Choosing the best robot for the job : affinity bias in human-robot interaction

Humans subconsciously judge others as being either similar or dissimilar to themselves, manifesting as an unconscious preference, or affinity bias, for those who are perceived to be similar. In human-to-human interaction, affinity bias can significantly influence trust formation and lead to discrimination, for example, in decisions related to recruitment and team selection. We investigate whether affinity bias is observed in human-robot interaction during team formation with social agents that differ in gender and skin tone. In this study, we asked 61 participants to order the resumés of 24 different avatars that varied in gender, skin tone, and competency under the pretext of choosing the “best” avatars to be the participant’s teammate. Then, using a wizard-of-oz style experiment, participants performed a task with two avatar teammates (one most preferred and one least preferred) to measure trust. Results showed that while avatars were predominantly chosen based upon competency, avatar appearance generated an affinity bias in resumé sorting, and participants were more likely to trust their preferred teammate.