  Taking advice from others requires confidence in their competence. This is
important for interaction with peers, but also for collaboration with social
robots and artificial agents. Nonetheless, we do not always have access to
information about others' competence or performance. In these uncertain
environments, do our prior beliefs about the nature and the competence of our
interacting partners modulate our willingness to rely on their judgments? In a
joint perceptual decision making task, participants made perceptual judgments
and observed the simulated estimates of either a human participant, a social
humanoid robot or a computer. Then they could modify their estimates based on
this feedback. Results show participants' belief about the nature of their
partner biased their compliance with its judgments: participants were more
influenced by the social robot than human and computer partners. This
difference emerged strongly at the very beginning of the task and decreased
with repeated exposure to empirical feedback on the partner's responses,
disclosing the role of prior beliefs in social influence under uncertainty.
Furthermore, the results of our functional task suggest an important difference
between human-human and human-robot interaction in the absence of overt
socially relevant signal from the partner: the former is modulated by social
normative mechanisms, whereas the latter is guided by purely informational
mechanisms linked to the perceived competence of the partner.
