The black sheep effect: The case of the deviant ingroup robot

Autoři: Andrew Steain aff001;  Christopher John Stanton aff001;  Catherine J. Stevens aff001
Působiště autorů: MARCS Institute, Western Sydney University, Sydney, Australia aff001
Vyšlo v časopise: PLoS ONE 14(10)
Kategorie: Research Article
doi: 10.1371/journal.pone.0222975


The black sheep effect (BSE) describes the evaluative upgrading of norm-compliant group members (ingroup bias), and evaluative downgrading of deviant (norm-violating) group members, relative to similar outgroup members. While the BSE has been demonstrated extensively in human groups, it has yet to be shown in groups containing robots. This study investigated whether a BSE towards a ‘deviant’ robot (one low on warmth and competence) could be demonstrated. Participants performed a visual tracking task in a team with two humanoid NAO robots, with one robot being an ingroup member and the other an outgroup member. The robots offered advice to the participants which could be accepted or rejected, proving a measure of trust. Both robots were also evaluated using questionnaires, proxemics, and forced preference choices. Experiment 1 (N = 18) manipulated robot grouping to test our group manipulation generated ingroup bias (a necessary precursor to the BSE) which was supported. Experiment 2 (N = 72) manipulated the grouping, warmth and competence of both robots, predicting a BSE towards deviant ingroup robots, which was supported. Results indicated that a disagreeable ingroup robot is viewed less favourably than a disagreeable outgroup robot. Furthermore, when interacting with two independent robots, a “majority rule” effect can occur in which each robot’s opinion is treated as independent vote, with participants significantly more likely to trust two unanimously disagreeing robots. No effect of warmth was found. The impact of these findings for human-robot team composition are discussed.

Klíčová slova:

Behavior – Games – Intelligence – Psychology – Questionnaires – Robots – Robotic behavior – Aptitude tests


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