Implications of AI Involvement for Trust in Expert Advisory Workflows Under Epistemic Dependence

Fuente: arXiv
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Autores principales: Kim, Dennis, Daneshi, Roya, Draper, Bruce, Sreedharan, Sarath
Formato: Preprint
Publicado: 2026
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author Kim, Dennis
Daneshi, Roya
Draper, Bruce
Sreedharan, Sarath
author_facet Kim, Dennis
Daneshi, Roya
Draper, Bruce
Sreedharan, Sarath
contents The increasing integration of AI-powered tools into expert workflows, such as medicine, law, and finance, raises a critical question: how does AI involvement influence a user's trust in the human expert, the AI system, and their combination? To investigate this, we conducted a user study (N=77) featuring a simulated course-planning task. We compared various conditions that differed in both the presence of AI and the specific mode of human-AI collaboration. Our results indicate that while the advisor's ability to create a correct schedule is important, the user's perception of expertise and trust is also influenced by how the expert utilized the AI assistant. These findings raise important considerations for the design of human-AI hybrid teams, particularly when the adoption of recommendations depends on the end-user's perception of the recommender's expertise.
format Preprint
id arxiv_https___arxiv_org_abs_2602_11522
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publishDate 2026
record_format arxiv
spellingShingle Implications of AI Involvement for Trust in Expert Advisory Workflows Under Epistemic Dependence
Kim, Dennis
Daneshi, Roya
Draper, Bruce
Sreedharan, Sarath
Human-Computer Interaction
The increasing integration of AI-powered tools into expert workflows, such as medicine, law, and finance, raises a critical question: how does AI involvement influence a user's trust in the human expert, the AI system, and their combination? To investigate this, we conducted a user study (N=77) featuring a simulated course-planning task. We compared various conditions that differed in both the presence of AI and the specific mode of human-AI collaboration. Our results indicate that while the advisor's ability to create a correct schedule is important, the user's perception of expertise and trust is also influenced by how the expert utilized the AI assistant. These findings raise important considerations for the design of human-AI hybrid teams, particularly when the adoption of recommendations depends on the end-user's perception of the recommender's expertise.
title Implications of AI Involvement for Trust in Expert Advisory Workflows Under Epistemic Dependence
topic Human-Computer Interaction
url https://arxiv.org/abs/2602.11522