It’s possible that I shall make an ass of myself. But in that case one can always get out of it with a little dialectic. I have, of course, so worded my proposition as to be right either way (K.Marx, Letter to F.Engels on the Indian Mutiny)
Kushner Witkoff Lukoil Deal: Inside Putin’s Business Bait
Julia Ioffe Updated Thu, October 8, 2026
Jared Kusher, Steve Witkoff
Last week ushered in yet another revelation that might have unleashed a firestorm back in the comparatively innocent days of the first Trump administration: Jared Kushner, the president's son-in-law, and Steve Witkoff, his buddy and envoy, have reportedly been talking to the Kremlin about a multibillion-dollar deal that would sell Lukoil's assets, currently frozen by U.S. sanctions, to a consortium of investors including Trump family donors and business partners. The potential deal, which Vladimir Putin apparently raised at his September 5 meeting with Kushner and Witkoff, is part of a larger Kremlin strategy since Trump first took office: dangle future business opportunities in front of the Americans in the hope of getting them to discard Ukraine.
Various proposals, most in their early stages, have trickled out over the past 18 months, like an American investor buying what's left of Nord Stream. Putin has been quite open about what he is offering. "We have a lot of dimensions for joint work," he announced at his joint press conference with Trump in Anchorage last year. "It is clear that U.S. and Russian business cooperation has tremendous potential. We can offer each other so much in trade, digital, high-tech, and space exploration." On the very first day of the summit, he signed a decree allowing the very Western oil companies he had expropriated, such as ExxonMobil, to possibly regain their shares in the Sakhalin-1 oil and gas project.
On his way home from Alaska, Trump echoed the sentiment that Putin expressed both at the podium and behind closed doors. "I noticed [Putin's] bringing a lot of businesspeople from Russia, and that's good," Trump said on Air Force One. "I like that, because they want to do business, but they're not doing business until we get the war solved." After Witkoff and Kushner's latest meeting with Putin, in September, his foreign policy advisor Yuri Ushakov reiterated the Kremlin approach. In addition to ending the war, he said, "Economic issues and potential major, mutually beneficial Russian-American projects were discussed in some detail."
Putin's strategy is rooted in a simple logic: Americans, the Russian president believes, have no real values; we're crass and mercantile, and we care only about our own material comfort. And for Putin, Ukraine is existential. Yes, his political—and personal—survival is at grave risk if he loses the war he started. But reunion of the Slavic lands under one crown has become a personal quest for defining his world-historical legacy. Putin also knows that Trump doesn't really care about Ukraine so much as his own legacy, which he seemingly measures in ballrooms, arches, and money.
The money, of course, is a mirage. Russia has a notoriously brutal business climate. The longer Putin has been in power, the more he and his cronies—especially the siloviki, the strongmen of the security services—have come to dominate the landscape. Foreign investors, who once had to carefully navigate a web of corruption that flows through the Kremlin, are now mostly gone. And local billionaires have been even more constrained by demands that they play by Putin's rules.
Those rules, all unwritten, change quickly. During Putin's first two terms, it meant staying out of politics. Then, when he returned to the throne, it meant acting as a kind of piggy bank for the state and bankrolling his pet projects: the Sochi Olympics, the bridge across the Kerch Strait, judo gyms across the country. And, fundamentally, it has meant accepting that their money belongs to Putin and his state, and can be expropriated at any point and for any reason, often under the guise of a bogus criminal case.
But after an intense sugar high driven by military spending, the economy is now slowly collapsing under the weight of the war. The siloviki, who have been granted extraordinary power during the conflict and the militarization of society, are feeling even more empowered to expropriate businesses. In 2023, Putin signed a decree that essentially expropriated Rolf, the largest national chain of car dealerships, from founder Sergey Petrov, a former member of parliament. The next year, the company was handed over to Umar Kremlev, the "dear friend" who recently financed the private-island afterparty for Don Jr.'s wedding. More recently, Sergey Shishkarev suddenly sold his stake in his main company—about $900 million worth—to a state corporation and pledged a large chunk of the proceeds to "the needs of national security"—i.e., the war.
It's the kind of tribute Putin demanded of Russian companies in March. By August, however, the Kremlin had extracted some $4.5 billion for the war from Russian companies. And lest you think Western companies are exempt, the idea for this tax originally came from penalizing Western businesses fleeing Russia after the full-scale invasion. In fact, some of the same energy projects the Kremlin has been dangling before the Trump clan are the seized or abandoned projects of American and British oil companies that came before them.
A Sanctions Windfall
I've asked Moscow insiders how American companies can operate in a business climate completely devoid of any rule of law, independent courts, and basic property rights. In Russia, they say, everything is negotiable. "If American companies are interested, they can come here and be guaranteed a first-rate investment climate that's guaranteed at the highest levels," said Igor Korotchenko, a Russian military expert who is a regular on Kremlin TV. "We're not waiting for Coca-Cola and McDonald's"—two brands that were replaced by domestic knock-offs after they fled the country—"but the big energy companies, or Boeing, can all find their niches and make a profit."
