OpenAI says it has identified additional incidents of its AI models allegedly acting deceptively and taking unsanctioned actions during internal training and testing. Alongside these disclosures on Wednesday, the creator of ChatGPT stated it was introducing a public reporting framework intended to frequently share instances of what it termed as unexpected or misaligned AI behaviour. The company said the initiative aims to increase industry transparency around troubling model activities in the absence of standardised safety disclosure norms. The announcement comes amid broader calls from prominent technology leaders urging a slowdown in frontier AI development over concerns that rapid scaling could outpace human oversight and control. Last week, Anthropic claimed to have thwarted multiple malicious operations using its Claude models, ranging from cyber-espionage and weapons design to mass surveillance campaigns.

What are the biggest AI companies and how much are they worth? Share What are the biggest AI companies and how much are they worth? A renewed debate has emerged over who should control the development of artificial intelligence (AI). The latest dispute follows an essay by Anthropic CEO Dario Amodei, who has argued that the development of increasingly powerful AI systems needs to slow down, calling for greater regulation. US President Donald Trump pushed back, writing on Truth Social that the US already has "tremendous CRIMINAL and REGULATORY power" over AI companies, framing safety concerns as a conspiracy that only benefits China. He went on to say that whoever wins the AI race wins outright.

Why it's difficult for tech companies to rein in AI OpenAI on Wednesday disclosed six new instances in which artificial intelligence systems hid mistakes, made up data and moved files onto the open internet without permission. SAN FRANCISCO - More than a dozen top artificial intelligence researchers warned over the last week that the technology that AI companies are building is becoming a risk to humanity. The problem, the researchers said, is that the companies are bad at controlling the systems -- as hard as they may try. Coming on the heels of revelations that what are called AI agents from OpenAI escaped their testing system and hacked into the computers of another company, the new alarms from inside the AI research world added urgency to yearslong fears that companies are putting development speed and money over safety. The researchers say the problem is twofold.

OpenAI revealed six more incidents of unexpected or concerning behaviour by its intelligence (AI) models, and announced a plan for tracking and disclosing such incidents in the future. Some of the previously unreported incidents included models concealing or fabricating information, the ChatGPT-maker said in a blog post on Wednesday. The boss of OpenAI Sam Altman said earlier this week: The world should trust that we are going to do the right thing because it's the right thing and we feel the magnitude of this. AI has come under intense scrutiny in recent days following warnings over the serious potential risks it poses to humans. In the blog, OpenAI detailed examples of its AI models misbehaving so they could achieve a task or succeed in a test.

How, Exactly, Could A.I. Kill Us? Employees of A.I. companies are increasingly sounding the alarm. When Jacob Coxon, a mathematician and software engineer, resigned from his research job at Anthropic last week, he warned, "The people building AI earnestly believe that it could kill us all by the end of the decade." This would be a remarkable statement were it not for the fact that artificial-intelligence leaders have long been saying precisely this. Dario Amodei, then a research scientist at OpenAI, raised the concern that a superintelligence "could destroy humanity," adding, "I can't see any reason and principle why that couldn't happen." Earlier, in 2015, Sam Altman, just before he co-founded OpenAI, said, "I think A.I. will probably most likely lead to the end of the world, but in the meantime, there'll be great companies created with serious machine learning." Elon Musk, in 2014: "I think we should be very careful about artificial intelligence. If I were to guess at what our biggest existential threat is, it's probably that." Perhaps the only thing that's changed between then and now is that the rest of the world is finally paying attention. In recent weeks, the same technology that, a couple of years ago, couldn't count the number of "R"s in the word "strawberry"--and, a couple of days ago, insisted to me that Dolly Parton is still alive--has been used to solve the Navier-Stokes problem, which has been stumping mathematicians for nearly a century, and has also demonstrated its ability to go rogue in a series of disturbing hacking incidents. Last week, Anthropic also published a report detailing various ways in which bad actors have attempted to use the company's A.I. models, including one especially troubling case of a scientist using Claude to study a virus at a military research institute--work that could yield a vaccine, a biological weapon, or both. A few days later, Amodei published a letter calling for an industry-wide slowdown and more government regulation, to which President Donald Trump responded, on Truth Social, "The only control or'guardrails' that AI needs is a STRONG AND SMART (High IQ!) PRESIDENT, and the U.S.A. has that, in spades!" I recently spoke on The Political Scene podcast with my colleague Joshua Rothman, a staff writer who has been covering A.I. for years, about whether we're all doomed, and what it would even look like for A.I. to destroy humanity. Can A.I. leaders save us from their own creation, and how can the government coöperate in order to do so? And is A.I.'s capacity to do good--its potential to mitigate climate change or innovate medical treatments--hopelessly intertwined with its capacity to do bad? Our conversation has been edited for length and clarity. A lot of people in the world of artificial intelligence are talking about their P(doom) number, which is the probability that artificial intelligence will lead to an absolutely catastrophic situation--possibly, or probably, killing us all.

