On the morning of 18 March 2026, Deborah Leslie stood at the lectern of the Supreme Court of Georgia, in downtown Atlanta, and tried to explain why several of the cases in her brief did not exist. Leslie was an Assistant District Attorney with Clayton County, assigned to appellate work and assets forfeiture, and she had filed papers opposing a new trial for Hannah Payne, a young woman convicted in 2023 of the murder of Kenneth Herring after a hit-and-run on a Clayton County road in 2019. Payne, then twenty-five, was serving life with the possibility of parole. Her lawyer, Brian Steel, had filed for a fresh trial on the grounds that her original counsel had failed to ask the jury to consider citizen's arrest as a defence. The state's response, signed by Leslie, ran to dozens of pages. It cited authorities. The authorities, in many places, were imaginary.

Chief Justice Nels Peterson did not bury the point. From the bench, he counted aloud: at least five citations to cases that did not exist, and at least five more to cases that existed but did not say what Leslie's brief claimed they said. The video of the exchange, which would later be viewed more than five million times across various clips, has the strangled politeness of a hearing that everyone in the room knows is going badly. Leslie initially suggested the citations might have been added to the version filed with the court rather than the one she had drafted. Peterson noted that the same non-existent cases appeared in the brief opposing Payne's motion below. The implication was unavoidable. The phantom citations were hers.

A week later, on 27 March, Clayton County District Attorney Tasha Mosley wrote to the Chief Justice. The letter, published shortly after by local outlets, conceded what was already obvious. Leslie had used artificial intelligence to draft the filing. She had not verified the output. The office had moved against her: a grievance with the State Bar of Georgia, suspension, a performance improvement plan, loss of privileges. In her own affidavit, Leslie said the errors were not intentional and that the references “were not independently verified before inclusion.” The Hannah Payne appeal, a case with a victim's family, a defendant on a life sentence, and a contested constitutional argument about the right to effective counsel, had been compromised by language a model invented in a few seconds at no cost.

The Georgia incident is not anomalous. It is the latest, most public entry in a list that legal scholar Damien Charlotin, who divides his time between Sciences Po Law School and HEC Paris, has been building since April 2025 in a database he started because he could not find anyone else doing the work. By the spring of 2026, his AI Hallucination Cases tracker had passed 1,200 documented incidents from courts around the world, with roughly 800 from the United States alone. On a single day in March 2026, he logged seventeen. The rate, Charlotin has said, is still rising. What began as a curiosity in late 2022, when ChatGPT first leaked into the workflows of overworked solicitors and overconfident litigants, has become a structural feature of contemporary legal practice. The machine is in the building. The machine lies. Sometimes the lies get caught. Sometimes they do not.

Lay this fact alongside another, less visible one. According to the Legal Services Corporation's 2022 Justice Gap study, conducted with NORC at the University of Chicago, ninety-two per cent of the substantial civil legal problems experienced by low-income Americans receive no, or insufficient, legal help. Seventy-four per cent of low-income households face at least one such problem in any given year. In England and Wales, Ministry of Justice statistics for the third quarter of 2025 showed that fifty-nine per cent of civil cases in the County Court involved at least one party with no legal representation. In state civil dockets across the United States, self-representation rates routinely exceed ninety per cent in housing, family, and consumer cases. The justice gap is not a metaphor. It is the operational reality of most non-criminal courtrooms in the English-speaking world.

This is the contradiction at the heart of the moment. Generative AI is the only piece of legal infrastructure that has, in living memory, become cheaper and more widely available rather than more expensive and more rationed. For the unrepresented mother fighting an eviction, the asylum seeker filling in a witness statement at midnight, the small employer hit with a discrimination claim, a free large language model is, on its worst day, more responsive than the legal aid hotline that has not picked up in three hours and, on its best day, capable of producing a coherent draft of a defence. The same technology, deployed by a tired prosecutor in a county DA's office or a partner under deadline at a magic-circle firm, can introduce phantom precedent into the foundations of a criminal appeal. AI is simultaneously democratising access and corrupting the evidentiary substrate. There is no clean way to keep one without the other.

The Hallucination Problem, Precisely

It helps to be technical about what is happening, because the loose language around “AI mistakes” understates the issue. A large language model does not retrieve. It predicts. Given a prompt, it generates the most statistically plausible next token, then the next, conditioned on its training data and on whatever it has just produced. When the prompt is “cite a case supporting the proposition that an officer's mistaken belief in probable cause is reviewed for objective reasonableness”, the model produces something that looks like a citation, because in the training data the answers to such prompts are followed by things that look like citations. Volume number, reporter, page, year, parenthetical court abbreviation. The format is the easy part. The model has internalised the format. What it has not internalised is the existence of the case.

This is why the hallucinations are so dangerous. They are not random. They are formally correct. A fabricated case will have a plausible volume number for the reporter, a sensible district, a year that lines up with the legal doctrine being argued, and often a holding that maps onto the proposition being supported. The fabrication is grammatical. The citation, considered in isolation, is indistinguishable from a real one until someone looks it up. The Stanford RegLab's preregistered study by Varun Magesh and Faiz Surani, published in the Journal of Empirical Legal Studies, gave the phenomenon a metric: even legal-specific tools hallucinated at startling rates. Westlaw's AI-Assisted Research generated incorrect or fabricated information thirty-three per cent of the time in their tests. LexisNexis's Lexis+ AI hallucinated seventeen per cent of the time. Thomson Reuters' Ask Practical Law AI sat near the same number. Premium products. Trained on real case law. Marketed to professionals. Still inventing.

The roll call of incidents starts with Mata v Avianca, the Manhattan personal-injury suit against the Colombian airline that became the founding text of the genre. In June 2023, Judge P. Kevin Castel of the Southern District of New York imposed sanctions of $5,000 on attorneys Steven Schwartz and Peter LoDuca, and on the firm Levidow, Levidow & Oberman, after Schwartz used ChatGPT to research a brief that ended up citing six cases that did not exist: Varghese v. China South Airlines, Martinez v. Delta Airlines, Shaboon v. EgyptAir, Petersen v. Iran Air, Miller v. United Airlines, and Estate of Durden v. KLM Royal Dutch Airlines. When opposing counsel pointed out that the cases could not be found, Schwartz had asked ChatGPT whether they were real; the model assured him they were and produced fabricated full texts. He had been a member of the New York bar since 1991. “It just never occurred to me”, he testified, “that it would be making up cases.”

Then came the parade. In late 2023, Michael Cohen, the former personal lawyer to Donald Trump, sent his attorney three citations he had pulled from Google's Bard, all fabricated, in support of a motion for early termination of supervised release. The judge declined to sanction Cohen but called the episode “embarrassing and certainly negligent”. In Texas, in November 2024, Judge Marcia Crone of the Eastern District sanctioned Brandon Monk in Gauthier v. Goodyear Tire & Rubber Co. after a brief produced with the help of Anthropic's Claude cited authorities that did not exist. In June 2025, the High Court of England and Wales handed down its joined judgment in Ayinde v London Borough of Haringey and Al-Haroun v Qatar National Bank QPSC, a decision that read less like a routine ruling and more like a public warning. The grounds for review in Ayinde, drafted by a barrister called Ms Forey, misstated section 188(3) of the Housing Act 1996 and cited five non-existent cases, including a phantom “El Gendi v Camden LBC”. In Al-Haroun, a solicitor's witness statement contained eighteen authorities that did not exist, with others misquoted or inapplicable, after the solicitor relied on his client's research without verifying it. The Divisional Court was blunt: GenAI does not extinguish professional responsibility, and Rule 11 equivalents in England and Wales apply with full force regardless of whether a human or a model produced the text.

Australia has produced its own running list. On 19 July 2024, before Justice Amanda Humphreys in Victoria, a solicitor in a marital dispute submitted a list of “relevant” prior cases that turned out to have been generated by AI. He became, that year, the first Australian lawyer formally sanctioned for AI-generated fabrications. He was barred from practising as a principal and required to work under supervision for two years. In August 2025, before the Supreme Court of Victoria, defence lawyer Rishi Nathwani, KC, apologised to Justice James Elliott for filing submissions in a teenager's murder trial that included fabricated quotes from a speech to the state legislature and non-existent citations purportedly from the same court. The errors caused a twenty-four-hour delay; Elliott eventually ruled the youth not guilty of murder by reason of mental impairment, but the embarrassment to the bar was complete. In the months that followed, a Western Australian solicitor was referred to that state's regulator for tendering documents citing four cases that either did not exist or were misreferenced.

South Africa joined the parade in 2025. In Mavundla v MEC: Department of Co-Operative Government and Traditional Affairs KwaZulu-Natal, the KwaZulu-Natal High Court found that of the nine authorities Mavundla's legal team had cited, only two were real. Among the fabrications was a confidently asserted “Hassan v Coetzee”, complete with a citation, a court, a year, and a tidy doctrinal proposition, none of which corresponded to any actual case. The court referred Mavundla's lawyers to the Legal Practice Council for investigation and ordered them to bear the costs of a hearing in which an inordinate amount of judicial and counsel time had been spent searching for cases that were never going to be found. The Cliffe Dekker Hofmeyr alerts that catalogued the affair noted, drily, that good intentions and apologies were no longer mitigation. They were table stakes.

