211–45.CrossRefGoogle ScholarPubMed
Kerr, Norbert L., and Tindale, R. Scott. 2004. “Group Performance and Decision Making.” Annual Review of Psychology 55 (1): 623–55.CrossRefGoogle ScholarPubMed
Kitcher, Philip. 1993. The Advancement of Science: Science without Legend, Objectivity without Illusions. Oxford: Oxford University Press.Google Scholar
Krause, Stefan, James, Richard, Faria, Jolyon J., Ruxton, Graeme D., and Krause, Jens. 2011. “Swarm Intelligence in Humans: Diversity Can Trump Ability.” Animal Behaviour 81 (5): 941–48.CrossRefGoogle Scholar
Polzer, Jeffrey T., Milton, Laurie P., and Swarm, William B.. 2002. “Capitalizing on Diversity: Interpersonal Congruence in Small Work Groups.” Administrative Science Quarterly 47 (2): 296–324.CrossRefGoogle Scholar
Reynolds, Craig W. 1987. “Flocks, Herds and Schools: A Distributed Behavioral Model.” In Proceedings of the 14th Annual Conference on Computer Graphics and Interactive Techniques, ed. Stone, Maureen C., 25–34. New York: ACM.Google Scholar
Seeley, Thomas D. 2010. Honeybee Democracy. Princeton, NJ: Princeton University Press.Google Scholar
Strevens, Michael. 2003. “The Role of the Priority Rule in Science.” Journal of Philosophy 100 (2): 55–79.CrossRefGoogle Scholar
Sumpter, David J. T. 2010. Collective Animal Behavior. Princeton, NJ: Princeton University Press.CrossRefGoogle Scholar
Thomas, David A., and Ely, Robin J.. 1996. “Making Differences Matter.” Harvard Business Review 74 (5): 79–90.Google Scholar
Ward, Ashley J. W., Krause, Jens, and Sumpter, David J. T.. 2012. “Quorum Decision-Making in Foraging Fish Shoals.” PLoS ONE 7 (3): e32411.CrossRefGoogle ScholarPubMed
Weisberg, Michael, and Muldoon, Ryan. 2009. “Epistemic Landscapes and the Division of Cognitive Labor.” Philosophy of Science 76 (2): 225–52.CrossRefGoogle Scholar
Wright, Sewall. 1932. “The Roles of Mutation, Inbreeding, Crossbreeding, and Selection in Evolution.” In Proceedings of the Sixth International Congress on Genetics, ed. Jones, Donald F., 355–66. Brooklyn, NY: Brooklyn Botanic Garden.Google Scholar
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