报告时间：2022年7月24日（星期日）9:00-10:30

报告平台：腾讯会议 ID:709 679 995

报 告 人：张颖婕 博士

工作单位：北京大学

举办单位：管理学院

报告简介：

With the explosive growth of data and the rapid rise of artificial intelligence (AI) and automated working processes, humans inevitably fall into increasingly close collaboration with machines and large-scale information. It is crucial to explore how humans and machines behave in collaboration mode under different information conditions. We cooperate with a large Asian microloan company to conduct a two-stage field experiment in which we tune the treatments by level of information volume, the presence of collaboration, and the availability of machine transparency. We find that in the human-machine collaboration mode, the presence of machine interpretations, when compared with their absence, could reduce humans’ potential resistance to machines’ recommendations. More importantly, the co-existence of large-scale information and machine interpretations can invoke humans’ systematic rethinking, which in turn, shrinks gender gaps and increases prediction accuracy simultaneously.

报告人简介：

张颖婕，北京大学光华管理学院市场营销系助理教授。于2018年在美国卡内基梅隆大学（Carnegie Mellon University）获得博士学位（信息管理与系统）。毕业后曾就职于美国德州大学达拉斯分校（The University of Texas at Dallas）。研究集中于运用跨学科方法论（如计量模型、机器学习算法、实地实验设计等）研究智能城市建设、共享经济、社交媒体、消费者行为等。在管理学、交通、计算机等领域的国际公认一流学术期刊以第一作者身份发表多篇论文，包括Information Systems Research, ACM Transactions on Intelligent Systems and Technology，Transportation Research Part C等。在国际顶级会议上报告论文20余篇。屡次获得国际顶会的最佳论文奖，并获得信息管理领域国际最佳博士论文奖（2019 INFORMS ISS Nunamaker-Chen Dissertation Award）。