Charlotin's tracker captures the cumulative shape. The early cases were almost all lawyers. By 2025, the share of pro se litigants caught submitting fabricated citations had grown sharply; Bloomberg Law reported that at least twenty-four self-represented litigants in the United States had been hit with monetary sanctions for AI-generated filings in the eighteen months following the second half of 2023. The trend in the data is unmistakable. The technology is not going away. The hallucinations are not going away. Adoption is outpacing verification, and the courts are catching up by issuing sanctions and warnings rather than by deploying any meaningful screening.

The Other Side of the Same Coin

Now consider who else is using these systems, and why. The New York State Bar Association published a piece on 10 February 2026 by its Pro Se Advocacy interest section titled “Pro Se Advocacy in the AI Era: Benefits, Challenges, and Ethical Implications”. The article does not pretend to resolve the contradiction. It frames it. It catalogues the practical uses to which an unrepresented person might put a chatbot: drafting letters to the court, preparing a defence to a parking ticket, navigating procedural requirements that the court itself communicates through forms a non-lawyer cannot reliably parse. It also notes the obvious risk: hallucinations that look like citations, advice that looks like guidance, and a tool that the client cannot themselves audit. The piece poses the question that the legal profession has, until very recently, been allowed not to answer: “Are the people, who otherwise would not have legal counsel, better served by at least having a chatbot to assist them?”

Similar commentary has come out of South Africa and Australia in the same window. The South African Daily Maverick ran a piece in July 2025 arguing that AI hallucinations were threatening the administration of justice in the country, while simultaneously acknowledging that the country's own access-to-justice gap, particularly in family and labour matters, had created a population for whom no realistic alternative to AI-mediated self-help existed. In one widely cited case, a self-represented litigant called Mr Makunga drafted heads of argument with the help of AI tools and online research, and the presiding judge commended the quality of his submissions, noting that some members of the practising bar had filed worse arguments than the AI-augmented ones. The South African legal profession is in the position of warning the public against the same technology that is, for many of those same members of the public, the only legal-adjacent help on offer. Australian commentators have made the same point, often more sharply: that decades of cuts to legal aid have produced a country where AI is not a luxury for the poor litigant but the default.

The numbers confirm what the rhetoric implies. The 2022 Justice Gap report from the Legal Services Corporation, the federally funded body responsible for funding civil legal aid in the United States, found that ninety-two per cent of the civil legal problems faced by low-income Americans received either no help or not enough. In 2021, LSC grantees were unable to provide adequate help on roughly 1.4 million of the 1.9 million problems brought to them. Across state civil courts, the New York City Bar Association has called the gap a “chasm”. In England and Wales, the Ministry of Justice's own statistics for July to September 2025 recorded that fifty-nine per cent of County Court civil cases involved an unrepresented party. In housing matters, in family proceedings, and in claims under £10,000, the proportion is higher still. The legal profession has been priced out of the lives of the people whom the legal system most often touches.

For those people, generative AI is not a fancy productivity tool. It is the only piece of legal infrastructure that scales to their need. A free model that responds in seconds, drafts in plain English, and produces something resembling a coherent argument is more meaningful in the life of an evicted tenant than a thirty-page government leaflet, a legal aid waiting list of nine months, or a self-help kiosk staffed by a volunteer who can offer information but not advice. The bar associations know this. They are also writing the practice notes that make their members liable for AI-generated errors. The result is a regulatory regime that, on paper, treats AI as a hazardous tool that licensed professionals must approach with caution, while in practice the same tool is being used as a substitute for those professionals by people the profession does not serve.

That asymmetry is not just uncomfortable. It is dangerous. When a lawyer files a brief with phantom citations, the lawyer is sanctioned, the judge is annoyed, the client may suffer reputational damage, and the firm pays the bill. Friction is built into the relationship. The lawyer has insurance, a regulatory body, a duty of competence. When a pro se litigant files the same brief, none of those scaffolds exist. The litigant is told, sometimes for the first time in their interaction with the system, that they have submitted falsehoods to a court. Their case is dismissed, or worse. Their credibility, which they did not choose to risk, is lost. They have no insurer, no body to pay sanctions, no firm to absorb the loss. They have a chatbot and the consequences.

Risk and Where It Lands

The doctrinal answer to “who bears the risk” is easy to state and brutal to apply. In every jurisdiction that has confronted the question, the answer has been: whoever signed the filing. Rule 11 of the United States Federal Rules of Civil Procedure binds the lawyer or the unrepresented party to the truth of every assertion. The Civil Procedure Rules in England and Wales impose comparable duties. The Legal Practice Council in South Africa has already announced that good intentions are not mitigation. Australian state bars have made the same point. The doctrinal posture is that the human is the author, the AI is the tool, and the tool's errors are the author's problem.

This makes intuitive sense for the represented client and their lawyer. It is much harder to defend in the case of the unrepresented. A pro se litigant who copies a fabricated case from a chatbot has not been negligent in the way a lawyer has been negligent. The lawyer is a trained professional with a duty of competence and an obligation to know that ChatGPT does not search; the litigant is a person who can read English and has been given a search box. The same conduct, on the same facts, attracts the same legal exposure but reflects radically different fault. Sanctions imposed on a pro se litigant for AI-generated falsehoods land on someone whose alternative was not better legal advice; their alternative was no advice at all. The system tells them, in effect, that they should have known not to use the tool that the system also will not give them an alternative to.

There are emerging cases that test the edges of this rule. On 4 March 2026, Nippon Life Insurance Company of America filed suit in the Northern District of Illinois against OpenAI Foundation and OpenAI Group PBC, alleging that ChatGPT, used by an opposing pro se litigant, had engaged in tortious interference with a settled contract, abuse of process, and the unlicensed practice of law. The Nippon complaint is one of the first attempts to push a portion of the risk back upstream, onto the maker of the tool, rather than letting it rest entirely on the user. It is far from clear whether the case will survive a motion to dismiss, and the substantive merits are contested, but the move is intellectually significant. If a chatbot purports to give legal advice to a litigant, and the advice is wrong, and the litigant's reliance produces real harm to a counterparty, then liability somewhere in that chain is unavoidable. The question is whether it stops at the user, where current doctrine puts it, or extends to the model, the deployer, or the platform.

State legislatures have begun to nibble at the same question. New York legislators are considering a bill that would expressly make companies liable for the unauthorised practice of law by their AI chatbots. The premise is that a tool that confidently advises a non-lawyer on the contents of a defence is, functionally, practising law without a licence; the licensing regime exists for a reason; and the licensing regime should bind the company that deploys the tool. The counter-argument, made vigorously by the deployers, is that disclaimers are visible, that the tool is a general-purpose system, and that holding the platform liable will simply shut the tool down for the very people who most need it. The argument is real on both sides. It is also, to borrow a WIRED instinct, a debate that exists because the legal system has refused to fund civil representation at the level the population requires.

The Patchwork of Rules

What courts have done in the meantime is improvise. Judge Brantley Starr of the Northern District of Texas issued the first published standing order on AI in court filings in 2023, requiring attorneys to certify either that no portion of the filing was drafted with generative AI or that any AI-drafted portion had been independently verified by traditional means. Filings without the certificate would be stricken. Starr's order travelled. By the end of 2025, Bloomberg Law's tracker had logged hundreds of standing orders, general orders, and local rules across federal and state courts in the United States addressing AI use in submissions. The orders are not uniform. Some require disclosure of the model used. Some require certification of independent verification. Some prohibit AI in particular categories of filing. Some are silent on pro se litigants and silent in different ways on legal aid clinics that use AI in supervised work.

In the United Kingdom, the Bar Council and the Solicitors Regulation Authority have issued guidance, and the Lord Chief Justice's office has updated its own guidelines for judges on the use of AI tools. The Ayinde judgment did most of the doctrinal work: lawyers are professionally responsible for everything they sign, AI cannot be invoked as an excuse, and serious cases will be referred to the regulators. In Australia, the Victorian Legal Services Board has begun to issue conditions on practising certificates for solicitors caught with fabricated citations. The South African Legal Practice Council has confirmed that referrals for AI-generated fabrications will be standard. None of these regimes is coordinated with the others. None deals systematically with the unrepresented litigant. All of them assume that the deterrent function of sanctions is sufficient, even though the data Charlotin is collecting suggests that sanctions are not, in fact, slowing the rate of submissions.

