I have taught several different courses on law and AI at Emory Law, and I’m currently teaching “Current Topics in the Law and Policy of AI.” I’m not wild about any of the Law & AI textbooks currently available (but they are getting better), and I think most people in the field are still teaching their own bespoke courses, like I do. What is missing from those courses is a general introduction that sets the stage for all of the material that follows, and so I have tried to fill that gap with a simple online Primer.
Part I is the background. What is AI, how we got here, how large language models work, why prediction is not the same thing as truth, and why systems that had improved slowly for decades suddenly became astonishingly capable.
Part I also covers what has happened since ChatGPT: the long 2023, the long 2024, and the turn since 2025 toward deployment and state regulation.
Part II is the policy. Why anyone wants to regulate AI at all, taking the benefits, the harms, and the real uncertainty between them seriously. How AI changes problems the law already knew about: the declining cost of malicious activity, surveillance through accumulation, inference, biased proxies, opacity, manipulation, distribution, and concentration. And how to think about law and AI, including where existing law is a starting point rather than an answer, the difference between regulating uses, capabilities, and domains, and what to make of arguments about artificial general intelligence.
In total, the primer runs to about 8,000 words, divided across six reasonably modular chapters.
I primarily wrote this for my students. But if you are putting together a Law and AI syllabus, or you just want to follow the argument without a computer science degree, help yourself.