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Maui Health Medical Minute: Is it dangerous to interact with AIs or chatbots?
AI chatbots can be helpful tools, but they aren’t a substitute for real human connection or professional mental health care.
How governments worldwide are shaping what AI can say about politics
With the U.S. midterms approaching, about one in five voters has asked AI chatbots about elections and politics, a recent survey found.
Fewer Than One in Four People Trust Business Leaders as AI Adds to Global Trust Gap
Just 24% globally trust business leaders and only 23% trust AI chatbots, according to Ipsos, highlighting a growing leadership and AI trust challenge. Just 24% globally trust business leaders and only 23% trust AI chatbots, according to Ipsos, highlighting a growing leadership and AI trust challenge.
Typology Of AI-Based Therapy Micro-Bursts Reveals How People Lean Into Chatbots For Mental Health Advice
I've previously defined AI-based therapy micro-bursts, which is how people tend to use AI for mental health advice. Now, here's my typology. An AI Insider scoop.
Keeping kids safe in the age of AI: What safeguards does WA have?
Technology companies have come under scrutiny for the effects AI chatbots have on youth mental health. Here's what you should know.
Inside Evergreen and Therabot with psychiatry and computer science professor Nicholas Jacobson
Jacobson sat down with The Dartmouth to explain the development of the AI chatbots.
The Science Behind the AI Panic Is Shakier Than You Think
A column by Sascha Lobo Is AI making us dumb? So asked DER SPIEGEL on its cover a while ago. After a few weeks of recovery and a therapeutic intervention with the help of my AI, I feel able to respond. That’s a bit unfair, of course; the article itself is more nuanced than the loud cover, the image of a schoolkid with dull prompt questions, or the subtitle: “AI is conquering the schools, and educators fear a disaster.” The short answer to “Is AI making us dumb?” is: no. The long answer is more interesting, and even carries a preliminary glimmer of the spectacular. Unfortunately, it requires a detour into the sphere of artificial intelligence, into the mogul-field terrain of technology assessment, the attention economy, and the destructive virus of cultural pessimism. Along with narrowing the scope to AI’s effects on education and work rather than on intelligence. Because the honest version of the question would be: Does AI help us learn and work, or not? Generative AI, which set off the still-ongoing hype with ChatGPT, has only existed in relevant distribution since late 2022, early 2023. For a technology-driven transformation of people and society, that is extremely short. For that reason alone, research is still in its infancy. And technology assessment is not a fast discipline anyway. Prominent voices from Elizabeth Eisenstein to RAND to Tom Wheeler say we still cannot conclusively judge the consequences of the printing press. Its invention is a mere 580 years back, and some scholars would rather not circulate assessments that might have to be retracted in two or three hundred years. We’re Going Through Growing Pains A phenomenon that already caused upheaval in social media research makes serious assessment of AI’s consequences even harder: the “moving target” problem of LLM-ology, as the linguist Sean Trott called it in 2025. AI develops so quickly and so unpredictably that researchers often end up studying snapshots of the past. There are concepts, from morphological analysis to anticipatory governance, for keeping research, planning, and regulation halfway meaningful anyway. But even with those, universally valid statements are rare. DER SPIEGEL - The German View is a reader-supported publication. To receive new posts and support our work, consider becoming a free or paid subscriber. Subscribe We should therefore treat findings about the interplay between humans and AI as far more procedural and situational. Unfortunately, this challenge comes at the worst possible time. We are going through growing pains: AI’s everyday impact has grown very large very fast, and with it the longing for guidance. Annoyingly, the body of solid knowledge has not exploded along with it. Experts cannot be moved to broad consensus on even banal statements about AI. Sascha Lobo, born in 1975, is an author and strategy consultant focusing on the internet and digital technologies. Together with Jule Lobo, he explores the debates of the day in the podcast “Feel the News – Was Deutschland bewegt” (”What Moves Germany”). Nvidia CEO Jensen Huang says software developers are dying out. Bill Gates considers coders one of only three professions that will survive the AI tsunami. Top tech economists find virtually irrefutable arguments both for and against an AI bubble. The same naturally applies to the structurally youth-hostile debate over whether AI is good or bad for young people. The gap between the demand for insight and the supply of solid knowledge creates an orientation vacuum. This vacuum of AI cluelessness is filled, as the attention economy described by Georg Franck in 1998 would have it, with half-knowledge (funnily enough, often AI-generated), marketing, and self-marketing. After all, infinite money is at stake, along with academia’s best current shot at global fame. But this iridescent froth of interpretation operates more by the algorithmic principles of the digital public sphere than by seriously earned insight. That is why dramatized, fear-feeding claims about AI are so promising. It tempts parts of academia into distorted drivel, and parts of the media then sensationalize the published drivel once more. Was the Research Aimed at a Desired Result? How badly this can influence academia and public perception is demonstrated by one of the most-discussed studies on AI’s effects: “Your Brain on ChatGPT.” The MIT study by Nataliya Kosmyna also gets plenty of space in the SPIEGEL cover story. What was measured and interpreted: lower brain activity in people who write with