There is a distinct strand of proposal that goes beyond after-the-fact sanction. The most robust version is the “hyperlink rule” advocated in legal-technology circles, which would require every authority cited in a filing to be backed by a working hyperlink to the actual case in a recognised public database, with verification carried out before submission. Some jurisdictions have flirted with the idea. None has imposed it as a hard rule, in part because the doctrinal infrastructure for stable case URLs is patchy and in part because requiring hyperlinks puts an additional procedural burden on litigants who already cannot navigate the existing forms. A weaker version is the retrieval-augmented generation (RAG) requirement, in which AI tools used in legal practice must ground their outputs in a curated, court-vetted database of authorities rather than in the open internet. Westlaw, LexisNexis, and Thomson Reuters all market RAG-based products. The Stanford RegLab study showed that those products still hallucinate, just less often. RAG is mitigation, not solution.

A more interesting proposal, surfacing in academic work and in the most thoughtful sections of the New York State Bar Association's pro se commentary, is a two-tier disclosure regime. Lawyers using AI face one set of rules: they must disclose, certify, and verify, and they will be sanctioned if they fail. Pro se litigants face a different set: they must disclose, but the court will treat AI-generated errors as a procedural defect that triggers an opportunity to correct, not a sanctionable falsehood, provided the litigant did not knowingly file material they suspected to be fabricated. The justification is that the unrepresented litigant has a different epistemic position. They were not supposed to know. The system that did not give them a lawyer cannot then sanction them for the only substitute available. The objection is that the rule creates a second-class evidentiary regime in which the truth of submissions depends on who made them, and that asymmetry is its own injustice.

The Hardest Cases

It is worth sitting with the kinds of cases where this matters most. The Ayinde claimant, on whose behalf phantom cases were cited, had a real housing problem. The barrister's failure did not invent the homelessness. It complicated the record on which the homelessness would be adjudicated. In Mavundla, a real dispute about traditional leadership was filed alongside fabricated authorities, and the case was referred to the Legal Practice Council in part because the court could not separate the genuine claim from the contaminated argument. In the Hannah Payne appeal, the constitutional question, whether her trial counsel had been ineffective in failing to present a citizen's arrest defence, is genuine and consequential. Leslie's hallucinated brief did not change the facts of the underlying killing. It changed the texture of the appellate record, made the prosecution's argument less credible, and forced the Georgia Supreme Court to spend its time policing the inputs rather than weighing them.

For the unrepresented, the most painful version of the problem is not the high-stakes appeal. It is the small case that was always going to be hard. A tenant in Manchester or Atlanta or Cape Town files a defence to an eviction. The defence cites cases that do not exist. The landlord's counsel files a reply that catches the fabrication. The judge, depending on jurisdiction, either strikes the defence or grants it grudging weight. The tenant loses the home that they were trying to keep, in part because the only legal help they could afford was a model that lied to them. The fault lies, on every doctrinal account, with the tenant. The injury, on any honest account, is on the tenant and the tenant's children.

That kind of case rarely makes the Charlotin database. It does not produce a published opinion. It does not generate a sanctions order. It generates a default judgment, a removal, a debt. Some portion of the court orders that are entered against unrepresented defendants in the United States and the United Kingdom in 2025 and 2026 are now, almost certainly, downstream of AI-generated filings that were never identified as such because no one in the courtroom had time or expertise to check. The dark figure of AI's contribution to the justice gap is, by definition, invisible. The cases we know about are the ones in which someone, on the other side, had the resources to look up the citations. Where there is no other side with resources, there is no audit. Where there is no audit, there is no record.

What Should Be Done

This article will not pretend that there is a clean fix. WIRED's instinct, properly, is to take a position rather than to nod sympathetically at every party. The position is this. The legal profession's current posture, in which sanctions land on the human signatory regardless of context and AI tools are treated as neutral hazards, is intellectually consistent and morally untenable. It works only if the system also funds the legal representation that would let people avoid the hazardous tool. It does not. The same legislatures and bar associations writing tighter AI rules have, for thirty years, allowed civil legal aid to be eviscerated. They cannot now have it both ways.

There are concrete steps. Court-vetted, publicly funded retrieval-augmented systems, designed specifically for unrepresented litigants in jurisdictions where self-representation is the norm, would meaningfully reduce hallucination rates and shift some risk back to public infrastructure where it belongs. The technology exists. The cost is a fraction of what jurisdictions spend on courthouse construction. The political will is the obstacle. Two-tier disclosure regimes, in which courts adopt different sanctions postures for represented and unrepresented filers, would acknowledge the moral asymmetry the current rules ignore. Mandatory hyperlinking of authorities, with court-side automated verification, would let scale solve a scale problem. Liability that extends, where appropriate, to the deployer of a model marketed as a legal assistant, would give platforms an incentive to invest in accuracy that disclaimers do not.

None of these will fix the underlying issue, which is that justice is expensive and most people cannot afford it. Generative AI has revealed that fact in a particularly acute way: the cheapest available legal counsel is also the least reliable, and the most reliable counsel has never been cheap. Treating AI as either saviour or saboteur misses the structure of the problem. The technology is a mirror. It reflects, with terrifying efficiency, both the procedural form of legal argument and the unwillingness of states to fund the substance. The Georgia prosecutor and the Manchester tenant are using the same tool for related reasons: their respective systems have not given them what they need to do their work.

Phantom precedent is what happens when a pattern-matching machine is asked to do the job of a research lawyer. It is also, more deeply, what happens when courts pretend that everyone in front of them has equal access to the means of producing reliable arguments. They do not. They have never. The arrival of AI has made that gap visible in a new way, and the next decade of legal regulation will be measured by whether courts and legislatures respond to the visibility or to the symptom. If the answer is more sanctions, more warning notices, and more standing orders, the gap will widen. If the answer is funded counsel, vetted public tools, and a doctrinal reckoning with who actually bears the risk when a model lies, there is at least a route through. The contradiction will not resolve itself. Someone has to choose.

References

1. CBS News Atlanta, “AI in Georgia courts raises new questions after Clayton County prosecutor admits citing fake cases”, 2026.
2. Atlanta News First, “Chief justice: Attorney cites nonexistent cases in opposing new trial for woman convicted of murder”, 23 March 2026.
3. Atlanta News First, “Attorney with Clayton County DA's Office apologizes for using AI, citing fake cases in court brief”, 30 March 2026.
4. Damien Charlotin, AI Hallucination Cases Database, damiencharlotin.com/hallucinations, accessed April 2026.
5. Eugene Volokh, “In One Day (Mar. 31), 17 U.S. Court Decisions Noting Suspected AI Hallucinations in Court Filings”, Reason, 6 April 2026.
6. New York State Bar Association, “Pro Se Advocacy in the AI Era: Benefits, Challenges, and Ethical Implications”, 10 February 2026.
7. Mata v. Avianca, Inc., 678 F. Supp. 3d 443 (S.D.N.Y. 2023), Opinion and Order on Sanctions, Judge P. Kevin Castel, 22 June 2023.
8. NPR, “Michael Cohen says he unwittingly sent AI-generated fake legal cases to his attorney”, 30 December 2023.
9. Gauthier v. Goodyear Tire & Rubber Co., E.D. Tex., Judge Marcia Crone, sanctions order, November 2024.
10. Ayinde v London Borough of Haringey; Hamad Al-Haroun v Qatar National Bank QPSC and QNB Capital LLC, [2025] EWHC 1383 (Admin), judgment of the Divisional Court, June 2025.
11. Information Age (Australian Computer Society), “First Australian lawyer penalised for AI blunder”, 2025.
12. NBC News, “Australian lawyer sorry for AI errors in murder case, including fake quotes and made up cases”, 15 August 2025.
13. Mavundla v MEC: Department of Co-Operative Government and Traditional Affairs KwaZulu-Natal and Others, [2025] ZAKZPHC 2.
14. Cliffe Dekker Hofmeyr, “Another episode of fabricated citations, real repercussions: South African courts show no tolerance for AI-hallucinated cases”, 4 July 2025.
15. Daily Maverick, “AI 'hallucinations' are threatening the administration of justice in South Africa”, 15 July 2025.
16. Varun Magesh and Faiz Surani et al., “Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools”, Journal of Empirical Legal Studies, Stanford RegLab, 2024.
17. Legal Services Corporation, The Justice Gap: The Unmet Civil Legal Needs of Low-Income Americans, 2022 Report, NORC at the University of Chicago.
18. Ministry of Justice (England and Wales), Civil Justice Statistics Quarterly, July to September 2025.
19. New York City Bar Association, “The Justice Gap Has Become a Chasm”.
20. Bloomberg Law, “Federal Court Judicial Standing Orders on Artificial Intelligence” comparison table, 2025.
21. Legal Dive, “Federal judge seeks to prevent generative AI mistakes in briefs”, 2023, on Judge Brantley Starr's standing order.
22. Vermont Law Review, “Mandatory AI Disclosures: Enforcing A Uniform Standard”, 2025.
23. National Law Review, “Preventing Fabricated AI Legal Authorities: The Case for a Mandatory 'Hyperlink Rule'“.
24. Bloomberg Law, “Big Law Grapples With AI-Fueled Pro Se Surge, Rising Legal Costs”, 2025.
25. Georgetown Journal of Legal Ethics, “GPT, Esquire: How the Nippon Case May Shape the Future of AI in Pro Se Litigation”, 2026.

