Explain to Shane

Artificial intelligence is transforming the legal and tax sectors of business. However, neither the legal nor the tax establishments may be ready for what’s coming. There's a real tension here. On one side, lawyers are using AI to draft filings and manage their work, and some firms are building their own AI systems. On the other hand, the legal world remains slow to adopt this new tool. What does that look like in practice? Would more consistent, data-driven outcomes make justice fairer, or merely more uniform? And when an AI system contributes to a legal decision, who is accountable if it gets something wrong?
To discuss this and more, Benjamin Alarie joins Shane. Benjamin is a leading voice in this debate and the coauthor, with Samuel Becher, of a new book, Superjustice: Law in the Age of Artificial Intelligence. He originated the concept of the “legal singularity,” the idea that advances in artificial intelligence could eventually make the outcomes of legal disputes almost perfectly predictable and perhaps even automate much of the practice of law. Ben is also the cofounder and CEO of Blue J, which uses the latest large language models and a vast database of authoritative tax content to deliver high-quality, source-driven answers to challenging tax questions.

Employees at several leading AI companies are asking the US government and international bodies to slow the development of frontier models. Doing so would put governments in the position of deciding when new models are safe enough to release. Yet policymakers also warn that the United States must move faster than China and that prerelease reviews could stifle innovation. Are these two goals in tension with one another? Can existing laws and liability rules address AI harms without giving governments control over which models reach the market? And can any international institution realistically govern a technology spread across the entire digital economy?
To discuss this, Shane is joined by Milton Mueller and Adam Thierer. Milton is a professor and director of the master of science in cybersecurity program at Georgia Tech University’s Jimmy and Rosalynn Carter School of Public Policy. He is also the cofounder and director of the Internet Governance Project at Georgia Tech. Adam is a resident senior fellow with the technology and innovation team at the R Street Institute and a visiting senior fellow at the Foundation for Individual Rights and Expression.

Until recently, concerns about AI agents conducting autonomous cyber operations were largely theoretical. The OpenAI–Hugging Face incident in July changed that, while Anthropic’s Mythos exposed software vulnerabilities buried for decades. Together, these incidents have forced policymakers to reconsider how governments and companies prepare for AI-enabled cyber threats. Can the federal government and private sector keep pace with increasingly capable models? Will open-source AI strengthen cyber defenses or make dangerous capabilities harder to contain? And can policymakers encourage companies to share threat information while holding them accountable for insecure systems?
Shane joins Evan Swarztrauber in a crossover episode with The Center Edge. Evan is the founder of CorePoint Strategies and a senior fellow at the Digital Progress Institute. He previously served at the Federal Communications Commission as a policy adviser to then-Chairman Ajit Pai and Commissioner Brendan Carr.

Americans rely on wireless connections for nearly every part of modern life, and demand for the airwaves that make those connections possible is only growing. But much of the nation’s spectrum remains accessible by federal agencies under a system approaching its 100th anniversary. How can the United States free up more spectrum for commercial use? Can the military rely more heavily on commercial networks without compromising national security? And could market-based incentives help federal agencies use this valuable resource more efficiently?
To discuss this, Shane is joined by Roslyn Layton, executive vice president at Strand Consult. She is also a digital policy fellow at Michigan State University’s Quello Center and a senior fellow at the National Security Institute at George Mason University’s Antonin Scalia Law School. She previously served as a visiting fellow at the American Enterprise Institute and on the president-elect’s transition team for the Federal Communications Commission.

New frontier AI models are changing the cybersecurity landscape. As advanced systems become more capable of finding and exploiting software vulnerabilities, the federal government is trying to determine how to protect critical infrastructure and maintain national security. The administration’s June executive order on AI and cybersecurity offers one answer, but it also raises several harder questions. Can the government keep up with rapidly developing models? If officials want to review every model before release, is that process really voluntary? And how can policymakers keep American networks safe without sacrificing innovation?

To unpack what comes next, Shane is joined by Kevin Frazier in a crossover episode with Scaling Laws. Kevin is the director of the AI Innovation and Law Program at the University of Texas at Austin School of Law and a senior fellow at the Abundance Institute. He has testified before Congress on artificial intelligence and emerging technology issues and is a regular contributor to Lawfare.