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

TL;DR

This study examines how AI involvement in expert workflows affects user trust in humans, AI, and their collaboration, highlighting the importance of perceived expertise and collaboration mode in trust formation.

Contribution

It provides empirical insights into trust dynamics in human-AI collaboration, emphasizing the role of perceived expertise and AI utilization in trust development.

Findings

User trust is influenced by AI's correctness and perceived expertise.

The mode of human-AI collaboration affects trust levels.

Perception of expertise impacts adoption of AI recommendations.

Abstract

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.