Tim Green UK-based Systems Theorist & Independent Technology Writer

Tim explores the intersections of artificial intelligence, decentralised cognition, and posthuman ethics. His work, published at smarterarticles.co.uk, challenges dominant narratives of technological progress while proposing interdisciplinary frameworks for collective intelligence and digital stewardship.

His writing has been featured on Ground News and shared by independent researchers across both academic and technological communities.

ORCID: 0009-0002-0156-9795 Email: tim@smarterarticles.co.uk

Listen to the free weekly SmarterArticles Podcast

In Summary: * Major event today was the regular 4-month checkup appoinment with my GP. He and I had a good discussion covering many issues of concern. Plans of action were made which should improve health im several areas.

Also worthy of note was taking the wife out for lunch at a favorite restaurant. Great meals, good time.

Prayers, etc.: * I have a daily prayer regimen I try to follow throughout the day from early morning, as soon as I roll out of bed, until head hits pillow at night. Details of that regimen are linked to my link tree, which is linked to my profile page here.

Starting Ash Wednesday, 2026, I've added this daily prayer as part of the Prayer Crusade Preceding the 2026 SSPX Episcopal Consecrations.

Health Metrics: * bw= 233.8 lbs. * bp= 139/80 (69)

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Activities, Chores, etc.: * 04:30 – listening to local news talk radio * 05:50 – bank accounts activity monitored. * 06:05 – read, write, pray, follow news reports from various sources, surf the socials, nap, * 08:00 – update med list for this afternoon's GP apt. * 08:40 – load weekly pill boxes * 12:00 – took the wife out for lunch on our way to my regular 4-month follow-up appointment with my GP. * 16:00 – on the way home, the wife wanted to stop and do a bit of grocery shopping * 17:30 – Listening to the Pregame Show ahead of tonight's Blue Jays / Yankees MLB game. I'll stay with this station for the radio-call of the game.

Chess: * 19:30 – moved in all pending CC games

What is this for? What should you expect?

• Long form writing, analysis, and at times journalism.
• Written works that I hope to revise/edit/expand into something publishable in a more traditional (i.e., print) sense.
• Reflections on current events and topics in pop culture/internet culture, nostalgia, politics, media, and/or technology.
• Occasional nods/links to works by others that are interesting or exciting to me (mainly in citation).

OK. Who am I? My name is Jean. I'm a writer, an educator, a musician, and a lot of other things (a dad, a husband, a Canadian, a Vancouverite). Hello and welcome.

Home now from my 4-month follow-up appointment with the GP. This visit went well, he and I exchanged more words this afternoon than in all our previous visits combined. All the issues I had in mind were discussed, and plans of action were made.

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And the adventure continues.

How could I ever be lonely when you are everywhere beauty thrives.

[Verse 1] There was ache in the morning There was want in the light I lay still in the silence Thinking of you through the night

Madness, I know it But it felt like a sign Something moved in the dawn air And whispered your name into mine

[Pre-Chorus] You were there and you were not A ghost inside my skin So I left my flesh behind me And went searching on the wind

[Chorus] Past the little beach at sunrise Where the gulls broke the dark Past the blue and endless water With your name against my heart

Over stone and over sorrow To the place where wild things grow I found you in tiny miracles Where the Burren flowers show

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But you were not abandoned You were held by something true Peace was blooming all around And it looked so much like you

[Pre-Chorus] Blue and yellow, red and periwinkle Soft against the stone You were love and you were quiet You were never quite alone

[Chorus] Past the little beach at sunrise Where the gulls broke the dark Past the blue and endless water With your name against my heart

Over stone and over sorrow To the place where wild things grow I found you in the miracles Where the Burren flowers show

[Bridge] And maybe love is not possession Maybe longing learns to kneel Maybe beauty doesn’t answer It just teaches us to feel

So I sat beside the flowers Where the ancient limestone sleeps And I loved you without reaching And I wanted without need

[Final Chorus] Past the little beach at sunrise Where the gulls broke the dark Past the Cliffs of Moher standing Like a wall around my heart

Over ache and over wanting To the place where wild things grow I found you in the miracles Where the Burren flowers show

[Outro] You were there and you were not You were near and out of view In the blue, yellow, red, and periwinkle Every tiny bloom was you

#song #poetry #wyst #FM

To the Tune of 'Sound of Silence'

Hello headache, my old friend, I’ve come to bargain with you again. Somewhere between “just one more round” And waking up face-down, profound, There’s a lesson I ignore with brewski beer: Morning’s here. And it brought drums.

In yesterday’s rooms, not quite alone, Searching for my lover’s tone. ’Neath the judgment of the bathroom light, Bleary-eyed blossom, avoiding the light. And the coffee whispered, “Poor thing, you were too immersed.” Could be worse. Now here comes the thrum.

And in this home’s quiet presence, Outside, a cardinal in the tree. His song today sounds blurry. No one dared Disturb the couch of silence.

“Hey, AI, can you sing my song for me? Make it easy and folky.”

#poetry #songwriter #beer

Reflecting on the past year of my entrepreneurial sabbatical.

Last year around this time, I decided to walk away from coaching. I informed my clients, completed my final sessions, and then closed up shop for good. The truth is that I enjoyed coaching, but I was just done. And not just from coaching itself, but from all things entrepreneurial. For the first time in my life, it was time for an entrepreneurial sabbatical.

I didn't know what to expect, but I certainly wasn't expecting it to be so challenging. Especially in the beginning. But it makes sense as I have been in the entrepreneurial mindset for decades. It wasn't something I could just “shut off” overnight.

As time went on, I started to settle into the slower pace of life. I focused on quality time with my wife and family and really integrating myself into where we live. I have started to appreciate the smaller moments. The simple things. Stuff that I would otherwise have ignored if I were working on my own project. I even had the opportunity to guest lecturer at my alma mater which I really enjoyed!

Where Things Stand

I'm getting the itch again, but I'm not ready to scratch it just yet. Life has a way of shifting priorities and right now I'm locked into some personal journeys. But that will change at some point. Because while I've stepped away from pursuing entrepreneurial projects, it hasn't stopped me from thinking.

So, I don't know exactly when, but I can tell that I am closer to the end than the beginning of this much-needed sabbatical. When it does end, I'll have a renewed sense of energy and clarity. That was the point of the sabbatical in the first place, and it seems to have worked.

#entrepreneurship

I’m a printaholic. I love printing PDFs into booklet form, folding, and stapling them. Sometimes, I’ll cut at the folds, two-hole punch them, and insert those two-prong holders if the book is too thick.

I love the way fresh blank pieces of paper is imprinted with jet ink and heated on both sides, how stacks of finished sheets are ready to be folded or sliced in half, and how freeing it is to give the middle finger to those who keep saying “we’re going to live in a paperless society.”

Unfortunately, today is a bad day in my printing world. I had to print out a lot of PDF documents for my son’s school to sign and turn in. When I tried to print them out my laptop didn’t recognize the hardware. Even after reinstalling the drivers the printer still didn’t work. My wife tried printing on her computer and it didn’t work as well.

The printer is a Canon MX-522 that I’ve had for years. After being a dedicated and reliable printer surviving multiple computers and operating systems, moving from one house to another, and replacing countless ink cartridges, it’s finally time to retire it. So thank you for your service Canon MX-522. Maybe someone else can put it to good use when I donate it.

Now the hard part is finding a reliable printer with ink cartridges that isn’t too expensive.

#printing #printer #documents #ebooks #ink #PDF #technology

Many a times I ask myself who do I want to learn photography. It is not a career option for me. It is not something I had always wanted to do. It’s just something I picked up last year.

Not long ago, I was writing an article. In that article, to emphasise my point, I wanted to add a pic of an umbrella that has come from the rain. A few droplets of the rain was supposed to be on the umbrella.

I wanted that picture to be clicked by myself. Obviously I could download one from google or unsplash but that does not produce the same emotion as the one that I had clicked with my own hands. The one I had edited according to my own preferences.

I could not find any.

This is when I thought why people take picture. Not because they also write something and need to hammer their point but the picture represents something to them. A lady wearing a red in autumn can mean nothing to me but it can very well remind someone of their home. Or the time when they were very emoted.

I am in my mid twenties and currently in a partial hospitalization program for intensive trauma therapy. And honestly, I had no idea what untangling years of suppression could actually look like.

I thought healing would be as simple as talking things out. That’s always what I had done. In a weird way, I think that’s why I convinced myself I had already worked through a lot of my trauma — because I was never secretive about it. I could name it. I could explain it. I could tell the story without crying.

What I didn’t realize is that naming something is sometimes only barely grazing the surface.

The truth is: I am exhausted.

