Government Data Mining and the Fourth Amendment
The author would like to thank participants in workshops at Stanford Law School and Florida Law School for their feedback on the content of this article, and Victoria Ianni for her research assistance. This paper is a version of a talk given at The University of Chicago Law School’s Surveillance Symposium, June 15–16, 2007.
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The government’s ability to obtain and analyze recorded information about its citizens through the process known as data mining has expanded enormously over the past decade. Since at least the mid1990s, the quantity of the world’s recorded data has doubled every year. At the same time, the computing power necessary to store, access, and analyze these data has increased geometrically, at increasingly cheaper cost. Governments that want to know about their subjects would be foolish not to take advantage of this situation, and federal and state bodies in this country have done so with alacrity.
Special thanks to Mario Barnes, Courtney Douglas, Paul Gowder, Deborah Turkheimer, to the audience at Northwestern Law’s Julian Rosenthal Lecture, and to Miranda Coombe, Sam Hallam, Caroline Kassir, and Danielle O’Connell for superb editing. Adeleine Lee and Alex Wilfert provided excellent research assistance. The authors contributed equally to this essay.
Antidemocratic forces rely on intimidation tactics to silence criticism and opposition. Today’s intimidation playbook follows a two-step pattern. We surface these tactics so their costs to public discourse and civic engagement can be fully understood. We show how the misappropriation of the concept of online abuse has parallels in other efforts at conceptual diversion that dampen democratic guarantees. Democracy’s survival requires creative solutions. Politicians and government workers must be able to operate free from intimidation. Journalists and researchers must be able to freely investigate governmental overreach and foreign malign influence campaigns that threaten the democratic process. Surfacing the two-step strategy is a critical start to combating it.
I would like to thank Jack Brake, Anne Marie Hawley, and Jonah Klausner for their thoughtful edits and Jake Holland for his indispensable advice all throughout the drafting process.
Illinois’s Biometric Information Privacy Act (BIPA) is the country’s most powerful law governing biometric data—data generated from an individual’s biological characteristics, like fingerprints and voiceprints. Over the past decade, BIPA garnered a reputation as an exceptionally plaintiff-friendly statute. But from 2023–2024, the Illinois legislature, Illinois Supreme Court, and Ninth Circuit Court of Appeals all sided with BIPA defendants for the first time. Most significantly, in Zellmer v. Meta Platforms, Inc., the Ninth Circuit dismissed the plaintiff’s BIPA claim because the face scan collected by the defendant could not be used to identify him.
It is unclear whether these developments represent a trend or an exception to BIPA’s plaintiff-friendliness. Which path is charted will largely turn on how courts interpret Zellmer: While Zellmer established that a biometric identifier must be able to identify an individual, lower courts have construed its holding narrowly to require that the entity collecting biometric data must itself be capable of identifying, rather than it being sufficient for any entity to do so. Reading BIPA this narrowly would significantly weaken the statute’s protections.
After detailing how employer and consumer cases catalyzed this recent defendant-friendly shift, this Comment proposes a two-step framework to determine whether a biometric identifier is able to identify, falling under BIPA’s reach. Given BIPA’s broad influence, where courts ultimately land on this question will be crucial to the protection of biometric data nationwide."
I would like to thank Professor Lior Strahilevitz and the editors and staff of the University of Chicago Law Review for their thoughtful advice and insight.
Recently, many states have reacted to the growing data economy by passing data privacy statutes. These follow the “interaction model”: they allow consumers to exercise privacy rights against firms by directly interacting with them. But data brokers, firms that buy and sell data for consumers whom they do not directly interact with, are key players in the data economy. How is a consumer meant to exercise their rights against a broker with an “interaction gap” between them?
A handful of states have tried to soften the interaction gap by enacting data-broker-specific legislation under the “transparency model.” These laws, among other things, require brokers to publicly disclose themselves in state registries. The theory is that consumers would exercise their rights against brokers if they knew of the brokers’ existence. California recently went further with the Delete Act, providing consumers data-broker-specific privacy rights.
Assembling brokers’ reported privacy request metrics, this Comment performs an empirical analysis of the transparency model’s efficacy. These findings demonstrate that the transparency model does not effectively facilitate consumers in following through on their expected privacy preferences or meaningfully impacting brokers. Therefore, regulators should follow in the footsteps of the Delete Act and move beyond the transparency model.