⚡ Quick Summary
This edited volume bridges AI’s philosophical, ethical, and regulatory dimensions. Structured in three parts—Ethics & Philosophy, Law, and Governance—it’s not just about LLMs or frontier models but the full arc of algorithmic systems, from “traditional” automation to emergent AI. Each chapter stands alone yet echoes a common message: current frameworks are fragmented, ethical challenges are evolving, and there’s an urgent need for interdisciplinary thinking. It’s a rigorous, academic response to the over-simplification of AI policy, ideal for readers ready to confront ambiguity, not escape it.
🧩 What’s Covered
The book is split into three sections:
Part I – AI, Ethics, and Philosophy
This section sets the tone by framing AI within philosophical discourse. Chapter 1 (Meert, De Laet, De Raedt) focuses on machine learning and reasoning, while Chapter 2 (Müller) explores cognition, intelligence, and normativity. Chapter 3 (Buijsman, Klenk, van den Hoven) digs into moral philosophy, examining autonomy, bias, and explainability through ethical theory.
A standout chapter advocates for “Design for Values”—integrating ethics directly into system architecture, rather than retrofitting it as principle-based checklists. The emphasis is on interdisciplinary co-creation and the inadequacy of ethics-by-guideline .
Part II – Legal and Human Rights Frameworks
This section dives into data protection, discrimination law, liability, and the limitations of current legal systems. Authors analyze how GDPR interacts with AI, the need for Algorithmic Impact Assessments (AIAs), and the potential over-reliance on risk-based regulation. It’s here that we see tension between existing norms and emerging capabilities, especially in contexts like facial recognition, employment, or predictive policing.
Part III – Governance, Policy, and Regulation
The final part considers institutional responses. There’s attention to soft law, national AI strategies, the role of the EU AI Act, and transnational governance proposals. The authors critique both regulatory overreach and under-specification, advocating for adaptive governance over static rulebooks.
💡 Why it matters?
This isn’t another list of AI principles—it’s a call to think structurally. The book offers a clear reminder: ethical principles are not enough if they’re disconnected from real design and institutional incentives. It provides legal scholars, ethicists, and policy advisors with vocabulary and argumentation to move debates beyond AI ethics-as-slogan into grounded regulatory design.
❓ What’s Missing
- Limited coverage of Global South regulatory perspectives.
- No applied case studies or implementation toolkits.
- Lacks actionable takeaways for tech practitioners—this is a theory-first, practice-second resource.
👥 Best For
- PhD students, law faculty, and policy researchers.
- Governance professionals building the theoretical case for regulatory reform.
- Legislators and civil society actors needing depth behind AI ethics claims.
📄 Source Details
Title: The Law, Ethics and Policy of Artificial Intelligence
Editor: Nathalie A. Smuha
Publisher: Edward Elgar (2024)
ISBN: 9781802205397
Pages: 300+
📝 Thanks to
📚 Edited by Nathalie A. Smuha, with contributions from leading scholars including Vincent C. Müller, Jeroen van den Hoven, and others. Thank you for advancing this multi-disciplinary foundation for AI governance.
Let me know if you’d like this review repackaged for your newsletter or as a comparative annotation with the EU AI Act.
