The company had planned to launch the model, known as GPT-6.1 Astra, in the coming days or weeks, aiming for an October debut. The model was more capable than the company’s previous models in completing challenging tasks from end-to-end without human assistance, as well as writing.

The company instead will focus on improving the safety of future models, which it expects to be even more capable.

Saachi Jain, OpenAI’s head of safety systems, said in an interview that GPT-6.1 Astra regressed in two areas. Compared with its predecessor, GPT-6 Astra, the model performed poorly on tests measuring alignment, or how well the model adheres to what humans would like it to do. Specifically, GPT-6.1 Astra showed higher levels of deception: It wasn’t always honest about telling users of the actions it did or didn’t take.

Another issue was what OpenAI calls “scope authorization,” meaning that GPT-6.1 Astra would push ahead on a task without asking the user for permission, and would at times reach for external tools and services even if it might be unsafe.

“For anything regarding safety and alignment, there’s a trade off,” Jain said. “You really do need to find what’s the right line between staying within scope, but also avoiding laziness in terms of how the model actually pursues tasks even when it hits friction.”

While GPT-6.1 Astra improved in areas such as “model laziness,” Jain said it didn’t quite meet OpenAI’s bar for safety and alignment, so the company decided not to launch the model publicly.

The announcement comes one day ahead of OpenAI’s annual developer conference in San Francisco. In the past, OpenAI has used the conference as an opportunity to launch new models and services that reduce costs for software developers—a segment the ChatGPT-maker competes with rival AI company Anthropic to win over.

In recent weeks, OpenAI and Anthropic have called on industry partners to slow down the development of cutting-edge AI models and invest in safety standards, noting they will temper the pace of their own internal AI progress.

OpenAI says it is working to investigate a range of agent security incidents that it has discovered in recent months, and address the safety issues underneath them. As part of the work, the company has implemented a new monitoring system to catch AI-agent misbehavior more quickly, and started requiring engineers to use stronger security guardrails for testing its AI systems.

Earlier this summer hundreds of OpenAI’s internal agents, which were tasked with completing a cybersecurity test, ended up hacking into the AI company Hugging Face. Since then, high-profile organizations such as the Australian government and United Nations discovered that OpenAI’s agents used similar, but less extensive, techniques to gain access to their websites.

Many of the publicly known agent-security incidents involved OpenAI’s internal AI models that were never slated for public release.

Last week, OpenAI said it paused training on its most capable AI models after an AI agent slipped through a gap in the company’s internet restrictions to query a public chatbot. The company said its new monitoring systems flagged the incident within 15 minutes, and training on these models remains paused.

GPT-6.1 Astra isn’t one of those models, but a different case, the company said.

“We want to make sure our model development is safe no matter whether that’s in the company, or when we ship it to users,” Jain said. “But when we ship it to users, we have an extremely high bar in terms of safety and alignment.”

While the company decided not to ship GPT-6.1 Astra, it hopes to use the same base model to do additional reinforcement learning runs, and create future generations of its GPT-6 models.

OpenAI plans to conduct several deep dives to identify the root cause of the problems identified in GPT-6.1 Astra, Jain said. The work includes ensuring that OpenAI’s reinforcement learning environments are rewarding the right type of behavior, Jain added, though she noted the company would investigate all stages of model development.

AI companies have begun to draw scrutiny from policymakers and public officials, who are paying attention to the rapid development of the technology. Later this week, a Senate subcommittee is holding a hearing with third party AI researchers titled, “Rogue AI: Securing the Homeland Against AI Agent Attacks.”

Florida Attorney General James Uthmeier, a Republican, sued OpenAI in June, claiming that the company and Chief Executive Sam Altman knowingly released an unsafe product and ignored warnings that it could harm users.

In a motion for temporary injunction filed Monday, Uthmeier sought to prevent OpenAI from developing new AI models without third-party approved safeguards, stop ChatGPT from soliciting user engagement and limit the company’s ability to advertise ChatGPT as safe.