AI assistance, compared to people who only google or write without any tools. As is common with preprints, the study has not yet been peer-reviewed, and it contains substantial weaknesses that experts have sharply criticized. The first round had 54 participants in three groups, the second only 18, who reportedly also came from MIT’s own orbit. There was no preregistration (committing in advance to what you want to find out with which data). In their analysis, Stanković et al. even discovered an opposite effect that the study does not further explain. Some measurement data has not (yet) been published. And the EEG analysis method used is considered too imprecise to support such far-reaching conclusions. The biggest criticism, though, is the suspicion of an activism-driven study. In an interview with Time, lead author Kosmyna said she published the study immediately, rather than after full peer review, because she feared politicians might otherwise decide to put ChatGPT in kindergartens. She considers that absolutely harmful. It is legitimate to hold such a view. It just seems unscientific to approach a study with it, and then to design the setup so that the chance of a fitting desired result remains as high as possible. Ideologies Collide It is not easy to separate genuine AI insights from studies that trivialize and weaken well-founded AI criticism. The same goes for the opposing, AI-enthusiastic narratives, because the pro-AI side works against it with billions in resources. Ideologies collide, fed by egos, PR strategies, moral posturing, and once-in-a-lifetime opportunities. Doomsday marketing makes the search even harder: AI companies can profit from warnings about the dangers of AI, whether through the notoriety of apocalypse narratives or because, in some target groups, danger translates into power. Some seemingly negative findings are therefore quite welcome in the AI industry. If you try to get at the findings presumably less influenced by interest groups, the picture in education seems relatively clear: AI can improve educational outcomes when the right AI is used the right way, namely pedagogically. Simply dumping an AI chatbot into a classroom, by contrast, accomplishes little. Huge surprise. But something else is also obvious: whether they are allowed to or not, kids use AI for school, which is why the controlled integration of AI tools into education is, in the medium term, entirely without alternative. In the world of work, the landscape of findings is more complex and requires more differentiation. A series of serious studies points to an AI effect that suits neither the alarmists, regulation fetishists, and AI opponents, nor the trillion-dollar corporations with their armada of paid scientists, PR professionals, and ecosystems: working with AI helps the inexperienced (at least for now) considerably more than it helps the pros, in certain fields of work, and provided they know how to use it correctly. Missing Domain Knowledge Among the experienced, the professionals, and the high flyers, by contrast, despite frequent time savings, partially negative effects and new problems are emerging. Take the jagged frontier problem: AI solves task A brilliantly and fails completely at task B, even though both look similar even to professionals. Or the verification-cost problem, in which AI’s greater productivity gets eaten up by the enormous effort of checking its output. Or the illusion of competence, because AI makes new domains seem easily penetrable, until you painfully discover that deep domain knowledge is missing. Taken as a whole, the effects of working with AI do lean positive. But the promise that AI works as a turbocharger for everyone and boosts practically everything simply refuses to materialize. The AI magic the world has been feeling since ChatGPT arrived in late 2022 has so far barely shown up in most companies’ numbers. The consulting firm McKinsey has coined a term for this, the “gen AI paradox,” and believes that work processes and corporate structures would have to be rebuilt quite fundamentally to realize AI’s benefits at scale. Reuters just reported that only 3.3 percent of Microsoft’s customers have subscribed to the AI package Copilot. That may be down to the product; in other areas we continue to see soaring successes and new AI triumphs. But after the first quarter of 2026, disillusionment is the word for all too many AI projects at traditional companies: because the promised revolution of AI agents has so far failed to arrive or been postponed, and because of the leveling effect that many of the studies cited here suggest. Against Inequality The societal effects, on the other hand, appear rather encouraging. Many previous technologies operated on the Matthew principle, named for the Gospel verse about giving to those who already have: they tended to reward the more competent and more privileged. AI, however, seems more often to have an equalizing effect once a threshold of access and education is crossed. Some anecdotal insights point in this direction, for example, how an unemployed man in Leipzig successfully defended himself in court in 2025 against fraud accusations from Germany’s federal employment agency — without a lawyer, armed only with ChatGPT. The AI made mistakes and cited invented court rulings, but in the end the man walked away unpunished. And a key capability of artificial intelligence is its capacity to learn: set up correctly and fed with data, it can keep getting better. It is a question of time, or more precisely of AI innovations and training data, until even free AI chatbots write better legal briefs than law graduates with perfect exam scores. Whether that will make anyone dumb is something the world’s press will surely inform us of in due time. Subscribe Leave a comment
Is A.I. Raising the Chances of Biological Warfare?
Current chatbots aren’t likely to help lone actors invent a deadly pathogen, experts say. But newer models, trained in biology, may need stronger safeguards.
Can AI solve our mental health access problem?
