If you’re a judge reading this, take a breath. The goal here isn’t to paint you as the problem. Quite the opposite. The best judges—the ones who believe in the rule of law, who sweat the details and carry the weight of their decisions—are the very reason this question deserves serious thought.

Could a well-trained AI, with full access to case law, statutes, and party filings, deliver more consistent, more affordable, and more impartial trial-level decisions? Could it even outperform us?

Let’s test the idea—not out of disrespect for the bench, but out of respect for justice itself.

A System Rooted in Humanity—For Better and Worse

Our trial courts were built around human judgment. That made sense when typewriters ruled and precedent lived in books. But in a world of real-time language models and digital archives of every decision ever issued, we must ask: is tradition alone a good enough reason to keep relying on one person’s memory, mood, and mindset to decide the most important matters in people’s lives?

And more provocatively: how much longer can we pretend that “human discretion” is inherently better than structured logic?

The Case for AI in the Trial Courts

1. It’s cheaper. Much cheaper. Judges are well-paid—and they should be, given the gravity of their role. But with salaries north of $150,000 annually (not including staff, clerks, or pension obligations), trial courts are expensive to operate. An AI model capable of evaluating briefs, applying precedent, and issuing draft opinions could cost as little as $15–$50 per month. That’s not an argument to devalue human labor—it’s a fiscal reality that deserves attention in an era of strained public budgets.
   
   
2. AI has infinite recall. When asked to synthesize multiple cases and statutory provisions, a judge may lean on memory, experience, or a clerk’s memo. An AI, however, doesn’t forget. Give it full access to the Westlaw archive, or just upload the controlling authorities—and it can trace doctrinal threads with surgical precision. It’s not that AI is smarter than a judge. It’s that it doesn’t tire, doesn’t forget, and doesn’t rely on gut instinct.
   
   
3. No more bias. No more guesswork. Even the most conscientious judges can’t fully escape implicit bias. Whether it’s fatigue, frustration, or unconscious favoritism, human decisions are colored by context. In some trial courts—particularly family law—discretion is so vast that outcomes can shift dramatically depending on who’s presiding. As any lawyer for child custody appeals knows, the abuse of discretion standard makes reversals exceedingly rare. That discretion, for better or worse, can hide all manner of biases behind legally sufficient reasoning—meaning uttering the right magic words on the record before stating the ruling.
   
   
4. AI doesn’t play favorites. It doesn’t get annoyed at an attorney’s tone. It doesn’t rush a decision because the docket is heavy or lunch is late. It just applies law to fact.
   
   
5. No clerks, no court reporters, no translators. Real-time AI transcription is already approaching—if not surpassing—human court reporter accuracy. Add in multi-language translation capabilities, and you remove barriers for non-English speakers while capturing an immediate, searchable record. That’s not science fiction. That’s off-the-shelf capability today.
   
   If you’re an appellate lawyer, imagine not having to explain to your client why they need to pay $4,000 or more for a transcript, on top of your legal fees. Instead, within one minute of the court proceeding ending, an automated email delivers a near-perfect transcript for free. It doesn’t matter how long the hearing lasted, how many objections were raised, or how many different languages were spoken—the transcript is in your inbox before you even leave the courtroom, and it didn’t cost a dime.
   
   
6. It’s not about replacing judges. It’s about improving justice. Some will read this and assume it’s an attack. That’s not the point. The point is that our justice system owes its stakeholders—litigants, taxpayers, and even judges themselves—an honest look at whether technology can help us deliver fairer, faster, and more consistent decisions. And in many contexts, AI can.
   
   

Addressing the Objections

“But judges bring empathy.”

Empathy, when misapplied, becomes bias. Justice isn’t supposed to turn on how sympathetic a party appears. The law should drive outcomes, not emotion—particularly in systems built on predictability and equal treatment.

“But what if the AI makes a mistake?”

So do humans. The difference is: AI can be audited. Every line of reasoning, every logic path, every weighted factor—visible. Line by line. Judges, by contrast, are black boxes. We can’t scan their thoughts or feelings, or decode what really swayed them in chambers. Maybe someday we’ll be able to render human emotion and bias into something measurable. But until then, only one system gives us source code we can read—and fix.

“But what about oral argument?”

Let lawyers still present live or recorded arguments. AI can evaluate not just the words, but tone and demeanor—perhaps more objectively than a fatigued bench at 4:45 p.m.

A Modest Proposal: Let’s Pilot It

Start small. A hybrid system in a civil docket. Judges review and override AI recommendations only if necessary. Track results. Measure appeal rates. Benchmark timelines. See whether litigants find the outcomes fairer, faster, and more consistent.

Justice demands humility—and the courage to improve even what we think works.

Final Word: Know Thy Judge? Or Know the Law?

Today, experienced attorneys know which counties lean conservative, which judges dislike certain arguments, and how to “read the room” rather than just cite the rule. That’s a problem.

You shouldn’t have to know your judge. You should only have to know the law.

AI might not be perfect. But it doesn’t need to be perfect to be better. It just has to be consistent, transparent, and free of personal agenda. That alone would be a revolution.