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Abstract: This Article is divided into five parts.
In Part II, we summarize the development of concepts of privacy and confidentiality, and examine how legal and statistical communities have reacted to two major changes in the privacy landscape of the last twenty years. In Part III, we provide a basic framework for enacting future privacy legislation to govern federal statistical agencies. We argue that federal agencies, and the laws that govern their conduct, should be framed with three broad principles in mind: (i) a commitment to bureaucratic justice; (ii) a level of regulatory coherence that justifies choices made; and (iii) a flexibility that allows anticipation of, rather than merely post hoc response to, challenges posed by future technology and methods. In Part IV, we set out various statistical methods that have been, and could be, employed to protect the confidentiality of data released to the public or government agencies. In describing these options, we discuss the limitations inherent in each and note the law's continuing role in enforcing these measures. Finally, in Part V, we conclude that increased dialogue between our disciplines can, and should, result in a better privacy regime that combines sound statistical methods designed to protect anonymity where appropriate, with legal enactments that promote legitimate sharing yet punish abuses. In so doing, we provide some specific approaches for legislating privacy that account for the trust needed to make statistical programs successful and for the data access and disclosure so important for the challenges currently facing this country.
Privacy, Census, Trust,
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