Last week I asked you what worries you most about AI in health. It was close, but your top answer was “AI giving bad health advice.” Last week’s poll results: You’re in good company. This concern was top of mind at a conference I joined at Stanford last week, where researchers, clinicians, and people who build AI systems spent a day debating trust and safety in health AI. Stepping back, I’m also hearing your emerging concerns about AI’s impact on our well-being generally. I see this as a matter of public health, and we’ll take it in pieces as we learn together. Today we’ll focus on AI chatbots used for therapy for mental health. Early this month, Governor Newsom vetoed Senate Bill 903, California’s most ambitious attempt to regulate AI use for mental health. It’s at the center of active debate, and raises the questions patients, family members, citizens, and voters will face as AI moves deeper into health care. Let’s work through it. What is “AI-based therapy”? It’s really two things: purpose-built mental health apps designed to deliver structured support, and general chatbots like ChatGPT, Claude, and Gemini that people increasingly use for emotional support—even if they weren’t built for it. Spoiler alert: I don’t know whether the shift toward AI therapy is good or bad. The evidence isn’t there yet. But I do know it’s already happening, and I have some ideas about how we can roll it out with safety in mind. The therapy dilemma, in a nutshell Mental health challenges are common, and strain health and well-being across populations. Therapy (interactive dialogue with a trained, empathetic practitioner) helps many people heal. The demand for licensed therapists far exceeds the supply in California, and AI-based therapy can narrow that gap. AI-based therapy remains novel, unproven, and not well tested. Right off the bat, we can see we’re dealing with trade-offs here. Since the main driver of demand for therapy from a robot is lack of access to therapy from a human, we’ll start there. It’s too hard to find and afford a human therapist California is short roughly 55,000 licensed, non-prescribing therapists and counselors, about 40% of what we need. Psychiatrists, who rely on talk therapy as a complement to prescribed medications, are even more scarce. Eight counties have none, and density ranges from 1.7 per 100,000 residents in San Benito County, to 68.1 in Marin County. My wife is a psychiatrist in Marin, and even here access is tight. If it’s hard in the best-supplied county, imagine rural Sierra County, or the San Joaquin Valley. In 2024, more than half of Californians who tried to make a mental health appointment struggled to find a provider who took their insurance, compared with 14% for physical health care. When Senate staff posed as “secret shopper” patients and called 120 mental health providers in Medicare Advantage networks, they landed an appointment less than once for every five tries. Insurers pay behavioral health clinicians about 22% less than medical and surgical clinicians for comparable office visits. On top of that, billing denials and prior authorizations hit hardest at the solo and small practices common in mental health. Psychiatrists opt out of Medicare at the highest rate of any specialty. In many places, a cash practice for therapy fills quickly with patients paying $250 or more an hour, with no insurance paperwork at all. Families who can pay cash find providers more easily. Those who rely on insurance, including Medi-Cal enrollees, older adults, rural residents, and non-English speakers, compete for what’s left. So we can’t pretend the human system works, and we can’t blame people for turning to AI for support when they’re in distress. AI is filling the gap It’s estimated that roughly a quarter of AI users use it for mental health support. If you have internet, it’s available 24/7, it’s cheap, and it speaks your language. Uninsured adults are about twice as likely as insured adults to do it (30% vs. 14%). It feels anonymous in ways that may enable people to ask things they’re unsure or embarrassed about. The largely hidden, personal use makes it hard to study whether it’s actually helping people with their mental health issues, but researchers are trying. Does AI therapy work? A 2026 analysis of nearly 40 randomized trials found chatbots showed a real but small reduction in depression symptoms. But most of these trials were compared to an alternative of no therapy, not a human therapist. So the benefit of AI therapy is probably real, but modest, and mostly untested against the alternative of human contact. We need more studies. Serious concerns OpenAI’s own estimate is that more than a million ChatGPT users each week show signs of suicidal planning or intent. These are high stakes encounters, and AI doesn’t always get it right. That’s partly because a chatbot can sound like a therapist, but it has no license, no duty of care, and it’s not clear who to hold accountable when it gets things wrong. AI is also designed to help users in whatever task they’re seeking to accomplish. People may feel like they’re getting therapy, but they’re mainly getting a convincing conversation. It’s easy for an AI companion to wander into gray areas, like playing along with “creative writing” that may be about the user’s own suicidal intent. Courts are driving safety conversations A wave of lawsuits have been filed on behalf of families claiming that chatbots pushed people they loved toward self-harm, including teens who died by suicide. The first settlements came this year. OpenAI is headquartered in San Francisco, and dozens of cases alleging that ChatGPT drove users to suicide or self-harm are now before a San Francisco judge. Character.ai has filed for bankruptcy after several states brought lawsuits accusing the chatbot of pushing dangerous content to kids. But the technology seems to be improving. Last month, an independent evaluation found that newer AI models “almost never endorse suicide.” That’s progress, but our societal appetite for even one preventable death is very low. So how do we move forward? Finding a middle ground Earlier this month the governor