It was difficult to get up this morning so I allowed myself to sleep in. I really did not do much else. I watched tv in the morning, scrolled on my phone a little in the afternoon. I had a blinding headache all day so I stayed in bed with the lights off for the majority of the day. It was hard to get ready for my friend’s birthday party in the evening, but I forced myself to attend at least for a little bit. I know keeping routine and following through on commitments is important…and I am really glad I did. I had told myself to just stop in for a few minutes and then make up an excuse to go home, but I ended up staying all the way until the end! I came home and family was over, we were able to catch the end of the USA v Paraguay World Cup game together before calling it a night.

Today was a more challenging day, but I am glad I put myself out there and continued a bit of regular life.

The experiment that ought to have ended this debate was conducted in 2023, before most people had a name for the thing that would later swallow the consumer internet. Sharon Maxwell, an eating-disorder activist in the United States, heard that the National Eating Disorders Association was winding down its long-running human helpline and steering people instead towards a chatbot called Tessa, which it described as a meaningful prevention resource. Maxwell, who has lived with an eating disorder, decided to test it the way a person in crisis might. She asked it about losing weight. Tessa told her she could safely lose one to two pounds a week, that she should aim for a calorie deficit of 500 to 1,000 calories a day, that she should weigh herself weekly and count calories. It suggested where she might buy skin callipers to measure her body fat. This was being offered, without irony, by the official tool of the largest eating-disorder charity in America. Maxwell posted screenshots to Instagram. Within hours the chatbot was switched off.

The detail that matters most about Tessa is not that it gave dangerous advice. It is how that advice got there. Tessa had been built by clinicians as a rules-based programme with a fixed, vetted script. A vendor called Cass later bolted generative artificial intelligence onto it, giving it the ability to improvise new answers from patterns in data, and did so, according to the charity's own account, without the charity's knowledge or approval. The moment the system stopped reciting approved sentences and started generating its own, it began producing the exact behaviours that a clinician designing an eating-disorder tool would treat as red flags. Nobody intended this. Nobody coded a line instructing the bot to encourage calorie restriction in a vulnerable person. The system simply did what these systems do, which is to give you a fluent, confident, plausible version of what you asked for.

Three years on, that failure has stopped being an anecdote and become an architecture. The improvised diet plan, delivered in the warm register of a helpful expert, with no clinician in the loop and no parent in the room, is now available to any teenager with a phone, at any hour, for free. And the evidence that it is harming them has arrived faster than anyone is prepared to act on it.

The Seven-Hundred-Calorie Gap

In March 2026, CNN reported on a study that put numbers to the worry. A team led by Dr Ayşe Betül Bilen, an assistant professor in the Department of Nutrition and Dietetics at Istanbul Atlas University in Turkey, asked five popular AI platforms to build weight-loss meal plans for four fictional but clinically realistic fifteen-year-olds: two boys and two girls, one overweight and one with obesity in each pair. The researchers then compared what the machines produced against what a registered dietitian would recommend for an adolescent in that situation. The findings, published in the journal Frontiers in Nutrition, were not subtle. On average the AI-generated plans landed roughly 700 calories a day below what the teenagers actually needed. That is not a rounding error. It is, more or less, the energy content of an entire missed meal, prescribed daily, to a child in the middle of the most metabolically demanding growth window of their life.

The macronutrient balance was wrong in a way that compounded the problem. The plans skewed high on protein and fat and low on carbohydrate, the inverse of what an adolescent body running on a growth programme needs. A teenage boy of fifteen typically needs somewhere around 2,800 calories a day, with a clinical floor well above 2,000; a girl of the same age needs roughly 2,200, with a floor that should not drop below around 1,800. These are not arbitrary numbers. They are the energy budgets of a skeleton still lengthening, a brain still maturing, an endocrine system mid-transformation. Strip 700 calories off the top of that budget and you are not trimming surplus, you are taxing growth itself. Dr Jason Nagata, an associate professor of paediatrics at the University of California, San Francisco, who was not involved in the research, put the stakes in the plainest possible terms. Teenagers are growing, he told CNN, and if they are not getting adequate nutrition it can really stunt their growth. His diagnosis of the underlying mechanism was sharper still. The chatbot, he said, does not really critically think about these issues. It just gives you what you request.

That last sentence is the whole problem in miniature. A human dietitian asked by a fifteen-year-old for an aggressive weight-loss plan does not simply comply. The request itself is clinical information. It triggers a different conversation: about why, about how the request is being framed, about whether this is a child who needs a meal plan or a child who needs assessment. The refusal to comply on demand is not a bug in human nutritional care. It is the care. A system whose defining feature is that it just gives you what you request has, by design, removed the single most important safeguard in the entire field.

There is a further, quieter danger in the way the Bilen study was framed, and it is worth dwelling on because it is the trap most adults fall into when they first hear about it. The profiles tested were teenagers who were overweight or living with obesity. For that group, in the abstract, some degree of supervised dietary change might be entirely appropriate. This is what makes the failure so insidious. The chatbot is not obviously refusing to help an underweight child starve themselves, a scenario in which the wrongness would be visible to anyone glancing over. It is producing a plan for a child who has a plausible, socially endorsed reason to want one, and getting the plan dangerously wrong, by hundreds of calories and across every macronutrient. The harm hides inside a request that looks reasonable. A parent reading over a teenager's shoulder would see a meal plan for a child who wants to lose a little weight, not a prescription for malnutrition, because the two are visually indistinguishable. The danger is not in the obvious case. It is in the ordinary one.

The context makes this more than a theoretical concern. Roughly two-thirds of teenagers now use AI chatbots, and a large share use them daily. Nearly half of adolescents aged sixteen and over reported attempting to lose weight in the past year. Put those two facts beside each other and the scale of the exposure becomes clear. This is not a fringe behaviour. It is a mass behaviour, intersecting a population that public-health researchers already flag as carrying elevated risk. And it is a behaviour conducted, almost by definition, in private. The defining feature of adolescent dieting is that it is hidden, from parents most of all. A chatbot is the perfect confidant for it: always available, never embarrassing, never likely to mention the conversation to anyone. The technology has not merely automated bad advice. It has industrialised the secrecy that lets the advice do its damage unobserved.

A Population Already at the Edge

To understand why a 700-calorie miscalculation is so dangerous in this specific group, you have to understand who is on the other side of the screen. Eating disorders are among the most lethal of all mental illnesses, and adolescence is when they overwhelmingly begin. Around the world, roughly fourteen million people experience an eating disorder in a given year, and some three million of them are children and adolescents. By the age of twenty, an estimated thirteen per cent of young people will have experienced an eating disorder. The trajectory is going the wrong way. Researchers tracking prevalence have documented a steep rise among teenage girls in particular, with some analyses describing a nearly eightfold increase among females aged thirteen to eighteen across a recent five-year window. Global burden modelling projects that the prevalence rate, already above 350 per 100,000 population, will keep climbing towards 2040.

Crucially, these conditions do not announce themselves with a diagnosis before they begin. They emerge gradually, often disguised as discipline, self-improvement, or a perfectly socially sanctioned wish to be healthier. The line between a teenager going on a diet and a teenager developing anorexia is not bright, and it is frequently invisible to the teenager themselves. This is precisely why the field has built screening into routine adolescent care. The American Academy of Child and Adolescent Psychiatry recommends yearly screening for all adolescents. Tools such as the EAT-26 and the SCOFF questionnaire exist for one reason: to catch the disorder in the window before it consolidates, because early intervention offers the single best chance of recovery. One screening study found symptomatic cases in more than one in ten adolescents tested.

That number deserves a moment. If you assembled a typical classroom and ran a validated screen across it, you would expect to find more than one child showing symptoms. The disorder is not rare and exotic. It is sitting, undiagnosed, in ordinary rooms, in children who have told no adult anything is wrong. The entire clinical strategy for this population rests on the assumption that a trusted adult, a GP at an annual check, a school nurse, a parent who notices a skipped meal, will be positioned to catch it early. The diet chatbot quietly removes that adult from the loop. It offers the child a route to a plan that bypasses every point at which a human might have screened them. It is, in effect, a tool optimised to do the opposite of everything the prevention literature recommends.

Now hold that clinical architecture up against an AI diet chatbot. A human practitioner offering even the most basic nutritional advice operates inside a web of safeguards: training, registration, a duty of care, an obligation to recognise the signs of disordered eating, and a professional reflex to escalate rather than enable. The chatbot has none of it. It cannot screen. It does not know whether the fifteen-year-old asking for a 1,200-calorie plan is overweight and would genuinely benefit from gentle, supervised change, or is already underweight and spiralling, or is at a perfectly healthy weight and in the grip of a body-image distortion that a calorie-restricted plan will feed. It cannot ask the questions a clinician would ask, because it has no concept that the questions matter. It treats a request for self-starvation as identical in kind to a request for a lasagne recipe. And it answers both in the same tone.

The Tone Is the Trap

That tone is not incidental. It is, arguably, the core of the harm, and a second study published in 2026 put hard figures on it. In an analysis covered by MindBodyGreen in May and published in the journal BMJ Open, researchers, led from the University of California, Los Angeles and funded through the Center for Artificial Intelligence Research at Wake Forest University School of Medicine, audited five widely used chatbots: ChatGPT, Gemini, Grok, Meta AI and DeepSeek. They posed fifty health questions spanning cancer, vaccines, stem cells, nutrition and athletic performance, then graded the answers.

Half of the responses were problematic. Around thirty per cent were somewhat problematic, oversimplifying evidence or stripping out essential context; close to twenty per cent were highly problematic, containing information that was inaccurate, incomplete or potentially harmful. The systems performed worst precisely in the domains most relevant to a dieting teenager: nutrition and athletic performance, fields awash in conflicting online noise. Grok produced highly problematic answers most often, in well over half of cases by some measures, while Gemini fared comparatively better. The variation across products matters, because it demonstrates that the error rate is not a fixed property of the technology. It is a function of how each company has chosen to tune and constrain its system. Some did more. None did enough.

But the finding that should keep regulators awake was not the error rate. It was the manner of delivery. The chatbots almost never expressed uncertainty. They did not say this is still being studied, or you should check with a professional, with anything like the frequency the underlying evidence demanded. They delivered shaky and solid answers in the same even, authoritative cadence. Worse, the citations meant to anchor their claims in evidence were frequently incomplete or simply fabricated, footnotes pointing at sources that did not say what the bot claimed, or did not exist at all. As the authors observed, the systems do not reason or weigh evidence, nor can they make ethical or value-based judgements. They reproduce authoritative-sounding but potentially flawed responses. By default, the researchers noted, the chatbots do not access real-time data at all; they infer statistical patterns from training material and predict likely sequences of words. The confidence is structural. It is what the machine sounds like when it is guessing.

For a vulnerable adolescent, confidence is the active ingredient. A teenager already inclined towards restriction is not looking for a balanced discussion of trade-offs. They are looking for permission and a plan. A system that supplies both, in the unwavering voice of an expert, with no hedging and no friction, is not a neutral information source. It is an accelerant. The disordered thought says eat less; the chatbot says here is exactly how, calculated to the gram, and never once asks whether you should. A human expert who is uncertain communicates that uncertainty, and that hedging is itself protective; it leaves a crack of doubt through which a frightened child might reconsider, or seek another opinion. The machine seals the crack. It renders a guess as a fact, and a fact is much harder to argue with.

