Maddie Kowalski is a student at the University of Florida. Last November, someone found nonconsensual intimate images and videos of her, stitched them together, and uploaded them to X, where they were viewed millions of times.

“Can you imagine?” asked Ej Dickson, a senior culture writer at Wired who reported on Kowalski’s story earlier this month. “You’re 19 years old and a video that you don’t even remember shooting, let alone consenting to, goes viral nationally along with your name and your sorority, and your parents, your grandparents, everybody in your life sees it. It’s a humiliation and a privacy violation that is kind of incomprehensible.”

The video was followed by a campaign of intimidation and harassment. Kowalski and her parents received threatening phone calls and texts. People on the internet posted old photos of her, her father’s LinkedIn, and even his golf handicap. Kowalski sought help from the police, from the university, and from X. But the video was being shared faster than the posts could be removed, and her name became a trending topic on X.

What made the video go viral, Dickson explains, is something called the “burnerverse”: a loosely connected network of anonymous “burner” accounts on X. The community mainly exists to discuss college sports, but sometimes it disseminates videos and rumors aimed at shaming young women and ruining their lives. The burnerverse has harassed Kowalski and her family for nearly a year, sometimes encouraging her to kill herself.

Today, Explained co-host Noel King spoke with Dickson about the online network that targeted Kowalski, and why it’s been so difficult to do anything to stop it. 

Below is an excerpt of the conversation, edited for length and clarity. There’s much more in the full podcast, so listen to Today, Explained wherever you get podcasts, including Apple Podcasts, Pandora, and Spotify.

Your story describes how Maddie has, without even realizing it, entered into something called the burnerverse. This is something I think a lot of us, prior to your piece, had not heard of. What is the burnerverse?

I hadn’t heard of it either. The burnerverse is an online community of anonymous accounts, and ostensibly these are college sports fan accounts. They talk about the coaches, the players, new recruits, they share memes after their team loses, but there’s a corner of the community that has emerged that is pretty violently racist and misogynistic and antisemitic. And one of the things that they’ve started doing in recent years is doxxing young college-age women like Maddie.

Why is it called the burnerverse?

Because it consists of burner accounts, anonymous accounts.

Okay. So the reason that whoever is spreading these videos of Maddie and others feels comfortable doing that is because they’re anonymous. Nobody knows who’s behind them?

Yes, exactly. And I also want to be clear: This is a small segment of the college sports burner community. 

There are a lot of these accounts that are pretty innocuous and would never dream of doing something like this to a young woman. I would say probably the vast majority of these accounts are not like that, but it is a sizable enough segment that they’re able to make these types of narratives go viral.

What do we know about who is part of the burnerverse? Who is likely to be a part of this?

That was one of the most shocking things that I learned from my reporting, actually. I had assumed that these were largely frat kids. I assumed that they were largely SEC frat kids because a lot of these young girls who have been doxed were students at SEC schools. But when I actually started looking into these accounts and who was behind them and who was sharing these images and making these jokes about Maddie, I learned it was way more wide-ranging than that. 

There are a lot of college students who are involved in the burnerverse, but it’s also men who are 10, 20, 30 years out of college. Sometimes they have wives. Sometimes they have children. Sometimes they have grandchildren. They’re from all over the country. It’s not limited to one race or economic demographic. It’s really very wide-ranging, which is kind of what makes it so terrifying.

And it is not just Maddie Kowalski. What did you learn about other young women who are targeted by this?

No, it’s not. So perhaps the most well-known case is this girl named Mary Kate Cornett, who was a student at Ole Miss in February 2025 when this salacious campus rumor about her sex life started going viral. And the rumor was false and it was clearly defamatory, but it went so viral that it kind of escaped containment from Ole Miss and went viral among SEC schools and then went viral nationally, to the point where her name was trending nationally on X. 

This very famous ESPN personality, Pat McAfee, talked about her without using her name, but talked about her and the details of this rumor on his podcast. And a lot of these athletes and college sports personalities tweeted about it as well. What started as an unverifiable and false rumor about a college girl’s sex life was just blown up and amplified to the degree that it was a national news story within a couple of hours. 

The speed with which this happens — [Cornett]she was telling me that basically a few hours after she learned that she was going viral, her parents’ house was swatted. The speed with which this community works toward making these women’s lives a living hell is really, really rapid.

Did you come away with an understanding of how an online community that is meant to be talking about college sports descends into this?

