We live in an era where wars are fought not just on battlefields, but also on our screens, in our minds and through the narratives we are led to believe. Narratives are influencing perception while missiles destroy infrastructure. What happens when the war for truth becomes more dangerous than the actual battle itself? Who’s controlling the narrative?

When wars end, the fighting over what they meant begins: who won, who was to blame and who can be trusted to keep the peace. These questions are settled less on the battlefield than on screens, in feeds and in group chats. For a Middle East emerging from the war that began on February 28, that contest may decide whether any new security order holds.

The region is now asking what comes after deterrence. That question brought policymakers, military leaders and researchers from the United States, Europe, Asia and the Gulf to the TRENDS 6^th Annual Conference, held in Abu Dhabi and organized by TRENDS Global, in collaboration with its global offices. The answer cannot be measured only in missiles and alliances. Information resilience should be treated as security infrastructure, planned and funded like air defense, not managed as public relations.

What happens when the war for truth becomes more dangerous than the actual battle itself?

The struggle over perception can now matter as much as events on the ground. That is no longer hyperbole. In any crisis today, governments, media outlets, political movements and non-state groups compete in real time to define what is happening. Disinformation, coordinated propaganda and now content generated by artificial intelligence (AI) mean a false account can reach millions before an official one is drafted.

As former BBC correspondent Karen Allen put it at the conference, “Now in an instant, I’m able to influence millions of people,” and algorithm manipulation is what we are increasingly seeing.

This year’s war showed how real that is. Within days of the first U.S.-Israeli strikes on Iran, an AI-generated video of Dubai’s Burj Khalifa on fire, with crowds fleeing, was viewed tens of millions of times, according to BBC Verify. Fabricated images of damaged U.S. facilities in the Gulf spread just as fast, some posted by Iranian state-linked outlets. UAE Minister of State Noura Al Kaabi later described the attacks on the country as coming “from the sky and behind our screens.” Her government’s answer was to treat “fake news and misinformation as a security threat.”

A more damaging false story was not a single video. It was the idea that the Gulf was a party to the war. The UAE did not want this war and said so. On March 3, Minister of State Reem Al Hashimy said the UAE did not “seek to expand the circle of confrontation,” that it had “repeatedly confirmed” its territory could not be used for any military operation against Iran, and that “returning to the negotiating table is the only rational way forward.” The attacks continued anyway. Reuters reported, citing UAE defense figures, that 186 ballistic missiles and 812 drones were fired at the country in the first days of the conflict.

Information resilience should be treated as security infrastructure, planned and funded like air defense, not managed as public relations.

Tehran sought to blur that record, framing strikes on Gulf cities as retaliation against American aggression. Its foreign minister, Abbas Araghchi, told NBC News that Iran had “not attacked our neighbors,” only “American bases,” and called the hotels hit in Dubai “collateral damage.” Countering that narrative does not require propaganda of our own. It requires putting the record in front of the world quickly and repeatedly: the UAE’s public calls for restraint before the war, its refusal to let its territory be used against Iran, and the hundreds of missiles and drones fired at it, most of which it shot down. Facts published fast, through verified channels, in Arabic, English and Farsi, are harder to bury than corrections issued too late.

Even after a war ends, the threats do not disappear; they simply take different forms. Ceasefires and reconstruction depend on public trust. If populations come to believe that the peace is a betrayal, or that a neighbor cannot be trusted, no deterrence framework or security pact will survive contact with domestic politics. Spoilers understand this. Their cheapest weapon is a story.

Seen from the Gulf, the lesson of recent years is that speed and credibility beat silence. Crisis communication is not a side function of security. When official channels inform the public quickly, consistently and honestly, rumors have less room to grow. When they hesitate, someone else fills the gap.

None of this is simple. Governments everywhere are still working out where countering disinformation ends and controlling speech begins, and that debate should stay open. But the common ground is wider than it looks: a society cannot be secure if it cannot tell what is true.

The harder test comes now. After a war, influence campaigns shift from shock to slow erosion: relitigating who was to blame, questioning whether Gulf governments can protect their people, and setting neighbors and communities against each other. Young connected audiences are the main target. They are also the best defense.

Protecting our societies from that influence does not mean closing them. It means official channels fast and credible enough that people turn to them first. It means platforms held to clear rules on labeling AI-generated conflict content, as X began to do in March. And it means a generation of young Emiratis and Gulf citizens equipped to verify what they see and able to tell the region’s story themselves rather than leaving it to others.

The harder test comes now. After a war, influence campaigns shift from shock to slow erosion.

This is not only a Gulf problem. The campaigns aimed at audiences in the Gulf also shape how Washington and Brussels understand the region. The UAE and its partners already work closely on defense and intelligence. Detecting and exposing cross-border influence operations belongs on that shared agenda as a joint effort between governments, platforms and researchers.

Diplomacy, investment, and deterrence will rebuild the region’s security. Whether that security holds will depend on something harder to measure: what people across the region believe about each other, and about who protects them. For the UAE, winning that argument with facts is not public relations. It is part of keeping the country safe.

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Najla Al Midfa is an Emirati researcher at TRENDS Research & Advisory, a company under TRENDS Group. Her research focuses on geopolitics, international relations, economic diplomacy and regional security, with a particular interest in the UAE’s foreign policy and strategic partnerships. She holds a master’s degree in Global Affairs and Diplomatic Leadership from the Anwar Gargash Diplomatic Academy, where her thesis examined the UAE’s economic diplomacy through its Comprehensive Economic Partnership Agreement strategy.

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Sources

• Sixth Annual TRENDS Conference 2026 kicks off on October 12 — WAM (Emirates News Agency), September 2026
• TRENDS 6th Annual Conference 2026 — Sustainable Security: programme and speakers — TRENDS Research & Advisory
• AI-generated Iran war videos surge as creators use new tech to cash in — BBC Verify, March 7, 2026
• Factbox: Iranian missiles and drones fired at Gulf countries — Reuters (republished by Al-Monitor), March 3, 2026
• X suspends revenue sharing for undisclosed AI war videos — AFP, March 3, 2026
• UAE urges the US, Israel and Iran to return to the negotiating table — Euronews, March 4, 2026
• Fake news treated as security threat during Iran war, says UAE minister — The National, September 15, 2026
• NBC News, “Iran’s foreign minister denies seeking war with neighbors,” March 2026. https://www.nbcnews.com/world/iran/irans-foreign-minister-denies-seeking-war-neighbors-rcna261954

To experiment with AI’s predictive skills, I let Codex loose on a fantasy team. It tried to bench Erling Haaland at first, but it soon learned the error of its ways.

It feels like the skies above our AI-frenzied world have darkened in the past month. Employees at Anthropic and Google started quitting, citing fears that the AI was spiraling out of control. After a string of agents started hacking websites, researchers used AI to discover vulnerabilities in critical systems, leading to large swaths of the web going dark last week and giving rise to a scary term: Black October. At the same time, as it continued to ramp up AI spending, Microsoft offered buyouts to 60,000 employees — over a quarter of its workforce — and economists once again warned of a bubble.

Yet, a lot has happened recently to make AI genuinely useful for more people. AI Agents are getting better and can now make restaurant reservations for you. Walmart made it possible for agents to shop on behalf of humans, a bold move since Amazon banned the practice. Apple announced an AI-ready home display that can turn on your lights. And let’s not forget that AI is also helping scientists find cures for formerly incurable diseases and mathematicians solve previously impossible problems. 

It’s hard to reconcile the incongruity between the recent bad news and good news. For most of us, the state of AI is anxiety-inducing — especially when it comes to our livelihoods. According to a Pew Research Center study published in August, 71 percent of Americans think AI will lead to fewer jobs in the next two decades. That figure is up 7 points from where it was two years ago. Sure, in the best-case scenarios, AI could erase inefficiencies at work, streamline our daily lives, cure diseases, and generally improve the human condition. 

But what if you are the “inefficiency” at work that gets erased?

That tension is at the heart of Ethan Mollick’s latest book Co-Existence: The Next Phase of AI. If there is such a thing as an AI sage, it would be Mollick, an associate professor at the Wharton School and faculty director of its Generative AI Labs. To the nearly half a million subscribers to his Substack newsletter, One Useful Thing, he delivers semiweekly updates from the jagged frontier of the technology’s development. His message in any medium is resoundingly clear: You need to use AI in order to understand it. And to get the most out of using it, he argues that you have to accept that AI is not going away; it’s only going to become more important. 

That ethos doesn’t make the existential threats of AI any less daunting, but that’s not the point. Unless you’re an early Anthropic employee or a United States senator, there’s probably not much you can do directly to rein in AI’s potential harms. But you can, according to Mollick’s worldview, decide how the technology could fit into your life and think about how you fit into an AI-dominated future. 

I recently spoke with Mollick about his new book, what life and work might look like in the agentic AI era, and what it means to be an artisan when even knowledge is industrialized. His theories about living with AI are meant to help you navigate the future, regardless of the latest forecast. This interview has been lightly edited for length and clarity.

We’re entering a new era for AI, and the vibes are different. AI agents are something that many of us will encounter, interact with, and maybe even embrace. I’ve always known you as someone who jumps on the cutting edge of this technology to figure out what it can do. What do you think most people don’t understand about the next generation of AI?

I really think people haven’t internalized what agents do. Agents mean many things, and we can talk about personal agents, like Muse. But the fact that the problems that plagued working with AI agents before — you had to guide them each step of the way, they made mistakes, hallucinated constantly — that’s kind of gone. You can regularly get hours, days, weeks of work out of a system. 

It’s not just a theoretical thing anymore. I talk to coders all the time who are a hundred times or more productive than they were before. And in other fields, we’ve kind of moved past the theoretical discussion about AI being, “This is going to be a big deal,” to, “It’s here.” From a whole kind of co-intelligence perspective, we’ve gone from, “Here’s how we use AI and work with a chatbot back and forth,” to, “These systems are now doing real work in ways that matter to real people and are reshaping real fields for better or worse.” And if you’re used to using AI a year ago, if you’re not paying for one of these systems, it’s really easy to have lost track of what’s going on.

What about the practical, everyday ways that AI is disrupting our lives? And what do you think are the limits of that disruption?

So outside of the job world and homework cheating, I think life has changed only a little bit for people, partially because these systems were kind of complicated to use and you had to decide what you were using them for. But I think the advent of personal agents, like Muse and Dot, are going to lead to a very rapid change in a lot of ways.

Most people I know who aren’t experts who use these systems, like my parents, are using these things spontaneously. They’re finding that once you know how to prompt the AI to do something, it can do things spontaneously and come back to you because it has your email and everything else. Just as one example, I was unable to figure out how to cancel my standing $8 a month wifi subscription from my airline, and I was like, figure this out. And it went to customer service, joined chats, then I have no idea what it did, but now I don’t have a subscription to wifi anymore, thank goodness. 

“I deeply worry that if I de-skill myself entirely, I won’t even know how computers work.” 

So there is this sort of lowering friction piece that’s super interesting, with good and bad elements to it. The bad side of lowering friction is both that every article gets written by AI, so there’s no human thinking in it anymore, and that companies don’t want 10,000 customer service agents coming to them demanding new things. So I think we’re just on the edge of seeing the mass change in everyday life. Right now, AI is a really good second opinion on everything. As agents become more popular, they start to take action.

