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dc.contributor.authorRossi, Alessandra
dc.contributor.authorDautenhahn, Kerstin
dc.contributor.authorKoay, Kheng
dc.contributor.authorWalters, Michael
dc.contributor.authorHolthaus, Patrick
dc.contributor.editorWagner, Alan R.
dc.contributor.editorFeil-Seifer, David
dc.contributor.editorHaring, Kerstin S.
dc.contributor.editorRossi, Silvia
dc.contributor.editorWilliams, Thomas
dc.contributor.editorHe, Hongsheng
dc.contributor.editorSam Ge, Shuzhi
dc.date.accessioned2021-01-28T00:12:31Z
dc.date.available2021-01-28T00:12:31Z
dc.date.issued2020-11-06
dc.identifier.citationRossi , A , Dautenhahn , K , Koay , K , Walters , M & Holthaus , P 2020 , Evaluating people's perceptions of trust in a robot in a repeated interactions study . in A R Wagner , D Feil-Seifer , K S Haring , S Rossi , T Williams , H He & S Sam Ge (eds) , Social Robotics - 12th International Conference, ICSR 2020, Proceedings : ICSR 2020 . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) , vol. 12483 LNAI , pp. 453-465 . https://doi.org/10.1007/978-3-030-62056-1_38
dc.identifier.isbn978-3-030-62055-4
dc.identifier.isbn978-3-030-62056-1
dc.identifier.issn0302-9743
dc.identifier.otherORCID: /0000-0001-8450-9362/work/87789613
dc.identifier.otherORCID: /0000-0002-0047-1377/work/87789446
dc.identifier.urihttp://hdl.handle.net/2299/23789
dc.descriptionFunding Information: Acknowledgment. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 642667 (Safety Enables Cooperation in Uncertain Robotic Environments - SECURE). KD acknowledges funding from the Canada 150 Research Chairs Program. Publisher Copyright: © 2020, Springer Nature Switzerland AG This is a post-peer-review, pre-copyedit version of an article published of 'Rossi A., Dautenhahn K., Koay K.L., Walters M.L., Holthaus P. (2020) Evaluating People’s Perceptions of Trust in a Robot in a Repeated Interactions Study. In: Wagner A.R. et al. (eds) Social Robotics. ICSR 2020. Lecture Notes in Computer Science, vol 12483. Springer, Cham. https://doi.org/10.1007/978-3-030-62056-1_38'
dc.description.abstractTrust has been established to be a key factor in fostering human-robot interactions. However, trust can change overtime according to different factors, including a breach of trust due to a robot’s error. In this exploratory study, we observed people’s interactions with a companion robot in a real house, adapted for human-robot interaction experimentation, over three weeks. The interactions happened in six scenarios in which a robot performed different tasks under two different conditions. Each condition included fourteen tasks performed by the robot, either correctly, or with errors with severe consequences on the first or last day of interaction. At the end of each experimental condition, participants were presented with an emergency scenario to evaluate their trust in the robot. We evaluated participants’ trust in the robot by observing their decision to trust the robot during the emergency scenario, and by collecting their views through questionnaires. We concluded that there is a correlation between the timing of an error with severe consequences performed by the robot and the corresponding loss of trust of the human in the robot. In particular, people’s trust is subjected to the initial mental formation.en
dc.format.extent13
dc.format.extent518323
dc.language.isoeng
dc.relation.ispartofSocial Robotics - 12th International Conference, ICSR 2020, Proceedings
dc.relation.ispartofseriesLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.subjectHuman-robot interaction
dc.subjectLong-term interaction
dc.subjectSocial robots
dc.subjectTrust
dc.subjectTheoretical Computer Science
dc.subjectComputer Science(all)
dc.titleEvaluating people's perceptions of trust in a robot in a repeated interactions studyen
dc.contributor.institutionSchool of Physics, Engineering & Computer Science
dc.contributor.institutionDepartment of Computer Science
dc.contributor.institutionCentre for Computer Science and Informatics Research
dc.contributor.institutionAdaptive Systems
dc.contributor.institutionECS Computer Science VLs
dc.date.embargoedUntil2021-11-06
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85097202293&partnerID=8YFLogxK
rioxxterms.versionofrecord10.1007/978-3-030-62056-1_38
rioxxterms.typeOther
herts.preservation.rarelyaccessedtrue


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