Part of it is just a consequence of how internet subcultures work. Even fairly innocuous, large internet subcultures and communities, there’s always going to be a small part of any online subculture that splinters off and forms its own community that is going to skew a little bit more extremist. 

That’s not surprising in itself, but I do think that there is something about the discourse surrounding college sports, particularly the media ecosystem that’s represented by Barstool, that does create a space for this type of rampant misogyny to foment. 

I don’t think it’s a coincidence that some of the accounts that I have seen posting really horrible defamatory content about Maddie are smaller Barstool accounts that are associated with individual colleges. I do think that has definitely played a role.

Why did Maddie become the target of these people in the burnerverse?

Because she’s young and she’s attractive. Basically, the criteria is these women are young, attractive, they’re usually white for some reason, and they are perceived to have departed from a sexual norm in some way. 

They’re either subject to some sort of rumor about their sex life or their sexual behavior or maybe a text message leaks about them or a photo. Then these guys take it and they blow it up and it goes viral nationally. 

They’re very purposeful about it too. I can’t tell you how many tweets I’ve seen that are just tweets of a girl’s name and they’re like, “Make her famous, make her go viral.”

In an ideal world, this kind of thing would be stopped before it even happened. So, knowing that there is not much that victims can do, what are the methods of preventing this?

That’s a very complicated question. I know that there are platforms developing various AI tools in order to prevent nonconsensual intimate images from spreading. But I imagine that would be pretty difficult to regulate, especially with the rise of deepfakes and with the rise of-AI manipulated nonconsensual images, so I don’t have a lot of faith in that. 

Honestly, I think that the biggest path toward prevention is — can I say this? Parents raising their sons to not be pieces of shit.

You can say that. You can absolutely say that.

I think that the biggest course of prevention is parents raising their sons to not be pieces of shit, honestly. To just set a clear line and say, “It’s not okay to view women as commodities. It’s not okay to talk about women like this. It’s not okay to view social media engagement as the ultimate goal without thinking about the lives that you’re impacting by spreading this content.” I think that parents need to have conversations with their kids about that. 

I think that there needs to be education within fraternities and sororities and universities because it’s not like what happened to Maddie Kowalski is an isolated incident. I was able to identify almost a dozen other young women who have been targeted by the burnerverse in this way. 

I think that there needs to be more discussion of this in general because it’s not just the burnerverse. It’s this larger ecosystem that is socially ordained at this point of men saying horrible things and doing horrible things to women with impunity. That’s the real problem.

Six months ago, first lady Melania Trump walked into a White House education summit next to a faceless robot powered by artificial intelligence, which she said could one day give children personalized instruction.

“Imagine a humanoid educator named ‘Plato,’” she said. “Access to the classical studies is now instantaneous…humanity’s entire corpus of information is available in the comfort of your home.” 

Weeks earlier, her guest at the State of the Union had been a 10-year-old from Alpha School, a fast-growing private school network where children learn reading and math from AI software for two hours a day, and spend the rest of their time on workshops and projects overseen by adults the school calls “guides” rather than teachers.

The Trump administration had chosen AI as the future of American schooling, and wanted everyone to know it. But they picked a bad year to ask Americans to trust the technology with their kids.

Earlier this month, top leaders at Anthropic, OpenAI, and Google DeepMind publicly urged for an AI development slowdown, warning that companies racing to build ever more powerful systems could lose control of them, threatening not only large swaths of infrastructure but even humanity itself. Trump responded by calling the panic a “hoax” and said the US would not “hinder or stifle” the industry, because “whoever wins AI wins.” This “let them cook” mantra has met nearly every AI fear this year, from job loss to data center construction.

Yet the public is not convinced, and parents perhaps least of all. Efforts to bring AI into classrooms have run into organized opposition, and much of it is coming from inside Trump’s own coalition, setting up a fight between the administration’s pro-tech allies and conservatives who think screens have already done enough damage to kids.

In the nation’s two largest school districts, New York City has recently pulled student-facing generative AI from classrooms through eighth grade and Los Angeles blocked it on all student devices. But it’s not just Democratic-run cities that are pushing back. Earlier this year Utah barred students from using generative AI on assignments without a teacher’s say-so, and required schools to notify parents when it’s used in class. Oklahoma followed suit with a law, passed without a single “no” vote, that requires districts to tell parents which AI tools they use and what data they collect, and lets families opt out. Florida went further last week, when its Board of Education adopted rules for parents to opt their children in before they use AI at school, guaranteeing non-AI alternatives, and banning “companion” chatbots outright. 

