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Recently there has been a remarkable advance in how artificial intelligence can directly impact the world: A layperson can vibe code an AI “agent” into existence and give it a task, and with little human oversight the bot will try to complete said task. But if the agent goes rogue and causes harm, who should be held accountable?

The legal system already has a framework for addressing such issues, according to Jordi Weinstock, Harvard Law School lecturer on law and Berkman Klein Center for Internet & Society adviser. It comes from assigning AI agents to a canine framework that determines — based on how “domesticated” or “dangerous” it is — whether it’s a Pomeranian, a pitbull, a fox, or a wolf. Weinstock explains in an interview lightly edited for clarity and length.

What is agentic AI and why is someone from Harvard Law School teaching about it?

Agentic artificial intelligence has become a buzzy term and is used for all kinds of things now, but a classic definition for agentic AI is that it’s an autonomous system that acts on behalf of a user or person, usually with little specific direction, to achieve a goal, and it does so by going about the world and imparting an impact on the world. In this moment where the term is being used very liberally, to me the most important element is that it’s an autonomous AI system that impacts the world directly.

The reason that is interesting to someone who teaches law and should be interesting to anyone studying law is because when a system can impact the world, it can harm the world. The law is very concerned with that. I focus on tort law, which is synonymous with the concept of responsibility — who is responsible when someone is harmed? Our legal system is built on the idea that harms that are redressable are those that are committed by a person or a corporation that is responsive to a court. But now we have the reality of entities that go about the world which aren’t necessarily responsive to a court.  At the end of the day, it’s a new class of thing out in the world and our legal system needs to adapt and embrace and understand that that exists and to evolve to accommodate for the impacts that it will have.

You’ve developed something you call the Canine Agentic Framework. Can you explain what that is and why people should care if an AI agent is a Pomeranian or a wolf?

I started teaching about agentic artificial intelligence eight years ago when I led a reading group at Harvard Law School about autonomous vehicles. In my view, an autonomous vehicle is a simple-to-understand version of an AI agent. When I was leading that reading group I was trying to show students that there’s something out in the world that can cause harm that isn’t human — how do you think about legal responsibility when that happens?

Canines are a great way to think about this because there’s a whole spectrum of canines, from Pomeranians to wolves, that could cause harm and are not human, and our society has spent some time thinking about who should be held responsible if they hurt someone. With a fluffy little Pomeranian, if it bites you, you know who to sue — you sue its owner. But if a wolf bites you, there’s no one to sue.

Now in the last couple of years, I’ve significantly expanded upon this concept in collaboration with Professor Jonathan Zittrain and Berkman Klein Center chief AI scientist Josh Joseph, in part through our course on “Agentic AI and the Law.” We’ve been thinking about this framework in multiple dimensions, specifically domesticity and dangerousness.

To some people it may seem like this analogy between canines and AI systems is a strain, but as agentic systems are developing and being deployed in the world, they really do seem to be mirroring this rubric.  We can measure agentic systems on both their domesticity — their relationship to a responsible party or how much you can control the AI system — but also you can measure their dangerousness.

“We can measure agentic systems on both their domesticity — their relationship to a responsible party or how much you can control the AI system — but also you can measure their dangerousness.”

Does the AI agent have access to money? That makes it much more dangerous. When explaining this to others, people can understand the idea that a pitbull is more dangerous than a Pomeranian, and that if a fox bites you there’s nothing you can do about it legally, but it probably won’t be as harmful as if a pitbull bites you. We’re starting to map that out onto agentic systems to demonstrate that which we’re just...