Law Commons^™

A Rule Of Persons, Not Machines: The Limits Of Legal Automation, Frank A. Pasquale

Faculty Scholarship

No abstract provided.

Addressing The Harm Of Total Surveillance: A Reply To Professor Neil Richards, Danielle Keats Citron, David C. Gray

Faculty Scholarship

In his insightful article The Dangers of Surveillance, 126 HARV. L. REV. 1934 (2013), Neil Richards offers a framework for evaluating the implications of government surveillance programs that is centered on protecting "intellectual privacy." Although we share his interest in recognizing and protecting privacy as a condition of personal and intellectual development, we worry in this essay that, as an organizing principle for policy, "intellectual privacy" is too narrow and politically fraught. Drawing on other work, we therefore recommend that judges, legislators, and executives focus instead on limiting the potential of surveillance technologies to effect programs of broad and indiscriminate …

William H. Sorrell, Attorney General Of Vermont, Et Al. V. Ims Health Inc., Et Al. - Amicus Brief In Support Of Petitioners, Kevin Outterson, David Orentlicher, Christopher T. Robertson, Frank A. Pasquale

Faculty Scholarship

On April 26, 2011, the US Supreme Court will hear oral arguments in the Vermont data mining case, Sorrell v. IMS Health Inc. Respondents claim this is the most important commercial speech case in a decade. Petitioner (the State of Vermont) argues this is the most important medical privacy case since Whalen v. Roe.

The is an amicus brief supporting Vermont, written by law professors and submitted on behalf of the New England Journal of Medicine

Tolls On The Information Superhighway: Entitlement Defaults For Clickstream Data, Lee B. Kovarsky

Faculty Scholarship

This paper addresses the collection of "clickstream data," and sets forth a theory about the legal rules that should govern it. At the outset, I propose a typology for categorizing privacy invasions. A given state of informational privacy may be represented by: the observed behavior, the collecting agent, and the searching agent. Using this typology, I identify the specific sources of concern about collection of clickstream data. Then, based on expected levels of utility and expected transaction costs of "flipping" to a different rule, I argue for a particular set of privacy defaults for data mining.