全球人工智慧治理(英文授課)

Course Overview: Artificial Intelligence Governance: National Strategies, International Initiatives, and the Future of AI Regulation examines one of the most pressing legal and policy challenges of our time: how to govern powerful and rapidly evolving AI technologies in ways that are effective, ethical, and globally coherent. As AI systems become embedded in critical sectors – from healthcare and transportation to finance, defense, and the justice system – governments and international bodies are racing to develop strategies that address risks, assert sovereignty, and define the rules of the digital era. This course offers a global and national comparative perspective on these efforts, investigating how different jurisdictions are approaching AI regulation, and how multilateral initiatives like the G7 Hiroshima AI Process, the Bletchley Declaration, and the United Nations AI resolution are shaping an emerging international governance architecture. We will also explore the increasingly influential roles of private actors, technical standard-setters, and civil society in designing rules for AI – often outside traditional legal frameworks. Designed for students in law, public policy, and interdisciplinary programs, this course emphasizes institutional design, legal interoperability, and the geopolitics of emerging technologies. It invites students to engage critically with real-world governance challenges and to think creatively about what effective, fair, and future-ready AI regulation might look like. Course Goals: By the end of the course, students will be able to: 1. Identify key ethical, legal, and policy challenges posed by AI systems. 2. Analyze and compare national AI governance strategies. 3. Evaluate the structure and impact of international initiatives (G7, OECD, UN). 4. Understand how legal design mediates global power and technological risk. 5. Apply governance frameworks to real-world regulatory problems. 6. Propose context-aware, ethically grounded governance solutions.

This course schedule is arranged to accommodate the visiting foreign instructor’s time in Taiwan. Classes will be held on the following specified dates and times. In principle, students from the Hsinchu Campus are required to attend classes in person. Please note that lectures will not be recorded. If a student is unable to attend due to an unavoidable scheduling conflict, they may arrange office hours with the instructor. Monday, 5/18: 9:10 a.m. – 12:00 p.m. Friday, 5/22: 6:45 p.m. – 9:30 p.m. Saturday, 5/23: 9:10 a.m. – 12:00 p.m. Monday, 5/25: 9:10 a.m. – 12:00 p.m. Friday, 5/29: 6:45 p.m. – 9:30 p.m. Saturday, 5/30: 9:10 a.m. – 12:00 p.m. Instructor’s Field of Specialization: David U. Socol de la Osa is an Assistant Professor at Hitotsubashi University and a Senior Associate at the University of Oxford EARTH Programme. Mr. Socol de la Osa specializes in law and technology, with a focus on AI governance, regulation of disruptive technologies, and international economic law. Before academia, he practiced at Latham & Watkins LLP and Simpson Thacher & Bartlett LLP, advising on cross-border technology transactions and regulatory compliance.

Requirements for Class Preparation and Review 1. Complete all assigned readings before class. 2. Prepare short memos when assigned. 3. Participate in group exercises and simulations. 4. Follow current developments in AI governance (optional weekly news brief). Message for Students This course invites you to explore how law, policy, and power shape the governance of artificial intelligence across jurisdictions. No technical background is required – only curiosity, and an openness to think beyond borders. Through readings, debates, and applied exercises, you’ll gain a grounded understanding of what “global AI governance” means, and what regulating technology and innovation could become. — David U. Socol de la Osa

COMPONENT/ WEIGHT DESCRIPTION Class Participation & Discussion/ 25% Active engagement, leadership in debate, and consistent preparation. Reflection Memos/ 10% Two short (300–500 word) written reflections. Comparative Briefing Presentation/ 25% Analytical presentation addressing national or international AI strategies. Final Project & Presentation/ 40% Research-based policy proposal (2,000–3,000 words) with presentation.

Foundational Readings:  The Cambridge Handbook of Artificial Intelligence, Edited by Keith Frankish and William M. Ramsey, Cambridge University Press  IBM, Artificial Intelligence Topic Hub, General Introduction and Corporate Perspective  McKinsey & Company, What is AI?, McKinsey Explainers Series  NASA, What is Artificial Intelligence?, Introductory Governmental Resource  Kate Crawford, Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence Introduction (pp. 1–21)  Artificial Intelligence: A Modern Approach, Edited by Stuart Russell and Peter Norvig, Introduction (pp. 1–29)  Luciano Floridi and Josh Cawls, A Unified Framework of Five Principles for AI in Society, Harvard Data Science Review  IBM Report, 10 Dangers of AI and How to Manage Them  Ryan Calo, Artificial Intelligence Policy: A Primer and Roadmap”, UC Davis Law Review Cross-Comparative & Multilateral Insights  Organisation for Economic Co-operation and Development, AI Principles OECD Principles, and Legal Instrument (2024)  United Nations AI Resolution (2024), A/78/L.49  Paris Agreement on Inclusive and Sustainable AI (2025)  G7 Hiroshima Leaders’ Communiqué on AI (2023): Guiding Principles, and Code of Conduct  Bletchley Declaration on AI Safety (2023)  Hiroki Habuka & David Uriel Socol de la Osa, Enhancements and Next Steps for the G7 Hiroshima AI Process. Cambridge Forum on AI Law and Governance  Center for International Economic Collaboration & Kyoto University Center for Interdisciplinary Studies of Law and Policy Report (2025): Comparative Global Frameworks for AI Governance  David Uriel Socol de la Osa, The Geopolitics of AI Governance: From Cooperation to Competition, and a Path to Stability. NUS Centre for Research in Law & Technology Blog  European Union, Artificial Intelligence Act (Articles 1–6), Summary  European Union, Luciano Floridi, The European Legislation on AI: a Brief Analysis of its Philosophical Approach, Philosophy & Technology  US, President Biden’s Executive Order on Safe, Secure, and Trustworthy AI (2023)  US, President Trump’s Executive Order on Removing Barriers to AI Leadership (2025)  Japan, METI AI Governance Implementation Guidelines (April 2024)  Japan, CSIS Interview, Hiroki Habuka. Unpacking Japan’s AI Policy  Japan, CSIS Report, Norms for New Technological Domains: Japan’s AI Governance Strategy  Singapore, Model AI Governance Strategy  China, Carnegie Endowment Article. Tracing the Roots of China’s AI Regulations.  China, Trackers: OECD, White & Case, Oxford  India, Carnegie Endowment Article. India’s Advance on AI Regulation.  India, Brookings Article. Re-envisioning AI Safety Through Global Majority Perspectives  India, IndiaAI Announcement, India Takes the Lead: Establishing the IndiaAI Safety Institute for Responsible AI Innovation.