is our reward

Publications in Crowds by NOMIS researchers

NOMIS Researcher(s)

January 1, 2022

Predictions pose unique problems. Experts regularly get them wrong, and collective solutions (such as prediction markets and super-forecaster schemes) do better but remain selective and costly. Contrary to the idea that face-to-face discussion hinders collective intelligence, social deliberation improves the resolution of general knowledge problems, with four consensually agreed answers outperforming the aggregate knowledge of 5,000 nondeliberating individuals. Could discussion help predict the future in an efficient, cheap, and inclusive way? We show that smaller groups of lay individuals, when organized, come up with better predictions than those they provide alone. Deliberation and consensus made individual predictions significantly more accurate. Aggregating as few as two consensual predictions did better than classical “wisdom of crowds” aggregation of 100 individual ones. Against the view that discussion can impair decision-making, our results demonstrate that collective intelligence of small groups and consensus-seeking improves accuracy about yet unknown facts, opening the avenue for efficient, inclusive, and inexpensive group forecasting solutions.

Research field(s)
Health Sciences, Psychology & Cognitive Sciences, Experimental Psychology

NOMIS Researcher(s)

Published in

November 1, 2019

The average judgment of large numbers of people has been found to be consistently better than the best individual response. But what motivates individuals when they make collective decisions? While it is a popular belief that individual incentives promote out-of-the-box thinking and diverse solutions, the exact role of motivation and reward in collective intelligence remains unclear. Here we examined collective intelligence in an interactive group estimation task where participants were rewarded for their individual or group’s performance. In addition to examining individual versus collective incentive structures, we controlled whether participants could see social information about the others’ responses. We found that knowledge about others’ responses reduced the wisdom of the crowd and, crucially, this effect depended on how people were rewarded. When rewarded for the accuracy of their individual responses, participants converged to the group mean, increasing social conformity, reducing diversity and thereby diminishing their group wisdom. When rewarded for their collective performance, diversity of opinions and the group wisdom increased. We conclude that the intuitive association between individual incentives and individualist opinion needs revising.

Research field(s)
Applied Sciences, Information & Communication Technologies, Artificial Intelligence & Image Processing