John O. McGinnis (Northwestern), The Unbundling of Legal Education:
Artificial intelligence is improving both quickly and in ways that increasingly matter for legal practice and legal education. One of the most important developments has been the rise of reasoning models to supplement large language models (LLMs). Earlier, LLMs were best understood as systems for fast, fluent text generation. But newer reasoning models are designed to spend more time on planning, deduction, and problem-solving. Models now also include agents that can use tools to look up information on the Internet, reducing the likelihood of hallucinations.
The result is an AI system that can deliberate for far longer than earlier models, draft extended memos, and solve increasingly complex problems. … These improvements profoundly affect the creation of legal information. In some contexts, frontier models can now answer online student questions with speed, fluency, and accuracy that rivals what a professor can provide on the spot. They can also produce a series of legal memos in a day that would have required a research assistant days, if not weeks, of effort.
What does this mean for legal education?
The first question is how it will change the legal profession, because legal education is downstream of the profession’s needs. Clients will not pay lawyers to do tasks that machines can perform more cheaply. The rise of analytic legal machines will not kill all the lawyers, but it will transform what lawyers do, what clients will pay for, and what law schools must teach. Lawyers must continue to adapt their work as AI capabilities evolve. …
Law schools should respond in several ways. First, they must ensure that AI literacy becomes part of professional formation. Even as AI replaces coding, companies continue to hire software engineers who can harness AI to write code. Being a master of AI is no less valuable for lawyers. Students need to learn how to use AI, but also how not to be used by it. …
Second, assessment must change. If students practice in an AI-rich world, we should stop designing assessments for every kind of course as though AI does not exist. …
Third, law schools should teach the strong bundle. That means more exercises that bring together doctrine, facts, ethics, strategy, and institutional roles. …
Fourth, we need more training in oral and rhetorical skills. …
Finally, AI will move us toward a more relational economy because humans still value human relations. Client counseling, negotiation, interviewing, leadership, and ethical judgment are key skills in this relational world. They are the parts of the legal bundle least likely to be commoditized. …
Of course, if AI continues to improve rapidly, as I expect, more radical reforms may be required. Some legal work today is protected less by technical necessity than by legitimacy, convention, and the human need for responsibility. It is still hard to imagine an AI arguing in court, counseling a board, or standing before a client and taking responsibility for a judgment. But conventions can change when technology changes what seems possible, useful, and legitimate. One can imagine, for instance, that in arbitration, the parties may choose to restrict themselves to AI lawyers and an AI judge to enhance predictability and thus the value of the contract. But the law school that begins now to train lawyers in judgment, persuasion, and the intelligent use of machines will be far better prepared for the next round of changes demanded by the accelerating progress of AI.
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