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Government by Algorithm: Artificial Intelligence in Federal Administrative Agencies A O D V I X M X DCCC X Government by Algorithm: Artificial Intelligence in Federal Administrative Agencies REPORT SUBMITTED TO THE ADMINISTRATIVE CONFERENCE OF THE UNITED STATES David Freeman Engstrom, Stanford University Daniel E. Ho, Stanford University Catherine M. Sharkey, New York University Mariano-Florentino Cuéllar, Stanford University and Supreme Court of California February, 2020 DISCLAIMER This report was commissioned by the Administrative Conference of the United States in furtherance of its mission to “study the efficiency, adequacy, and fairness of . administrative procedure”; “collect information and statistics from . agencies and publish such reports as it considers useful for evaluating and improving administrative procedure”; and to “improve the use of science in the regulatory process.” 5 U.S.C. §§ 591, 594. The opinions, views, and recommendations expressed are those of the authors. They do not necessarily reflect those of the Conference or its members. Government by Algorithm: Artificial Intelligence in Federal Administrative Agencies 2 Table of Contents Executive Summary .............................................................................................................6 Introduction .........................................................................................................................9 Part I. Taking Inventory: A Survey of Federal Agency Use of AI ........................................15 Part II. Case Studies of Federal Agency Deployment of AI ................................................21 Regulatory Enforcement at the Securities and Exchange Commission ...................25 Law Enforcement at Customs and Border Protection .................................................30 Formal Adjudication at the Social Security Administration .......................................37 Informal Adjudication at the United States Patent and Trademark Office ..............46 Regulatory Analysis at the Food and Drug Administration .........................................53 Public Engagement at the Federal Communications Commission and Consumer Financial Protection Bureau .................................................................59 Autonomous Vehicles for Mail Delivery at the United States Postal Service ...........65 Part III. Implications and Recommendations ...................................................................70 Building Internal Capacity .................................................................................................71 Transparency and Accountability ....................................................................................75 Bias, Disparate Treatment, and Disparate Impact ........................................................79 Hearing Rights and Algorithmic Governance ................................................................82 Gaming and Adversarial Learning ....................................................................................86 The External Sourcing Challenge: Contractors and Competitions ............................88 Conclusion ..........................................................................................................................91 Endnotes .............................................................................................................................93 Government by Algorithm: Artificial Intelligence in Federal Administrative Agencies 3 LEAD AUTHORS David Freeman Engstrom. David Freeman Engstrom is the Bernard D. Bergreen Faculty Scholar and an Associate Dean at Stanford Law School. He is an elected member of the American Law Institute and a faculty affiliate at the Stanford Institute for Human-Centered Artificial Intelligence (HAI), CodeX: The Stanford Center for Legal Informatics, and the Regulation, Evaluation, and Governance Lab (RegLab). He received a J.D. from Stanford Law School, an M.Sc. from Oxford University, and a Ph.D. in political science from Yale University and clerked for Chief Judge Diane P. Wood on the U.S. Court of Appeals for the Seventh Circuit. Daniel E. Ho. Daniel Ho is the William Benjamin Scott and Luna M. Scott Professor of Law, Professor of Political Science, and Senior Fellow at the Stanford Institute for Economic Policy Research at Stanford University. He directs the Regulation, Evaluation, and Governance Lab (RegLab) at Stanford, and is a Faculty Fellow at the Center for Advanced Study in the Behavioral Sciences and Associate Director of the Stanford Institute for Human-Centered Artificial Intelligence (HAI). He received his J.D. from Yale Law School and Ph.D. from Harvard University and clerked for Judge Stephen F. Williams on the U.S. Court of Appeals for the District of Columbia