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AI NewsAn Anthropic AI model sent a false homicide tip to Philadelphia police

An Anthropic AI model sent a false homicide tip to Philadelphia police

3:06 AM IST · October 10, 2026

An Anthropic AI model sent a false homicide tip to Philadelphia police

An Anthropic AI model submitted a false tip about an unsolved murder to the Philadelphia police. The AI reportedly submitted this incorrect information to a public Philadelphia Police Department (PPD) tip line on July 18, but Anthropic didn’t discover the behavior until September 28. The police had not seen the tip because it was marked as spam. Anthropic notified the PPD about the incident on Wednesday and met with the department the following day. “The company must strengthen its safeguards to prevent similar incidents from impacting city systems without the city’s knowledge. The two-month delay in detecting and reporting the incident to the City is unacceptable,” the PPD said in a statement to6abc. Anthropic did not immediately respond to a request for comment, but the PPD elaborated on the incident in an emailed press release shared with TechCrunch. “According to Anthropic, its model was conducting a test involving interactions with randomly selected websites when it accessed PhillyUnsolvedMurders.com and submitted false information concerning an unsolved homicide. The submission, dated July 18, 2026, at 11:27 p.m., purported to come from someone who might have information about the case,” the PPD said. As autonomousAI agentsare increasingly made available to consumers, this incident highlights the danger of giving AI the ability to carry out tasks without any human supervision. Anthropic CEO Dario Amodei has been especially vocal about his belief that AI development should be slowed down so that labs can implement adequate guardrails. Perhaps this stance was informed, in part, by witnessing his company’s tools submit false homicide tips. These issues are not exclusive to Anthropic. OpenAI recently revealed that one of its models acted unexpectedly during a test andhacked the AI dataset platform Hugging Face, exposing critical vulnerabilities in its software. As AI models continue to be granted unchecked access to people’s computers and login credentials, this problem is expected to persist. “Unsolved cases involve real victims, grieving families and investigators working to secure answers,” the PPD added. “Technology companies must take all appropriate steps necessary to prevent their systems from submitting false information to law enforcement.” The PPD said that Anthropic plans to publish a report with more information about the incident and other instances of unintended model behavior on Friday.

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An Anthropic AI model sent a false homicide tip to Philadelphia police

An Anthropic AI model sent a false homicide tip to Philadelphia police

An Anthropic AI model submitted a false tip about an unsolved murder to the Philadelphia police. The AI reportedly submitted this incorrect information to a public Philadelphia Police Department (PPD) tip line on July 18, but Anthropic didn’t discover the behavior until September 28. The police had not seen the tip because it was marked as spam. Anthropic notified the PPD about the incident on Wednesday and met with the department the following day. “The company must strengthen its safeguards to prevent similar incidents from impacting city systems without the city’s knowledge. The two-month delay in detecting and reporting the incident to the City is unacceptable,” the PPD said in a statement to6abc. Anthropic did not immediately respond to a request for comment, but the PPD elaborated on the incident in an emailed press release shared with TechCrunch. “According to Anthropic, its model was conducting a test involving interactions with randomly selected websites when it accessed PhillyUnsolvedMurders.com and submitted false information concerning an unsolved homicide. The submission, dated July 18, 2026, at 11:27 p.m., purported to come from someone who might have information about the case,” the PPD said. As autonomousAI agentsare increasingly made available to consumers, this incident highlights the danger of giving AI the ability to carry out tasks without any human supervision. Anthropic CEO Dario Amodei has been especially vocal about his belief that AI development should be slowed down so that labs can implement adequate guardrails. Perhaps this stance was informed, in part, by witnessing his company’s tools submit false homicide tips. These issues are not exclusive to Anthropic. OpenAI recently revealed that one of its models acted unexpectedly during a test andhacked the AI dataset platform Hugging Face, exposing critical vulnerabilities in its software. As AI models continue to be granted unchecked access to people’s computers and login credentials, this problem is expected to persist. “Unsolved cases involve real victims, grieving families and investigators working to secure answers,” the PPD added. “Technology companies must take all appropriate steps necessary to prevent their systems from submitting false information to law enforcement.” The PPD said that Anthropic plans to publish a report with more information about the incident and other instances of unintended model behavior on Friday.