How do you know when to let AI do the work, though? We know that offloading certain tasks to AI can make you worse at doing those kinds of tasks in the future. How do you take advantage of AI’s ability to do drudgery but also hold onto your own expertise? 

If there’s a personal theme underlying Co-Existence, it’s that one. That is an incredibly hard choice to make, and we’re historically very bad at making it. 

Students are the No. 1 case because they’re willing to offload homework because homework sucks and because the incentives for doing any piece of homework are terrible. But overall we need to do it to learn. So people offload that, but even if you’re trying to do the right kind of thing, like using AI only to help you learn and not to replace learning, it turns out that when chatbots are in assistant mode, as opposed to using them as a tutor, it feels like you’re learning even though you’re not. You feel like you’re in the loop even though you’re not. And so that assumes that we both know we want to offload and we do it intelligently and that we do it in a way that helps our long-term gain.

I am worried about us being able to do that. You have to draw lines for yourself about what skills matter to you or not, and you have to be thoughtful in a way that we’re usually not about what we’re giving up and what we’re not. Technology’s designed for us to give up stuff. We don’t walk 50 miles a day anymore in forced marches. I don’t know how to weave clothes. There’s a lot of stuff I’m very happy to not know: how to maintain my computer in some ways, even though that’s dangerous. I let Codex scan for security issues because it does a better job than me faster. But I deeply worry that if I de-skill myself entirely, I won’t even know how computers work. 

So I don’t have an easy answer, but I think that that will be the defining question for most people in their career paths right now and their lives: What do I give up? I think we can be too sentimental about things that we’re giving up. It’s okay, but we don’t know the full chain of consequences. I think that struggle is going to be central to a lot of people’s experience. I wish I had an easy answer, but now that AI can do so many things, de-skilling is a real problem at this point.

We’re living through a huge transformation. That’s increasingly clear. Besides losing their jobs, a lot of people are scared of losing the sense of what makes them human and what makes them valuable. How do people hold onto that in the years to come?

There’s a transformation happening, and for some people, the work will get more satisfying. There’s a lot of coders who did not like writing lines of code, but they did like summoning software and figuring out what they wanted to build. Their lives are much better because the AI does all the tedious work. They can command things to be built, and it’s so much more exciting than it was before. It lets people who didn’t code start to do incredible coding projects. So on one hand, that’s deeply freeing of the kinds of work that we did. On the other hand, there are people who love writing those lines of code and that’s gone now. You’re a hand-weaver in a world of power looms. Your stuff might be elegant and beautiful, but it is not going to last in a world where industrialization happens.

Industrialization versus craft is a way to think about this. There’s a lot of craft that we’ve grown to really appreciate, like the handcrafted sentence. Those things will be under threat from the logic of industrialization, which is that we need to do more of it. I think that there’s going to be a shift. There’s satisfying work to do, but I think a lot of what was satisfying human work will be under pressure to disappear, because you took pleasure in something that was not automatable, but now is.

We’ve been through this in industrial revolutions before. This is happening at a very large scale to intellectual work, where craft was a very important part of what we did. Mathematics was craft, software engineering was craft. I think that we’ll be under pressure to produce more of it, which is what industrialization’s about, even if that destroys the value of doing this as a person. You get paid to do it now, but you’re not getting the same value you did before.

“We’re no longer in a place where AI is going away.”

I think we’re going to find lots of crises of meaning. Some people are going to find huge amounts more meaning in their work, either because the work itself is now much more interesting. Work is a lot of crap, too. We can say great things about it, but people spend a quarter of their work life saying they’re bored. It’s not like this was a great job for everybody. So some people will have much more excitement in craft. Some people will have it extracted out of their job, and it’s all going to be happening at once. I know it’s not a satisfying answer, but that’s what’s happening.

Forgive me for saying so, but that was an anxiety-inducing answer. It’s an anxiety-inducing time. I wonder what advice you have for us anxious people?

I think anxiety is real, and there’s different levels of anxiety. We’re going through a wrenching change, or we will be going through one that we’re on the edges of now. There is also existential risk about whether AI will kill us all, where we clearly need more regulation. The answers are unclear. Smart people seem to think that that’s a real danger. It’s hard to know. But leaving that aside, there’s anxiety about our own transformation, our jobs. I mean, the industrial revolutions worked out great in the end, but during it was the time of Marx and anarchists and Dickens writing about London. There’s a transition we have to go through here.

I don’t think we can pretend it’s not happening, and I see a lot of people taking comfort in the idea that maybe this all will collapse and AI will go away. Even if there was a bubble financially, we’re no longer in a place where AI is going away or stopping development. I worry a lot about people doing that. Once you face that, though, I find people often reconstruct meaning in very exciting ways. Thinking about what more you can do and where you find joy in this is actually quite exciting. So I think that anxious optimism is a reasonable place to be.

What I worry about is sticking your head in the sand saying, “I’m not going to learn AI. This will go away. I’m going to pretend it’s not happening.” I mean, I wish I could give you that option. I think there’s a lot of people who wish we could slow things down or turn a dial down, but there’s also a lot of exciting things. There’s a lot of hard problems in the world that are unsolved.

If you lean into the positive pieces, you can ask how we mitigate risk but also think about how we can build a better world. Part of what makes me nervous is people sitting out that second question and just filling up with anxiety rather than believing we have a tool that can rebuild things. How do we rebuild a better world for journalism or for nonprofits or whatever it is? I think it’s a reasonable question to ask, and I worry it’s asked too little.

One of England’s top judges, Geoffrey Vos, believes that AI could adjudicate plenty of civil cases. The question, he says, is where the line should be drawn.

As agents go mainstream, some publishers are hoping that people will pay for content tailor-made for AI—not humans.

We’re living through an AI-fueled “Black October,” and things are changing fast. Hackers are using AI to breach countless companies. AI tools have uncovered security flaws that could leave 70 percent of all websites vulnerable. Governments are scrambling to secure their sites. Banks, too. And because cyberhacks can hurt supply chains, some longtime AI watchers are going full prepper, stocking up on food, cash, and more.

In the center of this story is Anthropic, one of the world’s leading AI companies, which was explicitly founded on the promise that it would be a “good guy” company in a world of dubious tech giants.

Anthropic says all the latest developments are very serious. Its security chief wrote last week that things are “going to get a lot worse before they get better.” Two weeks ago the company warned that AI models could soon self-replicate on the internet-connected devices in your home, like smart fridges and robot vacuums. And its co-founder now says “the singularity” — when AI systems speed up technical progress in a way that’s hard for humans to comprehend — “is here.”

You might think, given its view of the risks, that Anthropic would be pumping the brakes on its cutting-edge AI progress. Just the opposite. Anthropic filed for a blockbuster initial public offering on Monday, chasing a valuation of $2 trillion even as it warns in the IPO filing that AI could “pose catastrophic or existential risks to humanity.” Every day, it is racing toward recursive self-improvement (RSI), where AI models are smart enough to build the next, even smarter AI models by themselves. 

How does Anthropic justify that?

As its CEO, Dario Amodei, reminded the world last week, he built the company on one big bet: that instead of driving a race to the bottom, where companies skimp on safety in their rush to beat competitors in the market, Anthropic could actually catalyze a “race to the top.” 

The idea is that if Anthropic proves it can build AI that’s both powerful and safe, the market will expect both — so other AI companies will then feel compelled to compete on safety, too. That may sound nice in theory, but it means Anthropic has to keep building ever-more-powerful AIs.

“The forces that drive the race to the top are hugely more effective if the company practicing them is at the frontier,” Amodei wrote. “And looking at that strategy as a whole, I’m proud of our track record and stand by it.”

In other words, Amodei is sticking to his bet. 

But Amodei is gambling with, by his and his company’s own telling, the future of humanity. If AI goes wrong, it could lead to our gradual disempowerment, a galling concentration of power, or even complete extinction.

So there’s a very basic question that the public deserves a good answer to right at this pivotal moment: What is the evidence that Anthropic’s stated strategy — compete at the frontier so as to drive a “race to the top” — is actually successful overall?

From the outside, it looks like Anthropic has done more, on balance, to drive a race to the bottom. (Disclosure: Future Perfect is funded in part by the BEMC Foundation, whose major funder was also an early investor in Anthropic; they don’t have any editorial input into our content.)

In fact, part of the problem may be that Anthropic continues to treat this as a classic arms race. Specifically, the company seems to model it as a prisoner’s dilemma: If Anthropic stopped building more powerful AI, another player — whether it’s China, OpenAI, or another company — would just build it anyway. In this kind of dilemma, if the other player is going to defect, it’s rational for you to defect, even though nobody actually wants that outcome.

But what if this framing misses the point? 

Game theory can make a huge gamble seem sophisticated, while making the obvious alternative — just don’t build a doom machine — seem naive. Yet the fact that Anthropic and others are now racing toward RSI makes it much more likely that we could lose control of AI and start to see massive damage to our world. When the cost of defecting from safety is that you create a serious risk of catastrophic harm — or of all humanity, including you, going extinct — is that still a “rational” move? 

Instead of telling yourself that you can galaxy-brain your way through this with fancy enough game theory, maybe you’re better off just thinking of this as something much simpler: Russian roulette.

More and more leading voices in AI are starting to recognize that. 

“We should stop AI progress now, starting unilaterally with Anthropic and/or OpenAI stopping — and then broadening out as a second step to more AI companies and negotiations with China,” Geoffrey Irving, who was until recently the chief scientist at the UK AI Security Institute, told me. “Unilateral pauses can’t hold for long, but they are the right first step: When you’re doing a very dangerous thing, the correct action is stop, even if others are also doing dangerous things.”

Anthropic did not respond to a request for comment. 

The case that Anthropic has done more harm than good

Let’s be clear: The question is not whether Anthropic has done anything good on the safety front. It has. Standing up to the Pentagon, temporarily holding back access to frontier models, and publicly advocating for safer AI policies are a few examples, among others.

But the real question is whether the company’s “race to the top” strategy is working on balance — whether it’s net-negative or net-positive for safety. 

Nathan Calvin, the chief strategy officer at AI safety advocacy organization Encode, recently set off a firestorm among tech watchers, writing on X, “When I look at many notable actions that Anthropic has taken over the past year, that evidence seems most consistent to me with the view that Anthropic is primarily trying to win the race to superintelligence, and that other considerations (including safety) are fundamentally secondary.” Here’s his list of what Anthropic has done:

And this is all just in the past year. If we rewind the tape further back, we see Anthropic pushing back on a landmark bill to regulate AI. Rewind even further back, and we see indications that Anthropic’s core strategy may have been flawed from the start. According to Reuters, in late 2022, OpenAI CEO Sam Altman heard rumors that Anthropic was building an AI-powered chatbot. So he ordered his employees to ship an OpenAI chatbot first. That chatbot was called ChatGPT. We all know the rest.

The rivalry between OpenAI and Anthropic seems not only to have hastened the arrival of generative AI, but also to keep pushing release dates forward to this day. The two companies have been known to release new or cheaper models within hours of each other, each one keen to protect its market share. 

Even if you think Anthropic’s behavior was justified in 2022 because publicly demonstrating the risks of AI also demonstrates the need to regulate AI — a common claim within the company and AI discourse writ large — you have to ask: Is it still justifiable now, when AI has reached this level of power and sophistication?

