Human-AI Collaboration for the Detection of Deceptive Speech

被引：1
|
作者：
Tutul, Adullah Aman [1 ]
Chaspari, Theodora [1 ]
Levitan, Sarah Ita [2 ]
Hirschberg, Julia [3 ]
机构：
[1] Texas A&M Univ, College Stn, TX 77843 USA
[2] CUNY Hunter Coll, New York, NY 10021 USA
[3] Columbia Univ, New York, NY USA
来源：
2023 11TH INTERNATIONAL CONFERENCE ON AFFECTIVE COMPUTING AND INTELLIGENT INTERACTION WORKSHOPS AND DEMOS, ACIIW | 2023年
关键词：
Human-AI collaboration; trust; deceptive speech; TRUST; AUTOMATION; CUES;
D O I：
10.1109/ACIIW59127.2023.10388114
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
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页数：4
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