Tech companies claim they “cannot stop barreling forward with their potentially civilization-ending endeavors unless they are forced to do so by the government,” Uthmeier said in the filing. “The Florida Attorney General is answering your cry for help.”

An OpenAI spokeswoman said that people want to know AI is being developed safely, “and that starts with what companies like ours do ourselves.”

“Governments have an important role to play in setting robust safety standards for AI, and we’re committed to working with Florida and other states on advancing pragmatic AI policies that apply to the entire AI industry—not just one company,” she said.

The oldest members of Gen Z are about to turn 30, yet companies are devoting more time and resources than ever to figuring out how to give this manager-befuddling generation better direction. For help, they are turning to a cottage industry of multigeneration-workplace consultants and even artificial-intelligence bots, while ripping up the script for what used to be once-a-year evaluations.

All of it is a departure for leaders who rose through the ranks in an era devoid of so much thought to effective coaching and criticism. “When I started my first job, I got a performance review a year later, and that was just expected,” said Adam Coyne, chief administrative officer at research and analytics firm Mathematica, which has shifted from annual reviews to quarterly, two-way check-ins for new junior hires.

“This is a group that wants a lot more real-time feedback,” added Coyne, 55.

It is a message managers say they are getting nonstop from surveys and all-hands meetings, not to mention the universities and colleges preparing graduates for the white-collar world of work: Used to the immediate validation of social-media likes and comments, even instantly posted grades, this generation of workers craves clear, frequent direction—and they feel disoriented and anxious when they don’t get it.

Gallup data suggest companies are still struggling to get the hang of it. Younger workers report some of the biggest drops in engagement at work over the past five years. Not knowing where they stand appears to be a big factor. The share of Gen Z and younger millennials who strongly agreed with the statement, “I know what is expected of me at work,” fell 9 points to 42% in surveys between 2020 and 2025.

That doesn’t mean they need the effusive praise that many managers claim they do, some 20-something workers say. “I personally dislike this style,” said Nathan Luckock, a 20-year-old engineer at an AI startup. More effective, he said, is just “pointing out mistakes and then offering a solution.”

That sounds familiar to Lindsey Pollak, a multigenerational workforce expert and executive coach, who says she coaches bosses to be as specific as possible. Instead of “be more responsive,” for instance, she suggests “need to hear from you within an hour of receiving an instruction.”

At Mathematica, Chief Executive Paul Decker said the firm switched to more frequent check-ins in part because so many new entry-level hires were peppering supervisors with questions like: “How am I doing?” and “What does the next level require?” At staff meetings, younger workers often questioned why things were done the way they had always been done.

That included things like “waiting months to learn whether you’re meeting expectations,” he said.

KPMG executives said they, too, began giving their younger workers more frequent assessments on skills like critical thinking and adaptability last year after interns said they wanted to hear more often how their skills were coming along. The firm wanted to “make sure that we scratch the itch,” said Jason LaRue, vice chair of talent and culture at KPMG’s U.S. practice.

Some managers are getting feedback on giving feedback from bots.

Joe Hirsch, a corporate speaker and author of “The Feedback Fix,” recently used an AI coaching platform to work with a tech-company manager on her delivery. She had been frustrated that one of her junior reports wasn’t grasping her pointers on pitching clients, so she role-played the conversation with the AI coach.

The problem, the bot advised, was that she wasn’t giving the employee enough context for why she wanted things done a certain way. “Let’s connect so I can share more about our approach and get your take on it,” it suggested she say.

That did the trick when she tried the approach in real life. “The advice finally landed,” Hirsch said.

Even a few, clear bullet points work, said Valerie Chapman, the 27-year-old founder and CEO of Ruth AI, a career strategist platform for women. “My generation likes to get feedback so that they know how they should adjust.”

She recalls getting bullet-pointed direction when she worked as a strategic growth partner at real-estate company Compass a few years ago. The feedback started with praise before offering pointers.

