Judges, AI, Rule of Law
In 2024, UNESCO surveyed judicial actors across 96 countries: it found that 44% were already using AI tools, including ChatGPT, in their work. Only 9% had received any institutional training or guidance. Fast forward to 2026 — a pivotal year for AI adoption in legal systems around the world — and even jurisdictions that have yet to begin a national conversation about AI strategy are seeing more legal practitioners and judges experimenting with AI.
Last month, I spent a Saturday at the Inner Temple in London at a seminar on AI, human rights and the rule of law convened by the Bar Human Rights Committee of England and Wales with UNESCO’s Network of Experts on AI and the Rule of Law. In-person tickets sold out. Representatives from the Bar Council of England and Wales, the Law Society of England and Wales, JUSTICE, Doughty Street and the Thomson Reuters Foundation were in the room. More than a thousand participants in more than sixty-five countries joined by livestream.
The most thought-provoking framing came from Robin Allen KC in the closing session. Why do we believe in the rule of law at all? Because it is what stands between a society and street law. And it depends on one thing absolutely: the loser in any dispute must know enough about why they lost not to go looking for a remedy of their own. Anything that makes judicial decisions less explicable attacks that settlement directly. Current AI systems, ones that are black-boxed, where human oversight is a buzzword, where output is statistically plausible rather than reasoned, sit squarely in that category.
Allen provided a legal opinion to the Open Rights Group in March 2026 on the use of two AI tools by the Home Office: the Asylum Case Summarisation (ACS) tool, which summarises transcripts of asylum interviews, and the Asylum Policy Search (APS) tool, which summarises country-of-origin material (e.g. Country Policy and Information Notes (CPINs), guidance documents, and Country of Origin Information (COI) reports). These systems respectively summarised what asylum seekers said and matched claims against the Home Office’s retained country information. But the asylum seekers involved were not aware of it. The legal opinion concluded that the Home Office’s use of these AI tools in asylum decision-making did not conform with the principles in the AI Playbook for the UK Government and was at significant risk of being unlawful, in potential breach of the Secretary of State for the Home Department’s procedural obligations under Article 3 ECHR, various public law principles, data protection legislation and the public sector equality duty. When a parliamentary question asked how far the Home Office had complied with the Government’s own AI Playbook, Allen’s tally of ministerial awareness was: one hand up in Parliament.
And quietly, a threat aimed at judges themselves. Dr Margaret Satterthwaite, the UN Special Rapporteur on the Independence of Judges and Lawyers, gave the warning I have thought about most since. If a judge’s research and drafting runs through a commercial AI system, whoever can see the queries can see the judge thinking. Well-resourced litigants already model individual judges to predict outcomes and shop forums. France has restricted this. But shortly after the seminar, a colleague sent me Neal Katyal’s TED talk, in which the US Supreme Court advocate describes winning the Trump tariffs case with a bespoke AI system trained on twenty-five years of the justices’ questions and opinions. Katyal described how it predicted many of the questions asked at oral argument, sometimes almost word for word. That is judge-modelling as a star advocate’s openly declared edge. The talk drew its own backlash, too.
But imagine the modelling capability pointed at a bench by someone with worse intentions. Add inadequate protections, and AI-assisted judging becomes a surveillance channel into judicial deliberation, or what Satterthwaite called “epistemic capture”: lock the judiciary into a private system, and the system’s suggestions quietly become the boundaries of judicial thought. AI, she reminded the room, always involves a concentration of power — in the handful of companies that build it — and a potential transfer of power away from the people constitutionally charged with judging.
In some jurisdictions, Dr Kamel El Hilali of UNESCO noted, free-tier ChatGPT is being used to draft entire judgments.
According to the database at DamienCharlotin.com, the current tracked AI hallucination case count stands at 1,782. But Matthew Lee of Doughty Street shared that the interesting cases are no longer the ones where a lawyer gets caught. In the week before the seminar, an Italian court upheld a judgment on appeal notwithstanding a hallucinated citation in it; a US appellate court has done the same. Lee called the endgame the “8th time effect”: a hallucinated case is cited in a judgment, the judgment survives, the fake authority gets cited again — in academic work, in expert reports, in later judgments — until it hardens into legal principle. The corruption doesn’t announce itself. It compounds.
More than one speaker noted that the current England and Wales judicial guidance doesn’t require a judge to disclose whether or how AI was used. Every part-time judge Allen asked reported receiving no AI training at all; there is no mandatory requirement. He called it a total failure of leadership, and drew the comparison: when the Human Rights Act came into force, it was accompanied by two years of mandatory judicial training. The judiciary has done this properly before. It is choosing not to now.
Dr John Sorabji — who is helping prepare the Council of Europe judges’ 2026 opinion on judicial AI use — pushed the concern somewhere subtler. The obvious danger is substitution: the tool, not the judge, drafting the judgment. The insidious one is deskilling. If judges outsource the small cognitive work — summarising, drafting, even email, as many lawyers now do — they are slowly simplifying their own capacity to think and write critically. The limits of my language are the limits of my world. Lawyers, especially those trained in common law, recognise the nuances inherent in language and differing perspectives on the notion of ‘truth’. As one panellist put it, discussions about AI, shaped partly by computer science, often assume there is a single right answer — pushing towards one definition instead of a range of responses, losing nuance and context, reducing it all to writing that gets turned into 1s and 0s. What is a fact? What is fairness?
Sorabji’s half-serious proposal: mandatory minimum hours of AI-free work, the judicial equivalent of keeping the muscles from atrophying. Handing powerful tools to untrained users, he offered, is like giving a Ferrari to a seventeen-year-old.
The seminar was not all scepticism and no solution though. In December 2025, UNESCO published the Guidelines for the Use of AI Systems in Courts and Tribunals. It contains recommendations for judges, court staff and practitioners on the development, procurement, deployment and use of AI in justice settings. It was built from consultations across 160+ countries, designed for national adaptation, and is available online free of charge. In addition, UNESCO’s AI Essentials for Judges for the non-expert bench, its Global Toolkit on AI and the Rule of Law, and an 18-hour self-paced MOOC on AI, justice and the rule of law are also freely available.
To the small jurisdiction that is wondering what to build itself, and what it should take off the shelf, it would seem obvious that these are better starting points than, say, directly adopting Google search result AI summaries and using them to inform judicial thinking.
Materials from various jurisdictions offer useful reference points. Some working examples from the seminar: Brazil piloted its own internal judicial AI carefully, adjusted it, and when litigants started injecting hidden white text into filings to game it, sanctioned the lawyers and published a public alert. Singapore dismisses claims and fines litigants who file hallucinated citations, and litigants in person are directed to the official verification tools, namely the eLitigation GD Viewer for case law and Singapore Statutes Online for legislation. The US federal courts deliberately confine AI to narrow, repetitive work — e-filing automation, first-run transcription with human review, internal knowledge bases — and keep it away from adjudication.
I had more questions than answers from that seminar last month, but one thing is clear. Judges who are quietly experimenting with AI do not have to invent anything new overnight. They have to choose.
I attended the BHRC x UNESCO seminar on AI, Human Rights & the Rule of Law at the Inner Temple, London, 20 June 2026. The event was livestreamed; quotes are from my contemporaneous notes. Views are my own and nothing here is legal advice. This is AIOM, (hopefully) fortnightly from the Isle of Man. Feel free to subscribe if you think the interesting experiments are happening in places you haven’t been watching.