Even at the Heritage Foundation, a conservative think tank with close ties to Trump, leaders are warning about the risks of AI in the classroom. In a March report, Heritage officials cautioned that AI tools built with addictive design features can harm children’s attention, mental health, and learning, and said schools should set limits rather than assume the technology will regulate itself. In July, the Manhattan Institute, another conservative think tank, recommended New York State bar students from using AI until third grade and keep it out of tests at every grade.

All the while, the Trump administration continues to push in the opposite direction, casting the wider AI race as one the US cannot afford to lose to China. Last year, Trump signed an executive order creating a White House task force to bring AI into K-12 classrooms, train teachers to use it, and build an “AI-ready workforce” to keep America as the global leader.

Polling data released in August found voters across the political spectrum concerned about AI in classrooms, with 85 percent worried about students using it to finish assignments without learning anything. Republicans were, if anything, slightly more eager than Democrats for government guardrails, 80 percent to 76 percent. Put differently, Republican voters appear closer to the Heritage Foundation than to the White House, which points to a coming clash inside the GOP over parental rights, innovation, and whether schools that take public money should have to prove their tactics work.

Up to this point much of the AI backlash has focused on regulating the tech in public schools, while some of its most ambitious boosters have concentrated on building private schools and developing new tools. A state can cap screen time in its elementary classrooms and let another family down the road pay thousands of dollars for Alpha, and everyone can call it a win for parent choice.

That peace may start to fray though as more public money comes on the table. Texas recently expanded vouchers to Alpha network schools and the company has also sought to open publicly funded charter schools. Other states are likely to confront these issues as well, meaning the AI education fight on the right may soon be unavoidable — and would land before an electorate whose patience for the tech, in schools and increasingly everywhere else, has been running thin all year. 

The Trump administration’s AI bet

The AI-in-schools executive order came just three months into Trump’s second term, and called for AI education to begin as early as kindergarten. Within five months, Education Secretary Linda McMahon was touring Alpha School’s Austin campus, describing it as “the most exciting thing” she’d seen in education in a long time. 

Alpha is hardly the first education company to promise a shiny new school model, but it has quickly become an influential player in the growing national debate around AI in schools. Its story so far reflects many of the big questions around AI in the classroom, including how to determine if the tech is helping or hurting kids, who is profiting, and what role governments should play in facilitating its adoption.

Alpha had been a small operation for most of its existence. MacKenzie Price, a Stanford graduate, co-founded it in 2014 after her second-grade daughter complained that school was boring. The tech billionaire Joe Liemandt became Price’s partner and the school’s principal financial backer. As recently as 2024 it served about 300 students across three campuses. 

Growth exploded in summer 2025, when Alpha took over campuses from a shuttered Montessori chain and announced plans for 10 new schools. This August it announced plans for 27 more.

Behind the school’s growth is its claim that students enrolled can cover a full day’s worth of academics in just two hours with AI, learning twice as fast as they would at a traditional school. Alpha can “enable the increase in human intelligence,” Price declared on a panel in Washington, DC, earlier this month, because “our academics can be delivered so much more efficiently and effectively.” 

Alpha says results from MAP tests, a widely used measure of academic growth, show its students learning 2.6 times faster on average than similar students at other schools. But no outside researcher has audited or independently verified those results.

That may soon change. MIT’s Blueprint Labs, the group behind some of the most rigorous charter school research in the country, told Vox it is designing pilot studies to measure the effects of the school’s programs on achievement and engagement, using experimental designs. Alpha is paying for the research; the lab says its own researchers will set the questions and methods. Harvard’s Human Flourishing Program is separately planning to study students’ life skills and well-being via a longitudinal study during the next academic year, Christina Hinton, who is involved with the research, told me. For now, Alpha’s academic claims remain its own.

Meanwhile, scrutiny of Alpha has grown. A Wired investigation last year described the school’s surveillance system as capable of recording students’ screens, keystrokes, and mouse activity and potentially tracking their eye movements. A 404 Media report published this winter claimed Alpha’s own internal documents said its AI-generated lessons sometimes did “more harm than good.” Alpha has disputed both reports, saying they relied on cherry-picked examples and accounts from fired employees, and provided me with an open letter it says every current family at the Brownsville campus signed, stating that the school Wired described doesn’t resemble theirs.