I am having nightmares. My depression and mood swings feel like a new rollercoaster every day. I never know when the ride is going to drop suddenly or take a sharp turn. Sometimes it throws me into a corkscrew I didn’t see coming and I come out physically hurting — my neck tight, my head pounding, my forehead tense like I’ve been clenching against something for years.

That’s metaphorical, but also very literal.

My brain feels swollen. My body feels banged up. My nervous system feels like it’s screaming at me after spending years whispering.

I didn’t know healing could feel this physical. I didn’t know finally feeling things could make me feel worse before better. I didn’t know how much I had actually been carrying.

And maybe the hardest part is realizing how much I gaslit myself into believing I was “dramatic” because other people had it worse. But trauma is not a competition. Your body does not care whether someone else “deserved” to hurt more than you did. It only knows what it experienced and what it had to do to survive it.

So this is a trigger warning for anyone reading this: I am going to use this space to be honest about my experience. That may include talking openly about trauma, mental health, emotional instability, physical symptoms of stress, fear, grief, anger, and the ugly parts of healing people don’t romanticize online.

Please protect yourself accordingly if those topics are triggering for you. My goal is never to set anyone back. I just want to be real about what it can actually mean to unravel years of both little and big traumas.

I am learning as I go.

And despite how hard this is, my goal is not to stay trapped in the pain or turn my suffering into my identity. My goal is to build a brain that feels safe. A mind that is loving instead of constantly at war with itself. A nervous system that no longer feels booby-trapped by the survival mechanisms that protected me for years, but are no longer helping me grow.

I want my life back.

And I think that starts with finally telling the truth about what healing actually looks like.

My therapist asked me to write about the ways in which my early childhood trauma affected the direction of my life. So, naturally, I spent the following several days reading about cybernetics, coming up with projects, writing on my work-related blog, and generally avoiding the subject.

I'm intensely drawn to the idea of spending several hours writing about threat modeling, which overwhelmed my mind last night. I lay awake thinking about formal languages based on constrained English, threat inheritance, and using data flow graphs to identify risk. During that time I did not think about how frustrated I can get when my kids start fighting, or how overwhelming their feelings must be for them right now.

I designed and wrote a testing framework, now used by thousands of people. Tests are developed by multiple teams. Test definitions are relatively easy to write, and (unlike many other things) actually lend themselves well to being written by LLMs. This is true, despite the fact that LLMs didn't exist when I designed and wrote the first prototype.

I spend days, weeks, in deep thought. I thought about code. I thought about organizational structures. I've spent so much time reading and learning, trying to understand. I focused to the exclusion of everything else: first my pregnant partner, then my kids.

The first six weeks after the birth of each of my children was the most human I have been for a long time. The first week is nothing but survival. You must be present because a tiny life is relying on your constant attention. But even as the weeks rolled on, as I was off of work and able to focus on my family, the trial crept back in and pulled my attention away. Then the disability and leave team, having messed something or other up, threatened me.

It's so much easier to follow those threads: logic, fear, distraction. It's easier to fill my head with something than to leave it empty and quiet enough for the feelings to come in.

I never noticed before. It just felt exciting to hack for hours straight, order a sandwich to eat while reading some specification or other, focusing on each detail until my roommates broke my concentration with a glass of whiskey and chants of “bar night.”

Focus, then numb, for decades now. When did it even start? From the moment I got my eyes on the Internet, I was always thinking. Perhaps some of that was a reaction to the boredom of rural living, spending most of the day alone in my house while my mom was at work. I wasn't much older back then than my oldest is now. How much different it must be for her, unending activity vs my unending isolation.

The more I've unwound it, the more I've been able to allow myself to feel, the worse I feel I've gotten at my job. Then one day I couldn't do it anymore. I noticed it before I actually snapped. This time I noticed my feelings.

Years earlier I had put my fist through a window. That's what it had taken for me to realize there was a problem.

Before the shooting, I had spent a few years in therapy. After those few years I experienced something I hadn't ever experienced: I stopped thinking for a few moments. My internal dialog, which had never really stopped as long as I could remember, was silent. My therapist was Buddhist. We had focused on mindfulness. I had been gone to a meditation course at Toorcamp a little earlier and had been working on my awareness. After a bit more work, I was able to be present for a bit.

I hadn't noticed how much I had been suppressing my emotions by thinking. But the more I would take a moment here and there to just be present, the more I noticed them. I realized I needed to stop working as a consultant for a bit. I went to work somewhere else. On the walk to work every day I would stop for a moment and breathe.

Then Trump happened. It was a reminder of something I had left behind. My experience in the rural part of the American West Coast were dark. I was different, and the places I lived were not very tolerant of difference. And I was bored. There was a crushing boredom, a hopelessness, a feeling of being trapped. Looking back now, I realize it's not so much rural living as a reality constrained by my lack of access to a car. The Internet changed some of these things. Some people opened their minds a bit. (Other people became more radically entrenched in their intolerance.)

But at that time, in that place, I had felt trapped and hopeless. It had almost killed me, but I had escaped. Now the horrible thing I recognized, the wild incompetence, the anti-intellectualism, the fanatical religious authoritarianism, the blatant corruption, they were all there. They were all embodied in one man.

Folks living in cities felt the time warp. This thing didn't belong to the modern era. It was old and weird, clawing us all back in time. But for me that time also had a place. I had felt the time warp in reverse when I escaped. But the monster had followed me.

That focus, filling my mind with so much information that nothing else could get in, was adaptive under capitalism. It got me job after job. I was a top performer wherever I worked, because I never stopped trying to get better. My personal life would vanish as I poured myself into learning, growing, improving. I read books and took classes. No one could believe I had dropped out of high school. All of my peers had secondary degrees. I could pass for something that I wasn't, and part of that was driven by fear: fear that I would be found out, fear that I would, somehow, have to go back.

But back came for everyone, so I organized.

I had learned this skill, the skill of learning, the skill of focusing at the exclusion of everything. I had learned it to adapt to capitalism, to adapt to my trauma, to keep myself safe. I applied the skill. I applied it to my organizing, I applied it at work. I was always working on something. I worked on organizing plans. I wrote code. I worked on software architectures. I wrote papers, so many papers, to get these ideas funded. I pushed myself without feeling. I pushed until I broke. (or, I guess, until I broke a window.)

Time off, therapy, things started to get better. We realized we could leave. I paid attention to my feelings. We moved to the Netherlands.

I thought that things could be better, and they were. The longer I've been here, the more I've been able to be with my feelings. When I stopped working, I realized I needed to focus on my emotions if I wanted any hope of getting back to work. So I've been writing.

The more I do this, the more I let myself engage with feelings, the more I've started to notice this thing that I do. Sometimes it even comes in when I'm in therapy or talking about my feelings. I shift to the theory, the context, depersonalize it and think about my experience as part of the system.

But I didn't follow that thread last night. I let myself drift away from theory and notice what I had been doing.

This adaptation, which I learned to deal with childhood trauma, works well for capitalism but poorly for parenting. So here I am, trying to figure out how to balance the need to fill my head with information, theory and code, to get back to work against the needs of my kids for me to be emotionally available. And the transition is harsh.

I want to talk about capitalism. I want to talk about how it tunes people in maladaptive ways. I want to talk about how it is a system of death, a system that gradually makes social reproduction more difficult until it kills the society it infects. I want to talk about all this, so I don't have to think about how bad it feels to actually be in the thing. By thinking about this as a system, I can rally a comfortable anger against something horrible. By thinking about this as a system, I can remove myself from the experience of it. By thinking about this system, I can not feel it.

It is far easier to talk about this monstrous system, to clinically analyze it, than to admit that I feel scared, and sad, and helpless. The monstrosity of this faceless system, operating on the emotionless logic of profit, mirrors the incomprehensibility of the world of my own childhood.

And there's the answer. How has my childhood trauma shaped my life? How hasn't it? Every part of who I am is intermeshed with my strategies for adapting to this trauma. So then, what am I left with if I treat the trauma? How do I survive if survival in the capitalist system has been predicated on an adaptation to trauma that eliminates the feelings I need to help my kids grow?

How do I let go of something I need? How do I provide for my family without the tool that makes me successful?

Have been a little quiet on here of late, work, life and the end of the football season has been transpiring against me.

Calmer seas ahead so finding a little more time to spend with the formbook and I’ve found two today …

3.10 Catterick I wish there were eight runners here, but there isn’t. I’m am however, still going to put up INGLEBY ARCHIE as a selection. The 5yo will have absolutely needed his reappearance run LTO so I’m putting a line through that and what interests me here is he is – LTO aside – back in a class 5 off what is with Jack Nicholl’s claim, a career low mark at a grade where he is 3321158214. First run at the course against some rivals who love it here, but 13/2 seems a fair price for a horse who seems to relish racing at this time of year.