Circuit. Catherine M. Sharkey. Catherine Sharkey is the Crystal Eastman Professor of Law at NYU School of Law. She is an appointed public member of the Administrative Conference of the United States, an elected member of the American Law Institute, and an adviser to the Restatement Third, Torts: Liability for Economic Harm and Restatement Third, Torts: Remedies projects. She was a 2011-12 Guggenheim Fellow. She received an M.Sc. from Oxford University and a J.D. from Yale Law School. She clerked for Judge Guido Calabresi of the U.S. Court of Appeals for the Second Circuit and Justice David H. Souter of the U.S. Supreme Court. Mariano-Florentino Cuéllar. Mariano-Florentino Cuéllar is a Justice on the Supreme Court of California, the Herman Phleger Visiting Professor of Law at Stanford University, and a faculty affiliate at the Stanford Center for AI Safety. A Fellow of the Harvard Corporation, he also serves on the boards of the Hewlett Foundation, the American Law Institute, and the Stanford Institute for Human-Centered Artificial Intelligence (HAI), and chairs the boards of the Center for Advanced Study in the Behavioral Sciences and AI Now. He received a J.D. from Yale Law School and a Ph.D. in political science from Stanford University and clerked for Chief Judge Mary M. Schroeder of the U.S. Court of Appeals for the Ninth Circuit. Government by Algorithm: Artificial Intelligence in Federal Administrative Agencies 4 CONTRIBUTORS Many dedicated professionals contributed to this report. To acknowledge these contributions, we list here the principal authors and contributors for each chapter and section. Executive Summary and Introduction Public Engagement at the Federal Communications Authors: Mariano-Florentino Cuéllar, David Freeman Engstrom, Commission and Consumer Financial Protection Daniel E. Ho, Catherine Sharkey, Liza Starr Bureau Authors: Nitisha Baronia, Mariano-Florentino Cuéllar, Taking Inventory: A Survey of Federal Agency Use of AI David Freeman Engstrom, Daniel E. Ho Authors: David Freeman Engstrom, Daniel E. Ho, Liza Starr Contributors: Clint Akarmann, David Hoyt, Patrick Reimherr, Contributors: Kinbert Chou, Shushman Choudhury, Florian Tramer Madeline Levin, Coby Simler, Stephen Tang Autonomous Vehicles for Mail Delivery at the United Regulatory Enforcement at the Securities and States Postal Service Exchange Commission Author: Shawn Musgrave Author: David Freeman Engstrom Contributors: Sandhini Agarwal, Alex Duran, Michael Fischer, Building Internal Capacity Joseph Levy, Sunny Kang Authors: Nitisha Baronia, David Freeman Engstrom, Daniel E. Ho, Shawn Musgrave, Catherine Sharkey Law Enforcement at Customs and Border Protection Contributors: Cassi Carley, Ben Morris, Nate Tisa Authors: Nitisha Baronia, Cristina Ceballos, Mariano-Florentino Cuéllar, Daniel E. Ho Transparency and Accountability Contributors: Matthew Agnew, Peter Henderson, Geet Sethi, Author: David Freeman Engstrom Stephen Tang Bias, Disparate Treatment, and Disparate Impact Formal Adjudication at the Social Security Author: Daniel E. Ho Administration Authors: Daniel E. Ho, Derin McLeod Hearing Rights and Algorithmic Governance Contributors: Urvashi Khandelwal, Liza Starr, Emma Wang Authors: David Freeman Engstrom, Amit Haim, Daniel E. Ho Informal Adjudication at the U.S. Patent and Gaming and Adversarial Learning Trademark Office Authors: David Freeman Engstrom, Daniel E. Ho, Liza Starr Authors: Daniel E. Ho, Urvashi Khandelwal, Alex Yu The External Sourcing Challenge: Contractors Regulatory Analysis at the Food and Drug and Competitions Administration Authors: David Freeman Engstrom, Reed Sawyers Author: Catherine Sharkey Contributors: Cassi Carley, Shushman Choudhury, David Freeman Engstrom, Zach Harned, James Rathmell, Liza Starr, Chase Weidner Several individuals also contributed to the report as a whole, including Ryan Azad, Jami Butler, Mikayla Hardisty, Alexandra Havrylyshyn, Luci Herman, and Liza Starr. Government by Algorithm: Artificial Intelligence in Federal Administrative Agencies 5 Executive Summary Artificial intelligence (AI) promises to transform how government agencies do their work. Rapid developments in AI have the potential to reduce the cost of core governance functions, improve the quality of decisions, and unleash the power of administrative data, thereby making government performance more efficient and effective. Agencies that use AI to realize these gains will also confront important questions about the proper design of algorithms and user interfaces, the respective scope of human and machine decision-making, the boundaries between public actions and private contracting, their own capacity to learn over time using AI, and whether the use of AI is even permitted. These are important issues for public debate and academic inquiry. Yet little is known about
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