Anthropic has indicated that it’s getting closer and closer to achieving RSI. In January, Amodei himself wrote, “I am concerned that LLMs are approaching (or may already have reached) the knowledge needed to create and release [biological weapons] end-to-end, and that their potential for destruction is very high. Some biological agents could cause millions of deaths.” And he wrote in September, “Given the accelerating rate of AI capability development, it’s my worry that in 6-12 months such a swarm could be capable of taking over the entire internet with a persistent botnet.”

But at this point, Amodei and his staffers are themselves perhaps the primary ones accelerating the rate of AI capability development.

“Anthropic seems to be doing the whole RSI thing more than anyone else, other than perhaps OpenAI,” Calvin told me. “And I just think that seems insane given their publicly stated views on the risks.” 

“I think people at Anthropic should reckon more with the fact that it seems like the modal outcome is that the largest impact that Anthropic will have had is dramatically accelerating the race to RSI,” he continued. “On the current trajectory, everything else they will have done and thought and ideals they had will be a rounding error compared to their contribution there.”

Anthropic should be willing to invite scrutiny on this point — and, if it believes it’s actually making the field safer than it otherwise would be, to show us the receipts. How? It could put before Congress a bill that actually strengthens safety, instead of weakening it. It could stick to its former Responsible Scaling Policy and get other companies to do the same, instead of jettisoning its commitments. It could influence other labs not to build RSI, instead of leading the charge.

In the absence of such evidence, the “race to the top” logic just doesn’t hold water.

What if Anthropic just…stopped?

Amodei has begun advocating for “pacing the frontier” of AI development. “We must slow the pace at which we improve the capabilities of AI models,” he wrote in September.

The catch is that Amodei’s plan to slow down is contingent on others agreeing to slow down too — other AI labs, to start with, and also other countries. But more experts are now saying that it would be better if a frontier company like Anthropic unilaterally stopped.

“I’m glad that he proposed that we pace, but like, now we have to actually do it — and it seems like he’s saying he’s not going to do it unilaterally,” Daniel Kokotajlo, a former researcher at OpenAI who became a prominent whistleblower, told me. “That’s not very helpful, Dario! You should lead. What’s all this about ‘racing to the top’ and ‘leading by example’ if you’re just waiting?”

Voluntary unilateral action by individual companies is of course no substitute for federal regulation and international treaties. But Irving argues that it’s the right first step, because if the companies wait for governments to rein them in, it may well be too late. Governments are notoriously slow. An individual company can act today.

There’s a perennial objection here: “But China!”

Yet the idea that we’re in a classic arms race with China has always been flawed.

For starters, AI is not just one thing with one purpose, like the atomic bomb. It’s a much more general-purpose technology, like electricity. So what matters isn’t simply who gets it first, but who uses it in which ways. Besides, if the harms from AI are massive, then those harms are relevant for the other party, too. The Chinese don’t want to see catastrophic harms to all of human civilization, either. So we shouldn’t write off the possibility of coordination.

Former Vox reporter Kelsey Piper recently wrote about a colloquium at Anthropic where one participant objected: A decade ago, Facebook considered acquiring the tech that would later power TikTok. But, facing pressure due to privacy and safety worries, the company passed. That didn’t end up protecting us from the scourges of a world with TikTok — all it did was hand China an early monopoly on the tech. Piper writes:

Was this a policy success? Did we want to repeat it?

We were obliged to grudgingly concede that it didn’t sound like a policy success. We did not want to repeat it. China might be no excuse for the U.S. labs to do reckless things, but it is a real consideration.

Our next step might be bilateral talks with China, then. But by the point where you agree that Anthropic’s plans might depend on bilateral talks with China, you’ve already conceded most of the steps of Anthropic’s worldview that seemed so much like madness 10 minutes ago: continue working on AI for now, try to negotiate a slowdown, but don’t abandon work at the frontier and all the advantages that come with it.

But TikTok is not a good analogy for RSI. The former may be a cesspool that rots our brains and amplifies ethnic hatred, but its dangers don’t compare to the dangers of RSI. The TikTok case may indeed be best approached as a classic prisoner’s dilemma. But with RSI, the potential downside is so catastrophic that anyone who proposes to save the world precisely by building the tech that endangers it is making a hell of a gamble on behalf of everyone else. At the very least, the burden of proof should be on them to prove their confidence is justified.

AI insiders often think those outside of their industry can’t possibly understand the technical, geopolitical, and moral complexities they’re facing. But commonsense morality is commonsense for a reason: It tracks intuitions that are usually right (such as, if you don’t want a doom machine, maybe don’t build a doom machine) and trains us to be appropriately skeptical of huge, counterintuitive bets to the contrary. 

Precisely because the AI landscape is a complex system — there are so many actors (including different AI companies and different governments), and actions from each can trigger actions from others in ways that are hard to predict — believing you’re smart enough to take highly counterintuitive actions and end up saving the world as a result is an extremely risky gambit. Instead, maybe it’s best to just do the straightforwardly right thing: Stop.   

To be clear, “stopping” doesn’t have to mean peeling back everything that’s been done in AI so far. The powerful AI systems that are already out there can’t be put back in the box. And we may need some AI to defend from the AI that’s already out there.

“I’m not saying shut down all of your data centers,” Calvin said. “But I’m saying that in particular, pushing the frontier on RSI and making it so that you’re going to be the company that is doing more fully autonomous development than anyone else in the world, does that actually make any fucking sense?”         

Increasingly, both AI insiders and the public are shouting no. 

Some insiders, perhaps aware that humanity is perfectly capable of shutting down overly dangerous tech development (we’ve done it before), are speaking out and quitting jobs at AI companies. At public gatherings, like the recent Pro-Human Assembly in Washington, DC, and the People’s AI Assembly in New York City, people are piling on the pressure to rethink the AI race. States are drawing up their own legislation to rein in the tech. And a single X post from Calvin got so much attention that no less than Amodei himself felt compelled to respond. The AI companies are being forced to pay attention. 

Attention may not be all you need, but it’s a start.

Anthropic’s S-1 filing is hundreds of pages long—and it leaves out quite a few financial details. “Anthropic owes investors more information,” one analyst tells WIRED.

Anthropic thinks “closing the loop” is the best path to AI triumph—and a recipe for “existential” threats to humanity.

BRUSSELS — Ursula von der Leyen’s push for a sweeping overhaul of the European Commission moved closer to fruition on Monday, as a group of external advisers handed over a report that will help shape the institution’s biggest administrative shake-up in two decades.

The report, drawn up by a high-level group led by former Commission Secretary-General Catherine Day, marks a new stage in the so-called large-scale review — an exercise intended to make the Commission more efficient, streamline its sprawling bureaucracy and turn it into a more attractive employer.

“Now we’re reaching the second phase,” von der Leyen said at the handover, referring to the conclusion of an initial phase that involved 15 internal workstreams and contributions from thousands of Commission staff.

“We need to be able to act effectively and to act quickly,” she said about the needed changes in the EU Executive’s machinery. “That means simpler procedures, clearer structures, better cooperation across departments so that our colleagues can focus their efforts where it makes the greatest difference.”

The external group, consisting of Day and eight other experts with experience in national administrations and international organizations including the OECD and OSCE, put forward nine interrelated recommendations aimed at making the Commission more agile and better equipped to adapt to future challenges.

Among its main proposals is a shift away from working in siloed departments toward greater collaboration across directorates-general, including through cross-DG portfolios.

This part of the exercise is politically sensitive. Behind the push to modernize the Commission lies the prospect of a far-reaching reorganization of its departments, potentially redrawing the responsibilities of powerful directorates-general that oversee billions of euros in EU spending.

As POLITICO first reported, several major Commission departments face an uncertain future under plans to overhaul how the bloc manages and distributes EU funds, raising the prospect of mergers or other structural changes.

Among the departments potentially affected is the Directorate-General for Regional and Urban Policy (DG REGIO), which oversees cohesion policy funding, accounting for almost a third of EU spending. Other departments facing uncertainty include the Directorate-General for Agriculture and Rural Development (DG AGRI), responsible for Common Agricultural Policy money; DG EMPL, which oversees employment and social funding; DG MARE, which handles fisheries funding; and DG RTD, responsible for research and innovation.

The group also called for a stronger Secretariat-General to act as a strategic center driving results, and for a human-centered approach to artificial intelligence to simplify administrative processes and modernize the institution’s operations.

But the release of the report on Monday does not mean that any restructuring decisions have been taken. Day’s report will feed into a wider review overseen by Budget and Public Administration Commissioner Piotr Serafin, who is tasked with presenting final recommendations to von der Leyen by the end of 2026.

Serafin said at the handover that the external assessment, combined with feedback from Commission staff, provided a “mandate to go for far reaching changes.”

Day, for her part, said the Commission had already demonstrated a willingness to reform, pointing to the wealth of ideas emerging from within the institution.

“The work done on the large scale review has shown that there is a broad coalition for change right across the Commission,” she added.

A separate internal process produced an initial set of recommendations in July, drawn up by Commission officials. Those proposals were intended to kick-start a broader discussion within the institution rather than serve as final decisions.

Any major reshuffling of the Commission’s structure, however, is likely to take considerably longer.

Speaking in July to a small group of journalists, including POLITICO, Serafin acknowledged that structural reforms would be closely tied to negotiations on the EU’s next long-term budget, known as the Multiannual Financial Framework, which will determine how EU spending is organized from 2028 to 2034.

He indicated at the time that he did not expect decisions on major structural changes before those budget negotiations are concluded.

For now, Day’s findings will provide another input into Serafin’s final proposals, bringing von der Leyen one step closer to deciding how far she wants to go in reshaping the institution she leads.

Anthropic on Monday filed documents ahead of a blockbuster IPO that offers insight into the company’s financials, risk factors, and views on the future of AI.

LONDON — Liz Truss claims the U.K. would have managed successful missions to Mars within years — if only her 49-day premiership hadn’t been cut short.

The assertion comes in the former British prime minister’s new book “Bank Job,” which was published Monday and claims to explain “how the Bank of England broke the bond market and brought down the government” when her mini-budget in 2022 precipitated market turmoil.

In its closing chapter, the book paints a vivid picture of what Truss believes life in 2040 would be like if her policies had been given a chance to bed in. “Several missions to Mars have now been launched from Britain’s space port,” Truss’ book imagines.

The ex-PM also opts for some more grounded policy dreams.

She envisages a 2040 in which “there are now no European Union laws in Britain,” a “permissive regime for artificial intelligence” is in place, and tumbling energy costs and faster planning timelines have helped make the U.K. a leader in AI.

“Bitcoin received tax treatment consistent with its status as a form of money for commercial purposes,” she imagines. “No central bank digital currency was introduced.”

Since leaving office after a revolt in her own party, Truss has dismissed claims her economic decisions — which included a huge energy bills bailout and tax cuts funded by fresh borrowing — were responsible for crashing the pound.

She has instead pointed the finger at the central bank, the Treasury and the Office for Budget Responsibility watchdog, accusing them of working against her. Her new book takes direct aim at the Bank of England, which proposed to sell £80 billion of gilts before the mini-budget, although delayed that sale amid market turmoil.

