
The Oxford Handbook of the Foundations and Regulation of Generative AI
Oxford University Press
Will be published approx. on 25. August 2026
Book
Hardback
976 pages
978-0-19-894027-2 (ISBN)
Description
Generative AI technology holds immense transformative potential, with applications spanning from text generation to image creation and scientific discovery. Yet, its rapid development and adoption have introduced significant legal and ethical concerns, such as potential cybersecurity risks, misinformation, unsustainability, and algorithmic discrimination. The Oxford Handbook of the Foundations and Regulation of Generative AI offers theoretical insights and practical recommendations for ensuring the responsible development and application of this emerging technology.
Edited and written by leading scholars in law, AI ethics, economics, and computer science, this Handbook brings together a global team of experts to examine the foundational principles and regulatory challenges posed by generative AI systems. The Handbook introduces core technical concepts-including explainable AI (XAI), agentic AI safety, and prompting-and discusses pressing legal and ethical concerns such as AI bias, consumer protection, platform and worker rights, data protection, copyright, and liability for AI-generated speech. The volume also considers how generative AI is transforming industries, from business and legal practice to healthcare, finance, and cybersecurity. Finally, it concludes with in-depth analyses of AI regulation in various jurisdictions, including the EU, US, China, Brazil, India, and Australia.
Interdisciplinary in scope and global in coverage, this Handbook is an essential resource for anyone seeking to understand and navigate the evolving landscape of generative AI. It provides an accessible entry point for students, while offering the depth and rigor needed to inform practice, policy, and advanced research.
Edited and written by leading scholars in law, AI ethics, economics, and computer science, this Handbook brings together a global team of experts to examine the foundational principles and regulatory challenges posed by generative AI systems. The Handbook introduces core technical concepts-including explainable AI (XAI), agentic AI safety, and prompting-and discusses pressing legal and ethical concerns such as AI bias, consumer protection, platform and worker rights, data protection, copyright, and liability for AI-generated speech. The volume also considers how generative AI is transforming industries, from business and legal practice to healthcare, finance, and cybersecurity. Finally, it concludes with in-depth analyses of AI regulation in various jurisdictions, including the EU, US, China, Brazil, India, and Australia.
Interdisciplinary in scope and global in coverage, this Handbook is an essential resource for anyone seeking to understand and navigate the evolving landscape of generative AI. It provides an accessible entry point for students, while offering the depth and rigor needed to inform practice, policy, and advanced research.
More details
Series
Language
English
Place of publication
Oxford
United Kingdom
Target group
Professional and scholarly
Product notice
sewn/stitched
Cloth over boards
Dimensions
Height: 246 mm
Width: 171 mm
ISBN-13
978-0-19-894027-2 (9780198940272)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Prof. Dr. Philipp Hacker, LLM (Yale), holds the Research Chair for Law and Ethics of the Digital Society at the European New School of Digital Studies (ENS) at European University Viadrina Frankfurt (Oder). His research focuses on the regulation of digital technologies, particularly concerning artificial intelligence. For his work, he received several academic prizes, such as the 2020 Science Award of the German Foundation for Law and Computer Science. He regularly advises national and EU legislators, regulatory agencies, and industry. Philipp co-founded and co-leads the International Expert Consortium on the Regulation, Economics, and Computer Science of AI (RECSAI).
Dr. Andreas Engel, LLM (Yale), is a Senior Research Fellow at University of Heidelberg and a founding member of the International Expert Consortium on the Regulation, Economics, and Computer Science of AI (RECSAI), as well as a member of the board of trustees of the Deutsche Stiftung fuer Recht und Informatik (German Foundation for Law and Computer Science). He studied law in Munich, Oxford and at the Yale School, clerked at the German Federal Constitutional Court, and wrote his doctoral thesis at the Max Planck Institute for Comparative and International Private Law in Hamburg. Andreas researches the challenges of digitalisation, primarily from a private law perspective, and with a particular focus on (private) international law, IP law, and cybersecurity law.
Professor Sarah Hammer is Executive Director at the Wharton School, Adjunct Professor at the University of Pennsylvania Law School, and CEO of Wharton Cypher Accelerator. She is Academic Director of the Penn Law Executive Program on AI and is featured in Penn Law's massive open online courses on AI and digital assets. Hammer is co-chair of the International Expert Consortium on Regulation, Economics, and Computer Science of AI (RECSAI) and is a member of the American Law Institute Consultative Group on Civil Liability for AI. From 2018 through 2023, she served on the oversight board for the International Telecommunication Union (ITU), the specialized UN agency that sets global standards for ICT and leads AI for Good.
