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Introduction to AI Law and Policy: Primary Legal and Policy Sources on AI Governance, First Edition

Authors
  • Margaret Hu
Series / Aspen Coursebook Series
Description
Table of contents
Preface

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Introduction to AI Law and Policy: Primary Legal and Policy Sources on AI Governance offers a survey of law and policy introduced by artificial intelligence (AI) and other emerging technologies. As the law of AI is still nascent, this book will explore developments in law and policy that attempt to bring AI under increased regulatory and legal oversight. It provides a panoramic snapshot of a fastmoving phenomenon in a transformative moment of history, and attempts to capture a wide-lens story of technology that is disruptive and an area of law that is undergoing the earliest stages of experimentation.

Rather than cover all of AI-related legal issues, the casebook aims for breadth of the evolving history of a range of AI governance concepts. The approach will ground the student in how AI must be interrogated for its governance impact through a wide range of case studies. The evolving arc of AI governance is examined through a series of primary source materials—complaints and cases, statutes, regulations, reports, press releases and policy guidance documents—that span multiple areas of law and policy, including Data Privacy, Cybersecurity, Antidiscrimination Law, Product Liability and Torts, Intellectual Property, Antitrust, National Security, and other related fields. 

Benefits for instructors and students:

  • Legal definitions of AI, including AI systems, components, and domains
  • Representative frameworks of AI governance, including regulating automation and algorithmic decisionmaking
  • Specific pillars of AI governance aims and objectives, including:
    • Antidiscrimination
    • Transparency and Explanation
    • Data Privacy and Autonomy
    • Personhood and Citizenship
    • Human Oversight
  • Distinctions between AI and its treatment under the law
  • Conceptualization of AI ethics and AI audits
  • Preventive measures and AI remedies
  • Visualization of the future of AI labor, research, and energy policy
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Table of contents

SUMMARY OF CONTENTS

Contents 
Preface 
Author’s Note on Editorial and Research Process 
Acknowledgments 


Chapter 1. Introduction 
Chapter 2. Definitions 
Chapter 3. Conceptualizing AI Governance 
Chapter 4. Algorithmic Discrimination and Disparate Impact 
Chapter 5. Transparency and Explanation 
Chapter 6. Data Privacy and Autonomy 
Chapter 7. Personhood and Citizenship 
Chapter 8. Human Oversight and Generative AI 
Chapter 9. AI Ethics and Audits 
Chapter 10. Remedies and Preventive Measures 
Chapter 11. Humanity and Sustainability 
Appendix—Constitution of the United States 
Table of Statutes and Regulations 


Table of Cases 
Index 

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About the authors
Margaret Hu
Professor of Law

Margaret Hu is the Davison M. Douglas Professor of Law and director of the Digital Democracy Lab at William & Mary Law School. She is a research affiliate with the Institute for Computational and Data Sciences at Penn State University, and faculty affiliate with the Data Science and the Global Research Institute at William & Mary.

Professor Hu’s research interests include the intersection of AI and national security, cybersurveillance, and civil rights. Previously, she served as senior policy advisor for the White House Initiative on Asian Americans and Pacific Islanders, and served as special policy counsel for immigration-related discrimination in Civil Rights Division, U. S. Department of Justice, in Washington, D.C.

Product Information
Edition
First Edition
Publication date
2026-07-03
Copyright Year
2026
Pages
390
Print + eBook
9798899639388
eBook
9798899639395
Subject
Artificial Intelligence , Computer and Cyberlaw , Computer and Cyberlaw , Technology
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