Humans make best use of social heuristics when confronting hard problems in large groups

TL;DR

This study shows that humans effectively use social heuristics to optimize cooperation in large groups when facing complex problems, especially under challenging conditions, leading to maximal scores.

Contribution

It demonstrates that humans adaptively apply social heuristics in group problem-solving, with effectiveness increasing in larger groups and more difficult tasks, independent of individual traits.

Findings

Humans underestimate collaboration benefits in easy tasks and small groups.

Humans accurately judge collaboration benefits in hard tasks and large groups.

Social heuristics are more useful in complex, large-group problem-solving scenarios.

Abstract

We report the results of a game-theoretic experiment with human players who solve the problems of increasing complexity by cooperating in groups of increasing size. Our experimental environment is set up to make it complicated for players to use rational calculation for making the cooperative decisions. This environment is directly translated into a computer simulation, from which we extract the collaboration strategy that leads to the maximal attainable score. Based on this, we measure the error that players make when estimating the benefits of collaboration, and find that humans massively underestimate these benefits when facing easy problems or working alone or in small groups. In contrast, when confronting hard problems or collaborating in large groups, humans accurately judge the best level of collaboration and easily achieve the maximal score. Our findings are independent on groups' composition and players' personal traits. We interpret them as varying degrees of usefulness of social heuristics, which seems to depend on the size of the involved group and the complexity of the situation.