Fostering appropriate reliance on large language models: The role of explanations, sources, and inconsistencies

Authors: SSY Kim, JW Vaughan, QV Liao, T Lombrozo

Published: 2025

Publication: Proceedings of the ..., 2025 - dl.acm.org

The study examines factors that influence users' reliance on LLM responses, finding explanations increase reliance, while sources and inconsistent explanations reduce reliance on incorrect responses.

Methods: Think-aloud study followed by a pre-registered, controlled experiment to assess the impact of explanations, sources, and inconsistencies in LLM responses on user reliance.

Key Findings: Users' reliance on LLM responses, accuracy, and the influence of explanations, inconsistencies, and sources on these measures.

Institution: Wake Forest University, University of Illinois at Urbana-Champaign, Princeton University, University of California Berkeley

Research Area: Appropriate Reliance on LLMs, Explainable AI, Human-AI Interaction,Cognitive Psychology

Discipline: Cognitive Psychology, Artificial Intelligence, Human-Computer Interaction (HCI)

Sample Size: 308 participants

Citations: 38

DOI: https://doi.org/10.1145/3706598.3714020