School of Management | Released: 14:19, January 8, 2026Reporter: Zhang Ruina
Lecture Topic: Optimal Liability Design for Medical AI
Speaker: Professor Tingliang Huang, University of Tennessee
Host: Professor Ma Lijun, School of Management, Shenzhen University
Time: 10:00–12:00, Wednesday, January 14, 2026
Venue: Room B104, Mingli Building
Lecture Abstract
Artificial intelligence is being increasingly integrated into medical decision-making, bringing complex liability challenges, especially amid unobservable differences in physicians’ diagnostic capabilities. This study constructs a principal-agent model to explore medical liability design for physicians with private quality information. In the model, physicians can choose standard treatment, personalized judgment-based treatment, or adherence to imperfect AI-generated recommendations.
The research draws four key conclusions. First, a unified liability standard for all physicians who deviate from standard care can achieve first-best social outcomes under asymmetric information, especially when standard treatment is reliable or AI possesses high accuracy. Second, AI accuracy and optimal liability present a non-monotonic relationship. Improved AI performance does not always lead to lenient liability regulation; the optimal liability level either declines steadily or changes in an inverted-U trend, depending on the uncertainty of standard medical treatment. Third, information asymmetry does not always undermine social welfare. Welfare losses only occur when standard treatment is unreliable and AI accuracy is insufficient, showing an inverted-U variation. Fourth, information asymmetry acts as a double-edged sword in AI-powered medical scenarios, and improved information transparency cannot bring equal benefits to all stakeholders.
Speaker Biography
Professor Tingliang Huang currently serves as the Amazon Distinguished Professor of Business Analytics and PhD Program Recruiting Lead at the Haslam College of Business, University of Tennessee, as well as an Honorary Professor at UCL School of Management, University College London. His research focuses on business analytics and operational management, with publications in top-tier journals including Management Science, Marketing Science, Manufacturing & Service Operations Management, and Production and Operations Management.
He has received numerous prestigious academic awards, such as the 2025 Vallett Family Outstanding Researcher Award, the 2023 INFORMS Data Science Best Paper Award, and multiple POMS annual outstanding paper awards. He has also obtained six Meritorious Service Awards from Management Science and M&SOM. Additionally, Professor Huang holds associate or senior editorial positions at many authoritative international journals, making outstanding contributions to the development of operational management and decision science disciplines.
Released by: Department of E-Commerce, School of Management, Shenzhen University Written by: Lin Meiyan
Reviewed by: Ma LijunUpdated: 14:16, January 13, 2026
