Hostname: page-component-78c5997874-t5tsf Total loading time: 0 Render date: 2024-11-14T23:16:32.021Z Has data issue: false hasContentIssue false
  • English
  • Français

Diversity, Not Randomness, Trumps Ability

Published online by Cambridge University Press:  01 January 2022

Daniel J. Singer
Get access Rights & Permissions [Opens in a new window]

Abstract

A number of formal models, including a highly influential model from Hong and Page, purport to show that functionally diverse groups often beat groups of individually high-performing agents in solving problems. Thompson argues that in Hong and Page’s model, that the diverse groups are created by a random process explains their success, not the diversity. Here, I defend the diversity interpretation of the Hong and Page result. The failure of Thompson’s argument shows that to understand the value of functional diversity, we should be clearer about how we conceive of and measure that diversity.

Type
Discussions
Information
Philosophy of Science , Volume 86 , Issue 1 , January 2019 , pp. 178 - 191
Copyright
Copyright © The Philosophy of Science Association

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

†

I am very thankful to Scott E. Page, William (Zev) Berger, Meredith Tamminga, and two anonymous reviewers for comments on an earlier draft of this article.

References

Aaronson, S. 2017. “P=?NP.” Manuscript. https://eccc.weizmann.ac.il/report/2017/004/.Google Scholar
Brennan, J. 2017. Against Democracy. Princeton, NJ: Princeton University Press.CrossRefGoogle Scholar
Bright, L. K. 2017. “Decision Theoretic Model of the Productivity Gap.” Erkenntnis 82 (2): 421–42.CrossRefGoogle Scholar
Greathouse, C. R. 2013. “p v. bpp.” Open Problem Garden. http://www.openproblemgarden.org/op/p_vs_bpp.Google Scholar
Grim, P., Singer, D. J., Bramson, A., Holman, B., McGeehan, S., and Berger, W. J. 2019. “Diversity, Ability, and Expertise in Epistemic Communities.” Philosophy of Science, in this issue.CrossRefGoogle Scholar
Hong, L., and Page, S. E. 2004. “Groups of Diverse Problem Solvers Can Outperform Groups of High-Ability Problem Solvers.” Proceedings of the National Academy of Sciences of the United States of America 101 (46): 16385–89.Google ScholarPubMed
Karp, R. M. 1991. “An Introduction to Randomized Algorithms.” Discrete Applied Mathematics 34 (1–3): 165–201.CrossRefGoogle Scholar
Kuehn, D. 2017. “Diversity, Ability, and Democracy: A Note on Thompson’s Challenge to Hong and Page.” Critical Review 29 (1): 72–87.CrossRefGoogle Scholar
Landemore, H. 2012. Democratic Reason: Politics, Collective Intelligence, and the Rule of the Many. Princeton, NJ: Princeton University Press.Google Scholar
Martini, C. 2014. “Experts in Science: A View from the Trenches.” Synthese 191 (1): 3–15.CrossRefGoogle Scholar
O’Connor, C., and Bruner, J. 2017. “Dynamics and Diversity in Epistemic Communities.” Erkenntnis. DOI:10.1007/s11229-017-1487-8.CrossRefGoogle Scholar
Page, S. E. 2007. The Difference. Princeton, NJ: Princeton University Press.Google Scholar
Rosenstock, S., O’Connor, C., and Bruner, J. 2017. “In Epistemic Networks, Is Less Really More? Philosophy of Science 84 (2): 234–52.CrossRefGoogle Scholar
Rubin, H., and O’Connor, C. 2018. “Discrimination and Collaboration in Science.” Philosophy of Science 85 (3): 380–402.CrossRefGoogle Scholar
Stegenga, J. 2016. “Three Criteria for Consensus Conferences.” Foundations of Science 21 (1): 35–49.CrossRefGoogle Scholar
Thoma, J. 2015. “The Epistemic Division of Labor Revisited.” Philosophy of Science 82 (3): 454–72.CrossRefGoogle Scholar
Thompson, A. 2014. “Does Diversity Trump Ability?” Notices of the AMS 61 (9): 1–24.Google Scholar
UCLA College Diversity Initiative Committee. 2014. “Proposed Diversity Requirement.” https://ccle.ucla.edu/pluginfile.php/743624/mod_resource/content/6/082014%20REVISED%20DiversityReqProposal.pdf.Google Scholar
Vadhan, S. P. 2012. “Pseudorandomness.” Foundations and Trends in Theoretical Computer Science 7 (1–3): 1–336.CrossRefGoogle Scholar
Weisberg, M., and Muldoon, R. 2009. “Epistemic Landscapes and the Division of Cognitive Labor.” Philosophy of Science 76 (2): 225–52.CrossRefGoogle Scholar
Zollman, K. J. S. 2010. “The Epistemic Benefit of Transient Diversity.” Erkenntnis 72 (1): 17–35.CrossRefGoogle Scholar