Stop Reinventing Jury Instructions - GenAI Use Case

Every trial judge knows the moment. It is late in the day, counsel are debating language, and someone hands up a proposed charge pulled from a case you vaguely recognize. Another lawyer insists the pattern instruction is outdated. A clerk is searching through old files while you edit in real time and a jury waits down the hall.

At some point, most judges have the same thought. There has to be a better way to run this part of a trial.

There is, but it requires us to stop treating jury instructions as disposable documents and start treating them as institutional knowledge.

Over the course of a career, every trial judge builds a quiet collection of charges. The ones that worked. The ones that survived appellate scrutiny. The ones you refined after watching jurors wrestle with language that should have been clearer the first time they heard it. Yet too often those improvements live in scattered folders, aging hard drives, or the memory of a former law clerk. We solve the same problem repeatedly, not because it is unsolvable, but because we have never captured the solution in a durable way.

Trial judges should be building a living knowledge base of jury instructions.

Pattern instructions are the obvious foundation, but they should not be the ceiling. Gather the language you trust. Preserve the charges that held up on appeal. Borrow great phrasing from respected colleagues. Keep the versions that worked exactly the way you intended in front of a live jury. What begins as a personal library gradually becomes judicial memory that improves rather than resets with each trial.

This is where GenAI becomes useful long before a jury is ever sworn. Instead of assembling instructions during a charge conference, judges can use these tools ahead of time to organize and maintain their library so it is searchable, structured, and ready when needed. The law remains yours. The judgment remains yours. What disappears is the unnecessary assembly work.

Once that library exists, the dynamic inside the courtroom changes. You are no longer drafting under pressure. You retrieve, tailor, and refine. The time savings matter, but the real benefit is cognitive. When you are not expending energy assembling familiar instructions at the edge of exhaustion, you preserve mental bandwidth for the decisions that actually require judicial judgment.

Here is what that looks like in practice.

Assume you just tried a murder case with an added firearm charge. In a modern GenAI workflow, you would upload the indictment and give a simple instruction. Draft the jury charges using my standard instructions as the default. Build the set that corresponds to the counts in this indictment and format it the way I typically deliver it in court.

Then you add the only thing that changes from case to case. If self-defense is at issue, include the self-defense charge from my library. If there is a lesser included issue, pull the responsive verdict language and the related instructions. If counsel has submitted a special charge, compare it to the closest instruction in my library, flag any departures, and offer a clean version that tracks the governing law without importing unnecessary risk.

That is the difference. The base instructions are not something you re-create during trial. They are something you retrieve. The judge’s time is spent on the special issues, not on assembling a package that should already exist.

This same approach improves the charge conference itself. Lawyers will always propose special charges. Some will be excellent. Others will be recycled from questionable sources. Occasionally one introduces subtle appellate risk hiding behind otherwise persuasive language. A well-built knowledge base, paired with a secure GenAI tool, allows a judge to evaluate those proposals quickly by comparing them against vetted instructions, highlighting doctrinal tension, and flagging departures from language you already trust.

The judge still decides what goes to the jury. That responsibility does not shift. What changes is the speed and clarity with which the decision can be made.

A thoughtfully developed knowledge base promotes stability while fully preserving judicial discretion. Judges remain free to adapt language to the facts before them, but they do so from a tested foundation.

Over time, that foundation becomes institutional durability. Clerks move on. Judges retire. But the work does not disappear. Each trial makes the system better instead of forcing the next judge to begin again. It is not difficult to imagine courts eventually building shared repositories across divisions, perhaps even statewide. The jurisdictions that begin now will shape what those best practices look like. Those that wait will inherit someone else’s version.

None of this requires a sweeping legislative effort or a significant technology budget. A single judge can start tomorrow. Gather your strongest charges. Refine them. Store them somewhere searchable. Let AI assist with organization, retrieval, and comparison. Build the system once, then allow it to improve continuously.

The judiciary rightly respects tradition, but tradition was never meant to lock us into inefficient habits. Our obligation is not to preserve the mechanics of the past. It is to ensure the system functions as well as possible for the people who depend on it. Jurors deserve instructions they can follow, and judges deserve tools that protect their focus for the work only they can do.

No trial judge accepted the robe because they enjoy rewriting the same jury charge for the twentieth time. The modern trial courtroom will be shaped not only by what happens in front of the jury, but also by the operational decisions judges make long before the first witness is sworn.

Building a durable library of jury instructions is one of those decisions, and it is entirely within our control.