INGLEBY ARCHIE // 0.5pt E/W @ 13/2 (Bet365) BOG

4.50 Catterick An each way bet to nothing on Jedd O’Keefe’s old timer SAISONS D’OR here. A good winner LTO on the tapeta at Southwell and should find this easier than recent turf assignments with this being a 0-60. Is 5lbs lower than his last winning mark (over C&D) and similar to the selection in the 3.10, actually finds himself on a career low turf mark too. Ticks plenty of other boxes (course form, ground, trip etc) and hopeful he can be very competitive.

SAISONS D’OR // 0.5pt E/W @ 11/2 (Coral) BOG

Hello again. I hope you and your family are well.

POTUS has decided that those who attacked the capital during the constitutionally mandated ceremony of counting the votes of the electoral college must be rewarded. POTUS, in ordering the settlement of his own suit against the IRS, has ignored congressional power to spend money and forced them to create a fund to reward those who would have burned down the capital if they had had just a little more time.

In addition he has forced the justice department to make his family, business and any other organization they create, immune to any action by the irs. So, he can ignore the law, ignore the requirement to pay any tax, and prevent the department from auditing his or his family or business tax returns. So, if he fills in every line of his 1040 with zeroes, there is nothing the irs can do. No one else in the world has such immunity.

This is just another example of why POTUS and his cohorts must be removed from their positions as soon as possible. Otherwise POTUS and the MAGA Monsters will destroy our democracy.

POTUS Roaster

Thanks for reading my posts. If you enjoy them, please tell your friends and family, If you want to read more, please go to write.as/potusroaster/archive/

仕事らしい仕事の入っていない朝だった。 曇った窓を眺めているうちに、特に外へ出る理由もないまま、結局、公園まで歩くことにした。 外は、小雨が降っているようで降っていない。水たまりだけが残っていて、空はぎりぎり曇っている。

撥水の効いたシャツに黒いパンツ。 棚の下には、ゴアテックスのスニーカーが置かれていた。

橋の下を抜ける途中、軒下でノートパソコンを開いている人がいた。 雨粒が地面を叩く音のなかで、キーボードだけが乾いた音を立てている。

最近、自分のなかで、気分が変わる条件が変わった気がする。 前なら、新しい下着をまとめて買い替えるだけで、生活が少し更新された。 けれど今は、それではもう足りない。 何を変えれば、新しい日付の側へ移れるのか、自分でも分からなくなっている。

公園のベンチに座りたかったが、少し湿っていたので、立ったままうろうろしていた。 濡れた木の匂いがした。

微妙な寒さに、そういえば昔、腹巻きを買ったことがあったのを思い出した。 冷え対策だったと思う。 数日だけ真面目に着けて、すぐにやめた。 ああいう、生活を改善しようとする小さな決意は、たいてい静かに失踪する。

雨脚が少し強くなった。 遠くで、どこかのビルのエレベーターの音が聞こえた気がした。 エレベーターのなかでは、たまにピアノのイージーリスニングが流れていることがある。 この先の人生は、たぶんこんなふうにレールの上を進んでいくのだと、不意に脳へ感覚が浮かび上がり、少し抵抗したくなる。

植物園にも行きたいし、夜の天体観測もしてみたいし、釣りもしたい。 落語だって見に行きたいと思い続けている。 まだ、やりたいことをほとんどできていない。

けれど、やりたいことは、やる前がいちばん均整の取れた形をしていて、実際の生活はいつもその手前で止まり続ける。

年末の大掃除が待ち遠しい。 まだ梅雨も明けていないのに。 全部を捨てて、床を拭いて、空気を入れ替える日のことを考えると、少しだけ安心する。

公園の時計を見る。 まだ昼にもなっていなかった。 雨のせいで、時間が薄く伸びている。

立ち上がる。 帰ったら、多分、好きなソファに座って、夏に着る服でも眺めるのだと思う。

There is a particular kind of professional disappearance that does not show up in the unemployment figures. The illustrator still has a desk. The translator still has a website. The session musician still owns a violin. None of them have been fired. None of them have been informed, in any official capacity, that their occupation is being phased out. Their names remain on the same freelance registers, the same union rolls, the same tax filings as last year. And yet, quietly, almost imperceptibly at first, the floor underneath their work has begun to give way.

This is the strangest economic story of the decade, and it is unfolding without a moment of high drama. There are no factory closures, no mass layoffs, no town-square photographs of redundant workers carrying cardboard boxes. Instead, there is a slow, grinding compression of the rates a cover illustrator can charge for a magazine commission, a slight but stubborn drop in the volume of subtitling work coming through the agency in São Paulo, a pause in the email chain from the German publisher who used to commission a translator in Lagos every six months. Each individual moment is deniable. Taken together, they describe a structural rearrangement of the creative economy that the existing policy vocabulary, fixated on automation and job displacement, is not equipped to name.

UNESCO's flagship report on creativity and digital transformation, published on 18 February 2026 as the fourth edition of its Re|Shaping Policies for Creativity series, attempted to put a number on the rearrangement. Drawing on data from more than 120 countries, the report projected that creators worldwide are on course to lose up to 24 per cent of their revenues by 2028 as a direct consequence of generative AI, with music creators bearing the heaviest exposure and audiovisual creators close behind. An accompanying analysis published the same week by Inter Press Service amplified the geographical dimension of the problem, observing that the income losses are falling most heavily on freelance and self-employed creators in the global south, layering a new digital injury on top of long-standing inequalities in the cultural economy.

The numbers are striking, but they are not the most interesting part of the story. The most interesting part is the mechanism. This is not, in the conventional sense, a tale of automation. The translator working from Yoruba to Spanish has not been replaced by a translation engine in any specific role. She is still the translator on her own letterhead. What has happened is that the demand curve she used to live on has been displaced, almost overnight, by something that produces an approximate substitute for her output at near-zero marginal cost. The publishers, the production companies, the marketing agencies who used to commission her have not declared that they are switching to machines. They have simply stopped commissioning at the same volume, or they have begun negotiating from a position that assumes her labour competes with a free alternative. There is no transition point. There is no redundancy notice. There is no clean moment at which the policy concept of retraining becomes applicable, because the person is still doing the job. It is the job, as a paid activity, that is being hollowed out.

This distinction matters, and not only as semantics. The entire architecture of late twentieth-century labour policy, from unemployment insurance to active labour market programmes, was built on the assumption that economic dislocation comes with a clear event horizon. Someone is hired. Someone is laid off. Someone is retrained. Someone is rehired. Generative AI breaks the model not by accelerating the cycle but by detaching the harm from any of these events. The freelance writer is never laid off because she was never on a payroll. The illustrator does not get a redundancy package because there was no employer. The market she sold into has simply contracted, and the policy instruments designed to catch falling workers were not built to catch a falling market.

If the diagnosis is right, then the question that follows is the one the UNESCO report, the IPS News analysis, and a fast-growing literature on AI and the creative economy have all begun to circle. What policy instruments, beyond copyright reform, can address the harm? And who, in any meaningful sense, is responsible for the structural losses already under way?

The market, not the job, is the unit of analysis

To understand why this matters, it helps to look at what the existing debate is mostly about. Almost every legal and political fight currently being waged on behalf of creative workers concerns the upstream side of the AI value chain: whether AI labs should be allowed to train models on copyrighted works without permission, whether they should pay licensing fees for ingesting them, whether opt-out registers should be opt-in, whether the European Union's text-and-data-mining exception should narrow or expand. These are real and important fights. The Copyright Licensing Agency in the United Kingdom announced its Generative AI Training Licence to allow collective compensation for ingestion. The US Copyright Office has explored extended collective licensing on the Danish model. The Court of Justice of the European Union held its first hearing on generative AI and copyright in March 2026 in Like Company v Google, a case that may reshape the press publishers' right across the bloc.

Yet copyright, in any of its forms, only addresses one half of the harm UNESCO identified. The CISAC global economic study published in late 2024, conducted by the consultancy PMP Strategy on behalf of the international confederation of authors' societies, was unusually clear about this. The losses creators face split into two distinct streams. The first stream is the value of their existing works being scraped into training data without consent or remuneration. Copyright reform, however imperfectly, is built to address that. The second stream is the substitution effect: AI-generated outputs competing in the market against human-made works, depressing rates and shrinking commissions. Copyright, as currently understood, has very little to say about that second stream. Even a perfectly negotiated training licence does not change the fact that, once the model is trained, the marginal cost of producing a passable cover illustration falls towards zero, and the rate the illustrator can charge falls with it.

This is the harder problem, and it is the one to which the policy debate is only beginning to turn. The question is no longer simply how to compensate creators for the use of their work in training. It is how to sustain a market for human creative labour at all, when the marginal product of that labour can be approximated, however crudely, by a system that does not pay rent, sleep, or eat.

A taxonomy of instruments beyond copyright

The good news, if it can be called that, is that the policy toolkit available to address market collapse is broader than the copyright debate sometimes suggests. The bad news is that almost every instrument involves redistributing money from somebody who currently does not pay to somebody who currently does not receive, and the political economy of that redistribution is brutal.

