Problem Solving: When Groups Perform Better Than Teammates

Abstract

: People tend to form groups when they have to solve difficult problems because groups seem to have betterproblem-solvingcapabilitiesthanindividuals. Indeed, duringtheirevolution, humanbeingslearnedthat cooperation is frequently an optimal strategy to solve hard problems both quickly and accurately. The ability of a group to determine a solution to a given problem, once group members alone cannot, has been called “Collective Intelligence". Such emergent property of the group as a whole is the result of a complex interaction between many factors. Here, we propose a simple and analytically solvable model disentangling the direct link between collective intelligence and the average intelligence of group members. We found that there is a non-linear relation between the collective intelligence of a group and the average intelligence quotient of its members depending on task difficulty. We found three regimes as follows: for simple tasks, the level of collective intelligence of a group is a decreasing function of teammates’ intelligence quotient; when tasks have intermediate difficulties, the relation between collective intelligence and intelligence quotient shows a non-monotone behaviour; for complex tasks, the level of collective intelligence of a group monotonically increases withteammates’intelligencequotientwithphasetransitionsemergingwhenvaryingthelatter’slevel. Although simple and abstract, our model paves the way for future experimental explorations of the link between task complexity, individual intelligence and group performance.