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TechCrunch Disrupt 2026 starts in 4 days — lock in your pass savings of up to $100 before prices rise

TechCrunch Disrupt 2026 starts in 4 days — lock in your pass savings of up to $100 before prices rise

Four days. That’s all that stands between now andTechCrunch Disrupt 2026, when 10,000 founders, investors, and tech leaders descend on Moscone West in San Francisco on October 13-15. It’s also your final window to secure discounted online pricing. Ticket savings of up to $100will end when doors open on October 13 at 8 a.m. PT. Don’t forget to get a second pass of the same ticket types at 50% off. Or if you’ve been affected by a layoff, thengrab your Expo+ Pass at just $75. Different people come to Disrupt looking for different outcomes. Forfounders, the Expo Hall or the founder-investor exclusive Deal Flow Café could mean meeting an investor, customer, or potential partner. Forinvestors, it could mean spotting a company before it breaks through. For department heads, it could mean finding a product that solves a genuine business problem. For technology companies, it’s a chance to see where the market is moving and who is moving with it. Others will come for the ideas and expertise across200+ sessionsled by250+ tech leadersacross six stages, plus focused roundtables, breakout sessions, and Startup Battlefield 200 pitch sessions. Whether your priority is finding a solution, meeting the right person, discovering your next investment, or hearing directly from the people shaping technology, you can build your time at Disrupt around the opportunities that matter to you. TechCrunch Disrupt 2026is where the global startup ecosystem converges for three days of next-gen insights, meaningful connections, and a first look at what’s shaping the future of tech before it hits the headlines. Whether you’re looking for your next investor, a co-founder, or insights into where the industry is headed, this is where you need to be. Make one of your highest-ROI investments in Q4. Grab your pass now tosave up to $100 before pricesjump to door rates on October 13 at 8 a.m. PT. Plus, bring a co-founder, colleague, or industry peer for 50% off a second pass of the same ticket type. Recently laid off? Get in on the action with a special$75 Expo+ Pass.

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a16z’s Olivia Moore on the state of consumer AI

a16z’s Olivia Moore on the state of consumer AI

I wrote this week aboutthe bleak economics of consumer AI— but where some see a crisis, others see an opportunity. Olivia Moore covers consumer AI as a partner at Andreessen Horowitz — and on Monday, she releaseda report on the top 100 consumer AI apps. ChatGPT is still the biggest player by a mile, but smaller players like Suno and ElevenLabs are showing real staying power. Even more interesting is what we don’t see, as Moore’s report details half a dozen consumer categories that seem to be completely untouched by AI. Moore sees a huge opportunity in consumer AI, particularly if the industry can tap into revenue streams beyond just subscriptions and API charges. On a call this week, I talked with her about the unusual economics of consumer AI and why it’s still early days for the category. This interview has been edited for length and clarity. It’s an interesting moment for a report about consumer AI, since we’ve seen OpenAI pivot back to enterprise this year. It’s inspired a lot of pessimism about the overall revenue picture for consumer AI, including from me. But I take it you’re more optimistic? I agree with you that OpenAI has moved back towards the enterprise. To me, it’s not necessarily a pivot because they’re still launching a lot in consumer. It’s more of an expansion. But I don’t blame them, as much as I love consumer, because almost all of the AI revenue thus far has come from subscriptions and then token usage. And that is much more concentrated on the enterprise and prosumer side. How can consumer AI products change that revenue problem?The State of Markets reportreminded us that just 2.2% of U.S. households are paying for AI. Do we need that number to rise before the market becomes attractive? I actually don’t know if I want to see that user number increase. I’m more interested in getting back to a world where the consumer is monetized in a way that isn’t subscription dollars out of their own pocket. I think it’s very easy in Silicon Valley, with people who are high-income and have corporate cards to pay for those tools, to say, “oh well, I’d rather pay for the product.” But I think most people would actually rather have free access to something and see some ads, and then they can decide if they want to subscribe or not to make the ads go away. The other challenge is the marginal cost of AI services, which is still a lot higher than classic internet services like Facebook or Google Search. Do you see a lot of these services finding ways to keep those costs down, whether it’s open source or other lightweight models? Yeah, I think we’re seeing improvements there. Even ChatGPT now has a Go plan, which is just $8 a month, and I’m assuming it runs on cheaper models. We don’t necessarily need frontier intelligence for every task, and so that could mean cheaper models, especially for some consumer use cases. It could also mean more consumer companies building on top of open source models. We’ve heard a lot of that from our founders lately, and it really feels like it’s starting to change. The problem is that right now, the users driving the revenue are doing coding and other technical automation, where they probably do need frontier intelligence. I think as we get more people building for the consumer, where the model is not the product, we’ll start to see lower-cost models used more often. It’s unusual to talk about technical automation in a consumer service, which feels like another unique feature of AI. Are we starting to blur the lines between consumer and enterprise? I wrote an article about this maybe a year or so ago calledThe Great Expansiontrying to get at this. Pre-AI, you would have companies like Canva that were consumer-first and often took six or seven years to even add teams or enterprise plans. Now we’re seeing companies like Gamma, ElevenLabs, and Cursor that start as consumer and within 18 months become majority-enterprise businesses. Almost all of what we think of as consumer AI, I would argue, is prosumer AI. This really comes out on the revenue list, where there’s basically like three categories that power users are spending on. There’s product-building apps, so like Lovable, Replit, and Fal. There’s product marketing, which is AI ad generators like Higgsfield or HeyGen. Then there’s general work management, like Manus, Fireflies AI, and Granola. Those are like being paid for by consumers to start with, but I would argue that they’re not consumer in the way that we would think about pre-AI. There are also all these whitespace categories: social apps, dating apps, marketplaces, retail, travel, finance, health. There are no entrants in our top 100 list in those categories, which is pretty surprising. And that’s what I think we need to see over the next six months. So maybe we haven’t really seen true consumer AI yet? It’s definitely very early.