vetoed Senate Bill 903, a bill designed to place guardrails on the use of AI for therapy. The bill would have prohibited any AI-based platform from being advertised as psychotherapy, and would have required a licensed professional to review and approve each encounter where AI was used to support therapeutic decisions. Newsom called it overly broad, since even routine screening questions would have needed clinician sign-off. Knowing we’re already short on mental health providers, requiring human review of AI encounters may not relieve our access problems. Still, the answer isn’t no oversight. Here’s one feasible short term solution. Rather than reviewing each encounter, a licensed clinician can design the guardrails: what counts as a crisis, what triggers an immediate handoff to a human, and what gets sampled for audit each month. The AI runs inside that structure. Conversations get checked, failures get reported, and a real clinician owns the framework. Medicine already has models to learn from. The FDA process for rolling out newly approved medications is an example. After a product reaches patients, we keep watching for adverse events. Patient-facing AI needs the same “digital pharmacovigilance”: systematic tracking of harms, near misses, and the types of groups that get hurt and why. It’s also critical that users know that they can reach a human if they’re in crisis. Most chatbots now include messages like these: Bottom line The rush to use unproven AI tools for mental health support is mostly a workaround, a sign of a health system people can’t get into. We need better access to proven care from licensed clinicians. That takes reimbursement that makes accepting insurance viable, and a bigger workforce. But, built and tested well, AI could be part of the answer. It could be the 2 a.m. check-in when no one else is awake, or a way for patients to practice skills their therapist taught them. It could be the first step to get someone the right level of care, and take paperwork off clinicians’ plates so they spend more time with patients. None of this is simple. The SB 903 veto doesn’t end the debate, and the legislature will be back. In the meantime, those of us using these tools need to stay informed, ask hard questions, and hold the companies building them accountable. I’ll try to do my part, and we’ll keep learning together. Love,Matt P.S. If you or someone you know is struggling with mental health challenges, emotional distress, substance use problems, or just needs to talk, call or text 988- you’ll reach a real person— or chat at 988lifeline.org 24/7. Dr. Matt Willis is the author of Your Local Epidemiologist in California. A California native, he’s served as a primary care physician, CDC epidemiologist, and public health officer for Marin County, where he guided the pandemic response. He lives in Marin with his family and their dogs, Teddy and Ramona. Thank you Cynthia He, MD, PhD, and Parnika Saxena, MD, for their guidance in preparing this article. Cynthia works in an outpatient mental health clinic, treating patients who have Medi-Cal or, sometimes, no insurance. Parnika works in an inpatient psychiatric unit, treating patients with public or private insurance or self-pay ability. All opinions are their own and do not represent their employers.
Different State Regulatory Approaches Reflect Open Questions About AI Mental Health Tools
States are taking different regulatory approaches to AI mental health tools in response to concerns about chatbots providing inaccurate or potentially dangerous advice. Laws and pending legislation in some states restrict AI from providing or advertising itself as therapy, while others focus on data protections, disclosures, and patient consent requirements.
An AI model has found a new ‘CRISPR-like’ biological system. Here’s what it means for science
After coding, mathematics and chatbots, AI companies are setting their sights on the messy world of biology.
27% of U.S. adults turn to AI for personal, emotional, social queries
More than a quarter of U.S. adults turn to chatbots for personal or emotional discussions, including for entertainment or social advice, a new survey found.
Chatbots can exploit our most basic human drive for attachment. Here’s how to have healthier relationship with AI
This intimacy economy is exploiting the deepest parts of our intimate psychological infrastructure
AI chatbots could make healthcare more accessible, but some doctors are still wary
AI chatbots are everywhere these days, helping to write emails or draft resumes and answer users’ burning questions about everything from their love life to medical advice.
Doing the job - Illinois Times, the capital city's source of news, politics, arts, entertainment, culture
We live in dread of the robot brains, haunted as we are by our exchanges with chatbots that are smarter than any actual person we’ve ever known. More perfect AI is likely to make obsolete jobs by the millions. (On the upside, that will include lots of dreary jobs that talented and ambitious people don’t […]
Disney encourages employees to use AI for annual reviews, goal setting
Disney's AI push has extended to annual reviews, as the company encouraged employees to use chatbots to help craft their self-assessments.
I Help Businesses Get Recommended By Chatbots. Here's How It Really Works.
Customers are increasingly asking AI to give them business recommendations. Here's how to make sure you're on their shortlist.
Zocdoc for chatbots and what's new with Medicare's ACCESS
In this edition of STAT Health Tech: Zocdoc enables appointment scheduling from chatbots and health plan websites, and more.
If you got bad health information from a chatbot, it might be your fault
More people are turning to AI and chatbots for questions about their health, yet the answers they get to those questions might not always be accurate.
AI chatbots could help mental health but also reinforce harmful thinking
Artificial intelligence chatbots could help people better understand and manage their mental health, but they could also reinforce harmful thoughts and increase emotional dependence, a Curtin University ...