AI cultural levies

The most direct proposal, and the one that has gained the most traction in European policy circles over the past year, is a levy on AI systems pegged to their commercial use of human cultural output. Arthur Mensch, the chief executive of the French AI lab Mistral, surprised many observers in 2025 when he publicly endorsed a revenue-based levy of roughly 1 to 1.5 per cent on commercial providers placing AI models on the European market, with funds channelled into a central pot to support cultural creation. The Mistral proposal is hardly altruistic; it would also, conveniently, harden a continental moat against American and Chinese model providers. But its underlying logic is sound, and it draws on a legal heritage that goes back six decades.

The German Copyright Act of 1965 introduced the first private copying levy, attaching a small charge to the cost of devices and media that allowed users to duplicate protected works. The principle was that where copying is structurally uncontrollable, levy-funded compensation, distributed by collective management organisations, is a more workable alternative than litigation. Generative AI presents an almost perfect analogue. The training and inference of a foundation model, at any meaningful scale, is structurally beyond the reach of one-by-one licensing. A statutory levy on commercial AI services, collected by reformed collective management organisations and distributed to creators on a metered basis, would close the substitution-side gap that copyright cannot reach. It would also avoid the worst pathology of contemporary copyright reform, which is that platforms can outspend rights holders in any line-by-line negotiation.

There are real objections. A levy must be set high enough to matter and low enough not to suppress useful applications. It must be administered by institutions trusted by both creators and developers, which is not how the existing collective management landscape is universally regarded. And it must avoid becoming a moat for incumbents who can absorb a 1.5 per cent levy more easily than a research lab in Nairobi or a co-operative model in Buenos Aires. None of these objections is fatal. All of them require institutional design rather than policy retreat.

Statutory remuneration rights

A close cousin of the levy approach is the statutory remuneration right, which decouples permission from payment. Under such a regime, AI developers might be permitted to train on lawfully accessible works without negotiating individual licences, but they would owe a non-waivable payment to authors through a collective body. The European Parliament's commissioned study on generative AI and copyright, published in 2025, examined this possibility in detail. Springer Nature's International Review of Intellectual Property and Competition Law has run a series of analyses, by scholars including Christophe Geiger, arguing that a statutory remuneration right grounded in fundamental rights to participate in cultural life could be the most workable foundation for a new compact.

The advantage of a statutory remuneration right over a pure levy is that it sits more comfortably within the existing copyright framework. The disadvantage is that it still ties payment to the use of identifiable works, which means it primarily addresses the ingestion side rather than the substitution side. Combined with a levy, however, it begins to look like a serviceable architecture.

Public commissioning and the Irish experiment

While the levy debate continues, a quieter experiment has been running in Ireland since 2022. The Basic Income for the Arts scheme, originally a three-year pilot, paid 2,000 randomly selected artists 325 euros a week, regardless of output. The Irish Department of Culture, Communications and Sport opened applications for the 2026 to 2029 successor scheme in April 2026, and a published cost-benefit analysis found that for every euro invested, society received a return of 1.39 euros, a number that has been disputed in the Irish press but has not been seriously dislodged.

The Irish scheme is not a response to AI. It was designed to address the chronic under-monetisation of cultural work in a digital economy that had already eroded the freelance commercial base before generative models arrived. But its logic transfers cleanly. If the market for creative output is being structurally compressed by a technology whose externalities are not internalised, then a state instrument that decouples income from market success becomes more, not less, defensible. A universal creative income, scaled to the working population of practising artists in any given country, would stand to working creatives roughly as agricultural support payments stand to small farmers facing global commodity competition. It is unromantic, slightly bureaucratic, and precisely the kind of thing that has historically allowed cultural production to survive market shocks.

The political objection is that it looks like a cultural welfare state. The substantive objection is that, depending on how it is administered, it can entrench the credentialing power of arts councils and reproduce existing gatekeeping. Both are genuine. Neither is decisive against an instrument that, in Ireland at least, has empirical results to its name.

Public procurement as creative-economy policy

A surprisingly underused lever is the purchasing power of governments themselves. Public sector bodies are, in aggregate, among the largest commissioners of design, illustration, translation, audiovisual production, and music in most economies. The US General Services Administration's draft AI procurement clause, the December 2025 OMB memorandum M-26-04, the United Kingdom's Procurement Policy Note 017 from February 2025, and California's executive order on AI vendor certification signed by Governor Gavin Newsom in April 2026 all introduce disclosure obligations for AI-generated content within government contracts. None of them, however, goes the further step of creating a procurement preference for human creative work in cultural production funded by public money.

A modest reform would be to require, for example, that any public broadcaster, national museum, ministry of culture, or city government commissioning creative output beyond a defined threshold use human creators where reasonably possible, with transparent disclosure when generative tools are used. This costs the state more, in the short term, than letting procurement officers chase the cheapest bid. It also creates a stable demand floor for working creatives and signals, with the kind of clarity that markets respond to, that public money will not be deployed to accelerate the collapse of the freelance creative class. India's labelling thresholds for AI-generated visual and audio content, and the EU AI Act's transparency requirements, are early sketches of the disclosure architecture this would require.

Collective bargaining as economic infrastructure

The 2023 agreements between the Writers Guild of America, the Screen Actors Guild and the Alliance of Motion Picture and Television Producers are, for all their imperfections, the most concrete demonstration that collective bargaining can produce workable rules around AI in creative work. The WGA contract specifies that AI-generated material cannot be considered literary material for credit purposes and gives writers the right to refuse to use AI tools, while preserving their ability to challenge the use of writers' work to train AI. The SAG-AFTRA contract distinguishes digital replicas of identifiable performers from synthetic performers built from no individual likeness, and creates compensation and consent obligations around both.

These provisions are not perfect. The 2024 SAG-AFTRA video game performer strike, which ran for many months over precisely these AI consent and compensation issues in the interactive sector, demonstrated how quickly a contract negotiated for one segment of the industry begins to look incomplete when applied to another. But the agreements demonstrate the principle that collective bargaining can do work that copyright cannot, by setting industry-wide floors on consent, attribution, and compensation that apply regardless of the specific upstream provenance of any given AI output.

The implication for creative workers outside the unionised entertainment sector is uncomfortable but unavoidable. The freelance illustrator, the literary translator, the independent musician, the documentary editor often have no equivalent collective body. Building one, on a national or transnational basis, becomes infrastructure rather than ideology. The European Federation of Journalists, the European Writers' Council, the International Federation of Translators, and the Concerts Promoters Association are all operating in this space, as are emerging co-operative models among illustrators in continental Europe. Any serious policy response to the structural compression of creative labour markets needs to take seriously the question of how to fund and support these bodies.

Sovereign wealth approaches and creative commons funds

A more radical proposal, occasionally floated in policy circles and yet to find a serious political champion, is the sovereign wealth approach. The argument runs that the corpus of human cultural output ingested by foundation models is a non-rival public resource analogous to a national fishery or a hydrocarbon basin. Where states extract rents from companies exploiting natural resources, the rents fund either current public expenditure or, in the Norwegian case, an intergenerational sovereign wealth fund. By analogy, a national or supranational creative commons fund, capitalised by an ingestion-based levy on commercial AI training and operation, could be invested to provide perpetual support for cultural production.

The sovereign wealth analogy is imperfect. Cultural output is not extracted from a finite reservoir; it is generated, continuously, by living people whose labour the fund is meant to compensate. But the analogy is useful precisely because it forces a recognition that the value flowing into AI labs from human cultural output is, in macroeconomic terms, an unpriced externality of historic scale. The OECD's 2025 report on intellectual property and AI training data raised, without endorsing, the question of whether the absence of pricing on this externality represents a market failure that justifies non-market correction. That is exactly the conceptual frame a sovereign wealth approach would adopt.

The global south is not a footnote

Any honest reckoning with the policy space has to confront the dimension that the IPS News analysis put squarely on the table: the income losses from generative AI are not falling evenly across geography. They are falling disproportionately on freelance and self-employed creators in the global south. UNESCO's data, repeated in the Re|Shaping Policies for Creativity report, is sobering. In developed economies, 67 per cent of people possess essential digital skills; in developing economies the figure is 28 per cent. Cultural and creative leadership in developed countries has reached 64 per cent women in some institutional categories; in developing nations it is 30 per cent. Public funding for culture sits below 0.6 per cent of global GDP and is projected to decline. Only 61 per cent of countries surveyed have intellectual property frameworks UNESCO considers adequate.

These structural baselines were already producing inequality. Generative AI compounds them. Viviana Rangel, a Colombian independent expert quoted in the IPS News analysis, framed the problem in a sentence: the region does not produce this kind of technology; it consumes it. The economic flow runs in one direction. Cultural workers in Lagos, Lima, Manila, and Karachi see their commissions evaporate as European and North American clients route work through models trained on a corpus from which their own contributions are statistically marginal. The royalties and rents from those models, when they exist at all, flow to collective management organisations and rights holders concentrated in the North Atlantic.

