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A Meta-analysis of Vulnerability and Trust in Human-Robot Interaction

Peter E. McKenna Orcid Logo, Muneeb Ahmad Orcid Logo, Tafadzwa Maisva Orcid Logo, Birthe Nesset Orcid Logo, Katrin Lohan Orcid Logo, Helen Hastie Orcid Logo

ACM Transactions on Human-Robot Interaction, Volume: 13, Issue: 3, Pages: 1 - 25

Swansea University Author: Muneeb Ahmad Orcid Logo

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DOI (Published version): 10.1145/3658897

Abstract

In human-robot interaction studies, trust is often defined as a process whereby a trustor makes themselves \emph{vulnerable} to a trustee. The role of vulnerability however is often overlooked in this process but could play an important role in the gaining and maintenance of trust between users and...

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Published in: ACM Transactions on Human-Robot Interaction
ISSN: 2573-9522
Published: Association for Computing Machinery (ACM) 2024
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URI: https://cronfa.swan.ac.uk/Record/cronfa65907
first_indexed 2024-03-26T12:02:19Z
last_indexed 2024-11-25T14:17:06Z
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spelling 2024-11-08T11:32:52.2131284 v2 65907 2024-03-26 A Meta-analysis of Vulnerability and Trust in Human-Robot Interaction 9c42fd947397b1ad2bfa9107457974d5 0000-0001-8111-9967 Muneeb Ahmad Muneeb Ahmad true false 2024-03-26 MACS In human-robot interaction studies, trust is often defined as a process whereby a trustor makes themselves \emph{vulnerable} to a trustee. The role of vulnerability however is often overlooked in this process but could play an important role in the gaining and maintenance of trust between users and robots. To better understand how vulnerability affects human-robot trust, we first reviewed the literature to create a conceptual model of vulnerability with four vulnerability categories. We then performed a meta-analysis, first to check the overall contribution of the variables included on trust. The results showed that overall, the variables investigated in our sample of studies have a positive impact on trust. We then conducted two multilevel moderator analysis to assess the effect of vulnerability on trust, including: 1) An intercept model that considers the relationship between our vulnerability categories; and 2) A non-intercept model that treats each vulnerability category as an independent predictor. Only model 2 was significant, suggesting that to build trust effectively, research should focus on improving robot performance in situations where the users is unsure how reliable the robot will be. As our vulnerability variable is derived from studies of human-robot interaction and human-human studies of risk, we relate our findings to these domains and make suggestions for future research avenues. Journal Article ACM Transactions on Human-Robot Interaction 13 3 1 25 Association for Computing Machinery (ACM) 2573-9522 vulnerability, trust, risk, human-robot interaction 13 8 2024 2024-08-13 10.1145/3658897 COLLEGE NANME Mathematics and Computer Science School COLLEGE CODE MACS Swansea University Another institution paid the OA fee UKRI, EPSRC (EP/V026682/1, EP/R026173/1) 2024-11-08T11:32:52.2131284 2024-03-26T11:56:07.3076421 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Peter E. McKenna 0000-0002-8339-3086 1 Muneeb Ahmad 0000-0001-8111-9967 2 Tafadzwa Maisva 0009-0001-5364-0859 3 Birthe Nesset 0000-0002-5835-4413 4 Katrin Lohan 0000-0001-9843-316x 5 Helen Hastie 0000-0002-9177-7282 6 65907__32897__b3bd86b8096047bd82629667c395a13e.pdf 65907.VOR.pdf 2024-11-08T11:27:57.6849513 Output 3442570 application/pdf Version of Record true © 2024 Copyright held by the owner/author(s). This work is licensed under a Creative Commons Attribution International 4.0 License. true eng https://creativecommons.org/licenses/by/4.0/
title A Meta-analysis of Vulnerability and Trust in Human-Robot Interaction
spellingShingle A Meta-analysis of Vulnerability and Trust in Human-Robot Interaction
Muneeb Ahmad
title_short A Meta-analysis of Vulnerability and Trust in Human-Robot Interaction
title_full A Meta-analysis of Vulnerability and Trust in Human-Robot Interaction
title_fullStr A Meta-analysis of Vulnerability and Trust in Human-Robot Interaction
title_full_unstemmed A Meta-analysis of Vulnerability and Trust in Human-Robot Interaction
title_sort A Meta-analysis of Vulnerability and Trust in Human-Robot Interaction
author_id_str_mv 9c42fd947397b1ad2bfa9107457974d5
author_id_fullname_str_mv 9c42fd947397b1ad2bfa9107457974d5_***_Muneeb Ahmad
author Muneeb Ahmad
author2 Peter E. McKenna
Muneeb Ahmad
Tafadzwa Maisva
Birthe Nesset
Katrin Lohan
Helen Hastie
format Journal article
container_title ACM Transactions on Human-Robot Interaction
container_volume 13
container_issue 3
container_start_page 1
publishDate 2024
institution Swansea University
issn 2573-9522
doi_str_mv 10.1145/3658897
publisher Association for Computing Machinery (ACM)
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
document_store_str 0
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description In human-robot interaction studies, trust is often defined as a process whereby a trustor makes themselves \emph{vulnerable} to a trustee. The role of vulnerability however is often overlooked in this process but could play an important role in the gaining and maintenance of trust between users and robots. To better understand how vulnerability affects human-robot trust, we first reviewed the literature to create a conceptual model of vulnerability with four vulnerability categories. We then performed a meta-analysis, first to check the overall contribution of the variables included on trust. The results showed that overall, the variables investigated in our sample of studies have a positive impact on trust. We then conducted two multilevel moderator analysis to assess the effect of vulnerability on trust, including: 1) An intercept model that considers the relationship between our vulnerability categories; and 2) A non-intercept model that treats each vulnerability category as an independent predictor. Only model 2 was significant, suggesting that to build trust effectively, research should focus on improving robot performance in situations where the users is unsure how reliable the robot will be. As our vulnerability variable is derived from studies of human-robot interaction and human-human studies of risk, we relate our findings to these domains and make suggestions for future research avenues.
published_date 2024-08-13T20:29:20Z
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score 11.04748

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