Having The Right Attitude: How Attitude Impacts Trust Repair in Human-Robot Interaction,
dc.contributor.author | Esterwood, Connor | |
dc.contributor.author | Robert, Lionel + "Jr" | |
dc.date.accessioned | 2022-01-07T12:40:11Z | |
dc.date.available | 2022-01-07T12:40:11Z | |
dc.date.issued | 2022-01-07 | |
dc.identifier.citation | Esterwood, C. and Robert, L. P. (2022) Having The Right Attitude: How Attitude Impacts Trust Repair in Human-Robot Interaction, Proceedings of the 2022 ACM/IEEE International Conference on Human-Robot Interaction (HRI 2022). March 7-10, 2022, online | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/171268 | en |
dc.identifier.uri | https://dl.acm.org/doi/10.5555/3523760.3523806 | |
dc.description.abstract | Robot co-workers, like human co-workers, make mistakes that undermine trust. Yet, trust is just as important in promoting human–robot collaboration as it is in promoting human–human collaboration. In addition, individuals can significantly differ in their attitudes toward robots, which can also impact or hinder their trust in robots. To better understand how individual attitude can influence trust repair strategies, we propose a theoretical model that draws from the theory of cognitive dissonance. To empirically verify this model, we conducted a between-subjects experiment with 100 participants assigned to one of four repair strategies (apologies, denials, explanations, or promises) over three trust violations. Individual attitudes did moderate the efficacy of repair strategies and this effect differed over successive trust violations. Specifically, repair strategies were most effective relative to individual attitude during the second of the three trust violations, and promises were the trust repair strategy most impacted by an individual’s attitude. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | In Proceedings of the 2022 ACM/IEEE International Conference on Human-Robot Interaction, pp. 332-341 | en_US |
dc.subject | Human-Robot Interaction | en_US |
dc.subject | Trust Repair | en_US |
dc.subject | Human-Robot Trust | en_US |
dc.subject | Robot Trust | en_US |
dc.subject | Robotics | en_US |
dc.subject | Trust | en_US |
dc.subject | Human Robot Interaction | en_US |
dc.subject | Human Robot Collaboration | en_US |
dc.subject | Teaming with Robots | en_US |
dc.subject | Future of Work | en_US |
dc.subject | Human-Computer Interaction | en_US |
dc.subject | cognitive dissonance. | en_US |
dc.subject | trust repair strategies | en_US |
dc.subject | apologies | en_US |
dc.subject | denials | en_US |
dc.subject | explanations | en_US |
dc.subject | promises | en_US |
dc.subject | trust violation | en_US |
dc.subject | trust repair strategy | en_US |
dc.subject | Robotic workers | en_US |
dc.subject | TRUST REPAIR MODEL | en_US |
dc.subject | Attitude Towards Work Robots | en_US |
dc.subject | AWOR | en_US |
dc.subject | individual differences | en_US |
dc.subject | social computing | en_US |
dc.subject | AI trust | en_US |
dc.subject | artificial intelligence | en_US |
dc.subject | artificial intelligence trust | en_US |
dc.title | Having The Right Attitude: How Attitude Impacts Trust Repair in Human-Robot Interaction, | en_US |
dc.type | Conference Paper | en_US |
dc.subject.hlbsecondlevel | Information Science | |
dc.subject.hlbtoplevel | Social Sciences | |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Information, School of | en_US |
dc.contributor.affiliationum | Robotics Institute | en_US |
dc.contributor.affiliationumcampus | Ann Arbor | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/171268/1/Esterwood and Roboert 2022 HRI.pdf | |
dc.identifier.doi | https://dx.doi.org/10.7302/3781 | |
dc.identifier.doi | 10.5555/3523760.3523806 | |
dc.identifier.source | Proceedings of the 2022 ACM/IEEE International Conference on Human-Robot Interaction | en_US |
dc.identifier.orcid | 0000-0002-2685-6435 | en_US |
dc.identifier.orcid | 0000-0002-1410-2601 | en_US |
dc.description.filedescription | Description of Esterwood and Roboert 2022 HRI.pdf : Preprint | |
dc.description.depositor | SELF | en_US |
dc.identifier.name-orcid | Esterwood, Connor; 0000-0002-2685-6435 | en_US |
dc.identifier.name-orcid | Robert, Lionel P.; 0000-0002-1410-2601 | en_US |
dc.working.doi | 10.7302/3781 | en_US |
dc.owningcollname | Information, School of (SI) |
Files in this item
Remediation of Harmful Language
The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.
Accessibility
If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.