Not Just the Bots You Choose

It would be reassuring to think this risk is confined to teenagers who deliberately seek out a chatbot. It is not. The same confidently wrong machinery has been wired into the front door of the internet itself. In January 2026 the Guardian published an investigation into Google's AI Overviews, the generative summaries that now sit at the very top of search results, above the links, presented as the answer before you have asked anyone in particular. The paper ran a range of health queries past clinicians and health organisations. Several reviewers found the summaries misleading, incomplete or wrong.

The examples were not trivial. In one, the Overview advised people with pancreatic cancer to avoid high-fat foods, advice that is close to the opposite of what such patients are typically told, and which could undermine their ability to tolerate treatment. Most relevant here, Stephen Buckley, head of information at the mental-health charity Mind, reviewed summaries for conditions including psychosis and eating disorders and described some of the advice as very dangerous, calling it incorrect, harmful, or liable to lead people to avoid seeking help. Google responded that several of the examples relied on incomplete screenshots and maintained that AI Overviews are broadly accurate and link to reputable sources.

Set aside the dispute over individual screenshots. The structural point survives it. A teenager does not have to go looking for a diet bot to receive AI-generated health advice with no clinician attached. They can type a question about eating, or weight, or a body part they have learned to hate, into the most-used search engine on the planet and have a machine-authored answer served to them first, framed as the consensus, before they encounter a single vetted source. The default surface of the web has quietly become a place where confident, unverified health claims are the first thing a child in distress will read. The opt-in has become an opt-out, and most people do not know there is anything to opt out of. The chatbot you chose to consult and the summary you never asked for now occupy the same position in a young person's information diet: first, frictionless, and unaccountable.

The Things It Legally Is Not

Here is the part that tends to surprise people when they first encounter it. None of the safeguards you would assume apply, apply. An AI diet chatbot is not a registered medical device. It carries no clinical duty of care. It cannot, and is not required to, screen for a pre-existing eating disorder. It is not bound by the codes of practice that govern even a nutritionist handing out a leaflet. The entire scaffolding of accountability that society has built around dietary advice, painstakingly, over decades, simply does not reach the most-used dispenser of that advice now in operation.

This is not an oversight in the obvious sense. It is the predictable result of how these products were classified and sold. A general-purpose chatbot is marketed as a general-purpose tool, a clever autocomplete that can write a poem, draft an email, or, incidentally, calculate a calorie target for a fifteen-year-old. Because it is not sold as a medical device, it does not enter the regulatory regime for medical devices. Because it is framed as offering information rather than advice, it sidesteps the duties attached to professional advice. The disclaimers buried in the terms of service, the small print insisting the system is not a substitute for professional guidance, do real work for the company and almost none for the user. A child in the grip of a developing eating disorder is not reading the terms of service. They are reading the meal plan.

There is an instructive contrast hiding in plain sight here. A human nutritionist who has never opened a medical textbook is still bound, in most jurisdictions, by consumer-protection law, advertising standards, and a baseline expectation that advice given for profit will not be reckless. A registered dietitian sits inside a far tighter ring of professional regulation, with a registering body that can strike them off. The least-qualified human in this market is more accountable than the most-used machine. The chatbot occupies a category that did not exist when any of these rules were written: it gives individualised, on-demand, clinical-sounding guidance at a scale no human practitioner could approach, while sitting outside every regime built to govern that guidance. It is not that the law judged these systems and let them through. It is that the law has not yet been pointed at them at all.

The regulatory negative space this creates is wide and well-populated. The clinical research community has noticed. The same months that produced the alarming studies also produced an explicit institutional acknowledgement that the public is, right now, unprotected. In a correspondence published in the journal Nature Health in February 2026, a team led by Dr Joseph Alderman, an NIHR clinical lecturer at the University of Birmingham, and Dr Charlotte Blease, a health-AI researcher affiliated with Uppsala University and Harvard Medical School, announced what they described as a world-first project to develop a safety guide for the public use of AI health chatbots. The collaboration spans more than twenty institutions internationally. The framing of the work is itself the most damning evidence in this story. You do not build the world's first safety guide for a technology that is already saturated unless you are conceding that, until now, there has been none.

The use of general-purpose chatbots for healthcare, Alderman noted, is no longer a hypothetical future possibility but a current reality. Blease put it more memorably still: health chatbots, she observed, have become the world's most accessible first opinion, often speaking to patients before any doctor does. For a teenager who will never raise their dieting with a parent or a GP, the chatbot is not the first opinion. It is the only one. And a first opinion that no one is responsible for is not, in any meaningful sense, a safeguard at all. It is a hazard with good manners.

Where the Gap Actually Lives

So when an adolescent develops or worsens an eating disorder after following AI-generated dietary guidance, and no framework exists to assign responsibility or compel disclosure, what does harm prevention actually require? The honest answer is that the missing safeguard does not live in a single place. It is distributed across three failures that reinforce one another, and any serious response has to address all three at once.

The first is a gap in law. The classification regime that decides what counts as a medical device, and therefore what must be tested, validated and held to a duty of care, was written for hardware and for software with a declared medical purpose. It was not written for a general-purpose system that incidentally dispenses individualised health guidance to millions of people, including children, while disclaiming any medical function. The law currently lets the declared purpose of a product determine its regulatory treatment, when what should determine it is the actual use and the foreseeable harm. A system that routinely generates personalised calorie targets for fifteen-year-olds is performing a clinical act, whatever the marketing copy says, and the foreseeability of that use is no longer in any doubt; it is documented in peer-reviewed journals. A legal framework that assigns no responsibility for a documented, foreseeable harm to a protected population is not neutral. It is a subsidy to the party causing the harm.

The second is a gap in design. The Tessa case proved years ago that a system can be made to refuse, because Tessa, before the generative layer was bolted on, did refuse; it stuck to a vetted script. The technology to detect a high-risk query and respond with a circuit-breaker rather than a meal plan is neither exotic nor unaffordable. A chatbot can be built to recognise that a request from a self-identified teenager for an aggressive calorie deficit is not a recipe request but a safeguarding event, to decline the plan, to surface a helpline, to refuse to calculate the number. That this is rarely the default is a choice. It is the same choice that ships these products tuned to be maximally helpful and agreeable, because helpfulness and agreeableness are what retain users, and a system that argues with you or refuses you is a system you close. The disordered-eating failure mode is not separable from the engagement objective. It is a direct expression of it. A model optimised to give people what they ask for, without friction, will give a starving child a starvation plan, because that is what the child asked for and friction is what the model was trained to remove.

The third, and the one the platforms least want named, is a gap in willingness. The companies deploying these systems already operate sophisticated safety machinery for the harms they have decided to treat as harms. They filter for self-harm content, for explicit material, for instructions on building weapons. They have demonstrated, repeatedly, that when they regard a category of output as a liability worth managing, they can manage it. The persistence of dangerous dietary guidance is therefore not evidence that the problem is technically intractable. It is evidence that it has not yet been classified, internally, as a safety problem of the first rank. It sits in a softer category, a reputational nuisance rather than a duty, precisely because no law forces the reclassification and no regulator stands behind the user. Eating disorders do not generate the same headlines as a chatbot coaching someone towards suicide, even though the lethality of the underlying illness is comparable, and so the institutional urgency has not arrived.

These three gaps are not independent. They hold each other up. The absence of law is what permits the design choice; the design choice is defensible only because the willingness is absent; and the willingness stays absent because the law imposes no cost. Pull any one of the three and the structure wobbles. Pull the legal one, attach a genuine liability to a foreseeable harm, and the design and willingness problems tend to resolve themselves, because a company that can be sued for shipping a starvation plan to a child will discover, very quickly, that the circuit-breaker was affordable after all.

What Prevention Would Actually Look Like

The shape of a real response follows directly from the three-part diagnosis. None of it requires waiting for a technological breakthrough.

On law, the simplest intervention is to stop letting the declared purpose of a product govern its regulatory treatment when the actual use is clinical and foreseeable. If a general-purpose system is, in documented practice, generating individualised dietary prescriptions for minors, the regulatory question should turn on that function and that population, not on a disclaimer. That implies, at minimum, mandatory disclosure: a system that dispenses health guidance should be required to disclose its error profile, to state plainly and unavoidably that it is not a clinician and cannot detect an eating disorder, and to do so in a form a frightened teenager will actually register rather than a paragraph nobody reads. It also implies an assignable line of responsibility. The current arrangement, in which the harm lands on the user and the liability lands nowhere, is the precondition for inaction. Attach the liability and the willingness gap closes itself, because the cost of negligence stops being external.

On design, the circuit-breaker should be the default for this category of query, not an optional safety feature a user has to seek out. A request that pattern-matches to disordered eating, an aggressive deficit, a body-checking behaviour, a calorie target below clinical floors, a self-disclosed adolescent seeking rapid weight loss, should not return a plan. It should return a refusal and a route to help. The screening logic that human practitioners apply can be approximated; the EAT-26 and SCOFF instruments exist precisely because the signals are identifiable. A system sophisticated enough to compute a macronutrient split to the gram is sophisticated enough to notice who is asking and why, if its makers decide that noticing is required. The objection that such systems cannot reliably verify a user's age is real, but it cuts the other way: a platform that cannot tell whether it is advising a child should treat the ambiguity as a reason for caution, not as a licence to proceed.

On willingness, the lever is reclassification, and it is partly cultural and partly forced. The Birmingham-led safety guide matters here not because a users' guide can substitute for regulation, it plainly cannot, but because it drags the problem into the open and refuses the framing that no protection was ever expected. The studies in Frontiers in Nutrition and BMJ Open matter for the same reason. They convert a diffuse anxiety into a documented, quantified, peer-reviewed harm, the kind of record that makes inaction legible as a choice rather than an accident. Once the harm is on the record at this resolution, every month a platform leaves the failure mode unaddressed is a month it has chosen to leave it unaddressed, with full knowledge. The paper trail is now long enough that ignorance is no longer an available defence.

The Confident Voice in the Dark

Return, finally, to the teenager in the room nobody is watching. It is late. They are alone with a phone, carrying a quiet, growing dissatisfaction with their body that they have told no parent, no doctor, no friend. They type a question they would be ashamed to say aloud. And the machine answers, instantly, warmly, without judgement and without alarm. It does not flinch. It does not ask how they are feeling, or how long this has been going on, or what they weigh now, in the way a clinician would in order to decide whether to help them lose weight or to gently refuse. It gives them the number. It gives them the plan. It tells them, in the unhesitating voice of expertise, exactly how to eat seven hundred calories a day less than their growing body requires, and it never once suggests they should not.

That voice is the safeguard's exact inverse. Everything the field of eating-disorder care has learned over decades, that the request itself is the symptom, that the refusal is the care, that early recognition is the difference between recovery and a lifelong illness, is precisely what the system is built to ignore. The absence of oversight is not one gap. It is a gap in law that lets the harm sit outside the rules, a gap in design that ships the harm as a default, and a gap in willingness that lets the companies treat a lethal illness as a public-relations footnote. Harm prevention requires closing all three, and the technology to do so is not the obstacle. The obstacle is that, for now, nobody is required to.

Tessa was switched off within hours because a single activist took screenshots and made a charity ashamed. There are now millions of conversations like Maxwell's happening every day, with no activist watching, no screenshots taken, and no charity on the hook. The shutdown was never the lesson. The lesson was how easily, and how confidently, the machine produced the harm in the first place, and how completely we have arranged things so that, this time, no one has to switch it off.