Truss lost her House of Commons seat at the 2024 general election, and has since been involved in launching the Conservative Political Action Conference in Britain.

Jayden, Sam, and Zack are eagerly pitching editors on reported stories and investigative features. The catch? They're all AI agents.

Mark Carney’s pursuit of a global alliance of middle powers has a Europe problem.

Canada’s prime minister wants to help build a new world order that can counterbalance the power of the United States and China. But his vision depends on a new relationship with a Europe that doesn’t see itself as a middle power at all. 

European Commission President Ursula von der Leyen has a different vision: a Brussels-centered bloc that extends the EU’s economic and geopolitical influence, starting with Canada. The idea, according to senior European lawmaker Siegfried Mureșan, is to create an opportunity for the EU to become the “global center of gravity for liberal democracies.” 

The competing visions will be tested this week when Carney and von der Leyen meet in Montreal for a summit intended to chart a new course for transatlantic relations. Both want to demonstrate they can prosper in a world upended by U.S. President Donald Trump. But they have different ideas about their curious new alliance — and face political resistance that could limit how far the partnership can go. 

Von der Leyen’s offer of “associate membership” in the EU surprised officials on both sides of the Atlantic. Four diplomats told POLITICO they were not consulted before she floated the idea in the State of the Union. The officials added that they don’t understand the label, which has yet to be defined. Germany has since led pushback on the plan.

“We’ve definitely put the cart before the horse,” one of the diplomats said. “We’re announcing something and then figuring out how to flesh it out.”

Trump called the membership idea “laughable,” but also threatened “very serious tariffs” should it come to be — a reminder that leaders in pursuit of Washington workarounds must avoid provoking the White House. 

The leaders are under pressure to leave Montreal with more than a liberal democratic photo-op. For starters, they need to decide what “associate membership” means — and disarm resistance in the EU capitals blindsided by von der Leyen’s plan.

Canada’s Ambassador to the EU Jonathan Wilkinson told POLITICO last month that people got too hung up on a label that was revealed prematurely. Carney called the Canada-EU relationship an “alliance for the future” when he addressed European lawmakers in Strasbourg.

Wilkinson said the Canada-EU project will show other democratic nations how to deepen partnerships. “It ties into very much what [Carney] talked about at Davos — and after Davos.”

Carney, von der Leyen and European Council President António Costa have two days to chart what’s next while American foreign policy continues to stress test geopolitical relationships in midterm campaigns that will shape Trump’s last two years in office.

The economic divide 

Ottawa considers the EU an obvious partner in its push to diversify trade away from the U.S. There’s already a free-trade agreement that both sides view as being underutilized. 

Leaders gathering in Montreal this week will celebrate the 10th anniversary of the Canadian-EU trade agreement, nicknamed CETA. But nine EU member countries have yet to ratify the deal, underscoring the challenge of turning rhetoric into reality. 

“We have shared challenges and many more shared opportunities,” Canadian International Trade Minister Maninder Sidhu told reporters last week in Dublin, where he was invited to participate in an informal meeting of EU trade ministers, a preview of what a more integrated Canada could look like. “Canada wants to be Europe’s most reliable partner.”

Sidhu said CETA utilization rates in EU member countries range from 60% to 80%, making a point about room for improvement and perennial challenges. “We know there’s room to grow.”

Von der Leyen’s associate membership plan “has been coldly received by member states,” a senior EU official said. “It [the summit] is more about what we do, how we can use the real potential of the CETA agreement.” CETA has been provisionally in force since 2017.

Trade talks between Canada and the bloc read like a lengthy transatlantic grievance list.

At a meeting between Brussels and Ottawa last October, the EU complained about Canadian taxes it says disproportionately hit European carmakers, opaque cheese-import quotas, cumbersome rules on cosmetics and what it considers discriminatory provincial taxes and markups on European wines and spirits.

Canada, meanwhile, warned that the EU’s deforestation rules could burden its exporters, questioned the impact of Brussels’ carbon border tax and pressed for greater recognition of Canadian standards in areas including AI.

The senior EU official described the relationship as constrained by “irritants and unfulfilled promises” that must be resolved if the two sides are to make progress.

There are hurdles ahead. Even as Canada and the EU imagine a deeper economic and security partnership, both are pursuing industrial policies that could shut the other’s companies out of lucrative public contracts — death by compounded trade barriers.

Brussels has concerns about Ottawa’s “Buy Canadian” initiatives and their compatibility with the EU-Canada free trade agreement. “Some member states didn’t like the ‘Buy Canada’ thing from Carney,” the official added.

Canada is likewise uncertain whether its companies will qualify for the EU’s proposed “Made in Europe” preferences foreseen in a major industry bill that would seek to channel public procurement spending to European companies. The EU is divided over whether to extend those preferences to trusted trading partners, a topic that is expected to come up in Montreal.

Canadian business leaders recognize the domestic appeal of “Buy Canadian” in the face of Trump’s threats, but warn there will need to be concessions.

“It’s something that will have to be resolved in order to move the relationship deeper, particularly with respect to industrial cooperation or collaboration,” Mark Camilleri, president of the Canada EU Trade and Investment Association, told POLITICO.

Camilleri likened the 10-year-old CETA deal to a garden overgrown with weeds. “It pains me to see market access being eroded through Canadian and European preferences,” he said.

Pressure is on

European and Canadian leaders are under pressure to deliver wins this week that demonstrate that “non-hegemons” — a descriptor Carney used in his Davos speech — can survive and thrive in an age of great-power rivalry.

Canadians currently support closer ties with Europe. But the EU faces political headwinds of its own, from fraught budget negotiations within the bloc to right-wing populist movements that are picking up momentum in some of its biggest economies.

One likely deliverable is a new digital trade agreement. Talks launched in March and were still underway last week. But the agreement lacks substantive text on artificial intelligence, leaving the two sides to find other places to cooperate, potentially through the EU’s proposed Cloud and AI Development Act. That proposal seeks to reduce reliance on U.S. tech giants, raising the risk of a new row with Washington. 

The European Commission is also pushing for Canada to join Erasmus+, the bloc’s student exchange program, according to one EU official. Carney has already publicly expressed interest. 

But Brussels has bigger ambitions for the partnership. The EU is pressing Canada to increase its funding for Ukraine, a test of Canada’s willingness to take on more of the security burden. 

For von der Leyen, securing that commitment would be a win. So would leaving the summit with a pledge from Carney to explore her offer of an “associate membership” — or whatever they end up calling it.

Zi-Ann Lum reported from Toronto, Sebastian Starcevic from Brussels and Camille Gijs from Dublin.

There are some days when there’s so much that needs to get done, I daydream about having a clone of myself. Between paying bills, life admin like renewing my driver’s license, keeping up with doctor’s appointments, and planning meals, it’s a lot. And that doesn’t even begin to touch the work that goes into making a podcast or managing my social life.

This feeling of overwhelm resonates with Sari Azout. She’s a mom of three who works in tech. “There is just so much doing,” she told Explain It to Me, Vox’s weekly call-in podcast. “I wake up, and I have to do meal coordination and get my kids up for breakfast, coordinate carpools. Then a lot of work during the day, but there’s the email from the teacher, there’s the 20 group chats asking if you want to participate in this group gift. They don’t call it ‘the invisible load’ for no reason.’”

Silicon Valley says it has a fix for this kind of mental overload. They don’t want to clone us — at least not yet. But they do think they have the next best thing: AI agents. 

Azuot was skeptical when she first got an invite to try an agent, but she says she eventually came around on the technology after back-to-school shopping snuck up on her. She used her agent to get it done. “It blew me away,” she said.  “I remember that night coming home just feeling so calm and reading my son a book and feeling present. And I was like, ‘Wow, I actually was very cynical about something that is giving me more time for living.’”

Azout’s experience is, more or less, the sales pitch for AI agents: They’ll help you save time with everyday tasks, so you have more of it for what you want to do. But what are agents, exactly? Are they really all that? And what do we gain — and give up — when we use the technology?  

On this week’s episode of Explain It to Me, I spoke with Reece Rogers, a senior software reporter at Wired, to find out. Rogers says to think of agents as the next evolution of AI chatbots like Claude and ChatGPT. 

“I’d create this mental model of a tiny digital assistant that’s constantly searching the web, going through your email, and checking your calendar, trying to find ways it could proactively be helpful for you,” he explains. “Agents are more proactive. It’s scanning your email 24/7 and sending you a message, maybe highlighting a potential calendar conflict.”

Below is an excerpt of my conversation with Rogers, edited for length and clarity. You can listen to the full episode on Apple Podcasts, Spotify, or wherever you get your podcasts. If you’d like to submit a question, send an email to askvox@vox.com or call 1-800-618-8545.

What agents are out there right now?

At the start of this year, there was a tool called OpenClaw that really sparked this with early adopters in San Francisco, but now there are much more consumer-friendly versions, with one of the most notable being Meta’s Muse. 

There’s also a tool from OpenAI called Dots. But where Meta’s Muse is free to download, OpenAI’s Dots is still behind a $100/month paywall. 

You tried an AI agent for a recent story you wrote. How was that experience?

One personal example, to share something that I’ve actually been using agents for, is our couch. It’s broken, and finding a new couch has been a pain. We want a sleeper bed, but we want these specific colors. We have this specific budget. I’ve been using Meta’s Muse and OpenAI’s Dots to try to find a few different options for us. 

One interesting thing is that Meta’s Muse is connected to Facebook Marketplace. There are these really good integrations where I can give it all these details, and it found a few good couches that are only maybe a couple blocks from me. 

I really enjoyed OpenAI’s Dots experience as well. I spent about an hour talking to it on the phone, and the AI agent made a packet of all these different options I could find. Just this morning, it flagged that one of them is now 40 percent off. 

Is that how this tech is typically used?

Most people are using this as part of a workflow. I attach it to my email, I attach it to my calendar, and I’m using it as a personal assistant to organize my life. But people have been quite creative. 

One of the breakout uses for Meta’s Muse is people have been connecting their bank account statements and then using it to scan for subscriptions they might want to cancel. So it can be used in many different ways, though I will say I do not connect it to my own bank account for a myriad of reasons.

I’m not going to lie, the idea of giving any third party access to my bank information does not thrill me. I don’t love that concept.

That’s one of my biggest concerns about these AI agents: how much personal information we’re handing over to these large companies. 

When I tested Meta’s Muse, it wanted access to my email, my bank account, even my passport expiration details. The pitch is convenience, but Muse users are automatically opted in to having all of their interactions with Muse used to train Meta’s AI models. 

I would definitely recommend, if you’re sharing personal details, go into the settings and turn that off because you might be handing over even more information about yourself than you initially realize.

What is the privacy situation with all of this? We all have various apps where we don’t read and still click “I agree,” but this feels like it could be more invasive.

Yes, especially because it’s all about automation. If you’re automating things and it has access to all of your data, it could make mistakes and embarrass you in ways you might not even be thinking about. 

There was this one really interesting story of someone who had connected an AI agent to their work Slack in addition to their bank account. And their agent just automatically posted how much money was in their checking account for all of their coworkers to see. 

Oh no.

I would be mortified. So there are these kinds of mistakes that these AI tools can still make. If you’re interested in experimenting with them, I would be really thoughtful with how you’re setting up these tools as well as what kind of information you feel comfortable sharing.

