Knowledge Systems Laboratory
Stanford University

Abstract: Transparent Accountable Data Mining: New Strategies for Privacy Protection

Attempts to address issues of personal privacy in a world of computerized databases and information networks -- from security technology to data protection regulation to Fourth Amendment law jurisprudence -- typically proceed from the perspective of controlling or preventing access to information. We argue that this perspective has become inadequate and obsolete, overtaken by the ease of sharing and copying data and of aggregating and searching across multiple data bases, to reveal private information from public sources. To replace this obsolete framework, we propose that issues of privacy protection currently viewed in terms of data access be re-conceptualized in terms of data use. From a technology perspective, this requires supplementing legal and technical mechanisms for access control with new mechanisms for transparency and accountability of data use. In this paper, we present a technology infrastructure -- the Policy Aware Web -- that supports transparent and accountable data use on the World Wide Web, and elements of a new legal and regulatory regime that supports privacy through provable accountability to usage rules rather than merely data access restrictions.

Daniel J. Weitzner, Hal Abelson, Tim Berners-Lee, Chris P. Hanson, Jim Hendler, Lalana Kagal, Deborah L. McGuinness, Gerald J. Sussman, K. Krasnow Waterman. Transparent Accountable Data Mining: New Strategies for Privacy Protection Proceedings of AAAI Spring Symposium on The Semantic Web meets eGovernment. AAAI Press, Stanford University, Stanford, CA., USA, March, 2006. Also available as MIT CSAIL Technical Report-2006-007 and Stanford KSL Technical Report KSL-06-03.

The pdf version is available.

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