Trusting Autonomous Teammates in Human-AI Teams - A Literature Review

要旨

As autonomous AI agents become increasingly integrated into human teams, the level of trust humans place in these agents - both as a piece of technology and increasingly viewed as teammates - significantly impacts the success of human-AI teams (HATs). This work presents a literature review of the HAT research that investigates humans' trust in their AI teammates. In this review, we first identify the ways in which trust was conceptualized and operationalized, which underscores the pressing need for clear definitions and consistent measurements. Then, we categorize and quantify the factors found to influence trust in an AI teammate, highlighting that agent-related factors (such as transparency, reliability) have the strongest impacts on trust in HAT research. We also identify under-explored factors related to humans, teams, and environments, and gaps for future HAT research and design.

著者
Wen Duan
Clemson University, Clemson, South Carolina, United States
Christopher Flathmann
Clemson University, Clemson , South Carolina, United States
Nathan McNeese
Clemson University , Clemson, South Carolina, United States
Matthew J. Scalia
Arizona State University, Mesa, Arizona, United States
Ruihao Zhang
Arizona State University, Mesa, Arizona, United States
Jamie Gorman
Arizona State University, Tempe, Arizona, United States
Guo Freeman
Clemson University, Clemson, South Carolina, United States
Shiwen Zhou
Arizona State University, Mesa, Arizona, United States
Allyson Ivy. Hauptman
Clemson University, Clemson, South Carolina, United States
Xiaoyun Yin
Arizona State University , Gilbert, Arizona, United States
DOI

10.1145/3706598.3713527

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713527

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Trust and Responsibility in AI

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7 件の発表
2025-04-30 20:10:00
2025-04-30 21:40:00
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