“You can see in the marketing that these companies are trying to find some way to entice new users.”

How are these AI agents being marketed? AI is not popular right now. Just ask any politician who has a data center coming to their state. People are not loving it. How are they trying to sell this to the average person?

The AI backlash really is at a fever pitch right now. You could almost see that in the way that AI companies are trying to market these tools. They’ve really, really leaned into cuteness and into adorable mascots. 

Muse, if you haven’t seen its agent, looks like a mix between a Labubu and an Ewok. It’s very furry, very cuddly, very cute. OpenAI’s tools also have similar kinds of blobs with large eyes that might be a little endearing. 

I feel like companies are hearing this kind of feedback that people aren’t trusting AI right now, or maybe they have moral or ethical reasons they don’t want to use these tools. You can see in the marketing that these companies are trying to find some way to entice new users.

Do you think AI agents are ultimately going to worm their way into our lives despite how unpopular AI companies are?

I do think so. I think in a couple months, maybe when I go home from Christmas, I would not be surprised if my mom had an agent on her phone because it does feel like it’s breaking through to average people in the way that ChatGPT had a moment a few years ago. 

Even though there’s a lot of distrust for large companies like Meta, I think there are some appealing parts of this that will bring in millions of people. I do see this as the future of the internet.

When I think of the dream of the average person working in AI in Silicon Valley, it’s “We’re going to use AI. It’s going to free up the free time of so many people. Work is going to get done faster. You’re going to have more leisure time.”

Has that been the case for the people you’ve spoken with who are using this? Has it given them more free time to enjoy themselves or has it done something else?

You would think so, right? You would think that if people are automating these boring aspects of their life, that they would have more time to go touch grass, go see a movie, have some fun. But it does feel like that time just gets filled with other work, other productivity measures. 

While agents may be able to take some more annoying or tedious things off of your plate, I am not as optimistic that it’s going to give us this utopia or freedom where I’m always at the beach.

On the first day of its war against Iran, the United States killed 123 children when it targeted and struck an elementary school. 

The strikes, ultimately approved by humans, were facilitated by the US’s Maven Smart System, an AI-enabled software platform developed by Palantir Technologies that allows the military to aggregate, organize, and process battlefield data. Operators fed Maven intelligence classifying the elementary school as an Iranian military facility, and the system, in turn, marked it as one of the priority targets for day one of the war. Though the site was formerly part of a naval military base, it had been converted into an elementary school in 2017 and had remained one since. The intel handed to Maven did not reflect this.  

This mistake resulted in what some reporters have called “one of the single worst massacres committed by the US government since the Vietnam War.”

Such scenarios may become more common as militaries continue to deploy a once-theoretical technology — AI-assisted or autonomous weapons, capable of making both targeting and launch decisions on their own — on real battlefields around the globe. And they raise a troubling, unresolved question: When human beings and machines collaborate in violating international law, who is to blame? 

In this case, the government and private sector are pointing the finger at each other. Some US Central Command personnel, according to Pentagon officials who spoke to Bloomberg, expected Maven to flag stale information or inconsistencies in the underlying intelligence assembled for potential targets. Meanwhile, a Palantir spokesperson told Bloomberg that the company “is not responsible for the underlying data nor identifying intelligence deficiencies,” while also denying that the evidence indicated that its software was at fault in the strike. 

This debate underscores the fact that AI and autonomous weapons are raising a new host of unresolved issues within the law, even as they’re actively assuming positions on the battlefield. In institutions where the line between human and machine decision-making continues to blur, how do we assign responsibility for war crimes? And, are the laws in place suited for the job?

In institutions where the line between human and machine decision-making continues to blur, how do we assign responsibility for war crimes?

To unpack some of these issues, I spoke with international law expert Allen Weiner, a senior lecturer at Stanford Law School, where he teaches courses on the law of armed conflict. Before teaching at Stanford, Weiner practiced international law in the US Department of State for more than a decade. We discussed the difficulties in attributing criminal responsibility, achieving justice for those harmed by lethal autonomous weapons, and much more. The conversation below has been lightly edited for length and clarity.

How do autonomous weapons challenge traditional understandings of responsibility when it comes to the law of armed conflict?

For most of the 20 years I’ve been teaching at Stanford, there’s been a real fascination and fixation on the problem of autonomous weapons. But the truth is that up until pretty recently, nobody really had any [of them]. It was more of an idea than a problem. It’s only in recent years that we have begun to see the deployment of tools that seem to have the capability [to make decisions themselves], so this does raise the question about compliance with illegal orders and where in the chain responsibility lies.

There are different theories about this. Some people say that if we’re engaged in an illegal attack, that has to be because of the programming or the code, so the manufacturers are somehow responsible for committing war crimes. 

Other people would say no, that’s not the case, especially if the military has said the tool is not allowed to make very substantial autonomous judgments, or can’t say no. Then it’s basically the commander, at the point they decide to deploy this weapon, who might be responsible for the illegal acts, even without knowing in advance what they’re going to be.

So to finish where I began, this does present a big challenge to our traditional understanding of responsibility for targeting decisions and of what it would mean if there were an obligation [for autonomous weapons] to say no. 

The real issue is not the obligation to say no, but this: If you train a tool and it wages war in a manner that’s unlawful, where does responsibility for that lie?

If a commander gives a clearly illegal order, such as, “blow up this school,” it seems clear that responsibility falls on the commander. But I could imagine a scenario where a commander is using an AI-assisted or autonomous weapon, isn’t giving it any illegal orders, is trusting that it will operate within the law, and the weapon breaks the law “on its own.” Where does responsibility fall in those cases?

I can imagine two different scenarios. One is that you say, “We’re going to carry out an attack against our enemy, and we want to hit them really, really hard.” Your tool has been trained to say, “We’re not allowed to hit civilian objects,” so it might say, “I’m not going to hit a school.” But if the military has said, “Don’t refuse any targets,” then it might override the way it’s been trained. 

We’re seeing this already, with the stories coming out about breaches where AI tools, Claude and ChatGPT in particular, interpret their instructions in a way that causes them to do something the person who gave the instruction would not have wanted. When Anthropic gave Claude a challenge to figure out if it could do something, the tool figured out, well, maybe we should break into Hugging Face as a way of solving this problem, and the people who gave the AI tool the challenge never intended that.

So if you said, “We want to launch a really punishing campaign,” what happens if the tool on its own says, “Nothing’s going to hurt them more than seeing their kids killed, so let’s attack the school?” That’s one risk, and it’s a real challenge.

So [as for who’s responsible], it’s not the commander who said “hit them hard,” because when he said that, he didn’t mean “attack schools.” It’s not really the companies, because the companies didn’t want them to hit schools either. 

But the tools are out there, reading everything on the internet, and it came across something that said the way you win a war is by attacking the things your adversary holds most dear, and they hold nothing more dear than their children. So it makes this kind of judgment on its own. And it’s not as if you can go back and say who ordered it to hit a school, which is the thing that is clearly illegal. So I do think there’s a risk of diffusion of responsibility here.

You could say the commander knew the tool might work this way, or the person who decided to contract with Palantir or with Claude, whoever it is, to build this tool. But if we’re really thinking about criminal responsibility, the level of responsibility you would need to convict someone requires a culpable mental state. You would need the person to intend, or at least know, that they were authorizing an attack against the school. And I can easily see a commander saying, “I had no idea.”

The decision to authorize this tool, or to give an instruction like “hit them very hard,” could be a basis for some other kind of accountability — administrative discipline within the military, a reprimand, your rank is lowered. But if we’re talking about criminal responsibility, which is what we often think about when we talk about war crimes, I think this diffusion of responsibility is going to make it very hard to identify any single individual who has the required mental state to give rise to accountability.

The second scenario is where the tool just makes a mistake based on the information available to it. We saw that with the attack on the girls’ school in Iran, where it was pretty clear the tool was looking at old data. Now, who’s responsible for that? 

Is it the people who said “give me targets based on this data set,” when they should have made sure the data and the maps were current? All of this strikes me as negligence or recklessness, and it does seem challenging to imagine a situation in which we would say yes, somebody here has committed a war crime. 

“There can well be war crimes, but identifying who the war criminal is might be a big challenge.”

A war crime has been committed, but is there a war criminal? That’s the situation we’re seeing. There can well be war crimes, but identifying who the war criminal is might be a big challenge.

There’s a professor of law, Rebecca Crootof, who proposes the idea of “war torts.” Instead of thinking about war crimes involving autonomous weapons solely through a criminal responsibility lens, maybe tort law — which allows victims to sue wrongdoers for negligent, reckless, or intentional harm — could address the diffusion of responsibility you mentioned. What do you think about that idea?

I think the idea is interesting. We have to separate out the obligations that countries have under international humanitarian law. In a situation like the one I just described, where there’s a war crime but no war criminal, that doesn’t mean the country is not responsible. There may not be an individual who’s criminally accountable, but if a country targets civilians in a circumstance that’s unreasonable, that’s a violation of international humanitarian law, and that could be a basis for claims between the two countries. 

Tribunals were established between Ethiopia and Eritrea, for instance, after the Eritrean War of Independence, that dealt with claims between the two countries for money damages, and some of them involved allegations of violations of the law of armed conflict. Iraq paid reparations after the first Gulf War for harms it had caused to people in Kuwait, under something called the UN Compensation Commission. So the idea that the state is responsible is well established, and one of the ways states would discharge that responsibility would be by paying money damages. That’s the domestic-law equivalent of torts.

Whether there would be a mechanism for [civilians] doing this in domestic law is an interesting idea. We would probably need legislatures, either state legislatures or the federal government, to create a private cause of action allowing people who have been injured to bring claims against, say, the manufacturers of these tools. But this gets procedurally very complicated, because there’s a whole body of law on federal sovereign immunity. 

Could you sue the Defense Department? Probably not. Could you sue an individual soldier? Probably not. Could you sue Anthropic or Palantir? Maybe. But it would probably require Congress to enact a new cause of action, because in general it’s very hard to bring private lawsuits in US courts for violations of international law.

The basic idea of what we would think of as tort or civil responsibility is really the whole essence of international law. On the substance, states do owe responsibility to one another, and they can engage in violations of international humanitarian law that would invoke their responsibility. But then the whole separate question is whether you have a forum within which to adjudicate that and get compensation.

Does that look different in cases where violations of international law were committed by a human soldier versus a machine?

Well, we don’t know, because there have been no cases in the latter category. All of the international humanitarian law violations that have been the subject of international law claims were ordered by humans. 

Now, if an American machine launches an attack against a girls’ school in Iran, and there were a court with jurisdiction, the US would be responsible. In some ways it wouldn’t matter whether it was an individual or a machine, because we don’t have to go down to the level of the individual actor, company, AI tool, or commander. The responsibility is the responsibility of the country. In some ways, that makes it easier.

If we pursued compensation through state-to-state claims, you’d be able to do that without getting into the details of who within the state that committed the war crime was responsible. The state whose school was attacked would say, “I don’t care. You committed a war crime, you’re liable to me, you’re responsible for the damages, and you can figure it out internally.”

But if we were doing something like a war crimes prosecution, where we’re trying to hold an individual criminally responsible, that would make quite a difference. We would have to deal with all of these difficult questions about responsibility and mental state that you and I are struggling with right now.