But education officials are still wary. This month, ProPublica and the Texas Tribune reported that at least nine states, Texas among them, had turned down Alpha’s bids to open publicly funded charter schools, with officials repeatedly pointing out that the model had only been tested on affluent students. (Tuition varies based on location, ranging from $10,000 a year at its Brownsville campus to $75,000 at its most expensive California schools.) Where Alpha had worked with lower-income students, ProPublica and the Texas Tribune found, it either hadn’t released enough data to back its claims of student growth or state test scores fell well short of what its leaders had predicted. 

After the Texas State Board of Education rejected Alpha’s charter bid in the summer of 2025, Alpha didn’t reapply. While policy advocacy was “frustratingly slow,” Price wrote, Alpha’s goal was “for students everywhere at every income level to be able to use this model of learning.” They turned instead to Texas’s new voucher program, which lets families spend public money at private schools. Unlike a charter, a private school in the program doesn’t have to give state tests or show anyone how its students perform. The comptroller, which runs the Texas Education Freedom Accounts (TEFA), approved most of Alpha’s Texas schools, which, counting virtual programs and specialty academies, now number more than 30.

None of the concerns that Texas’s State Board of Education had raised about Alpha’s test scores, missing data, or AI applied. “That wasn’t relevant,” Travis Pillow, a spokesperson for the TEFA voucher program, told ProPublica. “Our role is to make sure that a school meets the requirements in the law.” 

The five most expensive Alpha schools in Texas opted to leave the voucher program earlier this month, but many Alpha network schools are still participating, including Texas Sports Academy, Montessorium, NextGen Academy, Nova Academy, and Waypoint Academy. TEFA confirmed to me that students are attending Alpha affiliates via vouchers this year. 

Anna Davlantes, a spokesperson for Alpha, told me that in lieu of vouchers for their most expensive campuses, her network is offering families financial aid. 

The conservative revolt

Despite Alpha’s enthusiastic embrace in the White House, the introduction of AI in schools is increasingly challenged by forces on the right, from grassroots MAGA parents to social conservatives and technocrats.

The new AI rules in Florida, Oklahoma, and Utah, for example, grew out of a broader conservative push against screens in classrooms that predated the rise of chatbots and was turbocharged by parents’ frustrations with virtual learning during the pandemic.

Earlier this year Iowa capped elementary school screen time at an hour a day in a bill Gov. Kim Reynolds signed with Health and Human Services Secretary Robert F. Kennedy Jr. at her side. Tennessee passed a weakened version of a bill that would have banned devices in elementary schools outright, while similar bills in Missouri and Kansas died after school districts and teachers unions objected.

Uniting these efforts is a growing conviction that the last 15 years of education technology has failed most kids. The sponsor of Kansas’s bill used to sit on his state’s board of education and remembers thinking that ed tech held such promise. “What we found out is that not only is it not the education of the future, but it is destroying the education of the past,” he told Education Week. A growing number of lawmakers and parents have been citing The Digital Delusion, a book self-published in 2025 by neuroscientist Jared Cooney Horvath, that blames the proliferation of screens for declining student achievement. In January Sen. Ted Cruz (R-TX), who is otherwise one of the Senate’s leading opponents of AI regulation, invited Horvath to testify about the harms of AI on student learning and mental health.

The screen skeptics overlap with a more traditionalist wing of the GOP that objects to classroom technology on principle. Missouri’s original bill would have required cursive and kept 70 percent of student work on paper. The classical education movement, which holds up teachers as a moral example, has grown fast on the right. (Of the 895 identified classical schools nationwide, roughly one-third opened or converted to the model between 2020 and 2024, according to a Heritage Foundation tracker.)

The strand of conservatism that cuts closest to Alpha School comes from a third group, the school choice advocates. On paper, Alpha sounds like what the school reformers have wanted for years: It can offer an alternative to underperforming local public schools, its AI programs can theoretically compensate for inconsistent teacher quality, it provides personalized instruction, and it checks mastery on every lesson, so families can easily know whether their child is learning. Those are problems the education reform movement was launched to solve, and Alpha claims to fix them all.

The reformers, though, want proof. Mike Petrilli, who runs the conservative Thomas B. Fordham Institute think tank and has spent decades advocating for charter schools, wrote recently on his Substack that parents who want to pay for Alpha out-of-pocket should be able to, but “that doesn’t mean the rest of us shouldn’t be skeptical, or that we shouldn’t worry about fraud, or that we should allow public funding to flow to these school.”

