Our weekly SRI Seminar Series welcomes Elizabeth Joh, the Martin Luther King Jr. Professor of Law at UC Davis School of Law, and a leading expert on policing, privacy, and technology. Joh served as a member of the UC Presidential Working Group on Artificial Intelligence, and is an elected member of the American Law Institute, a Faculty Advisory Board member of the UC Berkeley CITRIS Policy Lab, and an appointed member of the National Academies of Sciences, Engineering, and Medicine study committee on facial recognition.
In this talk, Joh will examine how advanced surveillance technologies used by modern police forces create new forms of knowledge that expand the capacities of policing. Joh argues that we must understand these new tools as “experiments on communities” that, while intended to provide more effective forms of policing, often generate ethical considerations and group harms that are difficult to grasp via traditional forms of legal analysis.
Talk title:
“Computational research for equity in the legal system training program”
Abstract:
To be a modern local police force means embracing new surveillance technologies that promise to amass the ever-enlarging universe of data around us and to produce actionable inferences about it. Whether described as using algorithms, artificial intelligence, or automated decision-making, all these surveillance technologies involve some degree of computational analysis of data that creates new forms of knowledge and permits new types of policing. The usual way we discuss the use of these technologies, however, is limiting. Not only is it limiting, but it also obscures important human costs that are an inevitable consequence.
We should reconsider how we approach these new policing tools. This talk makes one straightforward claim: algorithmic surveillance tools piloted by the police function as technology experiments on communities. These police technologies are experiments in the sense that they pose potential harms on those subject to the technology in the service of a theoretical but typically unproven benefit: more effective policing. With this framework, two observations follow. First, the model of technological experimentalism provides a more nuanced and comprehensive framework for understanding the use of algorithmic surveillance tools in policing. Second, experimentalism foregrounds both ethical considerations and group harms that are ill-suited to traditional legal analysis.
About Elizabeth Joh
Elizabeth Joh is a leading expert on policing, privacy, and technology. She served as a member of the UC Presidential Working Group on Artificial Intelligence (2020–21), and is an elected member of the American Law Institute, a Faculty Advisory Board member of the UC Berkeley CITRIS Policy Lab, and an appointed member of the National Academies of Sciences, Engineering, and Medicine study committee on Facial Recognition: Current Capabilities, Future Prospects, and Governance. She has spoken on policing and technology issues to audiences including the Justices of the Washington Supreme Court, the Judicial Research Training Institute of the Supreme Court of Korea, and the House of Lords Justice and Home Affairs Committee (UK).
Joh’s scholarship has appeared in leading law reviews including the Northwestern University Law Review, the California Law Review, and the Stanford Law Review. Her writing for general audiences has appeared in the New York Times, the Los Angeles Times, Slate, Politico, and the New York Review of Books. Since 2017, she has been the co-host of What Roman Mars Can Learn About Con Law, a popular podcast about constitutional law and current events.
About the SRI Seminar Series
The SRI Seminar Series brings together the Schwartz Reisman community and beyond for a robust exchange of ideas that advance scholarship at the intersection of technology and society. Seminars are led by a leading or emerging scholar and feature extensive discussion.
Each week, a featured speaker will present for 45 minutes, followed by an open discussion. Registered attendees will be emailed a Zoom link before the event begins. The event will be recorded and posted online.
Elizabeth Joh