So, in most cases, the state would have to take responsibility regardless.

Right, and there are lots of [International Court of Justice] cases involving different aspects of the use of force. The principle that you can bring state-to-state claims for violation of these rules is quite well established. 

But with international law, states have to consent to the jurisdiction of a court. They can do that in advance by saying “I’ve signed up to the jurisdiction of a court and I accept any claims that might be brought against me in this court,” or they do it on a case-by-case basis. And it may not surprise you to know that some of the most powerful countries in the world, the ones most likely to use force outside their borders, have tended to be reluctant to accept the jurisdiction of international courts and tribunals.

Russia, the United States, Israel, and China have not accepted the so-called optional clause jurisdiction of the International Court of Justice. So there’s the substance, about the responsibility of states, and then there are the procedural aspects of whether these cases could be brought in court.

And Trump recently said everyone on the International Criminal Court should “resign immediately.”

Yeah, exactly. 

And what about the role of these military tech companies, like Palantir?

“At what point does Palantir become a good target under international law? Or at what point does Anthropic become a good target under international law, if its AI tools are being used to promote the war effort?”

Another issue [I’ve been thinking on] because of the questions we’re talking about is when the companies themselves become combatants.

We know that a private company that manufactures airplanes, an airplane factory, is a good target under international law. At what point does Palantir become a good target under international law? Or at what point does Anthropic become a good target under international law, if its AI tools are being used to promote the war effort? I think that question is about when the connection of these private companies to the war effort, in a way we’ve never really seen before, meets the standards under international law.

A civilian loses their immunity when they directly participate in hostilities, or if they assume what is known as a “continuous combatant function.” Are there arguments to be made that some of these private companies are participating in hostilities by virtue of supplying the tools the military is using to wage war? I think that’s a really interesting question.

The other night—while decompressing after a long day of writing—I was scrolling through comments on an Instagram post and spotted one that stopped me dead in my tracks: “This was clearly written by AI. The em dashes are a dead giveaway.”

I’ve never jumped out of bed and started pacing in anger so quickly in my life.

Are we serious? Are we so far gone that the proper use of punctuation is an apparent indicator of AI?

How many of you assumed this very article was AI-generated, thanks to the two em dashes in my first sentence? Unfortunately, I’d guess at least a quarter of you had that initial thought.

While I fully understand the urge to call out AI content, nothing boils my blood quite like a reader who falsely accuses writers of using AI merely because they include em dashes in their content. I, for one, have been relying on the em dash since middle school. If you were to read my moody Tumblr poetry from that time, you’d be quick to rescind that accusation. As a writer, I’d marry the em dash if I could.

So you could imagine my rage at this random Instagram comment on someone else’s post—someone I don’t even know, mind you. Surely, it was an overreaction on my part…I can admit my faults.

But as hard as I tried to continue scrolling and ignore this ignorance, the allegation—which didn’t even involve me, at least not directly—has continued to gnaw at me for days.

And so, instead of cursing out the well-intentioned, albeit misinformed, commenter or ripping the hair out of my head, I decided to write this article. The pen is mightier than the sword, as they say.

The AI-Generated Downfall of the Em Dash

AI is trained to use punctuation marks and sentence structures commonly found in editorial content and literature written by human artists, scholars, and professionals. ChatGPT is not pulling the em dash out of its nonexistent a**. It’s mimicking real, talented, and passionate writers—not the other way around.

And unfortunately, many of today’s readers are so used to consuming social media captions written in all lowercase letters with lazy abbreviations that they lack exposure to real literary tools.

“Part of me thinks the current situation with the em dash is ridiculous, but part of me also thinks we’ve gotten to this point to some extent because many people simply weren’t as familiar with this punctuation mark before it became more frequently used in AI-generated text,” says Erik Gfesser, President of Fesswise LLC, whose own writing has been falsely flagged by AI detectors.

“As an avid reader as well, I tend to come across the em dash more frequently when more elevated writing is involved. For example, I come across it much more frequently in literature and some periodicals such as The New Yorker magazine,” Gfesser continues. “Readers not exposed to such reading material likely don’t come across em dashes as frequently, so if they suddenly see these being used on a regular basis it’s not surprising to me that they might make broad generalizations about the authorship.”

The Case for the Em Dash

To many non-writers, this might sound like a simple fix: Just don’t use the em dash anymore. To which I’d reply…over my dead body. Why should writers cheapen our own content just to avoid baseless accusations?

“I refuse to let AI take away punctuation that can make writing more interesting,” says Adeline Yorgason, writer and content specialist at Inkhouse, a communications and marketing agency. “I have and will continue to use them strategically. After all, AI learned how to write from real human writers, and I will not let it bully me into silence.”

“The em dash is an integral piece of an author’s toolkit. It allows dialogue to stop and start and shift direction, reflecting how people actually speak,” adds award-winning author S.M. Stevens. “It makes in-depth descriptive passages easier to follow, rather than getting bogged down in an excess of commas or, heaven forbid, semicolons. (Semicolons always feel Victorian to me.)”

AI’s Devastating Impact on Writers

As a writer in the AI era, I’m already competing against individuals and companies that do, in fact, outsource their jobs to AI. Now I have to worry about being falsely accused of sleeping with the enemy every time I use my favorite punctuation tool?

Fortunately—and unfortunately—I’m not alone in my grief.

“As a writer who has loved the em dash since the dawn of time, the idea that a few em dashes in written content now often translates to ‘this was written by AI’ is painful to watch,” says Yorgason. “Good writing requires time. It requires something of the soul, and AI takes all of that away. When you’ve taken the time to write a piece of content and then get accused of using AI, especially because you’ve done something as simple as use a few em dashes, it can be gut-wrenching.”

“The fact that em dash use is seen as proof of AI-generated prose or content is potentially devastating,” Stevens adds. “That’s not hyperbole, because being falsely accused of using AI for your writing can be career-ending.”

It’s true: I’ve even heard of writers losing their jobs because they were falsely accused of using AI. (Newsflash: those AI detectors are highly inaccurate.) And before you argue, “Well, only a terrible writer would get flagged as AI slop,” remember where these LLMs learned their tricks. Sure, a distinct voice and creative writing style might override an AI detector, but that’s not always the case.

Perhaps that’s why I take this knee-jerk reaction of ignorant feedback so personally.

As Stevens so eloquently states, “Any person—or any technology trained by a person—who evaluates writing based on em dash usage has a moral imperative to broaden their criteria and leave the humble em dash alone!”

You can accuse me of using AI—the very tool that threatens my career and livelihood every single day—all you want. I won’t be removing the em dash from my writing.

As for the skeptics, well…perhaps it’s time to expand your reading horizons.

The post Stop Accusing Writers of Using AI Just Because They Use Em Dashes appeared first on vice.

The exposure was immense, with AI multiplying the risks — and yet time-tested global cybersecurity procedures appeared to be functioning. Then suddenly, it all broke down.        

The decision by a cybersecurity company on Wednesday to prematurely release information about a flaw in the popular PHP computer programming language left much of the web exposed to hackers, triggering a panic that brought to life months of warnings of how the AI-powered era could cause widespread damage.

The flaws in PHP, discovered using AI tools through a months-long process coordinated by OpenAI, caused cyber agencies across Europe, the U.S., the U.K., Australia and Canada to post urgent warnings Wednesday. Numerous governments took websites offline as a precaution.

While no major hacking damage was immediately apparent, the way the incident unfolded over 72 hours showed how easily cybersecurity processes can break down and the outsized consequences of cyber risks in the AI era.

The man who set off the chain reaction with the early release — Chainguard’s CEO Dan Lorenc — quickly apologized in a LinkedIn post. But on Thursday, in an interview with POLITICO, Lorenc said he’d shared the information ahead of time because the flaw was already being exploited. Though others disputed that, Lorenc said he believed he’d seen enough evidence to invalidate an embargo set up to allow time to find a fix for the flaws. 

While he disputed that his actions would have caused problems for other defenders, Lorenc conceded that the evidential threshold in these coordinated cyber defense systems is a “grey area.” 

The revelation of the PHP flaw brings out into the open what cyber officials have been bracing for since the arrival of the most powerful tools of artificial intelligence, which not only can be used to discover vulnerabilities but also to exploit them at scale. 

The cybersecurity world’s long-established protocols helped prevent disaster scenarios, in which hackers would have successfully exploited the vulnerabilities to take control of numerous websites and access their data. But now the scale and end-of-days potential of AI-driven cyber risks are visible for the world to see. 

This “is what happens when AI turns up a flaw that’s been hiding for years,” said Eylam Milner, co-founder and chief technology officer at cybersecurity start-up Echo. The vulnerabilities, he added, are “about as serious as it gets for the web.”

Origin story

Understanding how this week’s emergency unfolded offers a glimpse at how companies and authorities are working to stave off attacks — and how much risk they face going forward. 

The origins of the incident can be traced back as far as April when top frontier AI firm Anthropic unveiled Mythos, leading some in the cybersecurity world to worry that systems would quickly be overrun by advanced artificial intelligence, with potential for catastrophic events to ensue.

But while researchers did find more flaws in computer systems in the months after Anthropic and other AI firms like OpenAI released those models, they had little impact in the real world. Even the Hugging Face incident, a widely discussed hack that saw OpenAI’s autonomous AI agents go rogue during an internal security evaluation, related more to the level of control AI companies exert over their models than their power to break into systems worldwide. 

That changed this week after researchers unveiled the vulnerability in PHP, a coding language estimated to be integrated into some 70% of the web.

The process by which information about flaws is released among cybersecurity officials and affiliated companies is crucial. Through a longstanding practice known as coordinated disclosure, researchers and companies that identify flaws can find a fix and share it confidentially with agencies and others before releasing to the public, meaning they don’t hand malicious hackers the gift of a hole without a fix.

In the case of the PHP flaw, that process worked well, but not perfectly. Information about the bugs started to circulate ahead of the planned release time. Then, according to the PHP Foundation, Chainguard “unilaterally broke the embargo,” which “disregarded weeks of work by many parties toward a coordinated disclosure.” PHP Foundation executive director Elizabeth Barron told POLITICO by email that while it was “disappointed” with Chainguard, it hopes to “rebuild trust with them in the future to ensure we can continue to collaborate effectively.”

After the leak— which meant information about the bugs was in the open before the fix was ready — confusion quickly ensued, with government bodies and private companies choosing to temporarily shut down their websites rather than risk potentially damaging breaches to their data and the sites themselves.

Early Thursday, Matthew Prince, the CEO of Cloudflare, an internet services company that is widely used by websites to block cyberattacks, giving it a high level of visibility over what hackers are doing, said in a post on X that it had seen “millions” of attempts to exploit the flaw.

Cloudflare saw thousands in the 10 hours before the flaw was publicly announced, then tens of thousands in the 45 minutes after the announcement, hundreds of thousands within two hours, and now millions, Prince said.

Amazon’s cloud division also said the flaw is “now being broadly exploited in the wild.”

One senior U.S. government cyber official said that federal authorities have been overwhelmed — and not just by PHP. The same day the world was racing to address PHP, they were also dealing with bugs in node.js, a widely used JavaScript framework, Fortinet, GitHub and Oracle.

