Bridging the Trust Gap: Investigating the Role of Trust Transfer in the Adoption of AI Instructors for Digital Privacy Education

要旨

Recent studies have demonstrated how AI instructors can be used for digital privacy education. However, these studies also highlights the lack of trust that certain individuals–particularly older adults–have in such AI instructors as a major obstacle to their adoption. The current paper introduces "trust transfer" as a means to enhance appropriate trust in AI instructors and improve learning experiences. A between-subjects experiment (N = 217) was conducted to test the effect of a human introducing an AI instructor on users' trust and learning experiences. Our findings reveal that this trust transfer positively impacts the perceived trustworthiness of the instructor, as well as users' perception of learning and their enjoyment of the educational material, regardless of age. Based on our findings, we discuss how trust transfer can help calibrate users' trust in AI instructors, thereby fostering AI use in digital privacy education, with potential extensions to other domains.

著者
Heba Aly
Clemson University, Clemson, South Carolina, United States
Matias Volonte
Clemson University, Charleston, South Carolina, United States
Kaileigh Angela Byrne
Clemson University, Clemson, South Carolina, United States
Bart Piet Knijnenburg
Clemson University, Clemson, South Carolina, United States
DOI

10.1145/3706598.3713570

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713570

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

G302
7 件の発表
2025-04-30 20:10:00
2025-04-30 21:40:00
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