報告時間：2022年7月24日（星期日）9:00-10:30
報告平臺：騰訊會議 ID:709 679 995
報 告 人：張穎婕 博士
工作單位：北京大學
舉辦單位：管理學院
報告簡介：
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.
報告人簡介：
張穎婕，北京大學光華管理學院市場營銷系助理教授。于2018年在美國卡內基梅隆大學（Carnegie Mellon University）獲得博士學位（信息管理與系統）。畢業后曾就職于美國德州大學達拉斯分校（The University of Texas at Dallas）。研究集中于運用跨學科方法論（如計量模型、機器學習算法、實地實驗設計等）研究智能城市建設、共享經濟、社交媒體、消費者行為等。在管理學、交通、計算機等領域的國際公認一流學術期刊以第一作者身份發表多篇論文，包括Information Systems Research, ACM Transactions on Intelligent Systems and Technology，Transportation Research Part C等。在國際頂級會議上報告論文20余篇。屢次獲得國際頂會的最佳論文獎，并獲得信息管理領域國際最佳博士論文獎（2019 INFORMS ISS Nunamaker-Chen Dissertation Award）。
