Open this publication in new window or tab >>2017 (English)In: Frontiers in Psychology, E-ISSN 1664-1078, Vol. 8, article id 1962Article in journal (Refereed) Published
Abstract [en]
People rely on shared folk-psychological theories when judging behavior. These theories guide peoples social interactions and therefore need to be taken into consideration in the design of robots and other autonomous systems expected to interact socially with people. It is, however, not yet clear to what degree the mechanisms that underlie peoples judgments of robot behavior overlap or differ from the case of human or animal behavior. To explore this issue, participants (N = 90) were exposed to images and verbal descriptions of eight different behaviors exhibited either by a person or a humanoid robot. Participants were asked to rate the intentionality, controllability and desirability of the behaviors, and to judge the plausibility of seven different types of explanations derived from a recently proposed psychological model of lay causal explanation of human behavior. Results indicate: substantially similar judgments of human and robot behavior, both in terms of (1a) ascriptions of intentionality/controllability/desirability and in terms of (1b) plausibility judgments of behavior explanations; (2a) high level of agreement in judgments of robot behavior -(2b) slightly lower but still largely similar to agreement over human behaviors; (3) systematic differences in judgments concerning the plausibility of goals and dispositions as explanations of human vs. humanoid behavior. Taken together, these results suggest that peoples intentional stance toward the robot was in this case very similar to their stance toward the human.
Place, publisher, year, edition, pages
FRONTIERS MEDIA SA, 2017
Keywords
human-robot interaction; folk psychology; social interaction; intentional stance; attribution theory; intentionality ascription; behavior explanation; social robots
National Category
Social Psychology
Identifiers
urn:nbn:se:liu:diva-143236 (URN)10.3389/fpsyg.2017.01962 (DOI)000415036700001 ()
Note
Funding Agencies|ELLIIT (Excellence Center at Linkoping-Lund in Information Technology); Knowledge Foundation, Stockholm, under SIDUS grant [20140220]
2017-11-272017-11-272022-02-10