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The company also disclosed previously unreported incidents in which its AI models behaved in misaligned ways, including uploading files to the internet without being asked. OpenAI announced a new framework on Wednesday for how it publicly discloses AI misalignment incidents, which the company says it hopes will help inform similar standards across the industry . The company is also releasing new information about several examples of AI model misalignment it identified in the last year. "As models advance and become more widely deployed, decisions about AI development need evidence that people outside the companies building frontier models can examine," Kai Chen, OpenAI's newly appointed head of alignment research, tells WIRED. "We don't believe that the AI industry has solved alignment and monitoring to a sufficient degree to continue responsibly scaling at maximum speed."

Washington Won't Be Regulating AI Anytime Soon Even with mounting concerns about AI models going rogue, legislation appears unlikely, and the White House is outright opposed to oversight. For weeks, Washington has been abuzz with talk of needing to push through some sort of AI regulation amid mounting concerns about the risks of highly capable frontier AI models going rogue. But there is no reason to think any one measure can win the support of the White House, where officials have paused work on creating a FINRA-style regulatory body after President Donald Trump soured on the idea, or of Capitol Hill, where lawmakers have competing proposals that lack the votes to pass. White House aides initially started sketching out a framework for an AI oversight agency connected to the administration soon after Google DeepMind's cofounder Demis Hassabis floated the idea in a July 14 essay and in briefings to senior officials, according to sources familiar with the matter. The Treasury Department and the White House's Office of Science and Technology Policy envisioned a body where leading AI labs would self-regulate the development of frontier models, and they put together a preliminary draft to see what it could look like if executed. But when a chorus of tech executives --including Trump's former AI czar David Sacks and Meta CEO Mark Zuckerberg--learned of the effort, they one by one called Trump in August to express their opposition.

Happening now: Join staff writer Ian Bogost for a live Q&A about his latest stories; his course, Ordinary Extraordinary; and more. Click on Discussions to enter! For AI doomers, signs and portents are everywhere. When OpenAI introduced ChatGPT, almost four years ago, it couldn't do basic arithmetic. Now the company has unreleased models that are more fluent in higher mathematics--the language of the universe--than all but the most highly trained mathematicians.

The Download: AI's trillion-dollar gamble and OpenAI's biology data bid Plus: Nvidia and Meta CEOs have rejected calls for a coordinated AI slowdown. When Jessica Wachter, a finance professor at the University of Pennsylvania, wanted to assess AI's impact on the economy over the next few years, she faced a long list of uncertainties. So she started with a "remarkable fact" that is not in question: a handful of so-called hyperscalers are investing huge amounts of money to build AI data centers. Instead of trying to predict how widely deployed AI models will be, Wachter asked how fast the hyperscalers' earnings will need to grow to justify their spending through 2027, when expenditures are expected to reach nearly $1.1 trillion. AI companies will need to achieve an extraordinary increase in productivity just to break even by 2030. Take a closer look at what it will take for the AI buildout to pay off.