A Model Regime of Privacy Protection (Version 3.0)

Abstract:     
A series of major security breaches at companies with sensitive personal information has sparked significant attention to the problems with privacy protection in the United States. Currently, the privacy protections in the United States are riddled with gaps and weak spots. Although most industrialized nations have comprehensive data protection laws, the United States has maintained a sectoral approach where certain industries are covered and others are not. In particular, emerging companies known as "commercial data brokers" have frequently slipped through the cracks of U.S. privacy law. In this article, the authors propose a Model Privacy Regime to address the problems in the privacy protection in the United States, with a particular focus on commercial data brokers. Since the United States is unlikely to shift radically from its sectoral approach to a comprehensive data protection regime, the Model Regime aims to patch up the holes in existing privacy regulation and improve and extend it. In other words, the goal of the Model Regime is to build upon the existing foundation of U.S. privacy law, not to propose an alternative foundation. The authors believe that the sectoral approach in the United States can be improved by applying the Fair Information Practices - principles that require the entities that collect personal data to extend certain rights to data subjects. The Fair Information Practices are very general principles, and they are often spoken about in a rather abstract manner. In contrast, the Model Regime demonstrates specific ways that they can be incorporated into privacy regulation in the United States.

This is the final version of this paper (Version 3.0), earlier versions of which are also available on SSRN. This version of the paper is published in the Illinois Law Review.

Keywords: privacy, databases, databrokers, ChoicePoint, identity theft, credit, legislation, regulation, information, security, data

JEL Classifications: K10, K20

Accepted Paper Series