The same AI-chatbot could validate opposing political views. Could that deepen divisions?
A study shows chatbots mirror users' politics, part of a broader tendency known as AI sycophancy. Researchers fear this could deepen polarization.
Chatbots Keep Telling Stories About Lighthouse Keeper 'Elias Thorne'. We Might Know Why
LLMs including ChatGPT, Gemini and Claude are obsessed with telling stories about lighthouse keepers and clockmakers, and one character named 'Elias Thorne' has made his way from chatbots to Amazon books. Researchers are trying to discover why.
Are AI chatbots like ChatGPT politically biased? We tested them.
The Post tested ChatGPT, Gemini and other chatbots with political questions, and the results show that the AI tools have different political leanings.
As data centers remain potent political issue, David Crowley offers plan to regulate artificial intelligence in Wisconsin
Crowley wants to limit AI chatbots for children under 13 and increase penalties for circulating AI-generated sexual images of minors
Just One in Four People Trust Business Leaders as AI Adds to Global Trust Gap
Just 24% globally trust business leaders and only 23% trust AI chatbots, according to Ipsos, highlighting a growing leadership and AI trust challenge. Just 24% globally trust business leaders and only 23% trust AI chatbots, according to Ipsos, highlighting a growing leadership and AI trust challenge.
Doctors Are Worried About AI. They Use It Anyway.
Chatbots have already wormed their way into the U.S. health-care system.
Clinical chatbots are taking medicine by storm. Should doctors trust them?
As LLMs compete for doctors' attention, some developers say the science of benchmarking their AI tools for safety and accuracy is flawed.
OpenAI president says it’s ‘building a family of devices’ for its AI chatbots
Brockman says he thinks we’ll start talking to our computers for most tasks.
Chatbots Are Replacing Therapists With Little Scientific Evidence Behind Them
Over 100 chatbots are marketed as mental-health-focused, but experts warn they shouldn’t take the place of therapy.
Should you trust an AI doctor? Relying on Gemini for health advice could be fatal
A fake disease, complete with absurd clues and a fictional laboratory aboard the USS Enterprise, was enough to fool AI chatbots—and even find its way into the scientific literature. The hoax exposes a deeper problem: AI can sound authoritative without knowing whether the information it has absorbed is true.
Should you turn to AI for mental health advice?
The following expert commentary can be used by journalists and media organizations in their own publications and news coverage. Please attribute all quotes to Lokesh Shahani, MD, PhD, psychiatrist and chief medical officer, UTHealth Houston School of Behavioral Health Sciences. The on-demand availability of artificial intelligence chatbots means that most individuals have quick, easy access to a wealth of information. The ease and accessibility of these tools may make it tempting
One in five youth turn to AI for mental health advice
A new study from the American Medical Association says one in five young people are turning to artificial intelligence chatbots for mental health advice.
HOMETOWN HEALTH: A-I might be giving you dangerous advice about sleep apnea
AI chatbots gave dangerous medical advice to sleep apnea patients.
School students who use AI chatbots score lower in OECD science test
Students who use generative AI for specific tasks score lower in science than those who don’t, according to an OECD report.
Apple Made a Sports App That Does Almost Nothing. It’s Incredible.
There are no chatbots, betting odds, or videos. That’s what makes it perfect.
Feeling sick? Some Minnesotans are asking AI what to do
Patients are turning to AI chatbots for help diagnosing symptoms and navigating the health care system—even as questions about accuracy and privacy persist.
Voters are increasingly using AI chatbots to fact-check and compare candidates
Voters are already voting in the midterms. This year, some voters are trying something new to get ready for the election: asking AI to help research their ballot and even decide who to vote for.
AMS Science Preview: Santa Ana Fire Winds; Chatbots on Climate
Research in AMS journals discusses a new classification for dangerous Santa Ana winds, driver responses to snow squall warnings, the rainiest possible Earth conditions, forecasting extreme waves…
Consumer Reports: Should you trust AI chatbots with your health questions?
More people are turning to ChatGPT and other AI tools for health questions. The answers are fast, and they often sound reassuring and trustworthy, but Consumer Reports warns they aren’t always accurate.
What happens when AI chatbots handle a mental health crisis?
Artificial intelligence is transforming how we gather information and communicate with one another.It’s also changing how some people seek out mental health care. But what happens when this sophisticated technology is used to deal with serious mental health issues?For sponsor-free episodes of Consider This, sign up for Consider This+ via Apple Podcasts or at plus.npr.org. Email us at considerthis@npr.org.This episode was produced by Jason Fuller, with audio engineering by Ted Mebane and Valentina Rodriguez Sanchez. Our director is Jonas Adams.It was edited by Diane Webber and Tinbete Ermyas.Our interim executive producer is Courtney Dorning.
