Privacy and Predictive Analytics in E-Commerce

Abstract

This Article discusses the implications of predictive analytics for consumer privacy in e-commerce and surveys potential regulatory responses. Part I introduces predictive analytics and illustrates its potential uses in e-commerce. Predictive analytics helps merchants operate efficiently and maximize profits, but also risks denying consumers important commercial benefits. Part II examines how predictive analytics harms consumer privacy. The prevailing theoretical accounts define privacy as the ability to control what others know about you and recognize privacy’s role in promoting personal autonomy and dignity. Predictive analytics harms privacy as control because individuals cannot know what the data they share will ultimately predict. In addition, predictive analytics harms consumer autonomy and dignity because it deprives them of significant commercial benefits based on secret formulas, and risks automating societal discrimination. Finally, Part III examines potential regulatory responses to the harms of predictive surveillance. Any regulatory response must be measured to avoid diminishing real commercial benefits and stifling innovation. In addition, regulation must be tailored to the type and degree of privacy harm posed by the varying uses of predictive analytics.

Keywords: Privacy, Predictive Analytics, Electronic Commerce, Predictive Analytics, Algorithms, Price Discrimination, Customer Segmentation, Discrimination, Disparate Impact, Federal Trade Commission Act, Fair Housing Act, Equal Credit Opportunity Act