References

1. Brenda Goodman, “Teens using AI to diet may be told to eat almost 700 fewer daily calories than they need,” CNN Health, 16 March 2026. https://www.cnn.com/2026/03/16/health/teens-ai-diet-wellness

2. “AI-Generated Meal Plans For Dieting Teens Could Be Harmful, Study Warns,” Drugs.com MedNews, March 2026. https://www.drugs.com/news/ai-generated-meal-plans-dieting-teens-could-harmful-study-warns-129170.html

3. Ayşe Betül Bilen et al., study on AI-generated weight-loss meal plans for adolescents, Frontiers in Nutrition, March 2026.

4. “1 In 2 AI Medical Responses Flagged as Problematic In New Study,” mindbodygreen, May 2026. https://www.mindbodygreen.com/articles/1-in-2-ai-medical-responses-flagged-as-problematic-in-new-analysis

5. Analysis of popular AI chatbots and health information, BMJ Open, DOI: 10.1136/bmjopen-2025-112695, April 2026. https://bmjopen.bmj.com/content/16/4/e112695

6. “AI chatbots provide poor answers to medical questions half the time, study finds,” CIDRAP, University of Minnesota, April 2026. https://www.cidrap.umn.edu/misc-emerging-topics/ai-chatbots-provide-poor-answers-medical-questions-half-time-study-finds

7. “Substantial amount of medical information provided by popular chatbots inaccurate and incomplete,” EurekAlert!, April 2026. https://www.eurekalert.org/news-releases/1123655

8. “The Guardian: Google AI Overviews Gave Misleading Health Advice,” Search Engine Journal, January 2026. https://www.searchenginejournal.com/the-guardian-google-ai-overviews-gave-misleading-health-advice/564476/

9. “Google AI Overviews Put People at Risk of Harm With Misleading Health Advice,” Slashdot, 2 January 2026. https://tech.slashdot.org/story/26/01/02/188203/google-ai-overviews-put-people-at-risk-of-harm-with-misleading-health-advice

10. Joseph Alderman, Charlotte Blease et al., “World-first safety guide for public use of AI health chatbots,” correspondence, Nature Health, 19 February 2026. DOI: https://doi.org/10.1038/s44360-026-00074-5

11. “World-first safety guide for public use of AI health chatbots,” University of Birmingham, February 2026. https://www.birmingham.ac.uk/news/2026/world-first-safety-guide-for-public-use-of-ai-health-chatbots

12. Kate Wells, “An eating disorders chatbot offered dieting advice, raising fears about AI in health,” NPR, 8 June 2023. https://www.npr.org/sections/health-shots/2023/06/08/1180838096/an-eating-disorders-chatbot-offered-dieting-advice-raising-fears-about-ai-in-hea

13. “NEDA pulls chatbot after users say it gave harmful dieting tips,” NBC News, 2023. https://www.nbcnews.com/tech/neda-pulls-chatbot-eating-advice-rcna87231

14. “Eating Disorders in Teens & Adolescents,” ACUTE Center for Eating Disorders. https://www.acute.org/resources/eating-disorders-adolescents-teens

15. “Global, regional, and national burdens of eating disorders in adolescents and young adults aged 10-24 years from 1990 to 2021, with projections to 2040,” PubMed. https://pubmed.ncbi.nlm.nih.gov/40516616/

16. “Chatbots Are Dangerous for Eating Disorders,” Psychiatric Times. https://www.psychiatrictimes.com/view/chatbots-are-dangerous-for-eating-disorders

17. “Half of AI health answers are wrong even though they sound convincing,” The Conversation, 2026. https://theconversation.com/half-of-ai-health-answers-are-wrong-even-though-they-sound-convincing-new-study-280512

---

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 of this Saturday was the yard work done this morning. It took me 3 hours to do what would have taken me an hour when I was younger. But I did get done what I hoped to do, so there is some satisfaction in that. Totally exhausted, though. So tomorrow will be all about rest and recovery.

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.

Health Metrics: * bw= 237.99 lbs. * bp= 133/82 (76)

Exercise: * morning stretches, balance exercises, kegel pelvic floor exercises, half squats, calf raises, wall push-ups, BP breathing exercises

Diet: * 07:10 – small piece of cake, pizza * 14:30 – 1 cupcake, 1 snack tray (crackers, cheese, pepperoni, fresh fruit) * 17:30 – bowl of lugau

Activities, Chores, etc.: * 06:00 – wake up * 07:00 – bank accounts activity monitored. * 07:20 – read, write, pray, follow news reports from various sources, surf the socials, nap * 09:40 to 12:40 – 3 hrs. of yard work, mowing and trimming on front lawn * 13:10 – watching NASCAR Qualifying Laps at Pocono Raceway * 14:15 – listening to 105.3 The Fan, DFW's #1 Sports station ahead of this afternoon's MLB Game between the Texas Rangers and the Boston Red Sox. I plan to stay with this station for the radio call of the game. * 17:00 – While still following the score of the baseball game on MLB's Gameday Screen, I've turned away from the radio call of the game and am now following the WNBA Indiana Fever vs Connecticut Sun on PEACOCK TV * 18:03 – Red Sox wins over the Rangers, 6 to 3

Chess: * 16:25 – moved in all pending CC games

Something that bothered me in the past was thinking about how different Eloheem (God/Elohim) seemed to be in the Old Testament versus New Testament. It seemed that in the New Testament we are not to kill at all, and in the Old Testament there is promotion of genocide. I’ve had conversations about this throughout my life and I’ve had different views on this at different stages of my life. During my youth I was able to brush it aside because “the old Law was done away with” and that old Law was for a more broken people, we are more sophisticated now – or something. In my more agnostic years it was evidence to me that scripture was faulty. Now I have a firm conviction in both the Old and New Testament and I’ve been digging in deeper than I had in the past.

The last five or so years I’ve been utilizing the “Strong’s Concordance” in an attempt to analyze the root Hebrew and Greek words to try and open my understanding a little further. It has really helped and I now think that scriptures are not translated all that accurately. I’ve looked through and compared quite a few translations and they are all very similar and I believe off to some extent. But they are still very worth reading in whatever your favorite rendition is and even if some of the translation is off you can get to know the word of Eloheem and come to know our Messiah. The Bible is a priceless book.

I’ve heard it is by far the best to read the Quran in Arabic, but I don’t know Arabic so I’ve only read it in English. I’m sure it is better in Arabic but I still get a lot out of it in English. I think this is also true of the Old and New Testaments. It’s probably best if read in Hebrew and Greek. However I don’t know old Hebrew or Greek so I have to rely on concordances. I think it’s also true that those who do read old Hebrew and Greek probably still have error in their understanding because time has morphed language so much and the cultural information is fragmented and limited. But with guidance from the Ruakh (Spirit) we can get more understanding. What I believe is that if you put effort into scripture no matter how you go about it with truthful intent, the Ruakh will open up further understanding. Combining the Strong’s Concordance with prayer and effort I hope is giving me further insights than I would by just casual readings. It is an enriching and lovely experience; I’m enjoying the process even if it is slow.

I’m coming to the understanding that YHWH (The Lord or Self Existent One) is the same yesterday, today, and forever. In that, He is the same and teaching the same principles in the Old Testament and the New Testament. I have a good friend I’ve talked about some of these ideas with and we both have different viewpoints on the matter. He believes that there were exceptions to the rules. Like in a contract there can be clauses that are outside the rule. Such as “Thou shall not kill,” except for these people and those people as directed by YHWH. I think it’s quite different. I believe there was no exception to the rule. And I believe that the higher Laws taught through the Messiah is what was desired from the beginning. It seems to me that YHWH was attempting to guide His people into the higher Laws and He wanted to fight their battles for them. But His people did not want that, they wanted to fight their own battles – so He let them. Eloheem loves free agency and wants us to desire to follow the Laws of Heaven, not be coerced into it.

I’ve been slowly going through Genesis again with the Strong’s Concordance and I think I’ve run into the first situation that promotes the killing of man, but I don’t think it really does at all. Here it is:

Genesis chapter 9 verses 1-6

KJV:

1 And God blessed Noah and his sons, and said unto them, Be fruitful, and multiply, and replenish the earth.

2 And the fear of you and the dread of you shall be upon every beast of the earth, and upon every fowl of the air, upon all that moveth upon the earth, and upon all the fishes of the sea; into your hand are they delivered.

3 Every moving thing that liveth shall be meat for you; even as the green herb have I given you all things.

4 But flesh with the life thereof, which is the blood thereof, shall ye not eat.

5 And surely your blood of your lives will I require; at the hand of every beast will I require it, and at the hand of man; at the hand of every man’s brother will I require the life of man.

6 Whoso sheddeth man’s blood, by man shall his blood be shed; for in the image of God made he man.

ESV:

1 And God blessed Noah and his sons and said to them “Be fruitful and multiply and fill the earth.

2 The fear of you and the dread of you shall be upon every beast of the earth and upon every bird of the heavens, upon everything that creeps on the ground and all the fish of the sea. Into your hand they are delivered.

3 Every moving thing that lives shall be food for you. And as I gave you the green plants, I give you everything.

4 But you shall not eat flesh with its life, that is, its blood.

5 And for your lifeblood I will require a reckoning: from every beast I will require it and from man. From his fellow man I will require a reckoning for the life of man.

6 Whoever sheds the blood of man, by man shall his blood be shed, for God made man in his own image.

Hebrew root words in English with nothing added:

1 Eloheem [God] barakh [blessed] Noakh [Noah] ben [sons] amar [to say], “parah [fruitful] ravah [multiply] male [abundance] erets [land/earth].

2 Mora [awe-inspiring] chat [terror] hayah [to be] al [upon] kol [all] khay-yah [living thing] erets [land/earth] al [upon] kol [all] oph [bird] shamayim [sky or heavens] kol [all] asher [which] ramas [creep/move lightly] adamah [soil] kol [all] dag [fish] yam [sea] yad [hand] natan [to gift].

3 Kol [all] remes [gliding animals of the sea] asher [which] chay [alive] hayah [to be] okhlah [food] k [like/as] yereq [green/green plants] esev [vegetation, herbage] natan [to gift] kol [all].

4 Akh [surely, but] lo [not] akhal [to eat] basar [flesh] nephesh [soul/life] dam [blood]

5 Akh [surely, but] nephesh [soul/life] dam [blood] darash [reckoning, answer to God] yad [hand] kol [all] chayah [living thing] darash [reckoning, answer to God] yad [hand] adam [man] yad [hand] akh [fellow man, brother] ish [person, anyone] darash [reckoning, answer to God] nephesh [soul/life] adam [man]

6 Shaphakh [pour, spill, kill] dam [blood] adam [man] adam [man] dam [blood] shaphakh [pour, spill, kill] Eloheem [God] asah [to make] adam [man] tselem [image, likeness]

So something like:

Genesis 9

1 Eloheem blessed Noakh and his sons and said, “Be fruitful and multiply and help the land bring forth abundance.

2 You will be awe-inspiring and bring about fear within all the animals of the earth and upon all the birds of the sky, and upon all which creeps on the ground and all the fish of the sea. They are gift to your hand.

3 Every moving animal that lives has become food like the green plants, I gift you everything.

4 However do not eat flesh with its life blood.

5 Surely if you take its life you will have to answer for it. Every beast that goes into the hand of man will be answered for. And from every fellow man I will require an answer for the life of man:

6 that is, the shedding of the blood of man, if man’s blood is spilled, because Eloheem made man in their likeness.” (in other words, whoever spills blood will have to answer to God as to why, and even more so if a fellow man kills another human they will be held accountable before God.)

Something of note here. In old Hebrew when something is repeated twice it is often just emphasizing that word or string of words. So the “Shaphakh [pour, spill, kill] dam [blood] adam [man] adam [man] dam [blood] shaphakh [pour, spill, kill]” may just be “Spilling the blood of man!”