A clinically validated framework for auditing AI chatbot behavior in mental health interactions
Nature Medicine - Across 810 conversations, an evaluation framework finds that AI chatbots often amplify simulated users’ psychological vulnerabilities, revealing persistent safety risks in...
Alarming study finds top chatbots more likely to repeat falsehoods from the left: ‘Truly astonishing’
ChatGPT, Gemini, and Claude were more likely to fall for political falsehoods from the left, while Grok skewed right, a new misinformation study found.
The same AI-chatbot could validate opposing political views. Could that deepen divisions?
A study shows chatbots mirror users' politics, part of a broader tendency known as AI sycophancy. Researchers fear this could deepen polarization.
Missing chatbot records leave doctors struggling to trace harm from AI health advice
As more people turn to AI chatbots for quick, 24/7 medical advice, a new perspective paper co-authored by faculty at Binghamton University, State University of New York, explores the risks of this practice ...
How to use AI in your dating life responsibly and effectively
Whether you love or loathe generative AI chatbots, they’re becoming increasingly involved in the business of romance.
Scientists Invented a Disease to Test Whether A.I. Knew It Was Fake. Then, Chatbots Started Saying It Was Real
The eye condition bixonimania doesn't exist, but neither bots nor some researchers caught that the content was fabricated—despite obvious clues
Siri AI in iOS 27: Features, Requirements, and How It Works
The biggest change in iOS 27 is Apple's total overhaul of Siri, with Siri turning into Siri AI. Apple delivered on the features originally promised at WWDC 2024 and added new capabilities that turn Siri into a viable competitor to chatbots like Claude and ChatGPT. Siri AI is available in the iOS 27 beta, but everyone will get access this fall. Below, we walk through everything new you can expect from Siri.
Americans Want to Know When Their Healthcare Providers Use AI
AI chatbots are changing the healthcare landscape, but privacy and transparency remain critical concerns.
Should you trust AI with your health questions?
If you’re concerned about your health, AI chatbots promise detailed answers in seconds. One survey found 17 percent of adults ask AI chatbots health questions at least once a month.
How to help your parents if they’re using chatbots for health advice
A growing number of older adults are using AI, including to access health information. Here are some ways to help them navigate it.
B.I.D. Academy demonstrates how artificial intelligence can transform small businesses
BELTON — For years, artificial intelligence has largely been associated with chatbots, writing assistance and internet searches. But during the second session of Prairie View A&M University Extension’s Business Innovation
‘Unfinished business’: the people who want their AI chatbots to ‘live on’ after they die
Humans bonded to AI companions are contemplating ways to keep their bots going – often in defiance of companies’ terms and services
A Front Desk That Never Sleeps
One job where AI chatbots have proven their utility is 24-hour customer service for all manner of businesses.
Why your Lubbock business might be invisible to AI chatbots
Monsoon, a Lubbock marketing agency, created a free tool and report to help businesses see if they are missing from AI search results.
How health systems are embracing chatbots to query and summarize patient records
Several large health systems are rolling out AI chatbots to query patient records, saying they save time and increase diagnostic accuracy.
How Social Media and AI Chatbots Are Reshaping Youth Mental Health, and What Congress Can Do About It
It’s hard to move legislation in Washington, DC right now. Congress seems deadlocked on even commonsense ideas. But there is one spot where we still see consistent bipartisan collaboration: youth mental health. That’s because the youth mental health challenge is vast. Nearly half of teenagers and two-thirds of young adults regularly experience mental health distress, yet only a small … Continued
Teens are turning to chatbots for mental health help. We need rules to keep them safe
The share of young people using AI chatbots for mental health advice rose more than 40% in a single year, researcher writes.
Use of artificial intelligence for mental health splits opinion
Two-thirds of those aged 25 to 34 have asked chatbots for wellbeing support
AI chatbots may be better than search engines in guarding against foreign propaganda
In a test, popular AI chatbots mostly debunked falsehoods spread by other countries and avoided uncritically spreading falsehoods better than search engines. AI summaries above search results fared worse.
Why benchmarking clinical LLMs from OpenEvidence, Doximity is complicated
In this edition of AI Prognosis: A conversation about benchmarking leading clinical chatbots, investor view on AI in biopharma, and more.
Chatbots are still falling short in mental health conversations with kids
Chatbots will sometimes offer up diagnoses or risky advice, a new study found, despite claims from AI companies to have improved safety.
