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  • This submission, made to the Canadian Competition Bureau's public consultation on algorithmic pricing, focuses on algorithmic personalized pricing (APP): the use of algorithms to set individualized prices based on consumers’ maximum willingness to pay. The authors argue APP represents a transformative shift in market dynamics. They analyze APP’s potential to facilitate first-degree price discrimination, and contend that the pursuit of this goal by firms, even if not fully achieved, raises significant concerns for consumer welfare, market transparency, and the normative foundations of competition law. The authors examine how well potential strategies used by firms to implement APP (collusion/coordinated competitor conduct, abuse of dominance, and deceptive marketing practices) are likely to fit within the ambit of Canada's Competition Act, particularly as recent amendments made important changes to the applicable legal frameworks. Noting that the precise ambit of the amended Act is not yet fixed, the authors argue that responding effectively to APP will require both creative interpretations of the new rules, and refined enforcement strategies and tools as competition law is adapted to a world where the incidence of algorithmic coordination and data-driven market distortions continues to increase, and with it, the erosion of consumer surplus. The submission concludes by advocating for public education, tailored enforcement guidance, and the development of consumer-side AI tools to counterbalance APP’s adverse effects on consumers and the proper functioning of competitive markets.

Last update from database: 9/4/25, 8:50 PM (UTC)

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