Social Justice for Data Science Lecture Series

Despite ample lip service for privacy, society is normalizing surveillance. People are slowly but surely being acclimated to all kinds of exposure by ignoring smaller, more frequent, and more mundane privacy diminutions. The proliferation of cameras and biometric sensors on doorbells, glasses, and watches, and the drift of data analytics into new areas of our lives like travel, exercise, and social gatherings have caused surveillance practices to recede into the backdrop of our lives. Invasive practices become routine through repeated exposures that acclimate us to being vulnerable and watched in increasingly intimate ways. In this talk, Professor Hartzog will make the case against normalizing surveillance, starting with the law. Because the law looks to norms and people’s expectations to set thresholds, the normalization of small privacy encroachments results in a constant re-negotiation of privacy standards to society’s disadvantage. This is particularly true for marginalized groups that bear the brunt of surveillance first and hardest. The result of normalizing surveillance is that the legal and social threshold for rejecting invasive new practices keeps getting redrawn, excusing ever more aggressive intrusions. In short, privacy law permits whatever people can be conditioned to tolerate. We are on track to tolerate everything.

Woodrow Hartzog is a Professor of Law and Class of 1960 Scholar at Boston University School of Law. He is also a Faculty Associate at the Berkman Klein Center for Internet & Society at Harvard University, a Non-resident Fellow at The Cordell Institute for Policy in Medicine & Law at Washington University, and an Affiliate Scholar at the Center for Internet and Society at Stanford Law School. He is the author of Privacy’s Blueprint: The Battle to Control the Design of New Technologies, published in 2018 by Harvard University Press, and the co-author of Breached! Why Data Security Law Fails and How to Improve It, published in 2022 by Oxford University Press.

Governance is the general ability to organize society into groups, whether as circles of citizens, friends, consumers, competitors, rights-holders, or as those beyond the pale of esteem, dignity or mutual regard. The systems of liberal democracy that we commonly identify as governance are being challenged, eroded, or are increasingly misaligned in purpose and function. Legal institutions--which promise fairness, transparency, opportunity to be heard, and collective repair--are frequently bypassed by the dissociative and de-socializing effects of immersive new computational technologies that exceed the influence of many normative legal regimes. Pervasive algorithmic ordering is surely recognized for its potential as a “distractive-extractive” force, or as a panopticon of serial exposure, or as a meme generator whose suggestive force invites us into mass hypnosis, seamless normativity and cult-like parasociality…but pervasive algorithmic ordering simultaneously distributes disciplinary power inconsistently, in vast networks of incommensurable incentives, a welter of uncoordinated performance baselines, and stern but incoherent “meaning-making” word-spew. These incongruities place stresses on the human organism at an individual level as well as on the stability of larger social organizations; and they corrode the trust mechanisms that legitimate structures of law and civil ordering. They are making us unhappy.

One simple question for lawyers is how to reconcile the comparative meanings of a data-fied self with a civilly righted “person” or legal subject. There are so many conversations about how data and social justice could serve or disserve each other that the very notion of a “self”—as a data configuration or otherwise--can sometimes feel abstracted, ineffable. This paper will be an attempt to materialize the granular disruptions of those abstractions; it will be a crude (auto)biography of one self’s various technologically-asserted identificatory “brands.” I will disaggregate and introduce some of the machine-assorted bits and pieces that compose (or discompose) each one of us: I’ll look at the vivid reality of my own epistemological and epidemiological trail: my medical score, my credit score, my consumer preferences, my job proficiency, my popularity. I will look at the narrative logics of the distributed agencies being generated in figurations of the virtual me, the social media me, the bio-me, the productive me, the reproductive me, the geo-located me, the writerly me, the overwritten me, the archival me—in other words, how the very mechanics of accumulating complex data make a corporatized data complex of me in relation to the complexity of all other “me’s.” The goal of this inquiry will be to compare mathematical and predictive modeling of human behavior with legal models of a “rights-endowed” legal subject or dignitary construct of legal personhood. This comparison will hopefully highlight, amidst the vast social restructuring we are living through, both failures in and opportunities for the continued guarantee of values that are at least nominally idealized as humanitarian and central to human happiness in liberal democracy: fairness, legibility, room to think, opportunity to talk back and dispute, and collective remediation.