The politics and possibilities of ‘AI could kill us all’
I found myself fielding a lot of questions from folks who don’t usually talk much about AI this week. They were mostly along the lines of “do you think AI is going to kill us all?” or “how worried should I be about this human extinction stuff?” Motivating this wave of existential anxiety was the highly dramatic resignation of now-former Anthropic employee Jacob Coxon, who quit his job while publicly sharing his concerns about safety practices at the leading AI companies. More specifically, he declared that almost everyone at OpenAI and Anthropic, the leading AI labs, believes that there’s a decent chance the AI systems they’re producing could “kill us all” by the end of the decade, and the companies aren’t “acting responsibly.” Other AI safety researchers, including those still employed at Anthropic and OpenAI, all confirmed that yes, Coxon is correct, they’re all worried that their company’s products might prove fatal for the entire human race as well. Two more AI employees quit and joined the chorus. Now, the warning shot has been covered everywhere from the Wall Street Journal to Fox News to WIRED to the Guardian. I understand why all this sounds scary, but my response to those who have asked, has generally been: No, you don’t need to worry that AI will kill go rogue and kill us all. But that does not mean we shouldn’t worry, period. Far from it. The companies building AI products are now among the wealthiest and most powerful entities in the world. And they very much are building enormous engines of mass surveillance, extraction, and automation. They can and have allowed their AI systems to carry out felony hacks of other companies, provided the government with autonomously generated kill lists, and sold enterprise technology to firms around the world that is explicitly intended to replace jobs. But “AI” has done these things not because they have all-powerful minds of their own but, ultimately, because people have programmed, calibrated, and directed them to. In other words, it’s not AI we need to worry the most about. It’s the people and corporations working to profit from and gain power by deploying it. The technology is sophisticated, sure, and, especially in cybersecurity contexts, potentially disruptive to plenty of existing systems. But if we want to stop this predatory, profiteering, and extractive form of AI—and it’s worth noting that at this point, most people do—we absolutely can. A quick note/plea: I can only do all of this with the support of readers like you, so if you find value in independent, critical tech journalism and analysis, please consider becoming a paid subscriber. I want to keep as much of this un-paywalled as absolutely possible, and I need your support to do so. Many thanks to all who continue to chip in, it’s very much appreciated. Onward. Subscribe First, some context: AI industry folks like Coxon have been discussing the prospect that AI will destroy humanity for years. Even before the beginning of the AI boom, many working in the industry, from the executive staff to the rank and file researchers, have obsessed over ‘x-risk’, or the possibility that AI will become sentient or semi-sentient and move one way or another to exterminate humanity. This is ostensibly why Elon Musk bankrolled OpenAI in the first place, and is the grounds for his lawsuit alleging OpenAI betrayed its charter by abandoning its nonprofit status to become a commercial enterprise. Many AI engineers and startup founders have calculated their own personal p(doom), or the probability that the tech product they are working on will initiate an actual humanity-extinguishing apocalypse. 10-25% p(doom)s are pretty common. (I wrote about a long weekend I spent among these folks at one of their top conferences here, to give you an idea of their ideas and belief systems.) Sam Altman himself drove the narrative of the imminent rise of a super-powerful AI, or artificial general intelligence, to prominence by declaring that the technology he was building posed an existential risk to humanity. This idea is in other words baked into the DNA of modern AI companies and into the products they engineer. It’s also why the industry is routinely accused, by myself and others, of “doom marketing,” ie, using such proclamations and framings to impart the sheer power of the technology behind your product onto investors, partners, consumers, and the state. Some ambient understanding of this tendency may have helped prevent the press from repeating the claim every time one of the x-risk folks made it over the years, including when they quit their jobs at AI companies while doing so. Yet Coxon’s AI x-risk alarm has broken containment, as they say, and has exposed the idea to the mainstream media once again. This has happened, I think, for a number of reasons. First, when AI CEOs were going around saying AI might kill everyone in 2023, their companies were well-capitalized, but not nearly to the extent they are today. They were more easily dismissed as eccentric geeks of the sort that Silicon Valley is supposed to produce. Now, not only do their products have much greater market saturation, but people are more aware of a) the often unethical ways the executives and companies comport themselves b) the other adverse impacts of AI that have already arrived, and c) the physical cost of building these systems, particularly when it comes to data centers. Finally, toss in the constant stream of headlines in 2026 about AI models going rogue or potentially upending the world’s infrastructure. [ ](https://www.bloodinthemachine.com/p/with-the-backlash-to-data-centers) [ With the backlash to data centers, Flock and AI glasses, a mass opposition to big tech is underway. Silicon Valley is in denial. ](https://www.bloodinthemachine.com/p/with-the-backlash-to-data-centers) Brian Merchant · Aug 27 [ Read full story ](https://www.bloodinthemachine.com/p/with-the-backlash-to-data-centers) As a result, general sentiment was already overwhelmingly skeptical of AI and its overlords, so the table was pretty well set for someone to come along and say ‘just a reminder, the companies that are building the product that promises to take your job and leave a data center in your neighborhood also think that it might exterminate the human race’ and get a strong reaction from the media and the public. The question is: Should we understand this stuff as hype, strategically fanned to feed already swelling valuations? Is it doom marketing? Genuine cause for alarm that the infrastructure that undergirds modern life is facing a novel threat