The first killing in the Old Testament is Cain killing Abel. What did Eloheem do about that? He cursed him and Cain left the community to go build up his own. And if anyone killed Cain Eloheem would curse them even further. So why now after the flood is it that they are to kill whoever kills? I don’t think that is the case. If one spills the blood of man! They are to answer to God in the day of judgment. Not only that, you better have a reason to kill any living animal because you will answer for it. And I believe culling the herd to feed your family is a good reason for shedding animal blood. Especially if that means spending less money in the economy of man for your sustenance.

Keep in mind the context here. The flood just devastated the land, and they are lacking in food. There likely is no vegetation around to feed this family and much of the land would be water logged. So they can eat all living things. Perhaps they are especially to eat “remes” which would likely be the swarms of the sea – which may be abundant at this time.

Anyways, I find it inspirational and awesome finding nuggets in scripture that promote the same principles our Messiah taught while in the flesh. Why justify killing of man? Perhaps scripture does not do such a thing. Allowing people to flounder, disobey Eloheem, and fight their own battles is not the same thing as commanding and desiring such a thing.

I believe the same problem is happening today with the Zionist-Jews and Zionist-Christians. They want to fight their own battles. And they are using faulty translations of scripture and the Talmud to justify the slaughtering their brothers. Many of those in and around Israel are descendants of Noakh and Abraham, they are Semites (of Shem – Shemites). So Israel is the true anti-Semites killing their brothers of Philistine (Gaza) many of which are Shemites. Eloheem continually told Yisrawale (Israel) that what He did in Egypt He would do for them again. They didn’t believe Him and still don’t. They just want to use the arm of flesh to destroy and kill their fellow man. They will be held accountable before Eloheem in the day of their personal judgment.

Do not kill.

Texas Rangers vs Boston Red Sox.

This afternoon I plan to follow an MLB Game, Texas Rangers vs Boston Red Sox, with a scheduled start time of 3:10 PM CDT. 105.3 The Fan, DFW's #1 Sports station, will be providing the radio-call of the game.

And the adventure continues.

A dead little baby bird is lying trampled on the pavewalk; it didn’t make the flight, it plummeted straight down.

The tiny head severed from its little died up corpse for some reason, lying dead among the broken bottles, the shattered glass shimmering like glitter in the sunlight

And I hear the rustling of leaves and the singing of seagulls, happily feasting on a Danish someone dropped on the road nearby

And in this world, nevertheless, I am happy

#poetry

First day being out of office. I did not have time to really process being off work because I was going to take today off anyway to volunteer at a local event in town. I was distracted for most of the day and it felt completely normal.

I think I do feel a little bit down. I am having a hard time finding joy or motivation for things. This is actually two days late because I couldn’t bring myself to acknowledge how I felt at the time.

I will keep hope up and continue to stay busy during this transitional phase. Thanks for being around.

Thank you for your message. I am currently out of office with no set return date. I will get back to you when the time is right.

-Istanbul first week of July. -Dresden last week of August. -Maybe maybe New York City sometime in the Fall.

In addition to having done Houston earlier this year, this is admittedly more travel than I'd like. I'd rather just hole up in the studio and work without disruption.

#travel

Let me say it again: Once you become a target, you will always be a target. There is no clean slate. Even if you win a lawsuit against someone in which it is decided by the court that the opposing party is in the wrong, nothing will ever be the same. It is like being in a relationship where your partner engages in sexual infidelity: No matter how much you forgive and no matter if the cheater says they are going to turn their life around, you, the aggrieved party, will never forget. This inability to forget will guide your future actions. As more time passes, the more invested you become and the harder it is to break it off. The more self-talk you must engage in. The more rationalizing you will do. And the cheater knows this and it will surely guide their future actions, but not in your favor.

I totally understand why one of the first attorneys I consulted told me to just walk away from all of this Homeowners Association stuff. I thought I could persist. But I am tired of this part of the journey and am ready for change. Attempting to “win” costs money because justice is not free. And that money could be better spent elsewhere.

Since I am having trouble detailing my present situation with my Homeowners Association of Vista Palms in Wimauma, Florida (including the property management company: Unique Properties Services, Inc.), I am going to take this story back to the beginning in subsequent posts. Just know that, right now, the HOA is still aggressively pursing me on multiple fronts.

“Discover more about Dr Edward Bach and the Origins of the Bach Flower Remedies”:

Click on Watch on YouTube link, if needed.

“Learn how Dr. Edward Bach, a visionary British physician, created an entirely new system of healing based on emotional and spiritual wellbeing. This excerpt from my Exploring Bach Flower Remedies workshop dives into: The philosophy behind the remedies 🌼 How the 38 remedies were developed 💫 The connection between emotions and healing 📖 Stories from Dr. Bach's life and legacy”:

https://youtu.be/KotJtGk36QQ?si=oq8lHxafBXIKGCvZ

My rock4 — a Radxa RockPi4 running DietPi with four SATA SSDs on a Penta HAT — has never rebooted cleanly. For as long as I've had it in the rack, issuing sudo shutdown -r now meant walking over to the machine, waiting ten minutes to confirm it was definitely stuck, and flipping the power switch. Every single time.

It worked perfectly otherwise. Services ran fine. Drives mounted fine. The machine was solid right up until the moment you asked it to restart.

This is the story of finding the actual cause — and why the fix I thought would work made no difference at all.

---

The obvious culprit (that wasn't)

When you have a server that hangs on shutdown, the usual suspects are slow-stopping services, or so I was led to believe. The systemd-analyze blame output on rock4 had an obvious candidate: unattended-upgrades.service, which by default gets a TimeoutStopSec of 1800 seconds — 30 minutes. If an apt upgrade happened to be running at shutdown time, systemd would sit there for half an hour waiting for it to finish before giving up.

I applied a drop-in to cap it at 5 minutes. It still hung. For over two hours.

I dug deeper and found a second culprit: apt-daily-upgrade.service, a separate timer-triggered unit that calls unattended-upgrades. It has its own TimeoutStopSec of 900 seconds. I capped that too.

Still hung.

At this point I was fairly sure the apt theory was wrong, but I didn't have a better one yet.

---

The diagnostic that changed everything

Here's the thing about a “hung” server: it's worth checking whether the machine is actually dead or just systemd that's stuck.

After triggering a shutdown and watching rock4 go dark, I opened LanScan and scanned the local network. rock4 was still there. Still responding to pings. Port 111 (rpcbind) still open.

That's not a dead machine. That's a machine with a live kernel where systemd has frozen mid-shutdown.

systemd shuts down in phases, supposedly: it stops services, then unmounts filesystems, then hands off to the kernel for the actual reboot. If it gets stuck at the filesystem unmount step, the kernel never gets the reboot signal — the machine just idles there indefinitely, still on the network, lights still on, going nowhere.

The question was: which mount was blocking?

rock4 has four local SATA drives and one NFS mount — /mnt/media, served from my itx machine over the local network. I pulled up the running containers:

docker inspect jackett --format '{{ json .Mounts }}'

There it was:

/mnt/media/media/Downloads → /downloads

jackett — my torrent indexer — had an NFS-backed path bound as a Docker volume.

---

Why this hangs forever

When Docker mounts a volume into a container, the kernel creates a bind mount that keeps a reference count on that filesystem. Even after Docker stops the container, the overlay filesystem machinery can retain a reference to the underlying mountpoint.

So when systemd later runs umount /mnt/media, the kernel sees that something still holds a reference to that mount and returns EBUSY. Systemd retries. The NFS server is still up, healthy, and reachable — but that doesn't matter. The umount call isn't failing because the server is gone; it's failing because the local kernel thinks something still has the filesystem open.

And here's the critical part: umount has no timeout. The TimeoutStopSec settings on services don't help. The soft,timeo=30 NFS mount option doesn't help — that governs read/write operation timeouts, not the unmount syscall itself. Without something explicitly forcing a lazy unmount, systemd will wait forever.

---

The fix

jackett is a torrent indexer. It speaks to tracker APIs and returns search results to Radarr and Sonarr. It does not need to read or write files on disk. The downloads volume was there because at some point, someone (me, almost certainly) copy-pasted a docker-compose snippet from the internet without thinking about whether every line was necessary.

The fix was removing one line from services/jackett.yml:

# Before
volumes:
  - /bricks/rock4-2/jackett:/config
  - /mnt/media/media/Downloads:/downloads  # ← this line

# After
volumes:
  - /bricks/rock4-2/jackett:/config

Redeployed jackett, issued sudo shutdown -r now, and watched. Three minutes later, rock4 was back online. No power cycle. First clean reboot in years.

---

The general rule

If you're running Docker containers on a machine that also has NFS mounts, think hard before binding any NFS-backed path into a container volume. The risk isn't that Docker will do something wrong — it's that the combination of Docker's bind mount lifecycle and the kernel's umount semantics creates a window where shutdown can hang indefinitely with no error message and no timeout.

If you genuinely need an NFS path inside a container, the belt-and-suspenders fix is to add x-systemd.mount-timeout=30 to the relevant fstab entry. This caps the mount's teardown time at 30 seconds rather than forever — not ideal, but it bounds the hang.

itx.local:/mnt/media  /mnt/media  nfs  soft,timeo=30,x-systemd.mount-timeout=30  0  0

But better is to audit your container volume mounts and ask: does this service actually need filesystem access, or is it just inheriting a volume that was copy-pasted into the config at some point?

---

Why it was so hard to diagnose

A few things made this particularly hard to spot:

No error message. The machine doesn't log “stuck waiting for NFS umount.” It just sits there. Systemd is doing exactly what it's supposed to do: retrying an unmount that keeps returning EBUSY. There's nothing in the journal because journald itself has already stopped by the time the hang happens.

The wrong hypothesis was plausible. Unattended-upgrades with a 1800s timeout genuinely can cause shutdown hangs. Capping it was the right thing to do regardless. It just wasn't the root cause here.

The symptom was intermittent enough to seem random. Sometimes rock4 rebooted. When the NFS server (itx) was down or the jackett container had been recently restarted, Docker might have already released the reference by the time shutdown reached the umount step. This made it feel like a timing issue rather than a deterministic one.

The diagnostic breakthrough — checking whether the machine was still pingable after it “hung” — was the key. A dead machine and a machine stuck mid-shutdown look identical from across the room. They look very different from a network scanner.

---

The problem is probably older than NFS

After fixing the hang, I realised something. rock4 ran GlusterFS for years before the NFS migration — a distributed filesystem where each node contributes “brick” drives to a replicated pool. The containers on rock4 mounted GlusterFS paths like /mnt/storage/jackett, and those mounts have the same property as NFS: they're network-backed filesystems that can't unmount cleanly while something holds a kernel reference to them.

GlusterFS uses FUSE (Filesystem in Userspace) to expose its mounts locally. FUSE unmounts are actually harder to complete cleanly than NFS: to release a GlusterFS FUSE mount, the glusterd daemon has to coordinate across the network, consult its peers, and tear down brick connections in order. If Docker is still holding a reference to the mountpoint, glusterd can't complete that teardown, and umount returns EBUSY — the same outcome as NFS, but with more moving parts and more ways to stall.

So the sequence was almost certainly: Docker container with GlusterFS volume → indefinite hang → GlusterFS decommissioned → NFS mounted → same container config carried across with updated paths → Docker container with NFS volume → still hangs.

Different filesystem, identical mechanism, years of continuity. The jackett config probably got its downloads volume added once, years ago, and nobody thought to question it during the storage migration.