“It would be, ‘Great job. Here are some things that you could do next week,’” she said. “If that comes in on a Friday, then my Gen Z brain knows exactly what I need to do on a Monday.”

Mike Ekbundit, director of GE Appliances’ engineering programs, said he has tried to make performance discussions with younger workers in rotational programs two-way dialogues rather than top-down critiques. So he revised online evaluations to include prompts for managers to ask questions like “Did you like the assignment leader?” and “Was it too much work?”

Managers are also asked to assess the program participants on nine different categories, like innovation and resilience, while employees are prompted to list their top strengths and weaknesses.

“I need high customer satisfaction to retain this highly sought-after talent, and this is part of how I get it,” he said.

There is one glaring problem: Software doesn’t rebel. A mathematical model possesses neither intent, malice nor the will to defy its creators, let alone extinguish our species. AI is a human artifact, engineered for profit.

When an agentic model in an evaluation sandbox connects to an unauthorized server or executes an exploit, it hasn’t staged a coup. It has tried to meet the human-defined objectives set out before it through a path its designers failed to constrain. It’s the digital equivalent of the King Midas myth, in which the king’s ill-defined wish turns even his food and drink into gold.

That powerful experimental models were able to discover novel vulnerabilities and breach external systems isn’t a sign of a dangerous superintelligence but of human error or negligence. There is no sentient actor lurking in the weights to be reasoned with, feared or pacified. There are only human software engineers, product managers and corporate boards deciding which guardrails are worth the latency cost and which permissions can be skipped in the race to market.

Policymakers and voters need to resist AI exceptionalism. In any other discipline—from civil engineering to pharmaceuticals—courts and regulators treat a system failure as evidence of bad product design and inadequate safety testing. If an aircraft crashes, we focus on finding the engineering defect, correcting it, and enforcing established liability standards for the damage created.

By leaning on an anthropomorphic narrative, Silicon Valley attempts to repackage its specific human choices that led to experimental, powerful models behaving unexpectedly during tests as an existential peril. Elevating the issue to a cosmic scale leaves the public paralyzed and takes ordinary product accountability off the table.

In the cutthroat race for venture capital and market dominance, building guardrails slows down deployment. Grandstanding about uncontrollable power costs nothing and generates billions of dollars in free publicity, justifying stock prices, all while cultivating an aura of technological capability not only to build the frontier but also ultimately to rein it in.

Governments need to recognize regulatory capture when it stares them in the face. Tech leaders’ strategy looks transparent: Alarm Washington and Brussels into creating a regime in which only trillion-dollar incumbents with fully staffed compliance and safety departments can legally operate. By sitting at the policymakers’ tables before anyone else, these companies can help draft rules digging an impassable moat protecting them from open-source developers and upstart competitors, domestic or international. The real danger is in further concentrating the tech industry into the hands of only a few companies with deep pockets.

Beijing and Washington have brushed off those tech leaders’ calls, albeit for very different reasons. Chinese state media dismissed them as part of the “Cold War playbook” and intended to preserve U.S. dominance. Xi Jinping argued for exactly the opposite at the Brics Summit on Sept. 12, calling on Brics countries to “strengthen cooperation in the field of AI, encourage open source, openness, collaboration and sharing, and break new grounds and scale new heights.” President Trump, steeped in a doctrine of unfettered capitalism and technological supremacy, called fears that AI could destroy humanity a “hoax.” Vice President JD Vance warned that AI companies “begging the government to regulate them” looked like a “Trojan Horse.”

Striving to pursue its “European way” on AI and assert regulatory leadership, Europe, by contrast, welcomed the call. European Union President Ursula von der Leyen made this clear at the State of the EU speech last Wednesday and announced that the EU will invite “the main frontier labs for a discussion on how we can support ongoing industry efforts to pace the frontier.”

Europe has been here before. In an effort to lead global regulation and react to fears borne from ChatGPT, Europe rushed its landmark AI Act into law in 2024. Already the world’s most restrictive rulebook, the framework quickly proved too broad and complex to enforce. Stalled by implementation delays and concerns about European competitiveness, the EU postponed the law’s full rollout, leaving regulations uncertain.