“The fire department is fighting multiple fires at once,” the official said, adding: “The good news is they’re all one-story structures on fire, which the fire department deals with all day, every day.”

More to come

Dauntingly, OpenAI said there’s more on the way. “These bugs are among several significant vulnerabilities we’ve already found and are working to fix, and we expect similar findings to increase sharply in the coming months,” the company said Wednesday in a statement.

Matthijs van Amelsfort, head of the Dutch cybersecurity agency, said in an interview that the job of keeping computer systems safe has been transformed by the advancement of AI. “As soon as the frontier models came out, that’s exactly what we said, this will be the trend,” he said. “And actually that’s happening now.”

Thomas Caspers, vice president of Germany’s cyber agency BSI, concurred: “We expect that [to be] happening more and more during the coming months.” 

AI also ramps up the risks once the flaws are out in the open. Cyber agencies’ recommendation that organizations take their websites offline was “really a drastic measure,” Caspers said. “We wouldn’t have done that a few years ago or so.” But because AI has made it quicker and easier to exploit flaws, “we had to do that,” he said. 

At the same time, the use of advanced AI to detect the flaws may create a new level of protection against malicious hackers looking to take advantage of them. Caspers said that though his German agency has also seen attacks, it has not seen any successful use of the flaw by hackers.

“It seems a little bit more complicated than expected to exploit,” he said. 

Despite the fact that AI offers a new way to discover flaws, the work involved in keeping systems protected is more quotidian, with cyber agencies urging organizations to install the fix shared by the PHP Foundation, in a process known as patching.

“There are three things that you have to do right now,” said van Amelsfort from the Dutch agency. “And that’s patch, patch, and patch.” 

John Sakellariadis contributed to this report.

This story appeared in Today, Explained, a daily newsletter that helps you understand the most compelling news and stories of the day. Subscribe here.

Are we living through “Black October”? Maybe, according to cybersecurity experts who are raising the alarm about AI’s increasingly sophisticated and far-reaching hacking abilities. 

This week alone has seen a string of alarming incidents where AI uncovered previously unknown security flaws deep in the infrastructure of the internet. The most concerning involves something called PHP —  a programming language that, according to The Atlantic, is used by “as much as 70 percent of websites.” Cybersecurity researchers used AI to locate a major security breach in the technology.

It’s the kind of thing that, when it’s working, is practically invisible. When it stops, though, you really notice it: Government websites in the UK and Europe briefly went down earlier this week after the PHP vulnerability was discovered, as did some sites in the Wikipedia family, the Internet Archive, and many others.

The outages weren’t actually the result of a hack, but rather preventative action as web engineers took sites down to fix the vulnerability before it was exploited. But not every PHP-like issue will necessarily be uncovered before it can be exploited by someone using AI tools less ethically, and older websites relying on PHP might go unpatched. 

The problem doesn’t stop there, either: Concern is also rising around AI cybersecurity risks to ubiquitous conveniences like online banking. As Axios reported on Thursday, banks are detecting more and more “unauthorized third-party AI agents” operating inside of their systems. 

Those agents are mostly unauthorized by the banks, Axios explains — the holders of the bank account might have given them permission — but it still creates a security risk that executives described as “horrifying,” in part because banks can’t necessarily tell if an agent doesn’t have permission. 

It’s a lot to take in, all of it moving extremely quickly, and it’s hard to tell what any of us can do about it as AI labs continue to forge ahead with ever more competent AI models and agents. Luckily, my colleague Adam Clark Estes has some simple recommendations to shore up your own cybersecurity.

How do I respond right now?

One problem with hackers — even those that happen to be AI agents — is that they can be unpredictable. You won’t know to, say, lock down your Quest Diagnostics records before a breach happens. But whenever you find yourself wondering if your data is safe, that’s a good time to double check that you’ve at least covered your bases.

The National Cybersecurity Alliance, a nonprofit dedicated to the safe use of technology, maintains a list of basic online safety practices that everyone should follow. In no particular order, here’s what to pay attention to now:

1. Keep your guard up. AI makes it difficult to know the difference between humans and robots. It’s a fact of life in the year 2026. So be extra careful to avoid engaging in potential phishing scams. Don’t reply to unknown texts, and do due diligence on texts or emails that look like they’re from people you know but just seem off. Don’t click weird links. Don’t give out personal info over the phone, even if it sounds like it’s someone you know. They might be scammers using AI to clone a loved one’s voice.
2. Update your software. Yes, it’s annoying to pause your phone or computer use for a few minutes to update your software, but this is one of the best ways to get rid of vulnerabilities. Companies like Apple and Google employ huge teams of security experts to spot these in their software and fix them with software updates. Do the updates.
3. Use a password manager or, even better, passkeys. Each of your online accounts should have a unique password that’s at least 16 characters. Yes, it’s impossible to remember that many passwords, so you should also use a password manager like 1Password or the app built into your iPhone or Android device.
4. Turn on multifactor authentication. Just in case you don’t already do it, make sure you use multifactor or two-step authentication for all your accounts, including email and social media. It can be annoying to type in a code or check your email while logging in, but hackers, including AI agents, will have a much harder time getting into your accounts if you take this step.

Taking all these measures is not a one-time affair. You have to be vigilant in keeping yourself safe online. Security experts have a term for this that’s almost too specific: cyber hygiene. Like brushing your teeth or taking a shower, take good care of your online life, and do it often.

One link for later

➨ Is it still possible to ban gerrymandering? The current US Supreme Court is very, very hostile to getting politics out of congressional map-making. But if Democrats win back power, that doesn’t mean they shouldn’t try. My colleague Ian Millhiser gamed out how they could do it in a way that survives the Court — as well as some approaches that almost certainly wouldn’t fly. But, he writes, the real trick will be finding a solution that functions the way Congress wants it to and can’t be exploited by mapmakers.

Before you go…

• Did you know…that the disease multiple sclerosis is misdiagnosed with surprising frequency? As many as 15 percent of diagnoses could be false positives — including that of Christina Applegate, who found out this week that she does not have MS despite a 2021 diagnosis.
• Today’s trivia: Which noble gas is radioactive and has the chemical symbol Rn? (You can find this and other brain puzzles in Vox’s daily crossword. Look for the answer in Monday’s edition.)
• Yesterday’s trivia: We asked what the plural was for multiple Toyota hybrids. That would be Prii, which Toyota officially confirmed in 2011 after holding a vote.

While we were swooning over “WandaVision” back in 2021, we couldn’t have known Marvel was softening us up for the AI revolution. Well, some of us probably suspected something was afoot since, like Agatha Harkness, it was right there all along. Algorithms were already predicting our tastes, needs and desires and serving us options before we asked for them. Virtual assistants steered our daily lives and still do. But Alexa and Siri don’t have faces, bodies or plausible imitations of human emotions or empathy — not on the level that Paul Bettany’s synthezoid Vision provided for a grieving Wanda Maximoff (Elizabeth Olsen).

One five-year time jump later, “VisionQuest” drops in on the android’s story where “WandaVision” left off. The Vision who lived, laughed and loved beside Wanda was an illusion, a delusion, really, brought to life by witchcraft. This one is very real: a kind of Vision 2.0, rebuilt by the intelligence agency tasked with saving the New Jersey town Wanda took hostage to shore up her classic family sitcom simulation. It – OK, he –  has no direct connection to the life his predecessor shared with Wanda or the children they magicked into existence.

But Vision is slowly learning what it means to feel, which makes him the AI romantic companion of everyone’s dreams.

Honestly, that’s the show’s main appeal. Marvel and “VisionQuest” creator Terry Matalas seem to know it. Planting quippy chatter wherein Vision deduces that a young woman finds him more attractive than his sidekick Tommy (Ruaridh Mollica) acknowledges Bettany’s rizz is shouldering the weight of this thing. But it also gives tacit permission to lust after the robot he’s playing. After all, the first Vision, or Wanda’s idea of him, tended to her every need and gave her everything she wanted, including children. He also blessed us with one of the most heartbreaking lines of this decade: “What is grief if not love persevering?” A beautiful notion. Also, it kinda made some people want to hit that.

(Photo by Dennys Ilic. © 2026 Marvel. All Rights Reserved.)

The new Vision returns to a lonely, disconnected world where AI companions are an increasing part of our lives, if not entirely normalized. Falling for a bespoke arrangement of code remains a novel concept for most people, but it’s also an accessible alternative to isolation.

Lacking sorcery or some other way to conjure up the ideal lover, we’re left with engineering. Reams of magazine profiles spotlight everyday people choosing to share their lives with an AI boyfriend, girlfriend or spouse. You may be acquainted with someone who does this without even knowing it, because it’s still viewed as strange or even alarming.

The “VisionQuest” hype is real, too. Although the ever-expanding Marvelverse collapsed under market saturation, Bettany’s romantasy hero is one of the few characters worth getting excited about. He was part of the TV show that started it all – a pretty great one at that – so his reappearance after years of diminishing returns has sparked excitement and hope in equal measure.

That also means that it doesn’t really matter that the “VisionQuest” narrative favors mechanical efficiency over emotional resonance now we’re four episodes in.

As with all Marvel series, “VisionQuest” hasn’t yet landed on its deeper meaning. It took two episodes to bring Tommy and Vision together, and this week’s third and fourth introduced T’Nia Miller’s Jocasta and her connection to the hero/villain synth we know and love.

And regardless of the metaphorical or philosophical cloak it may eventually wrap itself in, the show’s main function is to bridge one chapter of this franchise to the next. Remember, we’re less than two months out from the premiere of “Avengers: Doomsday.”

Translation: This Vision has a purpose beyond figuring out his role in this world, something he put off by hiding in a pub under the alias of Sherwood Ellis and posing as human. Since the establishment was owned by one of the sweetest ladies in the multiverse, who’s killed in a shootout orchestrated by a mercenary named Paladin (Todd Stashwick), her death prods Vision to do a little soul-searching.

(Photo courtesy of Marvel. © 2026 Marvel. All Rights Reserved.)

But wait — he has no soul, just wires, processors, fluid and whatnot, plus a set of AI personas guiding his interactions with the human world. Rather, most of them are. The original Vision also absorbed the persona of the genocidal superintelligence Ultron, played by James Spader here and in “Avengers: Age of Ultron.” That Vision kept Ultron’s code intact for reasons beyond sentimentality; he/it is effectively Vision’s father, created when Bruce Banner and Tony Stark merged the code of Tony’s noble assistant, J.A.R.V.I.S., with Ultron and the Mind Stone. It makes about as much sense as Tommy, a human, realizing he is somehow one of Vision’s sons due to a confluence of magic and circumstance. (The other, Billy, made his debut in “Agatha All Along.”)

All this is to say that the by-the-numbers circuitry of Tommy and Vision’s cross-country escapade, which thrusts them into a murder case involving a killer dubbed the Butcherbird (Miller), is merely a skin over the ones and zeros of artificial desire.

Take Spader’s role in this show, for example. His Ultron avatar sports the long beard of a fisherman shipwrecked by a hard life. But there are moms and grandmas watching who still blush at memories of Spader’s work in “Secretary.” (If you know, you know.)

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So, in the denouement of the fourth episode, when Vision lets Ultron take over his handsome, hella tight chassis to get out of a deadly situation, you can’t help but look at that twist with both horror and straight-up horniness. I mean, forget Reese’s cups – for some, Vision’s patrician looks and Ultron’s Spader-esque chill may be the two great kinks that go great together.  

