Document Type

Article

Publication Date

2024

Publication Title

McGill Law Journal

Volume

69

Issue

4

First Page

489

Last Page

513

Abstract

As much attention is turned to regulating AI systems to minimize the risk of harm, including the one caused by discriminatory biased outputs, a better understanding of how commercial practices may contravene anti-discrimination law is critical. This article investigates the instances in which algorithmic price personalization, (i.e., setting prices based on consumers’ personal information with the objective of getting as close as possible to their maximum willingness to pay (APP)), may violate anti-discrimination law. It analyses cases whereby APP could constitute prima facie discrimination, while acknowledging the difficulty to detect this commercial practice. It discusses why certain commercial practice differentiations, even on prohibited grounds, do not necessarily lead to prima facie discrimination, offering a more nuanced account of the application of anti-discrimination law to APP. However once prima facie discrimination is established, APP will not be easily exempted under a bona fide requirement, given APP’s lack of a legitimate business purpose under the stringent test of antidiscrimination law, consistent with its quasiconstitutional status. This article bridges traditional anti-discrimination law with emerging AI governance regulation. Pointing to identified gaps in antidiscrimination law, it analyses how AI governance regulation could enhance anti-discrimination law and improve compliance.

Creative Commons License

Creative Commons Attribution-No Derivative Works 4.0 International License
This work is licensed under a Creative Commons Attribution-No Derivative Works 4.0 International License.

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