UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

The Crowd Classification Problem: Social Dynamics of Binary Choice Accuracy

Becker, J; Guilbeault, D; Smith, N; (2021) The Crowd Classification Problem: Social Dynamics of Binary Choice Accuracy. Management Science 10.1287/mnsc.2021.4127. (In press). Green open access

[thumbnail of Becker Guilbeault Smith - Final Manuscript - 2021 12 May.pdf]
Preview
Text
Becker Guilbeault Smith - Final Manuscript - 2021 12 May.pdf - Accepted Version

Download (483kB) | Preview

Abstract

Decades of research suggest that information exchange in groups and organizations can reliably improve judgment accuracy in tasks such as financial forecasting, market research, and medical decision making. However, we show that improving the accuracy of numeric estimates does not necessarily improve the accuracy of decisions. For binary-choice judgments, also known as classification tasks—for example, yes/no or build/buy decisions—social influence is most likely to grow the majority vote share, regardless of the accuracy of that opinion. As a result, initially, inaccurate groups become increasingly inaccurate after information exchange, even as they signal stronger support. We term this dynamic the “crowd classification problem.” Using both a novel data set and a reanalysis of three previous data sets, we study this process in two types of information exchange: (1) when people share votes only, and (2) when people form and exchange numeric estimates prior to voting. Surprisingly, when people exchange numeric estimates prior to voting, the binary-choice vote can become less accurate, even as the average numeric estimate becomes more accurate. Our findings recommend against voting as a form of decision making when groups are optimizing for accuracy. For those cases where voting is required, we discuss strategies for managing communication to avoid the crowd classification problem. We close with a discussion of how our results contribute to a broader contingency theory of collective intelligence.

Type: Article
Title: The Crowd Classification Problem: Social Dynamics of Binary Choice Accuracy
Open access status: An open access version is available from UCL Discovery
DOI: 10.1287/mnsc.2021.4127
Publisher version: https://doi.org/10.1287/mnsc.2021.4127
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions.
Keywords: group decision making; collective intelligence; decision theory; wisdom of crowds; delphi method
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > UCL School of Management
URI: https://discovery.ucl.ac.uk/id/eprint/10134868
Downloads since deposit
63Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item