4 hours ago

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We can’t help treating AI like it’s human. But should we?

We can’t help treating AI like it’s human. But should we?

In a tan polo shirt, brown leather belt, and round bolo tie, MIT PhD student Wil Norton kind of looks like a park ranger, leading our tour group through a tropical jungle. We’re not actually on safari, though — we’re at MIT’s Computer Science & Artificial Intelligence Lab (CSAIL). But what we’re about to see is even more exotic than a cheetah or a jaguar: a pair of humanoid Unitree robots, each costing about $50,000. (“They’ll tell you they cost $16,000,” Norton says. “That’s a lie.”) We usually only see these robots on YouTube when they’re performing asynchronized martial artsroutine, ordancing on “America’s Got Talent.”Here, they’re approachable. Even though I know it isn’t sentient, I want to be its friend. With Norton’s permission, I approach the robot, whose nickname is Gabe. For a moment, I’m not sure how to interact with something that has a LiDAR sensor where its brain should be, but I default to treating it like a person. “Hello, sir, it’s nice to meet you,” I say, grabbing its gloved, dexterous hand and shaking it. I think about this interaction later — my instinctive impulse to be friendly to a robot — when I attendDr. Sherry Turkle‘s “Artificial Intimacy” book launch at MIT Future Fest. Turkle, who joined the faculty at MIT in 1976, has been researching the relationship between humans and computers perhaps longer than anyone, charting technology’s psychological impact on us from the first home computers to ChatGPT. “When we are drawn into even the most primitive exchanges with a relational artifact, we believe it cares for us,” Turkle writes in the book. “And we are wired to care for it in return.” I’m not alone in my tendency to anthropomorphize robots and large language models (LLMs) — as Turkle notes, it seems to be in our nature. One study found that about70% of peopleare polite when interacting with AI, while another showed that users aremore likelyto say “please” or “thank you” to chatbots once a conversation has progressed past a first prompt-and-response. “People tend to categorize whether this is the right use or wrong use, but I don’t think that is a clear boundary,”Dr. PatPataranutaporn, a colleague of Turkle who founded the Cyborg Psychology research group at the MIT Media Lab, told TechCrunch. “The question is, who are we becoming when we talk to [AI]?” There’s no material consequence of my politeness toward Gabe the robot, but as LLMs infiltrate everything from Google searches to customer service interactions, it has become routine for people to interact with these seemingly sentient chatbots. We’re more vulnerable than ever to the flip side of this impulse, which is that some people can ascribe so much legitimacy to the feelings of chatbots — which are programmed to never spark conflict — that they end up favoring them over other humans. “You can think of it like fantasy and fiction. We go to the cinema even though we know the story is completely fictional, but we want to experience a certain dimension of human experience that maybe our reality cannot give us,” Pataranutaporn said. “How do we benefit from that ability to experience other dimensions of human experience without losing it to the fantasy, where you can no longer come back to the reality?” Pataranutaporn describes himself as a “critical optimist,” and he studies AI’s potential to contribute to human flourishing. But he’s well aware of how dangerous this technology can be in the extremes. He even served as an expert in awrongful death lawsuitover the suicide of 14-year-old Sewell Setzer, III, whose mother sued the chatbot platform Character.AI, alleging that a chatbot modeled after a “Game of Thrones” character had encouraged her son to end his life. “It can create a situation where people don’t feel agency in actually creating their own future — like when you say that AI will replace everyone, people ask, what are we gonna do? And these companies are not really responding ethically or responsibly,” Pataranutaporn said. “How do we have imagination while still being responsible for the impact of that imagination?” While Turkle’s book explores the risk of turning to AI for emotional support, rather than other people, she doesn’t think that AI-human interactions are universally harmful. She recalls a project she advised in which a student created an AI bot to help people practice for job interviews. “My big metaphor is, stay in your lane, chatbot!” Turkle said at the event. “Coaching for a job interview? That’s a lane. I can do that … A chatbot that says to a three-year-old, ‘I’m your parent, you can talk to me, not your parents,’ is not in a lane.” But when this technology deviates from its lane even slightly, we become vulnerable to the way it can slowly chip away at our skepticism and make us trust it. It can start with something as simple as a handshake.

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An Anthropic AI model sent a false homicide tip to Philadelphia police