Maximizing as satisficing : On pattern matching and probability maximizing in groups and individuals

Abstract

Distinguishing meaningful structure from unpredictable randomness is a key challenge in many domains of life. We examined whether collaborating three-person groups (n = 81) outperform individuals (n = 81) in facing this challenge with a two-part repeated choice task, where outcomes were either serially independent (probabilistic part) or fixed in a particular sequence (pattern part). Groups performed as well as the best individuals in the probabilistic part but groups' accuracy did not credibly exceed that of the average individual in the pattern part. Qualitative coding of group discussion data revealed that failures to identify existing patterns were related to groups accepting probability maximizing as a “good enough” strategy rather than expending effort to search for patterns. These results suggest that probability maximizing can arise via two routes: recognizing that probabilistic processes cannot be outdone (maximizing as optimizing) or settling for an imperfect but easily implementable strategy (maximizing as satisficing).