[Mingli Lecture Hall, 2021, 18th] Assistant Professor Huang Yan, Carnegie Mellon University: Algorithmic Transparency with Strategic Users
Time: April 9 (Friday) 9:00-10:30 am
Tencent Conference Number: 342 825 772
Brief introduction of report content:
Should firms that use machine learning algorithms for decision-making make their algorithms transparent? Despite growing calls for algorithmic transparency, most firms have kept their algorithms opaque, citing potential gaming by users that may negatively affect the algorithms' predictive power. We develop an analytical model to compare firm and user surplus with and without algorithmic transparency in the presence of strategic users and present novel insights. We identify a broad set of conditions under which making the algorithm transparent benefits the firm. We show that, in some cases, even the predictive power of the algorithm may increase if the firm makes the algorithm transparent. By contrast, users may not always be better off under algorithmic transparency. The results hold even when the predictive power of the opaque algorithm comes largely from correlational features and the cost for users to improve on them is close to zero. Overall, our results show that firms should not view manipulation by users as bad. Rather, they should use algorithmic transparency as a lever to motivate users to invest in more desirable features.
Brief introduction of the speaker:
Dr. Huang Yan is an assistant professor at Carnegie Mellon University’s Tepper School of Business. Research interests lie in the use of quantitative methods to study the economic and social impact of technologies, especially artificial intelligence, machine learning, and crowd-based technologies, and the mechanisms behind them. Based on these understandings, propose strategies and policies to promote production and rational use of technology, and determine the effective design of technical support platforms and applications. Dr. Huang Yan received his bachelor's degree from Tsinghua University and his Ph.D. from Carnegie Mellon University.
(Contractor: Department of Management Engineering, Scientific Research and Academic Exchange Center)