Professor Brent Mittelstadt is Professor of Data Ethics and Policy at the Oxford Internet Institute, University of Oxford, where he founded theGover nance of Emerging Technologies (GET) research programme. Prof. Mittelstadt is the author of highly cited foundational works addressing the ethics of algorithms, AI, and Big Data; truth and accuracy in large language models (LLMs); fairness, accountability, and transparency in machine learning; data protection and non-discrimination law; group privacy; and ethical auditing of automated systems. His work in these areas has featured in policy proposals and guidelines from the European Commission, European Parliament, United Nations, and US White House, as well as products from Google, Amazon, and Microsoft.
Dr. Andreas Engel, LLM (Yale), is a Senior Research Fellow at University of Heidelberg and a founding member of the International Expert Consortium on the Regulation, Economics, and Computer Science of AI (RECSAI), as well as a member of the board of trustees of the Deutsche Stiftung fuer Recht und Informatik (German Foundation for Law and Computer Science). He studied law in Munich, Oxford and at the Yale School, clerked at the German Federal Constitutional Court, and wrote his doctoral thesis at the Max Planck Institute for Comparative and International Private Law in Hamburg. Andreas researches the challenges of digitalisation, primarily from a private law perspective, and with a particular focus on (private) international law, IP law, and cybersecurity law.
Professor Sarah Hammer is Executive Director at the Wharton School, Adjunct Professor at the University of Pennsylvania Law School, and CEO of Wharton Cypher Accelerator. She is Academic Director of the Penn Law Executive Program on AI and is featured in Penn Law's massive open online courses on AI and digital assets. Hammer is co-chair of the International Expert Consortium on Regulation, Economics, and Computer Science of AI (RECSAI) and is a member of the American Law Institute Consultative Group on Civil Liability for AI. From 2018 through 2023, she served on the oversight board for the International Telecommunication Union (ITU), the specialized UN agency that sets global standards for ICT and leads AI for Good.
Professor Brent Mittelstadt is Professor of Data Ethics and Policy at the Oxford Internet Institute, University of Oxford, where he founded theGover nance of Emerging Technologies (GET) research programme. Prof. Mittelstadt is the author of highly cited foundational works addressing the ethics of algorithms, AI, and Big Data; truth and accuracy in large language models (LLMs); fairness, accountability, and transparency in machine learning; data protection and non-discrimination law; group privacy; and ethical auditing of automated systems. His work in these areas has featured in policy proposals and guidelines from the European Commission, European Parliament, United Nations, and US White House, as well as products from Google, Amazon, and Microsoft.
Volume editor
Chair for Law and Ethics of the Digital Society, European New School of Digital StudiesChair for Law and Ethics of the Digital Society, European New School of Digital Studies, European University Viadrina
Senior Research FellowSenior Research Fellow, Heidelberg University
Executive Director of the Wharton School of Business and Adjunct Professor of LawExecutive Director of the Wharton School of Business and Adjunct Professor of Law, University of Pennsylvania
Professor of Data Ethics and Policy, Oxford Internet InstituteProfessor of Data Ethics and Policy, Oxford Internet Institute, University of Oxford
Content
- I. Introduction
- 1: Philipp Hacker, Brent Mittelstadt, Sarah Hammer, and Andreas Engel: Foundations and Regulation of Generative AI: An Introduction
- II. Foundations
- 2: Gerard de Melo, Sanmi Koyejo, and Stephan Mandt: Generative AI and Foundation Models: A Gentle Technical Introduction
- 3: Rumman Chowdhury: Responsible Data Practices and Generative AI
- 4: Gerard de Melo: The Art of Generative AI Prompting
- 5: Wojciech Samek: XAI for Generative AI
- 6: Eleanor Watson: The Challenges of Agentic AI Safety
- 7: Neel Guha, Julian Nyarko, Daniel E. Ho, and Christopher Ré: Building GenAI Benchmarks: A Case Study in Legal Applications
- 8: Gerard de Melo: Detecting AI-Generated Content: Challenges and Opportunities
- 9: Henry Shevlin: Ethics at the Frontier of Human-AI Relationships
- 10: Lynette Webb and Daniel Schönberger: 1. Generative AI and the Problem of Existential Risk
- III. Regulatory Challenges
- 11: Cary Coglianese and Colton R. Krum: Regulating Foundation Models and Generative AI
- 12: Roger Brownsword: Generative AI and the Rule of Law
- 13: Jonas Schuett, Markus Anderljung, Alexis Carlier, Leonie Koessler, and Ben Garfinkel: From Principles to Rules: A Regulatory Approach for Frontier AI
- 14: Seb Krier, Harry Law, and Kevin Klyman: How Risky are Open Frontier Models?
