AI Pricing: Adoption of Artificial Intelligences and Collusive Price

Jiaqi Liu

doi:10.62051/ed63gf48

Authors

Jiaqi Liu

DOI:

https://doi.org/10.62051/ed63gf48

Keywords:

Game Theory, Collusion, Regulation, Algorithm Optimization.

Abstract

With the growing integration of artificial intelligence (AI) in determining pricing strategies, there is an increasing concern about its potential to foster collusive behavior. Harrington (2012, 2018) underscores the challenge: if AI proves more adept at tacit collusion than humans or if AI-driven collusion is inherently tacit, then it presents a significant hurdle for prosecution under the prevailing interpretation of US antitrust laws. Validating these concerns, Assad et al. (2020) observed collusive price surges linked to the adoption of pricing algorithms among German gas stations. Drawing from game theory—specifically the repeated game paradigm—this paper crafts a foundational mathematical model to analyze competition versus collusion dynamics. It also evaluates the resultant welfare implications of both scenarios. The paper further delves into the broader challenges posed by AI-powered pricing and advocates for potential policy countermeasures, including algorithmic regulation and collusion detection mechanisms.

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References

Loevinger, Lee. "The Rule of Reason in Antitrust Law." Va. L. Rev. 50 (1964): 23.

Christiansen, Arndt, and Wolfgang Kerber. "Competition policy with optimally differentiated rules instead of “per se rules vs rule of reason”." Journal of Competition Law and Economics 2.2 (2006): 215-244.

Oppenheim, S. Chesterfield. "Federal Antitrust Legislation: Guideposts to a Revised National Antitrust Policy." Mich. L. Rev. 50 (1951): 1139.

Allen, Robert F. "Oligopoly, tacit collusion and the problem of proof under the antitrust laws." The Antitrust Bulletin 26.3 (1981): 487-506.

Che, Yeon‐Koo, and Jinwoo Kim. "Robustly collusion‐proof implementation." Econometrica 74.4 (2006): 1063-1107.

Laffont, Jean‐Jacques, and David Martimort. "Mechanism design with collusion and correlation." Econometrica 68.2 (2000): 309-342.

Dorner, Florian E. "Algorithmic collusion: A critical review." arXiv preprint arXiv:2110.04740 (2021).

Ezrachi, Ariel, and Maurice E. Stucke. "Artificial intelligence & collusion: When computers inhibit competition." U. Ill. L. Rev. (2017): 1775.

Ye, Peng, et al. "Customized regression model for airbnb dynamic pricing." Proceedings of the 24th ACM SIGKDD international conference on knowledge discovery & data mining. 2018.

Dafoe, Allan, et al. "Open problems in cooperative AI." arXiv preprint arXiv:2012.08630 (2020).

Dafoe, Allan, et al. "Cooperative AI: machines must learn to find common ground." Nature 593.7857 (2021): 33-36.

Chassang, S., & Ortner, J. (2022). Regulating Collusion. Annual Review of Economics, 15.