Literature DB >> 32096445

Factors that affect younger and older adults' causal attributions of robot behavior.

Richard Pak1, Jessica J Crumley-Branyon1, Ewart J de Visser2, Ericka Rovira3.   

Abstract

Stereotypes are cognitive shortcuts that facilitate efficient social judgments about others. Just as causal attributions affect perceptions of people, they may similarly affect perceptions of technology, particularly anthropomorphic technology such as robots. In a scenario-based study, younger and older adults judged the performance and capability of an anthropomorphized robot that appeared young or old. In some cases, the robot successfully performed a task while at other times it failed. Results showed that older adult participants were more susceptible to aging stereotypes as indicated by trust. In addition, both younger and older adult participants succumbed to aging stereotypes when measuring perceived capability of the robots. Finally, a summary of causal reasoning results showed that our participants may have applied aging stereotypes to older-appearing robots: they were most likely to give credit to a properly functioning robot when it appeared young and performed a cognitive task. Our results tentatively suggest that human theories of social cognition do not wholly translate to technology-based contexts and that future work may elaborate on these findings.Practitioner summary: Perception and expectations of the capabilities of robots may influence whether users accept and use them, especially older users. The current results suggest that care must be taken in the design of these robots as users may stereotype them.

Entities:  

Keywords:  aging; anthropomorphism; causal reasoning; human-robot interaction; stereotype

Year:  2020        PMID: 32096445     DOI: 10.1080/00140139.2020.1734242

Source DB:  PubMed          Journal:  Ergonomics        ISSN: 0014-0139            Impact factor:   2.778


  1 in total

1.  Does the Correspondence Bias Apply to Social Robots?: Dispositional and Situational Attributions of Human Versus Robot Behavior.

Authors:  Autumn Edwards; Chad Edwards
Journal:  Front Robot AI       Date:  2022-01-04
  1 in total

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