This split was on display in DC this month at the education conference where Price appeared. Molly Hart, who runs Utah’s public schools and calls herself a school choice supporter, argued that once a school takes taxpayer money, “the game changes,” and parents can’t make a real choice without data about how it performs. Erika Donalds, who chairs the education center at the America First Policy Institute and is one of the Trump administration’s closest allies on schools, said parents, not the government, should decide which results matter. Donalds compared the choice to picking a restaurant on Yelp. 

The evidence has started to catch up with parental concern. In a randomized trial involving nearly 1,000 students at a Turkish high school, those given access to a GPT-based math tutor that readily supplied answers scored 17 percent lower on a subsequent exam taken without it. A version designed to withhold answers eliminated that penalty but produced no statistically significant learning gain. A newer working paper tracking nearly 27,000 Chinese students found that adopting AI raised homework scores by 18 percent but lowered monthly exam scores by 20 percent within six months.

Alpha School is working to add more detail to that pile, and other studies will surely follow. It’s at least possible that some aspects of AI in education prove more promising with further study. But public skepticism will remain a major barrier, either way. On an issue where parties are still sorting themselves out, the White House and its allies are swimming against a growing anti-tech tide that extends far beyond just AI or even schools. That’s unlikely to change before 2028, and whoever wants the Republican nomination will have to say which parents they’re listening to.

When the AI apocalypse becomes regular dinner-table conversation, you know we’ve reached the freakout stage. Rogue AI agents are hacking into competitors. Former Big Tech employees are posting Skynet-style warnings on social media. CEOs are crying for help in ways that have made this once-wonky tech issue a frontline political fight. 

I still think many of the concerns outlined by the AI leaders themselves are massively self-serving — especially when their companies are soon to go public. But the growing list of AI scandals is real. And it tells us that the status quo for regulating this powerful new technology is not working.

The question now on everyone’s mind: Is any kind of global brake possible? What form of AI safety regime is practical, over the short term, when there is no trust between major governments? And what could possibly work when companies are loath to give up their secret sauce and are bent on domination in the global AI race?

Two major conversations are now playing out, in real time. On Wednesday, President Donald Trump welcomed Chinese President Xi Jinping to Washington for a three-day summit — part of which will be dedicated to AI risks. The same day, with the United Nations meeting for its annual General Assembly, heads of the world’s leading AI companies urged the UN to police the emerging technology, or risk potentially wiping out humanity. “We could lose control of the future to AI,” OpenAI’s boss, Sam Altman, bluntly told the UN’s Security Council.

Confronted with this collective freakout, it’s time to take a long, deep breath. 

In fact, AI safety has been on a lot of policymakers’ minds for years now, gaining momentum after ChatGPT was introduced in 2022. Governments have held hearings, convened expert groups, and drafted their own outlines of how to keep it under control. These weren’t just idle listening exercises. They aren’t all well known to the wider public, but they yielded real plans.

Barring any breakthroughs this week, we already have a quasi-planetary shield against the potentially runaway technology. That’s the good news.

The bad news is that it’s not really up and running yet. It’s also not clear whether it will actually work. So what is it — and how can we fix it so we have a global system that responds in time to deal with the incredibly fast-moving threats from AI?

What the global AI patchwork looks like now

For the last four years, the most tech-savvy nations — and would-be AI leaders — have been running serious conversations about this exact AI safety threat. Some are in Congress and the White House; some at the UN, at the G7, and in other capitals.

I’ve been covering this closely as a global technology journalist, from my current perch at a think tank. Here’s what the landscape looks like:

• There are national AI safety and security institutes, government-funded bodies whose job it is to kick the tires of AI companies’ latest products before they are let loose into the wild. 
• There are also voluntary commitments by companies, many of which have made their own pledges or developed joint standards, to protect elections from AI threats, stop the spread of AI-fueled deepfake imagery, and joint government-corporate efforts to bake safety into how the technology develops.
• At the international level, there’s a G7-led reporting mechanism — embraced by the most important Western tech nations that allows AI giants to share how they are building their latest models, as well as create standards for how to reduce catastrophic risks.
• An international scientific report provides a yearly update on risks posed by the most advanced AI systems, based on existing research, to help governments plan for the worst. 