Patricia Williams is University Distinguished Professor of Law and Humanities at Northeastern University, and Director of Law, Technology and Ethics Initiatives. A pioneer of both the law and literature and critical race theory movements in American legal theory, she has published widely in the areas of bias, language, and law. Her interrogations raise core questions of individual autonomy and identity in the context of legal and ethical debates on science and technology. A MacArthur Fellowship recipient, she is a frequent contributor to The Nation Magazine. 

Much attention has been paid to the risk artificial intelligence poses to employment, particularly in low-wage industries. Long-haul truck driving is perceived as a prime target for such displacement, due to the fast-developing technical capabilities of autonomous vehicles, characteristics of trucking labor, and the political economy of the industry. In most of the public rhetoric about the threat of the self-driving truck, the trucker is seen as a displaced party. He is displaced both physically and economically: removed from the cab of the truck, and from his means of economic provision. But the reality is more complicated. The intrusion of automation into the truck cab certainly presents a threat to the trucker, but the threat is not solely or even primarily experienced as displacement. The trucker is still in the cab, doing the work of truck driving-but he is joined there by intelligent systems that monitor his body directly. As more trucking firms integrate such technologies into their safety programs, truckers are not being displaced by intelligent systems so much as they are experiencing the emergence of intelligent systems as a compelled hybridization, a very intimate incursion into their work and bodies. This talk considers the dual, conflicting narratives of job replacement by robots and of bodily integration with robots, to assess the true range of AI's potential effects on low-wage work.

Karen Levy is Associate Professor in the Department of Information Science at Cornell University, and Associate Faculty at Cornell Law School. She studies the legal, social, and ethical dimensions of emerging technologies.

Professor Veena Dubal’s research focuses broadly on law, technology, and precarious workers, combining legal and empirical analysis to explore issues of labor and inequality. Her work encompasses a range of topics, including the impact of digital technologies and emerging legal frameworks on workers' lives, the interplay between law, work, and identity, and the role of law and lawyers in solidarity movements.

Professor Dubal has written numerous articles in top law and social science journals and publishes essays in the popular press. Her research has been cited internationally in legal decisions, including by the California Supreme Court, and her research and commentary are regularly featured in media outlets, including The New York Times, The Washington Post, The Wall Street Journal, The Los Angeles Times, NPR, CNN, etc. TechCrunch has called Prof. Dubal an “unlikely star in the tech world,” and her expertise is frequently sought by regulatory bodies, legislators, judges, workers, and unions in the U.S. and Europe.  Professor Dubal is completing a book manuscript that presents a theoretical reappraisal of how low-income immigrant and racial minority workers experience and respond to shifting technologies and regulatory regimes. The manuscript draws upon a decade of interdisciplinary ethnographic research on taxi and ride-hail regulations and worker organizing and advocacy in San Francisco.

Prof. Dubal received a B.A. from Stanford University and holds J.D. and Ph.D. degrees from the University of California, Berkeley, where she conducted an ethnography of the San Francisco taxi industry. The subject of her doctoral research arose from her work as a public interest attorney and Berkeley Law Foundation Fellow at the Asian Law Caucus where she founded a taxi worker project and represented Muslim Americans in civil rights cases. Prof. Dubal completed a post-doctoral fellowship at her alma mater, Stanford University. She returned to Stanford again in 2022 as a Residential Fellow at the Center for Advanced Study in the Behavioral Sciences.  Prof. Dubal is the recipient of numerous awards and grants, including the Fulbright, for her scholarship and previous work as a public interest lawyer.