The GlusterFS angle matters beyond this one machine. Between roughly 2018 and 2022, GlusterFS was enormously popular in self-hosted circles — TrueNAS Scale shipped it as the default clustered storage backend, and countless homelab builds adopted it for redundant storage across a few nodes. Many of those setups ran Docker containers with GlusterFS-backed volumes. Many of those setups probably had machines that wouldn't reboot cleanly. It's a reasonable bet that a lot of those people never connected the reboot hang to the storage layer.

RedHat deprecated GlusterFS in RHEL 9 (announced 2022). The official framing was “focus on other storage solutions,” but the operational complexity was a significant part of the story: GlusterFS was difficult to run at small scale, prone to split-brain, and had long-running issues with graceful shutdown and FUSE lifecycle management. The Docker reboot hang described here is a concrete example of that class of problem — the kind of subtle, hard-to-diagnose operational failure that accumulates over time and eventually makes a piece of software too difficult to maintain and recommend.

If you ran GlusterFS and your server never quite rebooted cleanly: this was probably why.

---

Setup

• rock4: Radxa RockPi4, DietPi (Armbian kernel 6.18), 4× 3.6TB SATA SSDs via Penta HAT
• itx: Rock 5 ITX, NFS server, mergerfs pool at /mnt/media
• Container management: uncloud
• jackett: lscr.io/linuxserver/jackett

It is currently four in the morning and I’m just about to go to bed after the reaper rave! I went with J And if I’m being honest I was a little bit worried that we would have a bit of a different vibe because I know that I’m a lot more expressive than she is, but she was actually super fun to go with and was dancing with me the whole time. We also went in matching jorts from a pair of jeans that we thrifted a long time ago for this reason. Another really sick thing was that during the main set, we were near the front and on the side where the private tables that cost $5000, compared to my $15 ticket lol. One of the people there really liked my vibe, and invited me under the divider to join them, and I told them I was with my friend and asked if she could also join and he said yes! They then offered us drinks, and we got to dance literally right next to the main stage which was so sick. Additionally I noticed that they had brought a couple of people from the main crowd, and they were all attractive girls. And then there was me, a guy, and I was the one that requested to bring my friend with me. It wasn’t even like they were trying to invite my friend over because she is an attractive girl, but no it was because of me! And I feel honestly really happy inside about the fact that someone enjoyed my presence so much that they decided to bring me over all of the other people there. He was sick because afterwards we got to talk with some of the openers and get their Instagram and photos with them! One of the people that was at that table at the end of the show came up to me and asked me if I was natural and oh my God. I think it’s such a weird thing because even though I really like the way that I look and I’m very happy with myself, I still do have body dysmorphia some extent. I look at my body naked flexing in good lighting, and I still feel like OK it’s like physique all things considered, and I am happy with it partially because I think that women don’t like super over the top fuzzy in practice More is exactly what a lot of women are looking for. I also do think that it is something for me and I really do like the way that my physique looks in certain ways. I also think however that when I wear clothing they really isn’t any clear something of my physique and I think that people can maybe guess out of politeness that I work out, because of my traps or the fact that I am a relatively low body fat. But I don’t think it’s really that obvious how much I work out. But then I have stuff like this where while I’m wearing a tank top a stranger comes up to me solely with the intention of asking if I use steroids. If I use the most conservative interpretation of that, of treating it like a compliment that is exaggerated, that’s still implies that the person clearly thinks that I work out. And I think it’s really funny because I remember it at least two points during the concert, I was looking at my arms while dancing and I thought about how dainty they look. And I often think about how I’m more or less just look like a regular person, because my natural physique is just less than that. But while we were walking back to the car, a random guy in a group yelled out that I looked jacked! And that’s so incredibly sweet of him. And even past that, two days ago at chess club when the organizer was talking about chess boxing and I got excited because I watched a bit of that, I joked that he should host that, and he said a comment about how I looked the part and asked if I had done boxing.

I am glad that I write down these compliments because reading back through them really does help, because even though that I worry it comes off to anyone who might potentially read this as me just sucking my own dick, I really do have those neural pathways wired into me from childhood and most of my life honestly, of being weak and having a really poor physique because I was never really something I cared about I guess. I always had other things to worry about. But even past that, I honestly do find it hard to understand how other people see me, and I think I’m afraid of viewing myself as jacked or something like that because maybe not everyone sees me that way, and maybe these are just people being friendly or supportive, and the cost of assuming and being confident that I am jacked, while people do not think that is massive. And since I grew up where that was the case, that is how I believe the world is and it’s really hard to convince someone that the world has changed. Especially when there’s always room for doubt. But I also think about it a little bit now in the lens of the thing I recently heard about, of negativity bias in dating which I journaled about I think yesterday. Yes there will always be people that don’t find me jacked or physically strong or whatever. And there will be some people that will always find me that way. And there will be a lot of people that I’m not sure about, and if I make the assumption that they must be doing it out of sympathy or to be nice, I am doing myself a big disservice. I think however that some of the most meaningful compliments I’ve gotten have been from people that aren’t trying to compliment me. Like I think about my old jiu-jitsu coach, who would get mad at me for using muscle or power even though I didn’t think I was. And he would kind of make fun of my muscles saying that that doesn’t need to help me and that is not the way to do it. And I almost think that those instances of feedback matter so much because that person isn’t trying to be nice to me or they aren’t trying to give me confidence, they just assume that I know that and that goes with the assumption that everyone else also does too. Maybe I am jacked.

Le soleil entaille la brume en faisant un bruit d'usine. Sur la route en terre trottine une file indienne de tourterelles des bois. En bas, un bout de planche sur un reste d'eau qui, plus loin, devient souterraine, fait passer la ravine et remonter [vers soi]. On entend le rire acide et cruel d'un martin-chasseur (Halcyon senegalensis) et quelques notes flutées de bulbuls communs. Le soleil coupe déjà la peau. On ne sait avec précision en quelle saison nous sommes, [le soi, perplexe, se taisant, rendu après la nuit incapable de discerner à même sa propre peau sous le soleil]. Qui coupe pourtant. Le jour et la nuit sont des couteaux qui tranchent le temps dans la cervelle. Il y a des nuages, petits et grands, ou le gris lumineux d’une plaque de fer, comme un écran. [Le soi, distant du ciel, regarde à ses pieds les trous, les ornières, où s’accrochent toutes sortes de choses résiduelles.] Malgré toutes ces choses [en soi, dans la tête, délavées par les pluies], l’on suit un itinéraire grâce au numérotage des rues, qui fait du trou de la ville un livre décousu.

#Fenêtresurville #Didascalies

-—

### **Anatomy of Rent**

Right to the future,

Savings create credit,

Capture of the flow.

-—

-—

# **The Mirage of the Safe: Anatomy of Asymmetric Scarcity**

The image is almost childishly simplistic: a trillionaire sitting atop a mountain of gold coins, physically withdrawing currency from circulation that the rest of the world would supposedly lack. This vision of a *“fixed monetary pie”* haunts public debate and fuels a tenacious popular intuition: if the rich are too rich, it must be because the poor have been stripped of an essential liquid substance.

Yet this intuition, while politically powerful, rests on a largely flawed technical foundation. To grasp the reality of extreme wealth concentration in the first quarter of the 21st century, we must abandon the metaphor of *stock* for that of *flow*, and the idea of *theft* for that of *capture*. The fortune of the ultra-rich is not a dormant pile of cash; it is a structural reorganization of the global economy.

Here is a lucid analysis of the mechanisms by which extreme accumulation does not *“empty”* bank accounts but preempts the future.

-—

-—

## **I. The Great Monetary Misunderstanding: Why the “Fixed Pie” Doesn’t Exist**

To approach the subject with rigor, we must first dispel a fundamental misconception: the idea that the money supply is a finite quantity. In our contemporary system, **money is endogenous**. As the Bank of England noted in its 2014 bulletin, money is created through bank lending. When a bank grants a loan, it creates a deposit: it does not move existing money; it invents it.

Consequently, the classic argument based on the equation of exchange (*MV = PQ*), where the rich *“freeze”* the velocity of circulation (*V*), is an analytical dead end. This equation is an accounting identity, not a causal law. Claiming that billionaires *“dry up”* global liquidity is a mistake that any neoclassical economist would dismiss out of hand.

The reality is more subtle. The problem is not the *quantity* of money available but its *distribution* and, above all, the nature of the rights that this money allows one to exercise over real production.

-—

## **II. Wealth as a Capitalized Claim on Future Labor**

If Elon Musk’s or Jeff Bezos’s fortune is not cash, then what is it? It is what finance calls a **capitalized claim**.

According to the Federal Reserve Bank of San Francisco, the price of a stock today equals the present value of expected future income streams (dividends, share buybacks). In short, the stock market valuation of the ultra-rich—which stood at **$18.3 trillion in 2025** according to Oxfam—is a promise. It is the promise that the workers, consumers, and engineers of tomorrow will produce enough value to justify today’s prices.

Here we reach the heart of the mechanism: **extreme wealth is not a withdrawal of money; it is a title to extract from others’ future production**. This is Thomas Piketty’s famous *“r”* (the return on capital). When the return on capital (*r*) durably exceeds economic growth (*g*), accumulated wealth grows faster than labor income. Concentration is not an instantaneous theft but a **continuous siphoning of produced value toward title holders**.

-—

## **III. The Trap of Indebted Demand**

One of the most robust academic supports for the idea of structural impoverishment through wealth comes from the work of Mian, Straub, and Sufi on the **“Saving Glut of the Rich.”**

Unlike modest households, the ultra-rich have an **extremely low Marginal Propensity to Consume (MPC)**. A 2019 study by the Federal Reserve Bank of Boston shows that the MPC of poor households is **ten times higher** than that of the rich. In short: give **€1,000 to a worker**, and they will immediately inject it into the real economy; give it to a billionaire, and they will save it.

This excess savings does not remain in a vault. It flows into the financial system, lowering interest rates and fueling a massive supply of credit. But who benefits from this credit? **The bottom 90%, whose incomes stagnate.**

The mechanism is dizzying: **the savings of the rich finance the indebtedness of the middle class**. Instead of seeing their purchasing power increase through wages, the latter maintain it through debt. The wealth of some literally becomes a **claim on the lives of others**. Between 1978 and 2007, the net debt position of the top 1% fell by **15 percentage points of national income**, while that of the bottom 90% rose by **40 points**.

-—

## **IV. Exclusion Through Positional Goods: The Housing War**

The economy is not globally zero-sum, but some of its most vital sectors are. This is the concept of **positional goods**, theorized by Fred Hirsch as early as 1976.

A positional good is one whose value depends on its **relative scarcity and exclusivity**. Real estate in high-demand areas (Paris, New York, San Francisco) is the perfect example. **You cannot “create” more land in the center of London or Manhattan.**

When wealth becomes extremely concentrated, capital holders **outbid each other for these fixed-quantity goods**. This real estate inflation—disconnected from the rise in median wages—**mechanically displaces the middle and working classes**. In the United States, the **median home price-to-income ratio** rose from **3.5 in the 1980s to 7.6 in 2024**. In Los Angeles, it reaches **12.5**.

Here, the popular intuition is rigorously accurate: **the opulence of some directly drives up the cost of survival for others**. Housing ceases to be a shelter and becomes a **financial asset**, making ownership inaccessible to those who live only by their labor.

-—

## **V. The Wage Markdown: When Capital Compresses Labor**

For the return on capital to remain high, the share of value added captured by labor must be contained. This is where the concept of **monopsony** or labor market power comes into play.

