Rewiring the Wisdom of the Crowd

Jason W. Burton, Abdullah Almaatouq, M. Amin Rahimian, Ulrike Hahn

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningpeer review


Digitally-enabled means for judgment aggregation have renewed interest in "wisdom of the crowd'' effects and kick-started collective intelligence design as an emerging field in the cognitive and computational sciences. A keenly debated question here is whether social influence helps or hinders collective accuracy on estimation tasks, with recently introduced network theories offering a reconciliation of seemingly contradictory past results. Yet, despite a growing body of literature linking social network structure and the accuracy of collective beliefs, strategies for exploiting network structure to harness crowd wisdom are under-explored. In this paper, we introduce a potential new tool for collective intelligence design informed by such network theories: rewiring algorithms. We provide a proof of concept through agent-based modelling and simulation, showing that rewiring algorithms that dynamically manipulate the structure of communicating social networks can increase the accuracy of collective estimations in the absence of knowledge of the ground truth.
Titel43rd Annual Meeting of the Cognitive Science Society (CogSci 2021)
Antal sider7
UdgivelsesstedSeattle, WA
ForlagCognitive Science Society
StatusUdgivet - 2021
Udgivet eksterntJa
NavnProceedings of the Annual Meeting of the Cognitive Science Society


  • Collective intelligence
  • Wisdom of crowds
  • Social networks
  • Agent-based model