In this episode, Justin Wales, Chief Legal Officer for Crypto.com makes a second visit to the podcast. This time around, he discusses his new book, The AI Legal Handbook, the emerging regulatory landscape, liability frameworks, and practical applications of artificial intelligence. Justin outlines how attorneys and regulators should approach modern AI models, the mechanics behind AI, and the effect of generative AI on legal education. The discussion covers key regulatory principles, the balance between strict liability and negligence frameworks, copyright issues in machine learning training, and the governance challenges of artificial general intelligence (AGI).
Things We Talk About in this Episode
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Transitioning from cryptocurrency regulation to developing a unified framework for artificial intelligence law
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The importance of legal professionals understanding underlying model mechanics and token prediction to evaluate hallucination risks
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Generative AI’s disruption of law school assessments and the pedagogical shift from written assignments to oral examinations
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The convergence of cryptocurrency rails, agentic AI systems, and decentralized compute infrastructure
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Foundational principles for AI regulation, emphasizing proportional oversight, human-centered accountability, and transparency over outright bans
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Managing the “black box problem” and balancing algorithm explainability with technical efficiency
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Comparative analysis of sector-specific guidelines versus federal mandates and the adaptability of existing rules of professional conduct
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Evaluating legal liability standards: applying negligence versus strict liability to autonomous vehicles, healthcare diagnostic tools, and AI chatbots
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Intellectual property considerations, fair use, and style mimicry in generative model training data
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Preparing legal, economic, and governance frameworks for artificial general intelligence (AGI)
Where to buy The AI Legal Handbook: JustinWales.com or Amazon.
Episode Credits
Editing and Production: Grant Blackstock
Theme Music: Home Base (Instrumental Version) by TA2MI