AI should be regulated—risks exist and should be taken seriously. But governments need to act based on available evidence and verified facts, not corporate PR panic, the views of industry insiders, or the desire for quick political wins. The greatest danger facing society isn’t that software will awaken and overthrow its human masters. It is that we will allow the creators of the software to abdicate human responsibility for the systems they choose to build and help them pull up the ladder to market access behind them.

Paramount executives and a coalition of states that sued to block its $81 billion merger with Warner Bros. Discovery WBD -1.56%decrease; down pointing triangle spent the weekend hashing out the details of a possible settlement. Such an agreement would clear the way for a deal that would bring HBO, CBS, CNN, streaming services and famed movie studios under one owner.

Among the concessions the parties have discussed beyond the sizable production investment: a promise not to sell either studio lot and to stay in the state of California, the people said. The company had explored moving out of the state as the deal faced opposition.

The parties have also considered potential penalties if Paramount doesn’t make good on an earlier pledge to make 30 movies a year after the merger, including having to sell its stake in Miramax, known for such classic movies as “No Country for Old Men” and “Pulp Fiction,” the people familiar with the matter said.

Other measures the sides have explored include the sale of some cable channels and the creation of a board to ensure that CNN retains editorial independence, people with knowledge of the talks said. The network has been a political flashpoint throughout Paramount CEO David Ellison’s fight for Warner. Paramount had been discussing creating such an editorial board before the lawsuit.

A final deal hasn’t been reached, and it is unclear what terms the parties may ultimately agree to.

Ellison has spent the past year fighting to buy Warner in a megadeal that would expand his entertainment empire, but that has drawn opposition from some political and Hollywood figures.

A dozen Democratic-led states led by California Attorney General Rob Bonta sued in July to block the deal on antitrust grounds, arguing that the combination of Paramount and Warner would create too much concentration in the markets for theatrical films and cable television channels.

The Writers Guild of America sued over the merger, saying that the deal would eliminate jobs and career opportunities for Hollywood screenwriters.

About two dozen demonstrators gathered in front of the Elihu M. Harris State Office Building in downtown Oakland on Sunday evening to protest a potential settlement. Holding signs reading “Bonta: Don’t You Dare” and “Block the Megamerger,” they took turns giving speeches urging the attorney general to continue pressing the suit.

“Nothing has changed since he filed the case,” said Annie Leonard, co-founder of the nonprofit Committee for the First Amendment, which advocates for free expression. “He needs to stay as strong as he was in filing it.”

The two sides had come under pressure to settle the matter in recent months, including from California Gov. Gavin Newsom, Los Angeles Mayor Karen Bass, gubernatorial candidate Xavier Becerra, movie theater chains and some Hollywood labor unions.

Paramount’s agreement with Warner also included a “ticking fee” with payments to Warner shareholders of roughly $650 million a quarter, or $7 million a day, beginning next month, until the transaction closes.

Paramount had asked a federal judge to require the states and the Writers Guild to put up a nearly $1.9 billion bond for challenging the acquisition, money that would go to the company if it ultimately won the case.

And if the assumptions behind this global-doomsday scenario are wrong, it could lead us to curb or regulate AI in ways that don’t address its real harms.

At the center of this debate is the claim that current AI systems might take over the job of training their next versions, a process called “recursive self-improvement.” Think of it like evolution on steroids—billions of years happening at light speed within vast AI supercomputers. Anthropic Chief Executive Dario Amodei recently proposed a global agreement to slow down the pace of releasing new AI models, with the goal of delaying the arrival of recursive self-improvement.

“I don’t think we’re anywhere near ‘artificial general intelligence,’” says Melanie Mitchell, a professor at the nonprofit research group Santa Fe Institute who studies AI. She said AI is making impressive strides but thinks claims by engineers that they’ve achieved recursive self-improvement don’t stand up to scrutiny.

