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Research and Analysis of Trust and Control in Human-AI Interaction for Decision-Making Systems in Optimizing Public Health Service

Year: 2025

Type: article

Abstract: This research investigates the interplay between trust and control in the context of AI-enabled healthcare decision-making using a cybernetic approach to how clinicians adjust their trust toward AI-powered clinical decision support systems. It seeks to uncover the barriers to AI implementation within clinical practices regarding dependency and trust towards AI technologies. Forty-two clinicians who used an AI-powered clinical decision support system in radiology participated in an empirical mixed-method study. Participants interpreted x-ray images with different levels of AI control and transparency. Trust ratings, override behaviors, and decision accuracy were captured and analyzed with t-tests, ANOVA, and regression models. Trust dynamics were explored through semi-structured interviews. The findings reveal that when the AI adheres to clinical reasoning, its transparency boosts trust, yet it diminishes confidence when an error occurs.

Source: Journal of Organizational and End User Computing

DOI: 10.4018/joeuc.388626

Authors: Xiaoxuan Yu, Yixin Chen, Qian Zhao, Hongming Li

Institutions: Northeastern University, Sheng Jing Hospital, China Medical University, University of Florida

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: diamond

OpenAlex ID: W4414200487

FWCI: 0.819

Cites: 40

Cited by: 4

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