Looking for Mr(s) Right: Decision bias can prevent us from finding the most attractive face

In realistic and challenging decision contexts, people may show biases that prevent them from choosing their favored options. For example, astronomer Johannes Kepler famously interviewed several candidate fiancées sequentially, but was rejected when attempting to return to a previous candidate. Similarly, we examined human performance on searches for attractive faces through fixed-length sequences by adapting optimal stopping computational theory developed from behavioral ecology and economics. Although economics studies have repeatedly found that participants sample too few options before choosing the best-ranked number from a series, we instead found overlong searches with many sequences ending without choice. Participants employed irrationally high choice thresholds, compared to the more lax, realistic standards of a Bayesian ideal observer, which achieved better-ranked faces. We consider several computational accounts and find that participants most resemble a Bayesian model that decides based on altered attractiveness values. These values may produce starkly different biases in the facial attractiveness domain than in other decision domains.