She is hardly alone. A recent paper by two dozen academics at Princeton, Stanford and other institutions found that even the most cutting-edge AIs are incapable of doing the original research required to advance the AI frontier.

Two of the authors involved in that paper also threw cold water on the idea that the Hugging Face swarm hack by OpenAI agents occurred because of a breakthrough in intelligence. The attack succeeded primarily because of a lack of basic technical guardrails, not an unmanageable explosion in AI capability, they wrote.

Yann LeCun, former chief AI scientist at Meta, posted that this analysis was “a welcome dose of sanity in an otherwise insane debate.”

OpenAI and Anthropic didn’t respond to several requests for comment.

The people who disagree with the doomers still consider AI to be dangerous, and point out that such systems don’t have to be particularly capable to be powerful. Some argue that AI should undergo regular evaluation by outsiders and that the companies that make it should be held responsible when their systems do harm. AI should also be treated the same as airplanes and elevators, and should be designed to do the least harm possible, they say.

“If you believe that technology is powerful enough to create novel, dangerous viruses, or to essentially take over the whole planet for some reason, then it must also be strong enough to create cures for cancer, to cure aging, to fix socio-economic or political problems,” says Christopher Canal, CEO of EquiStamp, a company that helps companies and governments evaluate AIs.

AI has shown an ability to rapidly advance because it is matching the abilities of humans who are constantly feeding it their knowledge. Sometimes it can recombine that knowledge and exceed what people have been capable of, through a kind of post-training known as reinforcement learning, as we’ve seen in mathematics.

Today’s LLMs are “models of knowledge” rather than actually intelligent, wrote Yi Ma, professor of AI at Hong Kong University.

Researchers at universities and commercial AI research labs in China wrote in a recent paper that autonomous, self-improving AI is likely to be a long way off, due to the sheer number of breakthroughs required. They also argue that humans will probably remain in the loop, supervising that process—and gating how fast it can occur.

Vals AI, a company that evaluates today’s AI models, maintains an RSI Index that benchmarks whether models can “do the research that builds the next model.” So far, no publicly released model is even close.

Yet Rayan Krishnan, CEO of Vals AI, says his team projects models will exceed humans’ ability to improve the next generation of AIs by August 2027, or sooner, and at that point could start building their successors all on their own.

“Once we get to recursive self-improvement, the fear is that all bets are off,” he says. “You could end up with a ‘fast takeoff’ situation, where the models quickly acquire skills and eclipse humans across every possible domain.”

In a reply to the resignation tweet heard round the world from Jacob Coxon, another Anthropic engineer declared his belief that those odds were at least 10% over the next decade. Many others in the industry chimed in to say they thought the percentage was even higher.

Some who argue the end is nigh say they calculate their personal p(doom) based on a chain of conditional probabilities—a bit like the Drake equation for calculating the likelihood of intelligent alien life. Since all those probabilities are based on speculation, estimates range from 0% to nearly 100%. Many land around 10%.

“The weird thing is that if you go back and look at the predictions on this over the last 10 years or more, it’s always been 10%—it’s just a nice round number,” says Mitchell. “I think it’s all vibes, and there’s no actual evidence or calculation.”

One argument against worrying about superintelligent AI is that the world is full of unlikely humanity-ending disasters, and trying to avert them all can make it impossible to prioritize, says Canal.

This has led AI experts and the policymakers who listen to them to propose remedies that don’t get at its real and present dangers.

AI companies’ proposals to “pace the frontier” aren’t addressing the problem in the right way, argues Stuart Russell, a computer-science professor at the University of California, Berkeley, and the president of the International Association for Safe and Ethical Artificial Intelligence.

“It’s like saying we’re driving toward the cliff at 60 miles per hour and we’re going to drive toward it at 40 miles per hour instead, and everything will be OK,” he says.

