题　目：Auditing and Overriding Black-Box Actions from Censored Feedback

嘉　宾：王世欣（Shixin Wang），助理教授，佐治亚理工学院

主持人：何斯迈，教授，上海交通大学安泰经济与管理学院

时　间：2026年10月20日（周二）14:00-15:30

地　点：上海交通大学徐汇校区安泰浩然楼308室

内容简介:

As organizations increasingly delegate decisions to algorithms and AI systems, managers face a fundamental question: When should they trust existing recommendations, and when is there sufficient evidence to justify an override? This question is challenging because the system's underlying information is often inaccessible, while observed outcomes are censored by the actions taken. Rather than learning the hidden information structure or optimizing a new policy, we develop a framework for auditing whether existing recommendations can be rationalized by the available evidence. We establish a sharp alternative: either the recommendations are consistent with optimal behavior under some information structure, or there exists a correction that improves performance under every explanation consistent with the data. We derive simple, exact auditing conditions and constructive corrections for pricing, inventory, and treatment decisions. Our results reveal when individual recommendations must be audited jointly and when local checks suffice. The framework provides a principled approach to deciding when to defend existing algorithmic guidance and when to intervene, without reconstructing or replacing the underlying system.

演讲人简介：

Shixin Wang is an Assistant Professor in the H. Milton Stewart School of Industrial and Systems Engineering (ISyE) at Georgia Institute of Technology. Prior to joining Georgia Tech, she was an Assistant Professor in the Department of Decisions, Operations and Technology at The Chinese University of Hong Kong (CUHK) Business School from 2021 to 2025. Her research interests lie in developing simple and robust pricing policies in revenue management, and designing sparse and reliable networks in supply chain and service systems. She obtained her Ph.D. degree from New York University Stern School of Business (2021), and her Bachelor degree in Industrial Engineering from Tsinghua University (2015).

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