Human-AI Collaboration for the Detection of Deceptive Speech

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

This paper investigates human trust in artificial intelligence (AI) during human-AI collaboration on a speech-based data analytics task. Human users worked together with an explainable AI algorithm that took as an input acoustic and linguistic measures for the detection of deceptive speech. The working performance of the AI was manipulated resulting in a high performing (HP) AI and a low performing (LP) AI. Trust was measured via self-reported and behavioral measures, which were associated with each other. Various personality characteristics, including openness, neuroticism, and extroversion, moderated one's trust in the AI, but results were mixed in terms of the considered self-reported and behavioral trust metrics.

Original languageEnglish
Title of host publication2023 11th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos, ACIIW 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350327458
DOIs
StatePublished - 2023
Externally publishedYes
Event11th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos, ACIIW 2023 - Cambridge, United States
Duration: 10 Sep 202313 Sep 2023

Publication series

Name2023 11th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos, ACIIW 2023

Conference

Conference11th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos, ACIIW 2023
Country/TerritoryUnited States
CityCambridge
Period10/09/2313/09/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

  • Human-AI collaboration
  • deceptive speech
  • trust

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