There's a prevailing concern in the corridors of legal education and law firms: What becomes of legal judgment in the age of AI? Can machines that analyze, draft, and identify risks replace the nuanced decision-making of trained lawyers? The answer, however, may surprise many. AI isn't replacing legal judgment; it's revealing how seldom we explicitly teach it.

This insight emerged from empirical classroom pilots conducted by the Product Law Hub using an AI-based legal coach named Frankie. The course aimed to see how students develop judgment skills required for legal practice when assisted by AI. The results were telling and pivoted more on the quality of AI explanations than on their correctness.

Teaching Judgment: More Than Spotting Issues

Legal training typically emphasizes the importance of judgment, expecting upcoming lawyers to adeptly weigh risks and make informed decisions. However, the actual training often hinges on correctness—did the student identify the correct issue and cite the appropriate authority? The assumption is that judgment will naturally develop along this path.

The classroom pilots challenged this assumption by providing students with realistic scenarios to navigate with AI's help. Surprisingly, the most substantial learning gains were not from the AI providing the right answers but from explaining why those answers were relevant in a given context. Students engaged more deeply and retained more when they understood the connection between legal issues and broader business impacts or stakeholder priorities.

From Correctness to Context: The Role of AI in Legal Training

Quantitative data from the pilot showed longer engagement times and higher completion rates when AI feedback linked legal decisions to practical business outcomes. Conversely, when AI feedback focused merely on correctness, students quickly moved on without grasping the broader implications of their choices.

This distinction underscores a critical point: legal judgment involves more than just finding the right answer—it requires understanding the 'why' behind it, a skill that needs explicit teaching.

The Misconception That Judgment Can't Be Taught

The persistent myth in legal circles is that judgment is an intangible quality gained only through experience. However, the pilot suggests that explicit instruction in judgment can significantly accelerate its development. AI, when programmed to elucidate reasoning paths and not just end results, can effectively supplement this learning.

Bridging the Gap Between Education and Practice

The pilot also revealed a close parallel between effective learning strategies in the classroom and those that enhance credibility in practice. Systems that provided contextual explanations built trust, while those that simplified complex issues too much tended to lose it. This observation is crucial as it suggests that the tools needed for effective legal education are the same as those required in practice.

Concluding Thoughts

AI has not made a case for the redundancy of lawyers but has highlighted a critical flaw in how they are trained. It underscores the necessity of teaching judgment explicitly—by modeling reasoning, explaining tradeoffs, and connecting legal decisions to their real-world consequences. This approach will not only refine the training of future lawyers but also enhance the capabilities of AI as a tool for legal education. The challenge now is to embrace these insights and transform how legal judgment is taught.