This dimension has implications for every instrument discussed above. A European AI cultural levy, however well designed, will tend to recapture funds from European AI providers and recycle them through European collective management organisations to predominantly European creators. That is not necessarily wrong, but it is not a global solution. The CISAC study's projection of 22 billion euros in cumulative losses to music and audiovisual creators globally over five years is a number that needs distributional analysis. Where do the losses fall? Where do the few gains fall? UNESCO's framing of the problem as a global development issue, rather than a North Atlantic intellectual property dispute, opens space for instruments that the copyright debate alone would not generate.

The most credible candidates, at this point, are international transfers built into the supranational architecture of AI governance. A share of any revenues raised through training data taxes, statutory remuneration rights, or AI cultural levies should be directed, by treaty or legislative carve-out, to a global fund supporting creators in the regions where the harm falls hardest. This is not charity. It is restitution for an extraction whose proceeds are presently retained by a small group of companies whose corpora include cultural output from every continent. UNESCO, by virtue of its mandate over cultural diversity and the global character of its 120-country reporting, is the obvious institutional vehicle, although the World Intellectual Property Organisation and the United Nations Conference on Trade and Development have credible roles to play.

The harder version of the global south argument concerns sovereignty. If a Senegalese government wants to protect its translators, illustrators, and musicians from market compression caused by foundation models trained largely outside its borders, what tools does it have? The honest answer is: not many, in the short term. National AI levies on a small market produce modest revenue. National copyright reform reaches AI labs only weakly. National public commissioning and basic income programmes are constrained by fiscal capacity. This is one reason why the architecture of any serious policy response has to be partly supranational. It is also why policy frameworks that treat the global south as an afterthought, or that solve the problem of the European illustrator while leaving the Lagos illustrator untouched, will be morally and politically unstable.

Who bears responsibility?

The question of responsibility is the one most likely to be flattened by political slogans, so it is worth taking slowly. There are at least five candidates for the moral and economic ledger, and a serious policy framework needs to assign weight to each rather than collapsing them into a single villain.

The AI labs themselves are the most obvious candidate. They built the systems whose outputs are compressing creative labour markets. They trained the models on corpora they did not pay for, in most cases, and they continue to extract economic rent from those corpora at scale. The defence offered by lab leadership tends to combine the argument that training on publicly available content is fair use with the argument that the productivity gains from foundation models will, over time, raise everyone's incomes including creators'. Both arguments are contestable. The fair use claim is being litigated across multiple jurisdictions. The productivity-spillover claim has, so far, generated almost no observable benefit for the working creators whose markets are contracting fastest. Responsibility, on any plausible reading, sits substantially with the labs, and the policy instruments above should be priced accordingly.

The platforms that distribute creative work are a second locus. Streaming services that ingest AI-generated music into the same recommendation streams as human-made music; stock image platforms that have become, in some categories, predominantly synthetic; commissioning marketplaces that allow buyers to specify AI-generated drafts as deliverables. Each of these platforms makes choices about how to label, reward, and surface human versus synthetic output. UNESCO's report observes that opaque algorithms and platform consolidation are themselves part of the structural undercutting. Procurement-style transparency requirements, content provenance standards, and labelling rules are the relevant instruments here, and platforms are properly the subjects of them.

Governments are the third candidate. They license the regulatory environment within which labs and platforms operate, and they hold the fiscal and statutory authority to introduce levies, statutory remuneration rights, public commissioning rules, and basic income schemes. They also have the slowest reflexes. The EU AI Act, the UK text-and-data-mining consultation, the patchwork of state-level AI laws in the United States, and the regulatory regimes emerging across Asia and Latin America operate on time horizons measured in years; market compression is occurring in quarters. Responsibility for that gap falls on legislatures and on public agencies that have not yet pivoted from a copyright-only frame to a market-structure frame.

The fourth candidate is the end user: the corporate or individual buyer who chooses an AI-generated cover, a synthetic voice-over, or an automated translation over a human alternative. Moral responsibility here is real but limited. Buyers respond to prices, and prices are an artefact of upstream institutional architecture; no buyer can plausibly be expected to internalise an externality the policy regime has not bothered to price. End-user weight matters most in the public sector, in editorial institutions whose readers care about provenance, and in industries where reputation rewards transparency. Disclosure rules, labelling standards, and provenance technologies make this responsibility legible and therefore actionable.

The fifth candidate, the most diffuse and the least talked about, is the public itself, conceived as the political constituency that decides whether to treat creative labour as economically valuable enough to defend. The Irish basic income scheme exists because Irish politics decided it should. The WGA and SAG-AFTRA agreements exist because audiences, in the end, did not want to consume an industry whose writers and performers were being squeezed past tolerance. The slow shift in European policy thinking towards an AI cultural levy exists because European publics and their elected representatives have, for now, not lost their attachment to the idea that cultural work is a public good worth supporting through institutional design. That political attachment is not automatic. It can erode. Where it erodes, the labs and platforms set the frame.

What a serious settlement would look like

A serious policy settlement, on the analysis above, is not a single instrument but a stack. Copyright reform sits at the bottom of the stack, addressing the upstream ingestion question that copyright is institutionally suited to handle. Statutory remuneration rights and AI cultural levies sit above it, addressing the substitution-side compression that copyright cannot reach. Public commissioning rules and procurement preferences sit above those, deploying the state's purchasing power to maintain a demand floor for human creative work. Universal creative income schemes, on the Irish model, sit above those, decoupling baseline livelihood from market success. Collective bargaining and trade-association infrastructure sits across the stack, providing the institutional capacity for creators to negotiate consent, attribution, and compensation in real-time as the technology evolves. International transfers, capitalised by the levies and routed through multilateral cultural institutions, sit on top, addressing the global south dimension that no national policy can solve alone.

No single country has the full stack today. Ireland has a basic income scheme. France and the European Union are debating a levy. The United Kingdom has a collective licensing prototype. Spain has labelling rules. Germany has a private copying levy heritage that could be retrofitted. The United States has the WGA and SAG-AFTRA agreements, the GSA procurement clause, and California's vendor certification regime. India has labelling thresholds. UNESCO has 8,100 catalogued policy measures across 120 countries. The pieces exist; what is missing is the integration.

This is, in some sense, the unromantic conclusion. The problem that generative AI has created in the creative economy is not, primarily, a problem that demands a new philosophical framework, although philosophical frameworks help. It is a problem that demands the assembly of a known set of instruments into a coherent stack, with serious institutional design and credible enforcement, and with explicit redistribution towards the creators and regions where the harm is concentrated. The political difficulty of that assembly is high. The intellectual difficulty is lower than the public debate sometimes implies.

The alternative, if no such stack is built, is reasonably easy to describe. The compression continues. The freelance creative class, in the global north and more sharply in the global south, contracts. The cultural production that survives concentrates among those with independent means, institutional employment, or audiences large enough to bypass the compression. The texture of cultural output narrows in ways that are hard to see in real time but legible in retrospect, in the same way the disappearance of regional newspapers became legible only after the fact. The labs and platforms continue to capture the rents from a corpus they did not build. Lodovico Folin-Calabi, the UNESCO director who told the press at the report's launch that the world must critically examine how these technologies are deployed and whose voices are represented, may turn out to have been describing not a turning point but a wake.

Whether the settlement gets built is, finally, a political question rather than a technical one. The technical question has answers. The political question, whether public, labs, platforms, and governments collectively decide that the structural losses already under way are worth correcting, has only the answers a generation chooses to give. The 24 per cent number is a forecast. It is also a decision, not yet made.

References & Sources

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2. UNESCO Diversity of Cultural Expressions. “Making creativity matter: UNESCO's latest Re|Shaping Policies for Creativity report calls for bold policy action.” February 2026. https://www.unesco.org/creativity/en/articles/making-creativity-matter-unescos-latest-reshaping-policies-creativity-report-calls-bold-policy
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16. Bird & Bird. “Like Company v Google: CJEU Holds First-Ever Hearing on Generative AI and Copyright on 10 March 2026.” 2026. https://www.twobirds.com/en/insights/2026/like-company-v-google-cjeu-holds-first-ever-hearing-on-generative-ai-and-copyright
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19. Euronews. “Spain could fine AI companies up to €35 million for mislabelling content.” 12 March 2025. https://www.euronews.com/next/2025/03/12/spain-could-fine-ai-companies-up-to-35-million-in-fines-for-mislabelling-content

Tim Green UK-based Systems Theorist & Independent Technology Writer

Tim explores the intersections of artificial intelligence, decentralised cognition, and posthuman ethics. His work, published at smarterarticles.co.uk, challenges dominant narratives of technological progress while proposing interdisciplinary frameworks for collective intelligence and digital stewardship.

His writing has been featured on Ground News and shared by independent researchers across both academic and technological communities.

ORCID: 0009-0002-0156-9795 Email: tim@smarterarticles.co.uk

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