講座題目：A Field Experiment on AI-Assisted Physicians
主講嘉賓：譚寅亮
時 間：2023年3月10日（星期五）上午9：30—11：30
騰訊會議：870-678-174 ，點擊鍊接入會，或添加至會議列表：
https://meeting.tencent.com/dm/UF4BgPiDWejI
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江南大學商學院
2023年3月6日
主講嘉賓簡介
譚寅亮博士是美國休斯頓大學鮑爾商學院決策和信息科學終身教授，鮑爾講席教授，以及供應鍊管理方向系主任。他同時還擔任慧與科技數據科學研究中心 資深研究員。此前他在美國杜蘭大學弗裡曼商學院管理科學方向擔任助理教授，副教授，戈德林國際教育中心行政主任，并獲得終身教授與講席教授職位。譚寅亮博士畢業于美國佛羅裡達大學沃靈頓商學院，學習運營管理及信息系統。他擁有豐富的商業分析方面的教學經驗，獲得過弗裡曼商學院年度最佳教師獎。其研究興趣主要集中在數字經濟，人工智能，以及科技管理與創新等領域。他在國際頂級期刊Management Science, MIS Quarterly, Information Systems Research, Production and Operations Management， Decision Science 等多次發表論文，并獲得過國際決策科學年會的最佳論文獎。譚博士現在擔任Production and Operations Management（國際頂級期刊）的資深編輯, Decision Sciences Journal的部門編輯, 以及Information & Management的副編輯。他于2019年被評為世界最佳40名40歲以下的商學院教授, 同年他獲得了國際決策科學學會頒發的早期職業成就獎。他于2022年獲得INFORMS 信息系統學會頒發的Sandy Slaughter早期職業成就獎以表彰他對信息系統領域做出的貢獻。
講座主要内容
AI assistants—software agents that can perform tasks or services for individuals—are among the most promising AI applications. However, little is known about the adoption of AI assistants by service providers (i.e., physicians) in a real-world healthcare setting. Specifically, we investigate the impact of AI smartness—whether the AI assistant is empowered by machine learning intelligence—and AI transparency—whether physicians are informed of the assistant feature. We collaborate with a leading healthcare platform to run a field experiment in which we compare physicians’ adoption behavior, i.e., adoption rate and adoption timing, of smart and automated AI assistants under transparent and non-transparent conditions. We find that AI smartness can increase the adoption rate and shorten the adoption timing, while AI transparency can only shorten the adoption timing. Moreover, the impact of transparency on the adoption rate is contingent on the smartness level of the assistant: AI transparency increases the adoption rate only when the AI assistant is not equipped with smart algorithms and fails to do so when the assistant is smart. Our study can guide platforms in designing their AI strategies. In particular, platforms should develop and apply smart AI algorithms in aiding physicians, and also keep physicians informed on such development and application, especially when the smartness level of the algorithms is low.
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