Race and Regulation Podcast Episode 10 - Administrative Law\u27s Racial Blind Spot

Administrative law has a racial blind spot, argues Daniel E. Ho of Stanford Law School. Judges have long set aside agency actions when government officials have failed to consider the differential impacts of their policy decisions on subgroups of business owners, park visitors, and even animals—but not when they have failed to consider differential impacts based on race or ethnicity. In this episode, Professor Ho traces how civil rights and administrative law have diverged over the past fifty years, as U.S. court decisions have removed issues of racial discrimination from administrative law’s purview. He concludes by discussing reforms that could better address racial inequities in the administrative state

How Not to Lie with Judicial Votes: Misconceptions, Measurement, and Models

In Part I, we describe the formal spatial theory often invoked to justify the statistical approach. While spatial theory has the nice feature of synthesizing theory and empirics, legal scholars may remain skeptical of its strong assumptions. Fortunately, measurement models can be illuminating even if the spatial theory is questionable. To illustrate this, Part II provides a nontechnical overview of the intuition behind measurement models that take merits votes as an input and return a summary score of Justice-specific behavior as an output. Such scores provide clear and intuitive descriptive summaries of differences in judicial voting. Confusion abounds, however, and in Part III we clarify prevailing misconceptions of such scores. We discuss how these scores relate to ideology, explain how such models grapple with the complexity and dimensionality of judicial decisionmaking, illustrate the problems of intertemporal extrapolation and cardinal interpretation of the scores, and highlight other common abuses of such measures. In Part IV, we demonstrate how modern measurement methods are useful precisely because they empower meaningful examination, data collection, and incorporation of doctrine and jurisprudence. We argue that existing uses are simply a special case of a much more general measurement approach that works synergistically with the qualitative study of case law. We demonstrate in Part V how such measurement approaches-when augmented with jurisprudentially meaningful data-----can advance our understanding of courts, with case studies of the constitutional revolution of 1937, the dimensionality of the Supreme Court, the historical origins of the standing doctrine, statutory interpretation, and backlash against Supreme Court opinions. We conclude with thoughts on the chief virtues of model-based measurement and the study of law

Algorithmic Accountability in the Administrative State

How will artificial intelligence (AI) transform government? Stemming from a major study commissioned by the Administrative Conference of the United States (ACUS), we highlight the promise and trajectory of algorithmic tools used by federal agencies to perform the work of governance. Moving past the abstract mappings of transparency measures and regulatory mechanisms that pervade the current algorithmic accountability literature, our analysis centers around a detailed technical account of a pair of current applications that exemplify AI’s move to the center of the redistributive and coercive power of the state: the Social Security Administration’s use of AI tools to adjudicate disability benefits cases and the Securities and Exchange Commission’s use of AI tools to target enforcement efforts under federal securities law. We argue that the next generation of work will need to push past a narrow focus on constitutional law and instead engage with the broader terrain of administrative law, which is far more likely to modulate use of algorithmic governance tools going forward

The Role of Theory and Evidence in Media Regulation and Law: A Response to Baker and a Defense of Empirical Legal Studies

We thank Professor Baker for a stimulating response to an Article in which we offered empirical evidence of editorial viewpoint diversity in the face of media consolidation. We appreciate his praise of the Article as apply[ing] innovative statistical techniques and as far superior methodologically to most empirical studies he has seen. At the same time, Baker denies the policy relevance to our Article because empirical evidence is entirely irrelevant to the field of media regulation under his preferred normative theory. Baker argues sweepingly that the legal academy\u27s increased willingness to consider the perspectives of quantitative empiricists and positive theorists is malignant, and that law is best confined to normative theory and value-based inquiries - to the exclusion of positive investigation. Because of the provocative nature of the specific critiques of our Article and the general across-the-board indictment of positive scholarship and empirical legal studies, we respond