AI is Creating a ‘Hive Mind' — Scientists Just Proved It
The big AI conference NeurIPS is under way in San Diego this week, and nearly 6,000 papers presented there will set the technical, intellectual, and ethical course for AI for the year. NeurIPS is a strange pseudo-academic gathering, where researchers from universities show up to present their findings alongside employees of Apple and Nvidia, part of the strange public-private revolving door of the tech industry. Sometimes they’re the same person: Increasingly, academic researchers are allowed to also hold a job at a big company. I can’t blame them for taking opportunities where they arise—I’m sure I would, in their position—but it’s particularly bothersome to me as a journalist, because it limits their ability to speak publicly.The papers cover robotics, alignment, and how to deliver kitty cat pictures more efficiently, but one paper in particular—awarded a top prize at the conference—grabbed me by the throat. A coalition from Stanford, the Allen Institute, Carnegie Mellon, and the University of Washington presented “Artificial Hive Mind: The Open-Ended Homogeneity of Language Models (and Beyond),” which shows that average large language model converges toward a narrow set of responses when asked big, brainstormy, open-ended questions. Worse, different models tend to produce similar answers, meaning when you switch from ChatGPT to Gemini or Claude for “new perspective,” you’re not getting it. I’ve warned for years that AI could shrink our menu of choices while making us believe we have more of them. This paper shows just how real that risk is. Today I walk through the NIPS landscape, the other trends emerging at the conference, and why “creative assistance” may actually be the crushing of creativity in disguise. Yay!
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OpenAI Declares "Code Red" — And Takes Aim at Your Brain
According to the Wall Street Journal, Sam Altman sent an internal memo on Monday declaring a company-wide emergency and presumably ruining the holiday wind-down hopes of his faithful employees. OpenAI is hitting pause on advertising plans, delaying AI agents for health and shopping, and shelving a personal assistant called “Pulse.” All hands are being pulled back to one mission: making ChatGPT feel more personal, more intuitive, and more essential to your daily life.The company says it wants the general quality, intelligence, and flexibility to improve, but I’d argue this is less about making the chatbot smarter, and more about making it stickier.Google’s Gemini has been surging — monthly active users jumped from 450 million in July to 650 million in October. Industry leaders like Salesforce CEO Marc Benioff are calling it the best LLM on the market. OpenAI seems to feel the heat, and also seems to feel it doesn’t have the resources to keep building everything it wants all at once — it has to prioritize. Consider that when Altman was recently asked on a podcast how he plans to get to profitability, he grew exasperated. “Enough,” he said.But here’s what struck me about the Code Red. While Gemini is supposedly surpassing ChatGPT in industry benchmarkes, I don’t think Altman is chasing benchmarks. He’s chasing the “toothbrush rule” — the Google standard for greenlighting new products that says a product needs to become an essential habit used at least three times a day. The memo specifically emphasizes “personalization features.” They want ChatGPT to feel like it knows you, so that you feel known, and can’t stop coming back to it.I’ve been talking about AI distortion — the strange way these systems make us feel a genuine connection to what is, ultimately, a statistical pattern generator. That feeling isn’t a bug. It’s becoming the business model.Facebook did this. Google did this. Now OpenAI is doing it: delaying monetization until the product is so woven into your life that you can’t imagine pulling away. Only then do the ads come.Meanwhile, we’re living in a world where journalists have to call experts to verify whether a photo of Trump fellating Bill Clinton is real or AI-generated. The image generators keep getting better, the user numbers keep climbing, and the guardrails remain an afterthought.This is the AI industry in December 2025: a race to become indispensable.