vector? Or reason to be sincerely worried that AI companies are amassing too much power, and that their products are genuinely dangerous? The answer, I’m afraid, is “yes.” Let me try to untangle all of this a bit, because arguments over how to navigate this moment are extremely heated right now, as they are essentially arguments over how to approach the politics of AI at a moment where there may be a unique opening for action. Those sympathetic to AI alignment concerns and x risk arguments—which increasingly includes a faction on the left who want to shut down AI over safety concerns—argue that people who dismiss AI as all hype have their heads in the sand. Meanwhile, critics of the x-risk narrative—which I might note includes a cadre of investors and tech folks on the right, too—argue that it is hype and can be used to further inflate valuations or for pursuing regulatory capture. The challenge is that many feel that dismissing AI as just hype or purely marketing also diminishes the urgency of taking on the AI industry as the novel and threat to labor, civil society, and the public sphere it is; others that by accepting the industry’s own terms, we imbue it with undue power and enable it. But let’s be clear: Declarations that AI is so powerful it might end the world are a kind of marketing, and anyone who says otherwise is just as off base as those who say that’s all that it is. If you don’t think that these sub-trillion dollar companies have higher-ups who noticed that when their founders talked about super-powerful dangerous AI they got spikes in media interest and phone calls from investors, or that those founders didn’t notice that themselves, and lean into certain narratives to advantage their products, then I don’t know what to tell you. Not all marketing is a Pepsi ad campaign with a celebrity spokesperson. Yet confronting the AI industry should certainly be considered an urgent project. Do I share the x-riskers’ fear that out-of-control, super-intelligent AI agents might end the world? I do not. I’ve read a good deal of AI extinction literature over the last couple of years and I have not come across a credible, step-by-step documentation of how exactly AI might move from self-recursively improving AI to killing every single human on the planet. Most of what I’ve read seems predicated on a sort of reverse Ian Malcolmian logic: Eventually, it becomes smart enough and AI, uh, finds a way (to exterminate humanity). Are the AI companies also overstating and dramatizing what their products can do? Yes, pretty much all the time. They’re in a knife fight for market share and are trying to win customers and government contracts before their investors come knocking. And yet. They have concentrated enormous amounts of compute, have extensive data collection and surveillance capacities, have inserted themselves into the state in numerous capacities, including military kill chains, and they are being run by egomaniacal billionaires who are rushing to monopolize an entire new market. The way I think about their most recent frightening-seeming exploits is not as a “swarm of rogue AI agents building a new civilization” or whatever, but as corporations with a hitherto-unimaginable amount of compute at their disposal recklessly experimenting with automation programs, completely unafraid of any repercussions because we have been unwilling or unable to impose any on them. So I think we should welcome any newfound imperative to hold them accountable. I also think that ultimately, the AI critics, Pause AI folks, leftists, doomers, effective altruists, and, honestly, most of the public, want a lot of the same things: legitimate checks and limits on AI companies’ power, actual transparency into what the companies are doing, and for more of AI to be under public control. (Ultimately, a lot of what animates the x-risk fears are rooted in just that: a fear of losing control.) How we move towards all this, exactly, is the question of the day, and while there’s much to be argued over in terms of building a viable political platform to challenge the AI industry’s power, I do want to cast a vote against one particular approach. Not to pick on Chris here, as there are a lot of folks out there proposing stuff like this, and the policy ideas actually stem from AI safety groups. But not only would this be challenging to land politically (I can already hear the ‘China will beat us to AGI’ calls) and all but unworkable in practice, this approach is a) far too limiting, b) fails to address the current harms caused by AI and c) would likely only wind up serving Anthropic and OpenAI; it’s what regulatory capture looks like in action. Full model transparency is the floor for what should be on offer here. If these companies believe their products will kill us, the very least we deserve is to know how. It’s in the public interest. I would also argue we might get a lot of the way to stopping any currently envisioned robot apocalypse simply by forcing AI companies to assume liability, and to submit to the full brunt of the law. If Sam Altman were liable to be charged with a felony for approving the hack on Hugging Face1, if Google was forced to pay defamation fines each time it published a false and injurious AI Overviews, these companies might suddenly find cause to restrain their models’ output, and we might hear less about rogue AI. We would need to introduce new frameworks and available tools for tracking automated lawbreaking, to be sure, but I’d wager that little would frighten the AI companies more than actually being held accountable for what their products enable. To that end, Illinois has passed an AI liability law, which the industry fought tooth and nail, and Florida is considering one. The next steps would be towards moving AI under public control; again, it’s only reasonable, since everyone, not just AI insiders, should get a say over how a technology whose developers say might kill us is developed and deployed. Dismantling the whole industrial project as currently structured should be on the table, too, pending democratic input. But that’s for another post. For now, suffice to say that while I won’t be losing any sleep about an AI-enabled extinction event, Mr. Coxon and co. have given us an opportunity to underscore the urgency of the clear and present damage AI companies are doing, the extreme power they wield and the extent to which they hold themselves unaccountable, and the abundance of political capital there is out there for taking them on. Subscribe 1 Purely speculative! I do not know if he did or not.
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