Algorithmic Transparency with Strategic Users

67 Pages Posted: 27 Aug 2020 Last revised: 3 Dec 2021

See all articles by Qiaochu Wang

Qiaochu Wang

Carnegie Mellon University - David A. Tepper School of Business

Yan Huang

Carnegie Mellon University - David A. Tepper School of Business

Stefanus Jasin

University of Michigan, Stephen M. Ross School of Business

Param Vir Singh

Carnegie Mellon University - David A. Tepper School of Business

Date Written: July 15, 2020

Abstract

Should firms that apply machine learning algorithms in their decision making make their algorithms transparent? Despite increasing calls for algorithmic transparency, most firms have kept their algorithms opaque citing potential gaming by users that may negatively affect the algorithm’s predictive power. We introduce an analytical model to investigate the issue of algorithmic transparency in the presence of strategic users from a firm’s perspective and present novel insights. Counter-intuitively, we show that the predictive power of ML algorithms may increase if the firm were to make them transparent. We identify a broad set of conditions under which making the algorithm transparent benefits the firm in terms of higher accuracy. The results hold even when the predictive power of the opaque algorithm comes mainly from correlational features and the cost for users to improve on them is close to zero.

Keywords: Algorithmic Transparency, Game Theory, Machine Learning, Strategic Classification, Signaling Game, Information Game

JEL Classification: M30, M31, M37, M38, M21, M15

Suggested Citation

Wang, Qiaochu and Huang, Yan and Jasin, Stefanus and Singh, Param Vir, Algorithmic Transparency with Strategic Users (July 15, 2020). Available at SSRN: https://ssrn.com/abstract=3652656 or http://dx.doi.org/10.2139/ssrn.3652656

Qiaochu Wang

Carnegie Mellon University - David A. Tepper School of Business ( email )

5000 Forbes Avenue
Pittsburgh, PA 15213-3890
United States

Yan Huang (Contact Author)

Carnegie Mellon University - David A. Tepper School of Business ( email )

5000 Forbes Avenue
Pittsburgh, PA 15213-3890
United States

Stefanus Jasin

University of Michigan, Stephen M. Ross School of Business ( email )

701 Tappan Street
Ann Arbor, MI MI 48109
United States

Param Vir Singh

Carnegie Mellon University - David A. Tepper School of Business ( email )

5000 Forbes Avenue
Pittsburgh, PA 15213-3890
United States
412-268-3585 (Phone)

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