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Trump’s New Big Tech Era, TSMC’s Shift, and the A.I. Conferences Steering 2026
It’s Monday, December 1st. I’m not a turkey guy, and I’m of the opinion that we’ve all made a terrible habit of subjecting ourselves to the one and only time anyone cooks the damn thing each year. So I hope you had an excellent alternative protein in addition to that one. Ours was the Nobu miso-marinated black cod. Unreal.Okay, after the food comes the A.I. hangover. This week I’m looking at three fronts where the future of technology just lurched in a very particular direction: politics, geopolitics, and the weird church council that is the A.I. conference circuit.First, the politics. Trump’s leaked executive order to wipe out state A.I. laws seems to have stalled — not because he’s suddenly discovered restraint, but maybe because the polling suggests that killing A.I. regulation is radioactive. Instead, the effort is being shoved into Congress via the National Defense Authorization Act, the “must-pass” budget bill where bad ideas go to hide. Pair that with the Federal Trade Commission getting its teeth kicked in by Meta in court, and you can feel the end of the Biden-era regulatory moment and the start of a very different chapter: a government that treats Big Tech less as something to govern and more as something to protect.Second, the geopolitics. TSMC’s CEO is now openly talking about expanding chip manufacturing outside Taiwan. That sounds like a business strategy, but it’s really a tectonic shift. For years, America’s commitment to Taiwan has been tied directly to that island’s role as our chip lifeline. If TSMC starts building more of that capacity in Arizona and elsewhere, the risk calculus around a Chinese move on Taiwan changes — and so does the fragility of the supply chain that A.I. sits on top of.Finally, the quiet councils of the faithful: AWS re:Invent and NeurIPS. Amazon is under pressure to prove that all this spending on compute actually makes money. NeurIPS, meanwhile, is where the people who build the models go to decide what counts as progress: more efficient inference, new architectures, new “alignment” tricks. A single talk or paper at that conference can set the tone for years of insanely expensive work. So between Trump’s maneuvers, the FTC’s loss, TSMC’s hedging, and the A.I. priesthood gathering in one place, the past week and this one are a pretty good snapshot of who really steers the current we’re all in.
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AI Distortion Is Here — And It’s Already Warping Us All
It’s a warning siren: people seeing delusions they never knew they had amplified by AI, a wave of lawsuits alleging emotional manipulation and even suicide coaching, a major company banning minors from talking freely with chatbots for fear of excessive attachment, and a top mental-health safety expert at OpenAI quietly heading for the exit.For years I’ve argued that AI would distort our thinking the same way GPS distorted our sense of direction. But I didn’t grasp how severe that distortion could get—how quickly it would slide from harmless late-night confiding to full-blown psychosis in some users.OpenAI’s own data suggests millions of people each week show signs of suicidal ideation, emotional dependence, mania, or delusion inside their chats. Independent investigations and a growing legal record back that up. And all of this is happening while companies roll out “AI therapists” and push the fantasy that synthetic friends might be good for us.As with most of what I’ve covered over the years, this isn’t a tech story. It’s a psychological one. A biological one. And a story about mixed incentives. A story about ancient circuitry overwhelmed by software, and by the companies who can’t help but market it as sentient. I’m calling it AI Distortion—a spectrum running from mild misunderstanding all the way to dependency, delusion, isolation, and crisis.It’s becoming clear that we’re not just dealing with a tool that organizes our thoughts. We’re dealing with a system that can warp them, in all of us, every time.
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Insurers Are Backing Away From A.I.—and That Should Scare You More Than Any Sci-Fi Predictions
Today I dug into the one corner of the economy that’s supposed to keep its head when everyone else is drunk on hype: the insurance industry. Three of the biggest carriers in the country—AIG, Great American, and W.R. Berkley—are now begging regulators not to force them to cover A.I.-related losses, according to the Financial Times. These are the people who price hurricanes, wildfires, and war zones… and they look at A.I. and say, “No thanks.” That tells you something about where we really are in the cycle.I also walked through the Trump administration’s latest maneuver, which looks a lot like carrying water for Big Tech in Brussels: trading lower steel tariffs for weaker European tech rules. (The Europeans said “no thank you.”) Meanwhile, we’re still waiting on the rumored executive order that would bulldoze state A.I. laws—the only guardrails we have in this country.On the infrastructure front, reporting out of Mumbai shows how A.I. demand is forcing cities back toward coal just to keep data centers running. And if that wasn’t dystopian enough, I close with a bleak little nugget from Business Insider advising Gen Z to “focus on tasks, not job titles” in the A.I. economy. Translation: don’t expect a career—expect a series of gigs glued together by hope.It’s a full Monday’s worth of contradictions: the fragile hype economy, the political favoritism behind it, and the physical reality—pollution, burnout, precarity—that always shows up eventually.
The Rip Current covers the big, invisible forces carrying us out to sea, from tech to politics to greed to beauty to culture to human weirdness. The currents are strong, but with a little practice we can learn to spot them from the beach, and get across them safely.
Veteran journalist Jacob Ward has covered technology, science and business for NBC News, CNN, PBS, and Al Jazeera. He's written for The New Yorker, The New York Times Magazine, Wired, and is the former Editor in Chief of Popular Science magazine.
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