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17 N.Y.U. J.L. & Bus. 1 (2020-2021)

handle is hein.journals/nyujolbu17 and id is 1 raw text is: NEW YORK UNIVERSITY JOURNAL OF LAW & BUSINESS VOLUME 17 FALL 2020 NUMBER 1 ALGORITHMIC PERSONALIZED PRICING PASCALE CHAPDELAINE* Price is an essential term at the heart of supplier-consumer transactions and relationships increasingly taking place in micro-marketplace chambers, where points of comparison with similar relevant products may be difficult to discern and time-consuming to make. This article critically reviews recent legal and economic academic literature, policy reports on algorithmic person- alized pricing (i.e. setting prices according to consumers' personal character- istics to target their willingness to pay), as well as recent developments in privacy regulation, competition law, and policy discourse, to derive the guid- ing norms that should inform the regulation of this practice, predominantly from a consumer protection perspective. Looking more closely at algorithmic personalized pricing through prevailing and conflicting norms of supplier freedom, competition, market efficiency, innovation, as well as equality, fair- ness, privacy, autonomy, and transparency, raises important concerns about certain forms of algorithmic personalized pricing. This article provides parameters to delineate when algorithmic personalized pricing should be banned as a form of unfair commercial practice. This ban would address the substantive issues that algorithmic personalized pricing raises. Resorting to mandatory disclosure requirements of algorithmic personalized pricing would address some of the concerns at a procedural level only, and for this reason is not the preferred regulatory approach. As such, our judgment on the (un)acceptability of algorithmic personalized pricing as a commercial * Associate Professor, Faculty of Law University of Windsor, (L.L.B., B.C.L., LL.M., Ph.D.). I thank Margaret Jane Radin, Anthony Duggan, Rory Van Loo, Jakob Metzger, and Maureen Irish, for their comments on earlier versions of this article, as well as the participants of the Expert Panel and Workshop E-commerce, Algorithms, Big Data, Consumer Deception and Protection (Windsor Law, February, 2019), and of the International Associ- ation of Consumer Law Conference (Indianapolis, June 2019) and of the Commercial Law Symposium (Windsor Law, October 2019). Thanks to the University of Windsor Faculty of Law for research grants making this publica- tion possible, to Shahnaz Dhanani and Andrew Gould for excellent research assistance, and to the team at NYU Journal of Law & Business for great edito- rial work. 1 Imaged with Permission of N.Y.U. Journal of Law & Business

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