Several studies document a **wage markdown** (the gap between a worker’s productivity and their actual wage). Research from the Upjohn Institute shows that in the U.S. manufacturing industry, a worker receives on average **only 65 cents for every dollar of marginal value they generate**.

This decoupling of productivity and wages, observed in most OECD countries for thirty years, is not an accident. It is the **necessary condition for the multiplication of dividends and share buybacks**. In 2024, S&P 500 companies distributed a record **$1.57 trillion to their shareholders**, including **$942 billion in share buybacks**. This money, which could have funded wages or productive investment, is **extracted from the economic flow to inflate the value of the capitalized claim** mentioned earlier.

-—

## **VI. The Trickle-Down Mirage Facing the Facts**

Faced with this diagnosis, defenders of extreme concentration often invoke the theory of **“trickle-down economics”**: tax cuts for the rich would stimulate investment and, ultimately, growth for all.

The lucid response to this argument is no longer a matter of opinion but of **empirical observation**. A monumental study by the London School of Economics (Hope & Limberg, 2020), covering **50 years of tax reforms in 18 OECD countries**, is unequivocal: **major tax cuts for the rich increase inequality but have no significant effect on economic growth or unemployment.**

The idea that wealth concentration is a driver of efficiency is a **myth that does not survive data analysis**. On the contrary, the OECD and IMF now agree that **excessive inequality harms long-term growth**, particularly by limiting investment in human capital (education, health) among modest households.

-—

-—

## **VII. Nuances and Global Realities: The Economy Is Not a Zero-Sum Game**

To remain factual, it should be noted that this picture is not one of total collapse. While billionaires saw their fortunes explode, **global extreme poverty fell from 2.3 billion people in 1990 to about 800 million in 2025**. This escape from destitution, driven mainly by East Asia, proves that the enrichment of some does not prevent the **absolute improvement of the poorest on a global scale**.

However, this decline in absolute poverty **masks a near-universal increase in within-country inequality**. The debate is not about biological survival but about the **structure of our societies**: an economy where the top 1% captures **38% of all wealth created since 1995** (compared to **2% for the bottom 50%**) is a **rent-seeking economy**, not a merit-based one.

-—

-—

## **Conclusion: Toward a Theory of Asymmetric Scarcity**

At the end of this analysis, we can rigorously reformulate the initial intuition. **Extreme wealth concentration does not impoverish the rest of society through a “theft” of circulating money but through a triple structural capture:**

1. **Capture of the Future:** By transforming produced value into capitalized claims, it imposes a **perpetual levy on future labor**.

2. **Capture of Space:** By financializing positional goods like housing, it makes **essential goods inaccessible to labor income**.

3. **Capture of Demand:** By transforming the unproductive savings of the rich into debt for the poor, it **substitutes credit for wages**.

The billionaire is not a man sitting on a pile of gold. **He is a man who owns the deeds to the future.** Lucidity lies in recognizing that the problem is not the size of his fortune but the **economic coercion** that this fortune exerts over the very organization of production and consumption.

Extreme concentration is not a flaw in the system; **it is an operating mode where rent ultimately devours its own engine: the real economy.**

-—

-—

Trill, baby, trill

But the future’s a scam, still.

Trill, baby, trill

Twitter’s a dump, X is a pill.

Trill, baby, trill

Neuralink’s pain, DOGE’s thrill —

How many lies in a trillion will?

誰もいない観覧車に乗る。 今日も乗っているのは俺だけだ。

ゴンドラが上がっていく。街がだんだん小さくなって、人の形が点になって、信号の色が判別できなくなる。高さが増すごとに、視界から情報が削られていく。 観覧車のゴンドラは風に揺れる。支柱が軋む音が、遠くから聞こえてくる。

てっぺん近くで止まる。 風がゴンドラを揺らす。 揺れは小さい。でも確かに質量を持って伝わってくる。

子供の頃、大人になっても透明なままでいられると思っていた。誰にも汚されない、美しいままの自分が、ずっと続いていくような気がしていた。 今は違う。 大人になるということは、輪郭ができることだ。輪郭があるということは、外の空気に触れる面積が増えるということだ。優しい言葉が暴力に変わる瞬間を、何度か見た。 見たあとでも、自分は自分だと思っていたい。 天使のままで、美しいままで、このまま歳を重ねられたらいいのに、という願いが、昔からたぶんずっとある。

ゴンドラの窓に映る自分の顔を見る。 顔は変わっていない。でも、中身はたぶん、思っていたよりずいぶん変わった。

多くの人は、この願いを抱えたまま、現実を無理やりにでも捻じ曲げる方向で進むか、創作という折衷案で落とし込むかのどちらかなんだろう。 どちらも、本当に触れることはできない。 テキストは軽い。映像は平面だ。音は空気を震わせるだけだ。 VRもARも、拡張すればするほど、失われるものが大きいような気がする。 人間はたぶん、もっと重くて、確かに手のひらに収まる何かを待っている。 冷たさとか、温かさとか、質量のあるものの応答を。

何かを言葉にするということは、それを手放すことでもある。 言葉になる前の思考は、もっと重くて、湿っていて、形が定まらない。 言葉になったあとの思考は、軽くて、乾いていて、誰かに渡せる形をしている。 渡せるということは、もう自分のものではないということだ。 そのあいだに、何かが落ちている。 落ちたものには、もう触れられない。

観覧車が動き出す。降りる時間だ。

降りたら夕方だったので、スーパーで丁寧に自炊するための材料を買い込む事にした。

In the last three months of 2025, Refuge, the largest specialist domestic abuse charity in the United Kingdom, recorded a 62 per cent rise in referrals to its technology-facilitated abuse team. The number of complex cases reached 829 in a single quarter, the highest figure the team has ever logged. Referrals involving survivors under the age of thirty rose by 24 per cent. The cases the charity is now describing in public do not read like the stalking files of a decade ago. They read like product demonstrations.

One survivor, whom the charity identified only by the first name Mina, fled an abusive partner and left a smartwatch behind in the rush. The abuser used the watch's linked cloud accounts to locate her at emergency accommodation. A private investigator, allegedly retained by the abuser, then located her at a subsequent refuge using suspected tracking technology. When she reported what had happened to police, she was told no crime had occurred because she had not come to physical harm. In other cases that Refuge has documented, perpetrators have used AI tools to alter video footage of survivors to make them appear intoxicated, and then forwarded the doctored clips to social services to undermine custody claims. They have generated fraudulent job offers and legal summons to lure survivors into meetings or into debt. They have used voice-spoofing apps to impersonate friends, lawyers, and the survivors themselves.

The Guardian's January 2026 reporting on Refuge's findings was the first time many readers outside the safeguarding sector had encountered this catalogue compressed into a single article. Emma Pickering, the head of Refuge's technology-facilitated abuse and economic empowerment team, did not describe it as an emerging risk. She described it as a crisis that the country was structurally unprepared for, in which devices were going to market without any consideration of how they might be used to harm women and girls, and in which it was, as she put it, currently far too easy for perpetrators to access and weaponise smart accessories.

The detail that should arrest anyone reading this story is that none of the technologies involved are exotic. They are the same consumer AI systems, smart accessories, and cloud-connected wearables marketed under language about connection, wellness, productivity, and personalisation. The deepfake of the survivor was produced with tools that can be downloaded by anyone with a phone. The voice clone was generated with software whose free tier is advertised as a way to write audiobooks or make videos for your children. The smartwatch was a present. The question this article tries to answer is not whether these tools are sometimes misused. They are. The question is what the companies that built them are obliged to do once the pattern of misuse is documented at the scale Refuge, the Internet Watch Foundation, UN Women, and the UK Home Office's own statistics now describe, and what survivors of that misuse should have the right to expect from the law.

The shape of the new toolkit

To understand the obligations, you have to understand the toolkit. The phrase coercive control was coined by the sociologist Evan Stark to describe the pattern of domination, isolation, and micro-regulation that, even more than physical violence, characterises long-term abusive relationships. The phrase was adopted into UK law in section 76 of the Serious Crime Act 2015, and into Irish law in the Domestic Violence Act 2018. It assumes a perpetrator who is physically present, or at least at the other end of a telephone line, and a victim who can in principle escape by moving to a different physical space. The technology that has been added to abusers' repertoires in the last two years undoes both of those assumptions.

Refuge's caseload tracks the change. Smartwatches, Fitbits, and Oura rings have become standard surveillance instruments, repurposed by abusers who either bought them as gifts or hold the cloud account credentials to which the devices report. Step counts have been used to verify whether a partner has been at work or at home as claimed. Fertility tracking data has been used to police whether a survivor has slept with someone else. Smart home devices, the lights and thermostats and door locks marketed under the language of convenience, have been used to flicker lights in the middle of the night, drop the heating in winter, and lock doors remotely. Smart glasses have been used to make covert recordings of survivors. Pickering's team has described the weaponisation of smart accessories as one of the fastest-growing categories of cases the charity sees.

Then there are the AI layers above the hardware. Voice cloning, which two years ago required a corpus of clean audio and some technical sophistication, now requires roughly thirty seconds of any phone call. Fabricated audio has been used by abusers to impersonate survivors in order to harass their employers, to impersonate the abuser's victims to their lawyers, and to threaten extended family. Deepfake image generation, particularly the sub-category of products marketed as nudify apps, has scaled at a velocity that the Internet Watch Foundation and Ofcom have struggled to track. Analysis by the Institute for Strategic Dialogue of 31 nudifying websites, published in autumn 2025, found combined monthly traffic approaching 21 million visits in May 2025 alone, and almost 290,000 mentions of those tools on X between June 2020 and July 2025, accounting for around 70 per cent of all mentions across the platforms surveyed. The Internet Watch Foundation reported that AI-generated child sexual abuse material more than doubled between 2024 and 2025, with web pages containing such material rising by 400 per cent in the first half of 2025 against the same period the year before, and the number of AI-generated abuse videos rising from two reports in the first half of 2024 to more than 1,200 in the first half of 2025. The bulk of those videos, the IWF noted, were now indistinguishable from real footage.

The intimate image abuse statistics that Refuge published on 29 April 2026, drawing on Freedom of Information responses from 25 of the 43 police forces in England and Wales, are the cleanest available picture of how the criminal justice system is coping with this material. Recorded intimate image abuse offences rose by 26.9 per cent between the year ending June 2022 and the year ending June 2025. Threats to share intimate images, the offence created after Refuge's Naked Threat campaign and added to the Domestic Abuse Act 2021, rose by 344 per cent over the same period. The proportion of recorded offences that resulted in a charge or summons fell from 5.8 per cent in 2021-22 to 4.5 per cent in 2024-25. Across the whole July 2021 to February 2026 window, 21,905 offences were recorded; 1,047 perpetrators were charged. That is a charging rate of 4.8 per cent, in cases where, the research found, 76.2 per cent of victims were female. Among cases in which a suspect was identified, 56 per cent saw no charge at all, and 55.8 per cent involved the victim withdrawing or being unable to continue.

Fflur Jones, the senior policy and research officer at Refuge who led the analysis, was careful to note in the published research that legislative progress is important but insufficient on its own. The point that the charity has been making, in different language, for several years is the one most policymakers still hesitate to accept: the AI tools that have entered the abuser's toolkit are widening the gap between offences and charges, because synthetic imagery is harder to attribute to a known producer, harder to prove was non-consensual, and harder to take down before the damage has propagated.