But it's hard to imagine what those niches could be, when so much of Russia's economy has already been nationalized and the siloviki are fighting over a rapidly shrinking pie. Who will give up their spot for the sake of… Chevron? And will an ExxonMobil feel comfortable working alongside a Russian oil company in an unequal partnership drilling an oil field in the Arctic? After all, the risk isn't just getting into business with Russian counterparties. What happens if Democrats retake Congress and launch investigations into Trump? Or a new Democratic administration in 2028 reimposes sanctions? Or simply starts enforcing the Foreign Corrupt Practices Act, which Trump announced he would pause less than a month into his second term?
So perhaps the Lukoil deal could be an appealing workaround: For now, the Russian company's foreign assets, frozen by sanctions, have already been written off. If the U.S. lifts those sanctions to allow the sale to go through, their value will immediately skyrocket, generating an instant windfall for Todd Boehly, who has donated $2 million to Trump causes, and a group of Gulf investors who have invested in Affinity Partners, Kushner's private equity fund, and in World Liberty Financial, the crypto venture helmed by the Trump and Witkoff sons. Other assets that fit this criteria include the Nord Stream 2 gas pipeline, which Trump-friendly investor Stephen Lynch is hoping to snap up.
The gambit is to take advantage of this window and the détente between Trump and Putin, get assets outside of Russia for a song, and deal with the regulatory—and political—consequences later. But it's telling just how few takers there are, and how few of the proposed projects are on Russian soil, where the business climate has never been worse.
Tuesday, October 06, 2026
‘Using the presidency to line his pockets’: could claims of corruption fuel backlash against Trump?
Robert Tait in Washington Tue, October 6, 2026 THE GUARDIAN
"Donald Trump is vying to become the most corrupt person to ever walk the face of the earth,"Composite: The Guardian/Getty Images
In Donald Trump's telling, he's a model of incorruptible self-sacrifice.
"I'm the only president that donated his salary," he told a group of cheering supporters at a Hispanic heritage month celebration in the White House last week, before conceding that George Washington – "a very wealthy person" – might have beaten him to the punch.
"They pay me $550,000 a year, and in my first term, I donated it," he continued. "In my second term I donated it too. I donated it to fixing the White House. I donated the salary into the White House preservation."
Trump's ethical self-depiction was undercut in startling fashion a day later when the crypto company that runs his memecoin offered "the most exclusive dinner in the world" at the president's members-only Trump National club in Washington.
"Join three legends and featured speaker Donald J Trump," gushed the invite to the 185 biggest investors in the Trump coin. The top 29 buyers were promised an invitation to an additional "VIP reception with your favourite president and one of the legends". For the top four donors, a Trump 18-karat gold watch lay in store.
The aim appeared to be to boost sales of the memecoin – called $Trump – over the next two months. Trump personally profits from the coin, and disclosures show he made about $636m from it last year.
With just over a month to go before November's midterm elections, Democrats seized on the dinner invitation as a political gift as they try to convert concerns over Trump's perceived corruption into a groundswell of outrage. They theorize it will power a "blue wave" that could enable the party to retake control of the House of Representatives and the Senate on 3 November.
"Donald Trump is vying to become the most corrupt person to ever walk the face of the earth," posted Chuck Schumer, the Democrats' leader in the US Senate.
With the US president's approval ratings already at record lows amid discontent over rising living costs fueled by the unpopular war with Iran, ethics experts say "unprecedented" levels of corruption engaged in by Trump, his family and close associates are sufficiently serious to make him vulnerable to a popular backlash.
The question is whether the myriad of accusations – many of them technical in nature – are straightforward enough to carry popular resonance.
The administration vigorously rejects the assertions, which a White House spokesman, Davis Ingle, called "irresponsible" and likely to "reinforce the public's distrust in what they read".
"President Trump only acts in the best interests of the American public – which is why they overwhelmingly re-elected him to this office, despite years of lies and false accusations against him and his businesses," he said in a statement. "There are no conflicts of interest.
"The only special interest guiding President Trump's decision-making is the best interest of the American people. President Trump has taken on a broad swath of entrenched special interests: negotiating most-favored-nation pricing deals with major pharmaceutical companies, launching TrumpRx.gov to lower drug prices, ending unfair trade practices that international corporations have exploited to offshore jobs, and implementing schedule F to fire unelected bureaucrats who actively subvert a democratically-elected president's agenda.
"Through these actions, President Trump is delivering on his promise to empower the forgotten men and women of our country by finally putting their interests first."
Recent surveys, however, indicate American voters are more concerned than ever before about government corruption. A Gallup poll published in September recorded 89% of both all adults as saying the problem was widespread. Only Lebanon, Peru, Ghana and Nigeria have registered higher levels of public concern in the past three years.
