AI in the courtroom

In these coming months, I will be thinking about AI in the courtroom as preparation for panel discussions and workshops: AI and its uses, regulations, implications for judicial reasoning, as a challenge for courts and judiciaries and their role in society. I will share those thoughts in this and upcoming blogs.

 

AI in the courtroom: a world-wide experiment

We are all part of a worldwide experiment. An experiment is a procedure carried out to determine the efficacy or likelihood of something previously untried, to provide insight into cause-and-effect by demonstrating what outcome occurs when a particular factor is manipulated. For the world-wide AI and justice experiment, we all provide materials, input, for the experiment to test the effects of the output of artificial intelligence. Most of the input is probably case law published online. The output is AI results, the factor to be manipulated is the workings of the AI.

Lawyers’ and case parties’ case information needs to be correct, and it also needs to be explainable, that is, based on solid reasoning and recognized sources. When the discourse found AI did not explain  what its sources were, the output factor was manipulated, and the references were included. So now, we can at least see where the information comes from. But that has not solved the problem. AI’s sources are not always real; AI fabulates sources, apparently because it is trained to please the users. The sources may be non-existent, they may exist but be irrelevant to the case, and they may argue something completely different. Courts and lawyers found this out when they checked the sources in claim documents. Court staff now need to check each reference, which creates a lot of extra work.

Judges using AI for their judgments also need to conform to some rules. One is fair procedure: parties must have equal opportunities to put their own case forward and test the other party’s case. This is standard case law now. Judges must also be transparent in their use of AI: in general search results, in testing evidence parties must have a chance to test the results. For judges finding general search results on the internet, judges searching for information. factual data not in the case file, but found on the internet of its own accord the case law is clear. The information needs to be disclosed and parties need to be given the opportunity to present arguments on the matter. Judges also need to be transparent about AI in composing their judgments. By now, there is an abundance of guidance on the use of AI. I will discuss that in another blog. 

 

Court Data: Now You See It, Now You Don’t

Some time ago, over lunch, I spoke with a justice who leads a team at a supreme court. Our conversation began with UNODC’s work to support women judges, but soon turned to a deceptively simple question: how should courts use performance data?

This question brought back a vivid memory from my own time as a judge. As an experiment, our team received a printout showing how many judgments each judge had produced over a given period. One colleague appeared to be performing exceptionally poorly. Yet the figures did not lead to a constructive conversation. My team leader felt he could hardly send this distinguished former lawyer to a judgment-writing course without embarrassing him. The printouts disappeared—and we never saw them again.

From embarrassment to improvement

The problem was not the data itself. It was the culture surrounding it. The figures were treated as a ranking—as evidence of winners and losers—rather than as a starting point for learning. So, I asked my colleague how she used the information generated by her court’s case-management system. Did it help her identify difficulties? Did she discuss it regularly with team members? Could judges see their own results, or those of the team as a whole?

She told me that she used the data primarily to spot problems. That is valuable—but it is only the beginning. I believe the entire team should have access to the team’s performance data, provided the figures are interpreted carefully and used fairly. Transparency allows judges to understand the average, see patterns, identify colleagues who may be able to offer advice, and recognize where they themselves can help. Used well, shared data can strengthen a culture of cooperation rather than competition.

What court data can reveal

Three of the most common, useful measures concern timeliness: clearance rate, time to disposition, and the age of the active pending caseload. Together, they show whether a court is keeping pace with incoming work, resolving cases within expected time frames, and allowing unresolved matters to grow old.

These measures are useful precisely because they can expose problems that are not obvious from individual output alone. While helping to design a digital procedure for appellate courts, for example, I discovered that the courts’ biggest constraint was a shortage of hearing rooms. If a case must wait nine months for a room, improvements elsewhere in case management will have only a limited effect.

Court data can reveal much more. Changes in the volume or type of filings may show whether diversion programs, alternative dispute resolution, or procedural reforms are working. Backlogs—cases that should already have been resolved—may point to bottlenecks, staffing shortages, or mismatched funding. Those pressures can also fall disproportionately on particular groups of court users. Data should therefore prompt questions, not merely produce rankings.

When measurement becomes a target

Performance measures also create risks. When funding or prestige is tied too closely to a metric, people may be tempted to manipulate the metric rather than improve the underlying work. In one recent case, a former colleague faced criminal charges for allegedly falsifying the signatures of two other judges on decisions he had made alone. The court received more funding for cases decided by a three-judge chamber than for cases decided by a single judge. His defense was that he had acted in the court’s interest.

That example captures the paradox of performance data. Hide the figures, and courts lose opportunities to learn. Turn them into crude targets, and the figures can distort behavior. The better approach is transparent, contextual, and developmental: share the data, discuss what lies behind them, and use them to improve systems as well as individual practice. Court data should be a mirror, not a scoreboard—and never a reward for making the numbers look good.

 

A Writer Needs Readers

Someone recently told me they had read my work — and appreciated it. That simple moment mattered more than I expected. Hearing that my long commitment to IT for courts still resonates reminded me that I still have things to say, and that there may still be people who want to hear it.

Over the past months, I’ve been rethinking the role of technology in justice. Technology evolves, court users’ needs shift, and the principles that anchor justice — impartial judging, independence, fairness, transparency, reasonable time — must continue to guide how we design and govern digital systems. As I wrote, this means ensuring that IT, including AI, supports performance, not just efficiency.

What surprised me was discovering that this “new thinking” wasn’t new at all. It has been present in my work since the early 2000s, from my first article in Nederlands Juristenblad to Doing Justice with Information Technology and even earlier, in a 2002 speech on “IT dreaming and reality.” The thread has always been the same: technology should strengthen the core values of justice.

My fascination with IT began even earlier. In 1984, during an internship, I encountered two enormous Wordplex machines used to produce arbitral decisions. It was primitive by today’s standards, but transformative then — a glimpse of how digital tools could improve the work of justice. That spark eventually led to the first information policy plan for the Netherlands judiciary in 2000, framing IT as a driver of performance improvement.

Rediscovering this history has reminded me why I started writing about justice and technology in the first place — and why I want to continue. There is still experience to share, still lessons worth passing on, and still readers who care about how courts evolve.

So, I’ll keep writing. And I hope you’ll keep reading.