Human perception is based on unconscious inference, where sensory input
integrates with prior information. This phenomenon, known as context
dependency, helps in facing the uncertainty of the external world with
predictions built upon previous experience. On the other hand, human perceptual
processes are inherently shaped by social interactions. However, how the
mechanisms of context dependency are affected is to date unknown. If using
previous experience - priors - is beneficial in individual settings, it could
represent a problem in social scenarios where other agents might not have the
same priors, causing a perceptual misalignment on the shared environment. The
present study addresses this question. We studied context dependency in an
interactive setting with a humanoid robot iCub that acted as a stimuli
demonstrator. Participants reproduced the lengths shown by the robot in two
conditions: one with iCub behaving socially and another with iCub acting as a
mechanical arm. The different behavior of the robot significantly affected the
use of prior in perception. Moreover, the social robot positively impacted
perceptual performances by enhancing accuracy and reducing participants overall
perceptual errors. Finally, the observed phenomenon has been modelled following
a Bayesian approach to deepen and explore a new concept of shared perception.Comment: 14 pages, 9 figures, 1 table. IEEE Transactions on Cognitive and
Developmental Systems, 202