Talk by Mr. Michael Karanicolas, Executive Director for the Institute for Technology, Law & Policy at UCLA.

In recent years, an increasing number of government agencies have incorporated algorithmic systems into their regulatory enforcement processes. The potential efficacy gains from these systems are easy to see, especially in the context of mounting public demands for the administrative state to do more with less. However, the broader impact of algorithmic tools on government functions is much less clear. Besides well-documented challenges with bias, drift, and accuracy, there are core questions around transparency, accountability, and procedural fairness related to the use of these tools in the context of official decision-making. There is a pressing need to develop an appropriate framework to guide the use of these tools across diverse official enforcement processes. My project, outlined in this talk, aims to address this pressing need for guidance across the administrative state. In doing so, it provides a straightforward and accurate assessment formula for agencies to assess whether or not algorithmic tools are appropriate for a particular process and, if so, what safeguards and strategies for oversight, public consultation, monitoring, and assessment are appropriate for each case.

Mr. Michael Karanicolas is the Executive Director of the UCLA Institute for Technology Law & Policy. Before joining UCLA, he was the Wikimedia Fellow at the Yale Information Society Project, where he remains an affiliated fellow. Prior to his academic career, Michael spent a decade as a human rights advocate, where he worked on projects to develop frameworks supporting freedom of expression and online privacy in emerging democracies. A widely published scholar, Michael’s research encompasses a number of thematic areas, but generally focuses on the application of human rights standards in an online context. His latest project, with the Administrative Conference of the United States, aims to map appropriate safeguards for the use of AI in regulatory enforcement. Michael holds a B.A. from Queen’s University, an LL.B. from the Schulich School of Law at Dalhousie University, and an LL.M. from the University of Toronto.

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