DaDaDanDeLions@proton.me

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The Punyversal Law

A Foundational Statement for the Creation of the Punyverse

1. The First Law

Nothing is too small to be everything. This is the governing principle of the Punyverse. It declares that every trivial act, object, and moment holds the full weight of existence folded inside it. The kettle, the fag break, the toilet, the bald patch, the seagull, the yellow‑sticker bargain — each is a doorway into the infinite.

1. Meaning in the Mundane

The Punyverse teaches that all Meaning is local, lived, and ordinary. It does not exist in distant heavens or abstract philosophies. It hides in the everyday: the mutter, the sigh, the stumble, the small victory, the petty irritation. The Punyverse is the only cosmology honest enough to admit that the universe is built from these moments.

1. Wisdom in the Ridiculous

In the Punyverse, all Wisdom appears from the comic, the awkward, the absurd. Humour is not an escape from truth — it is the form truth takes when it becomes bearable. The cosmic reveals itself through the ridiculous because the ridiculous is the most human scale of understanding.

1. Reciprocal Being

The Punyverse expresses you, and you express the Punyverse.

You are shaped by the insignificant things you live among, and those insignificant things are shaped by the meaning you give them. This reciprocity is the engine of Punyversal reality.

1. The Cosmic Fold

The Punyverse is a universe of scale inversion:

• the trivial is divine • the divine is trivial • the small is infinite • the infinite is small

Everything contains everything.

Nothing is merely what it appears to be.

1. The Central Claim

The Punyverse encapsulates all Meaning and all Wisdom, for nothing small is ever merely small. This is the heart of the Punyversal Law. It is the mythic foundation upon which the entire Punyverse is built.

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

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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.

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.

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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