AI Lawyer

Artificial intelligence is usually sold as productivity: faster research, faster drafting, faster answers. In this episode of New Law Order, Yale Law professor Scott Shapiro explains that the real story is power. If the law is a system for coordinating human behavior at scale, then tools that can interpret rules, test edge cases, and generate persuasive legal analysis may change who can navigate the system—and who gets steamrolled by it.

The conversation also explores a darker symmetry: the same tools that help people comply with legal obligations can help sophisticated actors evade them. Shapiro sketches the emerging role of artificial intelligence as both compliance engine and exploitation engine—and what that means for the balance of justice when the best “legal hacker” is a machine.
Shapiro draws a crucial distinction between generative models and rule-based systems. Generative tools can sound authoritative while being intentionally or accidentally wrong, which can present dangers. Rule-based approaches, by contrast, raise a different question: what happens when the logic is correct but the reasoning is no longer human-followable? At that point, “legal reasoning” starts to look more like an appeal to authority—raising uncomfortable issues about legitimacy, transparency, and trust.

In this conversation:
Law as a Social Technology: why legal systems exist and what they are built to do
Generative Models versus Rule-Based Reasoning: reliability, hallucinations, and explainability in legal work
When Legal Reasoning Stops Being Human: what legitimacy requires when the logic becomes unreadable
Artificial Intelligence as Exploitation: using models to find loopholes, stress-test regulations, and “break” contracts

Guest: Scott Shapiro is a Yale Law School professor and legal philosopher whose work explores the structure of legal systems and how technology changes the way law is interpreted and applied.

This episode originally appeared on the TalksOnLaw podcast New Law Order, a series exploring the future of law in an age of AI and structural change in the legal industry.
For more conversations with the figures reshaping the legal business, subscribe to New Law Order. For a CLE-eligible version of this interview and more legal analysis, visit www.talksonlaw.com. For questions or comments, email [email protected].

Guest: Prof. Daniel Solove, George Washington University Law School.

Artificial intelligence is radically shifting how our personal information is collected, shared and analyzed — and our traditional privacy laws are scrambling to keep up. In this episode we sit down with privacy scholar Prof. Solove, a leading expert on privacy law, to explore how AI is exposing the limits of the American right to privacy. From the third‑party doctrine to the landmark decision in Carpenter v. United States, Solove traces how government reliance on privately‑gathered data enables surveillance to expand without constitutional oversight. He argues that the privacy framework built for discrete searches is ill‑suited to a world of continuous, AI‑driven streams of personal data. Tune in to understand where we are, how we got here, and what might come next for privacy in the AI era.

Daniel Solove is a professor of law at George Washington University Law School and a leading scholar on privacy and data protection.

For attorneys, a CLE version of this interview can be found at www.talksonlaw.com or by following this link.

Guest: Prof. Tejas Narechania, Berkeley Law School.

This episode of the AI Lawyer Podcast explores the legal challenges of AI market concentration and competition with Professor Narechania, an expert in telecommunications law and antitrust policy. As the costs of developing advanced AI models rise, Professor Narechania examines whether AI is headed toward a natural monopoly and what that means for fairness, innovation, and legal accountability.

Will a small group of companies dominate AI development? What legal risks arise from monopolistic control over critical technologies? Professor Narechania breaks down the structural market forces driving AI consolidation and explains how antitrust laws, interoperability requirements, and public infrastructure models could shape the future of AI governance.

For attorney listeners, a CLE version of this interview can be found at www.talksonlaw.com.

Guest: Judge Paul Grimm, Duke Law Professor and former U.S. District Judge.

This episode of the AI Lawyer Podcast explores the “perfect evidentiary storm” created by generative AI and deepfakes in the courtroom. Judge Grimm, a leading expert on evidence and artificial intelligence, unpacks the legal, ethical, and practical challenges of AI in the justice system.

How can courts manage audio and video deepfakes that appear undeniably real? What are the dangers of relying on "black-box" AI systems in pivotal legal decisions? Judge Grimm provides essential insights and explains why the rules of evidence must evolve to meet the demands of AI-driven technology.

Guest: Prof. Mitt Regan, Georgetown Law School.

As autonomous weapons become a reality on the modern battlefield, their ethical and legal implications are sparking intense debate. Georgetown Law Professor Mitt Regan dives into the complexities of AI-enabled weapon systems, exploring how these technologies challenge the principles of international humanitarian law (IHL). With conflicts in Ukraine and Israel showcasing the rapid deployment of AI-driven military tools, Professor Regan unpacks the risks of automation bias, the importance of meaningful human oversight, and the gaps in existing legal frameworks.

Mitt Regan is a professor of law at Georgetown Law Center and an expert on the laws of war and international law. For attorneys, a CLE version of this interview can be found at www.talksonlaw.com or by following this link.