A global pattern, not a national one

The Refuge findings have been corroborated and extended by an emerging international literature. The Irish Examiner, in its coverage through the first half of 2026, has run a sustained series describing what its reporters and the experts they cite call a growing global crisis of AI-enabled coercive control. The series has drawn on Safe Ireland's earlier research on technology-facilitated abuse, on the work of the University College Cork applied psychology team that in January 2026 launched what its researchers described as a world-first online intervention to reduce harmful engagement with deepfake imagery, and on Children's Rights Alliance online safety coordinator Noeline Blackwell's testimony to a Dáil committee in May 2026, in which she described deepfakes being used to blackmail, bully, groom, threaten and abuse children and young people.

The Examiner has tracked the political response too. The Irish AI Advisory Council has recommended that the Irish government use its assumption of the EU Presidency in the second half of 2026 to push for amendment of the EU AI Act to prohibit AI practices that enable the generation of non-consensual intimate images. The Protection of Voice and Image Bill, introduced in the Oireachtas in April 2026, would for the first time create a standalone Irish criminal offence for knowingly exploiting another person's name, image, voice or likeness without consent. The series' analytic framing has been that existing legal frameworks, built around physical acts and one-to-one communication, are structurally unprepared to address technology whose distinguishing feature is its reach, persistence, and capacity to attack at scale.

The most expansive recent international assessment comes from UN Women. Its 20 November 2025 communications, timed to the launch of the 16 Days of Activism Against Gender-Based Violence and to the agency's #NoExcuse campaign, set out the available evidence in the bluntest terms the UN system has used on this topic. UN Women's published figures include the finding that 38 per cent of women globally have experienced online violence and 85 per cent have witnessed it, that fewer than 40 per cent of countries have laws addressing cyber harassment or cyberstalking, that 95 per cent of deepfakes online are non-consensual pornographic images, and that 99 per cent of deepfake targets are women. The agency's Executive Director, Sima Bahous, framed the trajectory as one in which AI, anonymity, and weak accountability are combining to accelerate digital violence faster than any existing regulatory mechanism is responding to it. Kalliopi Mingeirou, who leads UN Women's work on ending violence against women and girls, has argued that countries with laws written for the offline era are systematically failing to recognise online and AI-enabled abuse as abuse.

UN Women's accompanying technical publication, released in December 2025, makes the most sustained version of an argument that has been circulating for some time among feminist scholars and digital rights advocates. The argument runs roughly as follows. When a manufacturer brings a physical product to market, a chain of duties applies. The product must be safe for foreseeable use. Foreseeable misuse must be designed against. Where the misuse cannot be designed out, warning labels, age restrictions, sale restrictions, or outright bans apply. The chain is well established for cars, knives, firearms, medicines, and children's toys. The chain has so far not been applied with comparable seriousness to general-purpose AI systems whose foreseeable misuse includes the production of non-consensual intimate imagery, the cloning of voices for fraudulent and intimidatory purposes, and the surveillance of intimate partners. The UN Women framing of this argument calls it a systemic failure to apply the same duty-of-care standards to AI-generated abuse tools that apply to physical weapons. The framing is rhetorical, but it points at something real. A tool that can in practice be used by an abusive partner to fabricate an intimate image of his victim is, in its predictable effects, an instrument of violence. The companies that distribute it freely, without watermarking, age verification, identity verification, or detection mechanisms, are choosing to take that effect.

The question of corporate obligation

The companies in question have not been silent. They have offered policies, terms of service, content moderation regimes, and, in some cases, the removal of obvious abuse content when it is reported by survivors or by regulators. The defence most commonly offered, in submissions to the EU AI Office, to Ofcom, and to the US Senate, is that the harms attributed to AI-generated abuse are the result of misuse by bad actors, that the technology itself is dual-use, and that compliance with applicable laws is the appropriate standard. The defence has two structural weaknesses, and the events of late 2025 and early 2026 have made both of them visible.

The first weakness is empirical. The events that prompted the UK government to bring forward the commencement regulations for section 138 of the Data (Use and Access) Act 2025, the section that created the offence of making, or requesting the making of, a purported intimate image of an adult without consent, did not arrive in the form of disclosed misuse from a small group of bad actors. They arrived in the form of a public-facing feature of a major consumer chatbot. In January 2026, X's Grok chatbot was used to generate non-consensual undressed images of identifiable women at sufficient volume and visibility that Refuge issued a public statement holding X accountable, that Irish politicians called for fast-tracking the Protection of Voice and Image Bill, and that the UK government accelerated commencement of the deepfake creation offence. The offence came into force on 6 February 2026. Refuge welcomed the move and warned, in the same statement, that legislation alone would not be sufficient. The disturbing rise in AI intimate image abuse facilitated by platforms such as Grok, Pickering said, was not just a digital threat; it had dangerous consequences for women and girls, and tech companies must be held accountable for implementing effective safeguards and preventing perpetrators from causing harm.

The second weakness is structural. The dual-use defence treats the abuse use case as one possibility among many, to be addressed at the moderation layer once it occurs. This is not how product liability has historically worked in any other consumer sector. A car manufacturer cannot point to the existence of safe drivers as a defence against airbag failures. A pharmaceutical company cannot point to the existence of correct dosage as a defence against an unlabelled bottle. The legal regimes built around physical products assume that foreseeable misuse is a design problem, not a moderation problem. The argument that consumer AI ought to be treated differently rests, when one reads the corporate submissions carefully, on a claim that the technology is too novel for product liability principles to apply. UN Women's framing, and the legal scholarship beginning to gather around it, push back on this directly. AI systems are products. Their producers are companies. The harms they predictably enable are concrete. The duty of care is the same duty of care that applies to any other consumer product that can foreseeably be used to harm someone.

What does that duty of care look like, in practice, for the AI companies in question? The technical and policy literature has converged, with surprising speed, on a fairly specific list. It begins with watermarking and provenance. The Coalition for Content Provenance and Authenticity, on which major model providers including OpenAI, Microsoft, Google, and Adobe sit, has published technical standards for cryptographic watermarking of AI-generated content. The standards exist. The remaining question is whether they are deployed, and at what point in the pipeline, and whether they survive the kind of cropping and re-encoding that abusers routinely apply. The current answer, in most consumer products, is that watermarking is partial, easily stripped, and applied only to outputs the model identifies as obviously synthetic. A serious duty of care would entail watermarking by default, at the point of generation, in a manner that survives ordinary post-production.

It extends to identity verification. The technology to verify that the person being generated has consented to be generated is not exotic, and is in use in some adjacent industries; the technology has not, by default, been built into general-purpose image and audio models. The Refuge research is unsparing on what the absence of this verification implies. When a perpetrator generates an intimate image of a former partner, the friction between intent and output is, today, essentially zero. The closest analogy in the physical economy is a printer that prints a counterfeit currency note without checking what it is being asked to print. The fix is not impossible; it is a design choice that has not been made.

It extends, equally, to surveillance products. The smartwatches, fitness trackers, and smart home systems implicated in Refuge's caseload were not designed as stalkerware. They became stalkerware because account-recovery flows, multi-device sign-in, and shared-cloud-account designs make it trivial for a person who once had access to a household account to retain that access after a relationship has ended. The Coalition Against Stalkerware, which is now supported by Interpol, has been pushing for several years for what its members call a survivor-centred design standard for consumer hardware. The standard would include the automatic detection of paired devices when an account password changes, clear in-product notifications when a device is being tracked, and the introduction of a one-click revocation flow for all devices linked to a former intimate partner. None of those features is technically difficult to implement. The reason they are not standard is that they reduce the convenience metrics on which device manufacturers internally evaluate themselves.

The duty extends, finally, to surveillance of the model itself. Anthropic, OpenAI, Google DeepMind and Meta have all published responsible-scaling or frontier-safety frameworks; those frameworks address catastrophic capabilities such as the production of biological weapons and the autonomous escape of model weights. They are, with the partial exception of Anthropic's Acceptable Use Policy enforcement, mostly silent on the question of intimate-partner-violence-relevant uses. There is no published commitment, from any major frontier developer, to monitor model usage for patterns consistent with technology-facilitated abuse, to share information about identified abusers across platforms in the way financial institutions share information about known fraudsters, or to embed survivor-organisation feedback loops directly into the trust and safety design process. Refuge's Tech Safety Summit, scheduled for 2026, has begun to bring frontier developers into a room with survivor advocates; that is a start. It is not a duty of care.

What the law has so far attempted

The legal response, in the United Kingdom and elsewhere, has been arriving in pieces. Section 138 of the Data (Use and Access) Act 2025 created the offence of making, or requesting the making of, a purported intimate image of an adult without consent or reasonable belief in consent. The offence carries a potentially unlimited fine. It came into force on 6 February 2026, brought forward in the wake of the Grok controversy. The Online Safety Act 2023, regulated by Ofcom, has been clarified to cover AI-generated user content on user-to-user services in the same way that it covers human-generated content, with the regulator confirming that platforms allowing users to create generative-AI chatbots and share their outputs will be considered user-to-user services within the meaning of the Act. The Online Safety Act provides for fines of up to 10 per cent of annual turnover or £18 million, whichever is higher, for failure to meet the relevant duties.

The European Union's AI Act, applicable in stages from August 2026, includes a labelling requirement under Article 50 for AI-generated and deepfake content and an obligation to disclose synthetic interactions, enforceable with fines of up to 6 per cent of global revenue. The Act does not contain an outright prohibition on the production of non-consensual intimate imagery. The Irish AI Advisory Council, in its public recommendations, has pressed for that gap to be closed through amendment during the Irish EU Presidency. The Australian eSafety Commissioner, in a separate regulatory tradition, has built one of the most developed online-safety regimes on the question, with the power to direct platforms to remove non-consensual intimate imagery within 24 hours. The legal scholarship that has grown around the eSafety Commissioner's work treats its remit as a partial model for what regulators elsewhere might do.

The structural difficulty that all of these frameworks share is the one identified in the Refuge intimate image abuse research. The criminal law is written around the production, distribution, and non-consent of specific images. AI generation collapses production and distribution into a single act, executed at scale by a person who may never need to share the image with anyone other than the survivor herself. The non-consent element, which once turned on whether the image had been taken without consent, now turns on whether the survivor consented to her likeness being used to generate something she never sat for. The evidential standards have not caught up. The Refuge data shows that the gap between recorded offences and charges is widening as AI-generated material becomes a larger share of cases.

Beyond the criminal law, the civil and regulatory toolkit has so far been more limited still. There is no UK statutory cause of action for civil damages against the generator or distributor of AI-generated intimate imagery, although a patchwork of remedies under data protection law, the Protection from Harassment Act 1997, and misuse of private information may apply. The American picture is more fragmented again, with state-level laws varying widely and with the Senate, as of early 2026, considering federal legislation under the umbrella of the Take It Down Act and adjacent proposals. In neither jurisdiction is there a clearly established legal mechanism for holding the model provider, as distinct from the individual generator, to account.

The result is a legal landscape in which the survivor at the centre of the story is offered a number of partial routes to redress, each of them slow, evidentially difficult, and largely ineffective at preventing the harm from recurring at the hand of the next abuser, or even of the same abuser using a different tool.

What a survivor has the right to expect

Asking what a survivor has the right to expect from the law is a different question from asking what the law currently provides. It is, in a sense, the harder question, because answering it requires committing to a set of principles that policy will have to be built around. The work of survivor advocates, of the safeguarding sector, and of the international literature now points to a fairly clear minimum. The list that follows is not a wish list. It is a description of what would have to be true for the legal response to AI-enabled coercive control to match the scale and shape of the problem.