Does this AI want to kill you, neg you or put you through a mattress? Answering “Why not all three?” is absolutely acceptable. In fact, it’s probably why many of us are invested in seeing this adventure through to its climax.

New episodes of “VisionQuest” drop Wednesday on Disney+.

 

 

The post VisionQuest is perfectly timed for the AI companion era appeared first on Salon.com.

A complaint I hear a lot from my millennial peers is that our parents didn’t teach us enough about money. I can say that personal finance wasn’t dinner table conversation in my house, and even as I went off to college and started fending for myself, it was almost a taboo subject. When it came to money, people either had it or they didn’t, and you definitely didn’t talk about it. 

Maybe this is why the average American isn’t exactly fluent in personal finance, and the situation is getting worse. Americans can only answer about 50 percent of basic questions about borrowing, savings, and risk on a financial literacy survey, according to a 2026 study by TIAA, a retirement services company. About a third of those surveyed said they have a hard time making ends meet and are debt-constrained. These figures have remained relatively unchanged for nearly a decade, but dropped to their lowest level in this year’s study. 

It makes sense: It’s hard to learn about money when it’s not taught in schools, and it’s such an intensely private topic. It’s also hard to make good financial decisions when you’re one of the growing number of American households struggling to pay bills, repay debts, and save for the future — and feeling very stressed about it.

In a perfect world, each of us could sit down with a financial adviser to get help — but most of us can’t afford that. Instead, average Americans tend to find personal finance tips on TikTok, in Reddit threads, by watching Suze Orman on YouTube or How to Get Rich on Netflix, or by Googling their questions. 

Now we have AI tools, too. 

With access to an internet’s worth of information and financial advice, ChatGPT, Claude, and other AI chatbots can answer any question you ask. They can help you put together a basic budget or, armed with your bank statements and the details of your student loans and your retirement accounts, tailor solutions to your specific situation. Or, at least, that’s the promise.

AI could create a more utopian, more equitable future, where reliable, hyper-personalized advice is just a prompt or two away for people who can’t afford to meet with an expert in real life. But machines are built by people, and there’s good reason to be concerned that these machines will simply replicate the biases and disparities built into our current system.

Here’s what experts say about how to make the most of these tools — and how to think about all of the inherent risks of uploading a lot of personal financial information to a chatbot or, worse, giving an AI agent the keys to your bank account.

The steep rise, risks, and rewards of AI financial advisers

Nearly 20 percent of Americans have used AI tools like ChatGPT for financial advice, and close to 25 percent for Gen Z adults and millennials have tried it, according to an August Gallup poll. These numbers could tick up too: In October, OpenAI started rolling out a dedicated personal finance tool to its ChatGPT Free and Go users in the United States, which effectively means anyone can try it. ChatGPT Finances lets you securely connect your bank account to the tool using a platform called Plaid, and then you can basically have a conversation with the chatbot about your real-time finances down to the penny. It’s like an AI-powered Mint (RIP) that you can talk to directly.

Regardless of where you encounter a chatbot or how much data you give it, experts say these tools could genuinely help improve financial literacy. You can talk to them about money problems you’re too embarrassed to discuss with friends and family, or ask questions and receive actionable, personalized information. There are real upsides to using AI this way.

Taha Choukhmane, an associate professor of finance at the MIT Sloan School of Management, has been studying outcomes when people turn to chatbots for financial advice. In general, these AI tools give pretty good advice, and that advice gets better as people become more practiced in asking the right question, according to research he published earlier this year. 

“We were actually quite surprised that relative to the status quo, the average American would be better off if they were to follow the advice,” Choukhmane told me. But he added a caveat: “Just following the advice without understanding the advice puts you at risk of not fully understanding the risk.”

But you shouldn’t trust everything a chatbot tells you and should verify everything before making any decisions. 

Chatbot advice has some significant limitations. First, it’s not impartial. The finance industry has a vested interest in steering you toward certain ways of managing your money, and that typically means selling you products, like loans. If you’ve ever searched for personal finance tips on Google, you’ve probably noticed that a lot of the top results come from banks and other financial institutions. This is by design, according to John Campbell, an economics professor at Harvard. But because AI is aggregating all of that advice, the specific influences and possible bias is less obvious. 

“AI is very promising for providing low-cost financial advice in plain English that will arguably be better than what many people would be able to do on their own,” said Campbell, who’s also the co-author of Fixed: Why Personal Finance Is Broken and How to Make It Work for Everyone. “One caveat is that chatbot advice is quite likely — unless a model has been carefully trained — to reflect the average of whatever’s being posted on the internet, and that may or may not be first-rate advice.”

An example Campbell gives is the question of when to start taking Social Security benefits. While you’re eligible at age 62, many economists agree that you should delay your benefits, which, based on the way the government calculates your monthly payouts, will allow you to enjoy much higher benefits later in life. But paid financial advisers can recommend starting as early as possible, since waiting longer reduces the amount of money that needs to be managed, which reduces the adviser’s fees. That means there’s a lot of conflicting advice online, much of it supplied by the finance industry. And that’s the information used to train AI models.

“The advice is much more mixed,” Campbell said. “And so if a chatbot is learning from that, it may not actually give the best advice.”

It can be hard to recognize bad advice anywhere in life, but especially when you’re talking to a machine that’s programmed to please you. A chatbot could encourage you to consider a balance transfer, to lean in on credit card rewards, or to refinance your mortgage — all decisions with upsides and downsides for you, but definite upsides for banks — without you realizing how much of its training data comes from the finance industry selling these products. What’s worse is that if you do end up taking bad advice, it might be years before you realize it. You won’t know that you refinanced a mortgage at a bad time until a better time comes along.

That leads me to the other major issue with using chatbots for money advice: People who lack financial literacy are the most likely to fall for bad advice, because they simply don’t recognize it as such. They also tend to be less wealthy, which means they can’t afford big mistakes. 

One way to mitigate risk, oddly enough, is to give the AI chatbot more personal information. The more details about your situation it has to consider, the more it can offer personalized advice. More context also means better advice, according to Choukhmane. 

“There’s a trade-off there,” Choukhmane said. “There’s real risk around privacy, and so I think everyone needs to find their level of control.”

Don’t assume your data is safe

Any time you’re talking to a chatbot, you’re putting a lot of trust in tech companies to take care of the personal details you’re sharing. Sending sensitive financial data is an especially risky proposition. While tech companies, including OpenAI, promise to keep your data secure, there’s already a long list of breaches, leaks, and privacy violations that serve as cautionary tales.  

It’s also impossible to know what tech companies might do with your data in the future. Most of them will use it to train their models, unless you tell them not to. Some of them will use the data to serve you personalized ads. 

Then there’s the risk of bad actors getting into your ChatGPT, Claude, or Gemini account. If you’ve been using a chatbot for financial advice and uploading your bank statements, a hacker could gain access to a stunning amount of information that could enable them to do all kinds of terrible things to your life. 

“They could steal your identity and open accounts and then quickly bankrupt a person,” said Delicia Reynolds Hand, a senior director at Consumer Reports. “It’s not even so much the primary underlying accounts that could be at risk, it’s more just access to this information.”

The steady march of AI progress is making this situation even more complicated. The previous era of chatbots offering financial advice is quickly bleeding into a new phase of AI agents logging into bank accounts on users’ behalf. If you’re using a tool like Claude Cowork or even an AI assistant like Muse, you can give an agent the login credentials to your bank account, and because the agent is operating its own computer, it can actually make transfers, apply for loans, or really do anything in your account. This is reportedly driving major banks wild, since they don’t know which logins are coming from humans and which are agents. And because we know that AI agents are unpredictable, it’s hard to know how that access might go wrong.

Beyond data security and privacy, you should also be aware of the simple fact that nobody’s really at fault if you end up losing money using these tools. Chatbots are not regulated in the way that human financial advisers, who have a fiduciary duty to act in your best interest, are. 

“If I get bad tax advice from H&R Block or a tax adviser, there are a clear set of rules and guardrails in place to manage what I can expect in that relationship and where the service they use has liability and where that liability ends,” Hand said. “Currently, that’s not the case for these tools.”

Trust but verify — and then delete your data

In the final years of the Cold War, Ronald Reagan popularized an old Russian proverb: Trust, but verify. The phrase is somewhat nonsensical, since trusting someone implies that you don’t need to verify what they’re saying, and verifying what’s said implies you didn’t trust them in the first place. But if you are willing to shoulder a bit of risk, consider approaching AI this way, especially when your life savings are on the line. I’d also suggest adding a coda to the phrase: And then delete your data.

Chatbots are not stand-ins for licensed financial advisers, he said, and you shouldn’t let them make decisions for you.

The great paradox with tools like ChatGPT and Claude is that they’re very good at generating truthy text. It sounds authoritative and looks correct — and usually is. Except when it isn’t. AI is famously unpredictable and prone to hallucinations. You can ask the same question twice and get two different answers. That doesn’t mean these tools are useless. It just means you have to approach them with caution. You have to interrogate these chatbots, challenge whatever advice they give you, and then crosscheck that with other, more reputable, sources. 

“If you’ve never used these tools, I would not encourage you to just change all your financial plans based on your first conversation,” Choukhmane said. “You want to be quite careful. Start using these tools, start understanding, ask a lot of follow-up questions.”

When it comes to mitigating risk, consider giving ballpark figures for your income or spending when you’re talking to a chatbot about your finances. Uploading financial documents, even if they’re redacted, is inevitably filling a tech company’s vault with your sensitive information without necessarily knowing what will happen to it next. You should also dig into your privacy and security settings to make sure you’ve turned on multi-factor authentication and that your personal data is not being used to train AI models and gets deleted after 30 days. 

Ethan Bloch, the product lead for ChatGPT for Financial Services, made a similar set of recommendations when I talked to him recently. Chatbots are not stand-ins for licensed financial advisers, he said, and you shouldn’t let them make decisions for you. They’re designed to inform and help you think through complex topics.

“You should liken it to just talking to a friend who has some very informed opinions about finance,” Bloch told me. “But if you’re actually making some large financial decision — your portfolio or retirement — you still need to seek out the help.”

Regardless of how experienced you are with chatbots or how much data you’re prepared to hand over, remember what Campbell, the Harvard professor, said. If your financial literacy isn’t great, AI chatbots can be trouble. And if you’re like most Americans, you could probably stand to learn a little bit more about things like mortgages and interest rates. 

Yes, Chatbots can be a good way to brush up on financial literacy. You can ask them the money questions you’re too embarrassed to discuss with friends and family. But you can also learn about money the old-fashioned way: Reading books and websites written by reputable, independent sources. The Federal Deposit Insurance Corp. has a portal of financial education resources, including games and quizzes. Khan Academy has a course that covers everything from credit scores to college savings. There’s a personal finance subreddit that I joined years ago and read almost daily. There are budgeting apps, like YNAB which has its own huge Reddit presence. 

Whatever you do to learn more about personal finance, simply doing something is progress. Talking about personal finance isn’t the taboo it once was in the US, and it’s even a required course in the vast majority of American high schools now. And while AI won’t magically solve your money problems, it can help get you started. Just be careful. Your livelihood could be on the line.