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Modelling Human Trust in Robots During Repeated Interactions

Muneeb Ahmad Orcid Logo, Abdullah Alzahrani, Simon Robinson Orcid Logo, Alma Rahat Orcid Logo

International Conference on Human-Agent Interaction

Swansea University Authors: Muneeb Ahmad Orcid Logo, Abdullah Alzahrani, Simon Robinson Orcid Logo, Alma Rahat Orcid Logo

DOI (Published version): 10.1145/3623809.3623892

Abstract

Modelling humans’ trust in robots is critical during human-robot interaction (HRI) to avoid under- or over-reliance on robots. Currently, it is challenging to calibrate trust in real-time. Consequently, we see limited work on calibrating humans’ trust in robots in HRI. In this paper we describe a ma...

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Published in: International Conference on Human-Agent Interaction
ISBN: 979-8-4007-0824-4
Published: New York, NY, USA ACM 2023
URI: https://cronfa.swan.ac.uk/Record/cronfa64046
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spelling v2 64046 2023-08-08 Modelling Human Trust in Robots During Repeated Interactions 9c42fd947397b1ad2bfa9107457974d5 0000-0001-8111-9967 Muneeb Ahmad Muneeb Ahmad true false d2f9f67e9bfd515f861a917fe1d00321 Abdullah Alzahrani Abdullah Alzahrani true false cb3b57a21fa4e48ec633d6ba46455e91 0000-0001-9228-006X Simon Robinson Simon Robinson true false 6206f027aca1e3a5ff6b8cd224248bc2 0000-0002-5023-1371 Alma Rahat Alma Rahat true false 2023-08-08 MACS Modelling humans’ trust in robots is critical during human-robot interaction (HRI) to avoid under- or over-reliance on robots. Currently, it is challenging to calibrate trust in real-time. Consequently, we see limited work on calibrating humans’ trust in robots in HRI. In this paper we describe a mathematical model that attempts to emulate the three-layered (initial, situational, learned) framework of trust capable of potentially estimating humans’ trust in robots in real-time. We evaluated the trust model in an experimental setup that involved participants playing a trust game on four occasions. We validate the model based on linear regression analysis that showed that the trust perception score (TPS) and interaction session predicted the trust modelled score (TMS) computed by applying the trust model. We also show that TPS and TMS did not change significantly from the second to the fourth session. However, TPS and TMS captured in the last session increased significantly from the first session. The described work is an initial effort to model three layers of humans’ trust in robot in a repeated HRI setup and requires further testing and extension to improve its robustness across settings. Conference Paper/Proceeding/Abstract International Conference on Human-Agent Interaction ACM New York, NY, USA 979-8-4007-0824-4 Trust, Measurement, Repeated Interactions, Human-Robot Interaction 4 12 2023 2023-12-04 10.1145/3623809.3623892 COLLEGE NANME Mathematics and Computer Science School COLLEGE CODE MACS Swansea University 2024-05-31T16:45:36.3811666 2023-08-08T11:22:39.3803434 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Muneeb Ahmad 0000-0001-8111-9967 1 Abdullah Alzahrani 2 Simon Robinson 0000-0001-9228-006X 3 Alma Rahat 0000-0002-5023-1371 4 64046__29283__c67bc23b6639406491dfad491eeacd60.pdf Modelling_Human_Trust_in_Robots_During_Repeated_Interactions_HAI_2023.pdf 2023-12-17T22:34:36.4713493 Output 1192593 application/pdf Accepted Manuscript true true eng
title Modelling Human Trust in Robots During Repeated Interactions
spellingShingle Modelling Human Trust in Robots During Repeated Interactions
Muneeb Ahmad
Abdullah Alzahrani
Simon Robinson
Alma Rahat
title_short Modelling Human Trust in Robots During Repeated Interactions
title_full Modelling Human Trust in Robots During Repeated Interactions
title_fullStr Modelling Human Trust in Robots During Repeated Interactions
title_full_unstemmed Modelling Human Trust in Robots During Repeated Interactions
title_sort Modelling Human Trust in Robots During Repeated Interactions
author_id_str_mv 9c42fd947397b1ad2bfa9107457974d5
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author_id_fullname_str_mv 9c42fd947397b1ad2bfa9107457974d5_***_Muneeb Ahmad
d2f9f67e9bfd515f861a917fe1d00321_***_Abdullah Alzahrani
cb3b57a21fa4e48ec633d6ba46455e91_***_Simon Robinson
6206f027aca1e3a5ff6b8cd224248bc2_***_Alma Rahat
author Muneeb Ahmad
Abdullah Alzahrani
Simon Robinson
Alma Rahat
author2 Muneeb Ahmad
Abdullah Alzahrani
Simon Robinson
Alma Rahat
format Conference Paper/Proceeding/Abstract
container_title International Conference on Human-Agent Interaction
publishDate 2023
institution Swansea University
isbn 979-8-4007-0824-4
doi_str_mv 10.1145/3623809.3623892
publisher ACM
college_str Faculty of Science and Engineering
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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
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description Modelling humans’ trust in robots is critical during human-robot interaction (HRI) to avoid under- or over-reliance on robots. Currently, it is challenging to calibrate trust in real-time. Consequently, we see limited work on calibrating humans’ trust in robots in HRI. In this paper we describe a mathematical model that attempts to emulate the three-layered (initial, situational, learned) framework of trust capable of potentially estimating humans’ trust in robots in real-time. We evaluated the trust model in an experimental setup that involved participants playing a trust game on four occasions. We validate the model based on linear regression analysis that showed that the trust perception score (TPS) and interaction session predicted the trust modelled score (TMS) computed by applying the trust model. We also show that TPS and TMS did not change significantly from the second to the fourth session. However, TPS and TMS captured in the last session increased significantly from the first session. The described work is an initial effort to model three layers of humans’ trust in robot in a repeated HRI setup and requires further testing and extension to improve its robustness across settings.
published_date 2023-12-04T16:45:34Z
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