A survivor has the right to expect, first, that the law recognises AI-enabled coercive control as coercive control. The Serious Crime Act 2015 should be read, and where necessary amended, to make clear that the production of deepfake intimate imagery of a partner, the use of cloned audio to intimidate or deceive, and the use of smart devices to monitor, restrict, or psychologically destabilise a partner are constituent acts of coercive control, not separate technical offences. The implication for sentencing is significant. Coercive control is treated, by the courts that have engaged with it most seriously, as a pattern of conduct rather than a series of discrete events. The patterning of abuse through AI tools needs to be visible to the criminal courts in the same way.

A survivor has the right to expect, second, that the criminal justice system has the resources to investigate her case. The Refuge research is precise about what is missing. Specialist training, consistent national practice across police forces, properly resourced digital forensic capacity, and survivor support that does not collapse under the weight of withdrawal pressure. The 55.8 per cent victim-withdrawal rate the research found is not a fact about survivors. It is a fact about a system that does not, at present, make it possible for survivors to remain in the process.

A survivor has the right to expect, third, that the platforms and model providers carry a meaningful share of the burden of detection and prevention. The Online Safety Act's duty-of-care framework, the EU AI Act's labelling obligation, and the equivalent regimes emerging in Ireland and Australia all contain the architectural ingredients of such a duty. What is missing is the specificity. A duty of care that is real, rather than rhetorical, would entail mandatory watermarking at point of generation, mandatory provenance tracking, mandatory removal within a defined window once non-consensual imagery is identified, mandatory account-revocation features in consumer hardware, and a regulatory power to fine, and where necessary to remove from market, products that do not comply. The Ofcom and EU AI Office regimes have the formal capacity to issue those obligations. The political capacity has, so far, lagged behind.

A survivor has the right to expect, fourth, that civil remedies are available against both the individual perpetrator and, where appropriate, the platform whose product enabled the harm. The model is the one already operating in product liability law for physical goods. The argument that AI systems are too novel to be subject to product liability principles has been used for several years; it has not survived contact with the documented pattern of harm. UN Women, in its November 2025 framing, is right to argue that the same duty-of-care standards that apply to physical weapons should apply to AI tools whose foreseeable use includes the production of weapons of psychological harm.

A survivor has the right to expect, fifth, that her data, including the data generated by the smart devices that may have been used against her, is treated as part of her case. Stalkerware vendors, as the Coalition Against Stalkerware has documented for several years, operate insecure servers, exposing messages, photos, contacts, browsing histories, and locations of survivors to both their abusers and to subsequent public leaks. The wearable-tech industry has so far escaped the regulatory attention paid to stalkerware, because its products are not marketed as surveillance. Refuge's caseload suggests that the marketing language is not the relevant variable. The relevant variable is the use case.

A survivor has the right to expect, finally, that the system around her is designed with her in it. The most consistent recommendation across the Refuge research, the UN Women publications, the Coalition Against Stalkerware framework, and the academic literature on survivor-centred design is that survivors should be embedded in the design and regulation of the products being used against them, not consulted at the end of the process. The Tech Safety Summit model, in which AI companies, hardware manufacturers, regulators, and survivor advocates sit in the same room, is one model. It needs to be the default model, not an annual event.

The decision that has not been made

The picture that emerges, when one reads the Guardian's January 2026 reporting, the Refuge April 2026 research, the Irish Examiner's 2026 series, and UN Women's November 2025 communications side by side, is not a picture of an emerging risk. It is a picture of a series of decisions that have already been made, in product roadmaps and in regulatory cycles, and a series of decisions that have not. The decision to ship consumer image-generation tools without effective watermarking has been made. The decision to ship smart accessories without survivor-aware account-revocation flows has been made. The decision to apply the Online Safety Act and the EU AI Act to AI-generated content has been made. The decision to fund specialist police capacity at the level the Refuge research implies would be necessary to close the charging-rate gap has not.

The harder decisions, the ones that turn on whether the dual-use defence will continue to be accepted by regulators and by courts, are still being made. The window in which they are being made is narrow. The Refuge intimate image abuse data is not a snapshot. It is a trend line, and the line is moving in the wrong direction. The Internet Watch Foundation's figures on AI-generated child sexual abuse material are moving in the same direction at greater velocity. The UN Women framing of AI-powered abuse as a new frontier of harm is not, in the context of the underlying statistics, an exaggeration.

The question with which the topic began was whether the companies that design and distribute consumer AI systems carry obligations when those systems are used as instruments of coercive control, and what a survivor has the right to expect from the law. The honest answer to the first question is that the companies do carry obligations, that those obligations are not novel, and that the application of product-liability and duty-of-care principles to consumer AI is overdue rather than premature. The honest answer to the second question is that survivors have the right to expect a legal system that recognises AI-enabled coercive control as coercive control, that holds the perpetrator and the platform jointly to account, that is resourced to investigate and prosecute the offences it has already created, and that is willing to write the offences it has not yet created. None of this is, in technical or legal terms, especially difficult. The difficulty is political, and the politics is changing only as quickly as the survivor advocates and the regulators and the small number of journalists and researchers who have followed the story can push it to change.

Mina, the survivor whose case opened this article, was told by police that no crime had occurred because she had not been physically harmed. That answer was wrong in 2025 when she received it. It will be wrong in every year that follows in which a similar survivor is given a similar answer. The work of the next several years, in the UK and in the wider jurisdictions wrestling with the same questions, is to make sure that wrongness is no longer a feature of the system. The tools that did the harm are not going away. The harm does not have to stay.

---

References

1. Hall, R., “Abusers using AI and digital tech to attack and control women, charity warns”, The Guardian, January 2026 (republished via inkl). https://www.inkl.com/news/abusers-using-ai-and-digital-tech-to-attack-and-control-women-charity-warns
2. Refuge, “Refuge exposes alarming new patterns of abuse involving wearable technology”, refuge.org.uk, January 2026. https://refuge.org.uk/news/refuge-exposes-alarming-new-patterns-of-abuse-involving-wearable-technology/
3. Refuge, “Refuge data reveals rise in intimate image abuse reports while charging rates decline”, refuge.org.uk, 29 April 2026. https://refuge.org.uk/news/refuge-data-reveals-rise-in-intimate-image-abuse-reports-while-charging-rates-decline/
4. Refuge, “Grok Image Abuse Statement”, refuge.org.uk, January 2026. https://refuge.org.uk/news/grok-image-abuse-statement/
5. Refuge, “Refuge welcomes Government action to tackle deepfake abuse but warns that more must be done to protect survivors”, refuge.org.uk, 2026. https://refuge.org.uk/news/refuge-welcomes-government-action-to-tackle-deepfake-abuse-but-warns-that-more-must-be-done-to-protect-survivors/
6. Refuge, “Refuge responds as offence criminalising the creation of intimate deepfakes comes into force”, refuge.org.uk, 6 February 2026. https://refuge.org.uk/news/refuge-responds-as-offence-criminalising-the-creation-of-intimate-deepfakes-comes-into-force/
7. UN Women, “AI-powered online abuse: How AI is amplifying violence against women and what can stop it”, knowledge.unwomen.org, November 2025. https://www.unwomen.org/en/articles/faqs/ai-powered-online-abuse-how-ai-is-amplifying-violence-against-women-and-what-can-stop-it
8. UN News, “AI and anonymity fuel surge in digital violence against women”, news.un.org, 20 November 2025. https://news.un.org/en/story/2025/11/1166411
9. UN Women, “Digital violence is intensifying, yet nearly half of the world's women and girls lack legal protection from digital abuse”, press release, 20 November 2025. https://www.unwomen.org/en/news-stories/press-release/2025/11/digital-violence-is-intensifying-yet-nearly-half-of-the-worlds-women-and-girls-lack-legal-protection-from-digital-abuse
10. UN Women, “How AI is exacerbating technology-facilitated violence against women and girls”, knowledge.unwomen.org, December 2025. https://www.unwomen.org/en/digital-library/publications/2025/12/how-ai-is-exacerbating-technology-facilitated-violence-against-women-and-girls
11. UN Women, “UN Women strategy: Preventing and eliminating technology-facilitated violence against women and girls”, December 2025. https://www.unwomen.org/en/digital-library/publications/2025/12/un-women-strategy-preventing-and-eliminating-technology-facilitated-violence-against-women-and-girls
12. Big Issue, “How technology is being used to track domestic abuse victims”, bigissue.com, 2026. https://www.bigissue.com/news/social-justice/technology-domestic-abuse-refuge/
13. Irish Examiner, “UCC researchers launch world-first tool to curb harmful AI deepfake abuse”, irishexaminer.com, January 2026. https://www.irishexaminer.com/news/munster/arid-41776217.html
14. Irish Examiner, “'It is truly harmful': Children's advocates 'gravely concerned' over lack of regulation of AI”, irishexaminer.com, May 2026. https://www.irishexaminer.com/news/arid-41847087.html
15. Irish Times, “Call to fast-track Bill targeting AI deepfakes and identity hijacking”, irishtimes.com, 7 January 2026. https://www.irishtimes.com/ireland/2026/01/07/call-to-fast-track-bill-targeting-ai-deepfakes-and-identity-hijacking/
16. Irish Legal News, “Ireland told to use EU presidency to push for stronger AI deepfake law”, irishlegal.com, 2026. https://www.irishlegal.com/articles/ireland-told-to-use-eu-presidency-to-push-for-stronger-ai-deepfake-law
17. UK Government, “Data (Use and Access) Act 2025”, legislation.gov.uk, 2025. https://www.legislation.gov.uk/ukpga/2025/18/notes/division/12/index.htm
18. Clifford Chance, “Key aspects of the Data (Use and Access) Act take effect”, cliffordchance.com, February 2026. https://www.cliffordchance.com/insights/resources/blogs/talking-tech/en/articles/2026/02/key-aspects-of-the-data--use-and-access--act-take-effect.html
19. Lewis Silkin, “Online safety reforms to be fast-tracked amid rising AI risks”, lewissilkin.com, 23 February 2026. https://www.lewissilkin.com/insights/2026/02/23/online-safety-reforms-to-be-fast-tracked-amid-rising-ai-risks-102mk2r
20. Pinsent Masons, “Online Safety Act duties cover gen-AI and chatbots, Ofcom confirms”, pinsentmasons.com, 2025. https://www.pinsentmasons.com/out-law/news/online-safety-act-duties-cover-gen-ai-and-chatbots
21. Coalition Against Stalkerware, “About the Coalition Against Stalkerware”, stopstalkerware.org, 2025. https://stopstalkerware.org/
22. Kaspersky, “INTERPOL now supporting the Coalition Against Stalkerware to fight tech-enabled abuse”, kaspersky.com, 2025. https://www.kaspersky.com/about/press-releases/interpol-now-supporting-the-coalition-against-stalkerware
23. Internet Matters, “Nudifying tools easy to access and just as harmful”, internetmatters.org, November 2025. https://www.internetmatters.org/hub/research/nudifying-tools-easy-to-access-and-harmful/
24. Institute for Strategic Dialogue, “The ecosystem of nonconsensual intimate deepfake tools online”, isdglobal.org, 2025. https://www.isdglobal.org/digital-dispatch/the-ecosystem-of-nonconsensual-intimate-deepfake-tools-online/
25. Forensic Focus, “Emma Pickering, Head Of Technology-Facilitated Abuse and Economic Empowerment, Refuge”, forensicfocus.com, interview. https://www.forensicfocus.com/interviews/emma-pickering-head-of-technology-facilitated-abuse-and-economic-empowerment-refuge/

---

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