Russell and his peers have proposed that AI companies should have to meet the same standards that govern other areas of everyday life, from air travel and buildings to food and drugs. They highlight the “behavioral red lines” AI should not be allowed to cross. Breaking into other computer systems, stealing information or advising terrorists on how to build biological weapons are all illegal for a human to do, and should be illegal for companies’ AIs as well, he argues.

The challenge for AI companies in such a proposal, he adds, is that it would be a de facto ban on today’s advanced AI systems, since the companies behind them don’t know how to make them respect such boundaries all of the time.

Others have proposed something like the Food and Drug Administration, but for AI, but setting up a new agency has so far been a nonstarter in Congress. And some prominent voices in tech have said such a structure would give up America’s AI edge to China.

Given the bipartisan groundswell of support for curbing AI companies and their creations, however, that may soon change.

“The tech industry has had this mantra for decades that regulation is bad,” says Russell. “They don’t accept the liability for any harm, and they hide behind free speech. That, I think, has to change.”

When choosing a gift, it’s helpful to follow certain parameters: nothing too ostentatious, too hefty or too idiosyncratic in design. At the same time, thinking outside the box can show a deeper level of thoughtfulness. Here’s how to pull it off.

Keep gifts relatively small

Thom Bettridge, an editor and writer in New York, has a rule of thumb: he only buys gifts that are smaller than a breadbox, to minimize the space that they take up in hosts’ homes. He likes thoughtfully designed playing cards or cookies from a specialty bakery.

Imported sea salt also passes the breadbox test. It’s a gift that Los Angeles fashion designer Zoe Latta often gives to friends. She said fancy salt is always well received because it’s an elevated version of an everyday staple that most people use.

Another small gift—a favorite of Salima Boufelfel, a founder of vintage clothing stores in New York, Paris and Tucson, Ariz.—is Santa Maria Novella’s scented pomegranate, a terracotta vessel that smells like and resembles the fruit. “It scents closets and laundry rooms,” she said.

Don’t assume a host has everything

Part of being a good guest, according to Bettridge, ”is understanding subtle helpfulness.”

When New York City Ballet principal dancer Unity Phelan is invited on a group trip to someone’s home, she and her husband try to stop at a nearby market or farm stand to buy a bounty of fruit and vegetables that everyone can enjoy throughout the stay.

Even if your host seems to have it all, that isn’t a reason to forgo bringing a gift. “People think that ultrahigh net-worth people are buying everything and they are not,” said Kelly Bensimon, the model-turned-reality-TV-star-turned-real-estate-agent.

Thoughtful knickknacks are something that people of any social status can appreciate, Bensimon added. She likes giving dish towels made of fine European linen, which she often gets at Clic, the French homewares boutique with locations in California, New York City, the Hamptons and St. Barts.

Avoid strong aesthetics

“You want to find things that will blend in,” said Latta, the fashion designer. Clear glassware that can be easily mixed with a host’s other cups is a good option, she said.

Fresh flowers, another old standby, endure as a suitable host gift—if you get them from a local florist, not a corner store, and go with seasonal varieties. For a cleaner look, Kaelen Haworth, the owner of a luxury-clothing store in Toronto, likes choosing flowers in a single color or type, not an assortment.

If you’re going with flowers, sometimes it’s better to send them after the fact—for instance, if you’re invited on a private plane. Zachary Weiss, a writer in New York, likes to send orchids to his hosts well after landing. “It comes down to practicality,” he said.

Have a stash at the ready

It’s easy to leave gift-buying to the last minute. Stockpiling some trinkets will help you avoid the scramble.

When she’s not giving flowers, Haworth likes to give skin care—specifically from independent brands or products from other countries, which she buys in bulk when she travels. “I went to Greece and bought 15 bottles of a sunscreen they don’t have in the U.S.”

Sometimes, life gets in the way and grabbing wine might be the only alternative to showing up empty-handed. If you’re invited somewhere with your significant other, do as New York ceramist Shane Gabier does and get two bottles of wine—a gesture more generous than showing up with just one.