- 15: Rachel Adams, Leah Junck, and Fola Adeleke: GAI as a Modality of Interdependencies: Imagining Tech Futures in Majority World Settings
- 16: Jerry John Kponyo, Francis Kemausuor, Eric Tutu Tchao, Henry Nunoo Mensah, and Rachel Yayra Adjoe: Promoting Transparency in Generative AI: A Focus on Africa
- 17: Philipp Hacker, Frederik Zuiderveen Borgesius, Brent Mittelstadt, and Sandra Wachter: Generative Discrimination: What Happens When Generative AI Exhibits Bias, and What Can Be Done About It
- 18: Jan Trzaskowski and Marie Jull Sørensen: Generative AI and Consumer Protection
- 19: Jeremias Adams-Prassl: Platform and Worker Rights in the Age of Generative AI
- 20: Pietro Ortolani: Generative AI and Content Moderation
- 21: Reuben Binns and Lilian Edwards: ChatGPT Tells Fibs About Me: Are Data Protection and Libel Adequate Tools to Protect Reputation in the LLM Era?
- 22: Peter Henderson, Tatsunori Hashimoto, and Mark A. Lemley: Liability for AI-Generated Speech
- 23: Graziana Kastl-Riemann: Regulation of Generative AI Speech: An EU Perspective
- 24: Amy L. Stein: Generative AI and Sustainability
- 25: Irene Solaiman, Zeerak Talat, and others: Evaluating the Social Impact of Generative AI Systems
- 26: Andreas Engel: Generative AI and Copyright
- 27: Herbert Zech: AI and Patents: The Role of Inventorship
- IV. Applications
- 28: Laurence Ales, Christophe Combemale, and Ramayya Krishnan: Generative AI, Adoption, and the Structure of Tasks
- 29: Alex P. Miller, Kartik Hosanagar, and Ramayya Krishnan: Harnessing AI for Business Insight: Key Considerations for Deploying LLMs in Summarization Pipelines
- 30: Alexandre Zavaglia Coelho: Data, Automation, and Artificial Intelligence: (Generative) AI in Legal Practice
- 31: Elizabeth Chan, Kiran Gore, and Eliza Jiang: Generative AI in International Arbitration
- 32: Kelly Richdale: AI and Health: Exploring the Opportunities, Risks, and Challenges
- 333: Joyce Nakatumba-Nabende, Ann Lisa Nabiryo, Peter Nabende, Jennifer Winfred Namuyanja, Andrew Katumba, and Derrick Ssekidde: Generative AI in Agriculture for Smallholder Agricultural Advisory in Sub-Saharan Africa
- 34: Julia Powles: Generative AI and Education
- 35: Sarah Hammer: Generative AI and Finance
- 36: Thomas Wischmeyer and Michael B. Strecker: Generative AI and Cybersecurity
- V. Global and Regional Considerations
- 37: Jeannie Marie Paterson: Regulating Generative AI in Australia: Challenges of Regulatory Design and Regulator Capacity
- 38: Dora Kaufman: Generative AI Regulation in Brazil
- 39: Ignacio Cofone: Generative AI Regulation in the US and Canada
- 40: Rogier Creemers: The Regulation of Generative AI in China
- 41: Kai Zenner: The Genesis of the EU Foundation Model Regulation: How Brussels has Adjusted the AI Act After the Release of ChatGPT
- 42: Debayan Gupta: Generative AI in India
- 43: Adrian Ang and Alexander Yap: Generative AI Regulation in Singapore
- 44: Christopher T. Marsden: Generative AI Regulation in the UK
- 45: Matthijs Maas and José Villalobos: International Perspectives