Ebrahim on Algorithms in Business, Merchant-Consumer Interactions, & Regulation

Tabrez Ebrahim (California Western School of Law) has posted “Algorithms in Business, Merchant-Consumer Interactions, & Regulation” (West Virginia Law Review, Vol. 123, 2021) on SSRN. Here is the abstract:

The shift towards the use of algorithms in business has transformed merchant–consumer interactions. Products and services are increasingly tailored for consumers through algorithms that collect and analyze vast amounts of data from interconnected devices, digital platforms, and social networks. While traditionally merchants and marketeers have utilized market segmentation, customer demographic profiles, and statistical approaches, the exponential increase in consumer data and computing power enables them to develop and implement algorithmic techniques that change consumer markets and society as a whole. Algorithms enable targeting of consumers more effectively, in real-time, and with high predictive accuracy in pricing and profiling strategies. In so doing, algorithms raise new theoretical considerations on information asymmetry and power imbalances in merchant–consumer interactions and multiply existing biases and discrimination or create new ones in society. Against this backdrop of the concentration of algorithmic decision-making in merchants, the traditional understanding of consumer protection is overdue for change, and normative debate about fairness, accountability, and transparency and interpretive considerations for non-discrimination is necessary. The theory that notice and choice in data protection laws and consumer protection laws are sufficient in an algorithmic era is inadequate, and countervailing consumer empowerment is necessary to balance the power between merchants and consumers. While legislative activity and regulation have conceivably increased consumer-empowerment, such measures may provide a limited or unclear response in the face of the transformative nature of algorithms. Instead, policy makers should consider responsible algorithmic code and other proposals as potentially effective responses in the analysis of socio-economic dimensions of algorithms in business.