Tag: law

AI in the courtroom: promise, safeguards, and the digital reality

Where the AI Act draws the line

When the IBA panel asked me to say a few words about the EU AI Act, one question stood out: what does it mean for courts? The Act treats certain AI uses in the administration of justice and democratic processes as high risk because they can pose risks to democracy and the rule of law. An example is a system that helps a judicial authority reach a ruling with legal effect. Such systems must meet requirements designed to prevent or reduce those risks, including risk management, data quality, technical documentation, registration, transparency, and human oversight. As public authorities and entities providing public services, courts and judiciaries must also conduct a fundamental rights impact assessment for high-risk systems.

Support the judge, not replace them

AI can support judicial decision-making and judicial independence, but it must not replace the person making the final decision. The Act also draws a distinction between that kind of assistance and purely ancillary administrative work that does not affect the administration of justice in individual cases. Examples of the latter include anonymizing or pseudonymizing judicial decisions, documents, or data; facilitating communication between personnel; and carrying out administrative tasks. The high-risk classification should not extend to systems used solely for those ancillary activities.

What are courts using today?

To see how courts in Council of Europe member states are using technology for administration and decision support, I turned to the most recent CEPEJ evaluation report. If CEPEJ’s “case management” category is treated as ancillary administration, it has the highest score on the ICT Deployment Index: 5.66. If “decision support” includes assistance in reaching rulings with legal effect, its score is much lower: 2.64. Those comparisons depend on how the categories are interpreted. CEPEJ says the figures show that countries are still focused on basic digital infrastructure, such as e-filing and case registration.

The next wave is taking shape

The EU Justice Scoreboard reports that nine out of 27 EU member countries report using AI for “core activities”. The current CEPEJ evaluation cycle also shows that AI is being used in areas such as class actions, automatic anonymization of judgments and specialized translation. These developments may become more visible in the next evaluation cycle. For now, the contrast is striking: while the possibilities are expanding, the foundations of court digitalization are still being built. Those statistics are dated 2022. CEPEJ says it will publish its next evaluation in December 2026, with more recent information on the use of AI.

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.