Sensitivity of Trust Scales in the Face of Errors

Birthe Nesset, Gnanathusharan Rajendran, Jose David Águas Lopes, Helen Hastie

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)
58 Downloads (Pure)

Abstract

Trust between humans and robots is a complex, multifaceted phenomenon and measuring it subjectively and reliably is challenging. It is also context dependent and so choosing the right tool for a specific study can prove difficult. This paper aims to evaluate various trust measures and compare them in terms of sensitivity to changes in trust. This is done by comparing two validated trust questionnaires (TAS and MDMT) and one single item assessment in a COVID-19 triage scenario. We found that trust measures are equivalent in terms of sensitivity to changes in trust. Furthermore, the study showed that trust could be measured similarly through a single item assessment in comparison with other lengthier scales, in scenarios with distinct breaks in trust. This finding would be of use for experiments where lengthy questionnaires are not appropriate, such as those in the wild.
Original languageEnglish
Title of host publication17th ACM/IEEE International Conference on Human-Robot Interaction (HRI)
PublisherIEEE
Pages950-954
Number of pages5
ISBN (Electronic)9781665407311
DOIs
Publication statusPublished - 29 Sept 2022
Event17th Annual ACM/IEEE International Conference on Human-Robot Interaction 2022 - Online, Sapporo, Japan
Duration: 7 Mar 202210 Mar 2022
https://humanrobotinteraction.org/2022/

Conference

Conference17th Annual ACM/IEEE International Conference on Human-Robot Interaction 2022
Abbreviated titleHRI 2022
Country/TerritoryJapan
CitySapporo
Period7/03/2210/03/22
Internet address

Keywords

  • HRI
  • error
  • measure
  • single item assessment
  • trust

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Electrical and Electronic Engineering

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