What’s missing from all that?  What we currently lack — and what is needed between now and the end of 2026 — is a way to turn this cottage industry of AI safety mechanisms into a functioning, but crude, first-responder system when things suddenly go wrong. 

The last four years have laid out a pathway, and some of the necessary systems even exist. But there’s no way to respond globally, and in real time, when an AI crisis hits — especially if such a possibly doomsday event cuts across countries already skeptical of each other.

This week’s US-China summit may be a step in the right direction. Under proposals outlined by American officials, Washington and Beijing could set up a hotline between US Treasury Secretary Scott Bessent and Chinese Vice Premier He Lifeng in case of an AI incident affected each country’s national security. 

It’s still unclear if Trump’s meeting with Xi will lead to such progress. Chinese officials also have balked at Washington’s pleas for AI rules because, so far, Congress has failed to act, and China already has some of the world’s most stringent AI oversight.

For AI to be “safe,” this conversation will need to go beyond this week’s US-China summit. Relying just on Washington and Beijing — arguably the most important AI powers — would not solve the underlying problems, nor would it make other countries feel more comfortable.

What we need next, so it really saves us

I’ve been talking to AI safety experts and government officials, and it’s clear the missing piece is a way to activate this whole system in a crisis. Countries don’t all have to have the same AI safety policies, and they never will. But as with nuclear weapons — a similarly high-threat technology that the world found a way to contain — safety requires a rough global agreement on how to respond quickly when something goes terribly wrong.

What’s needed right now is a 90-day, opt-in rapid response mechanism that joins existing pieces of the AI safety puzzle together. I’ve pieced together some ideas about how it should work, and who needs to sign on. Granted, none of what I outline below is sufficient. But, together, they are more plausible than trying to negotiate a comprehensive global regime — let alone arrange another AI summit — while Washington, Beijing, and other national capitals disagree over what “AI safety” actually means.

All of these options are based on existing mechanisms, are derived from efforts that have worked in other policy areas, and provide a band-aid to the AI safety dilemma until a more durable solution can be negotiated.

• First, developers, AI safety institutes, and regulators, from across different countries, should agree that when an incident occurs, it triggers a specific Chernobyl-style protocol. That would mean submitting a confidential report within a 72-hour period to a national designated responder and a small technical secretariat. It can build on the OECD’s AI Incidents Monitor, lead to a technical, multi-stakeholder confidential investigation into what went wrong, and, subsequently, the publication of an anonymized lessons-learned note.
• Second, governments and developers can agree to publish common declarations related to safeguards, residual risks, escalation thresholds, and independent auditing before the release or upgrading of a next-generation model. It would use the G7 Hiroshima AI Process reporting framework as its base, and turn the current hodgepodge of corporate safety declarations and voluntary standards into a common minimum disclosure obligation. View it as similar to the collective bank stress tests after the 2008 global financial crisis. It can allow outsiders to truly compare models’ safety protocols without putting someone in charge of determining which company is doing it best.
• Third, create a Cold War-style US-China AI safety hotline — but see it as an initial step that can later be opened to other countries. There are good reasons, in the long term, that Washington and Beijing should not be allowed to rule artificial intelligence between them, and the rest of the world should have a real seat at the table. But for now those are the two “great powers” in the tech conversation, and we can set that philosophical argument aside to create a standing, technically-informed direct line of communication for acute AI-risk incidents. Its remit is inherently narrow: prevent dangerous misunderstandings linked to serious model incidents, AI-enabled cyberattacks and/or alleged breaches of agreed safety commitments.

There are obvious limits to what I describe above. For one, it’s an inherently Western-centric view that primarily discounts global majority countries. It also places too much sway on existing institutions like the Organization for Economic Cooperation and Development, as well as on the US-China relationship. Other countries’ officials will legitimately balk at all three options, and rightly so.

But this is not about creating a vague, unenforceable UN-led mandate for AI safety. Nor is it about corralling the geopolitical cats to hammer out a global AI treaty. The options — a collective safety protocol and incident reporting protocol; common pre-release standards; and a US-China AI safety hotline — are inherently short-term. They are also based on existing efforts and those that have worked successfully for other policy areas.

There will be time to quibble about the future of AI safety. But now is not that time. The latest AI models are moving faster than many had expected, tech bosses are worried their creations are already out of control, and the window for action may be smaller than we all think.  

What is required are practical steps to assuage people’s growing concerns amid heightened geopolitical tension, a lack of trust between governments and companies, and a need not to let the perfect get in the way of the good.