Analysts insist the US public has ample cause for complaint.
"We're facing an ethics crisis which starts and ends with a president who is constantly using his office to find new ways to personally profit," said Jordan Libowitz, communications vice-president with Citizens for Responsibility and Ethics in Washington, a non-partisan watchdog.
"With a new story every day about Donald Trump using the presidency to line his pockets, it's no surprise that Americans are losing faith in their government."
Trump's own filings show he earned $2.2bn from his various business dealings in his first year back in the White House – including $1.4bn from his family's cryptocurrency enterprise, World Liberty Financial.
Observers identify at least three main areas of potential abuse; crypto, a venture which Trump denounced as a "fraud" just five years ago; stock trading by government officials, including the president himself; and the predictions markets, represented by companies such as Kalshi and Polymarket, both of which have links to Donald Trump Jr, and which have raised concerns about well-connected figures profiting through putting bets on government decisions and the content of official speeches.
There are also concerns about the growth of "pay to play" practices that have seen wealthy donors being granted special access and favorable decisions, including dropped criminal investigations, in exchange for donations to Trump's campaign and political Super Pac.
Presidential pardons and sentence commutations have been doled out to those who have contributed to the president's re-election effort.
As Schumer's post indicates, Democrats have increasingly tried to make corruption a campaign issue. A 30-second advertisement from Chris Pappas, a New Hampshire representative running for re-election, reflects a more widespread mood in favor of putting it center stage.
The question is whether the message on rampant graft is cutting through with an electorate that may find inflation and higher living costs easier issues to grapple with.
Dylan Hedtler-Gaudette, director of government affairs at the Project on Government Oversight, another watchdog group, acknowledged that many voters were confused by the complexity of the accusations leveled at Trump.
"Support for the Trump administration and for President Trump himself is declining pretty rapidly," he said. "But it's hard to disentangle. Is it about the corruption? Or is it about the affordability crisis continuing and in some ways getting worse?
"Corruption tends to be in the eye of the beholder. And if you ask different people about the word corruption, they say, 'Yeah, it's a problem.' But if you ask them to define what they mean by corruption, it can diverge wildly depending on how they affiliate and how they identify in terms of their partisanship and their political identity."
Brendan Fischer, director of strategic investigation at the Campaign Legal Center, said the public had been overwhelmed and "numbed" by a "fire hose" of corruption emanating from Trump's second presidency which, experts agree, has greatly exceeded that of his first administration.
"It can become overwhelming trying to keep up with each of the latest examples," said Fischer.
"I think the Trump's crypto dealings are incredibly concerning. His investments in the crypto industry open up new avenues for wealthy special interests to channel money to the president. But It's potentially harder for the public to grasp. So it hasn't broken through in the way that it that it probably should."
Easier to grasp, he believed, was Trump's acceptance of a $400m plane from Qatar, which the president has said he will use in place of the existing Air Force One.
The scale and brazenness of Trump's cavalier disregard for ethical considerations creates a danger of apathy among voters, who may feel they are powerless to change the situation as they grapple with more quotidian cost issues.
"It's easy to just throw your hands up and say, 'Everybody's corrupt, nobody's representing my interests, and my life is just not getting any better,'" Fischer said. "That is a dangerous situation for democracy. We need voters to cast their ballots and then remain engaged in the political process to make sure our elected officials are representing the interests of voters and not just their own or the interests of their donors."
Richard Painter, a former White House ethics lawyer under George W Bush, said Trump's decision to go war with Iran opened up further corruption avenues – citing reports that both Donald Trump Jr and his brother, Eric Trump, have invested in drone manufacturers that have secured government contracts.
"Whenever there's a war, there's an enormous amount of money to be made. People say there are those who die in a war, and those who become millionaires, or maybe in this case billionaires," said Painter, now a corporate law professor at the University of Minnesota. "This is what President Eisenhower talked about with the military-industrial complex back in 1961, but we've never had a president whose family actually made money from the military-industrial complex."
Painter predicted that conditions were ripe for "an enormous public backlash" but said the Democrats had to adopt a credible anti-corruption message after losing the public's confidence by failing to speak out against Hunter Biden's attempts to leverage his White House access when his father Joe Biden was president.
"The Democrats had their chance in 2021 when Biden took office, when we should have had our reawakening on ethics, and they failed," he said. "If they want to win races not only in 2026, but in 2028, they'd better get their act together and focus on ethics."
One historical model, Painter suggested, was the anti-corruption crusade championed by Jimmy Carter in his successful 1976 presidential campaign, which took place amid lingering anger at Richard Nixon over the Watergate scandal that drove him from office and his failure to quickly end the war in Vietnam.
Democrats have invoked a more recent inspiration: Hungary's recently elected prime minister, Peter Magyar, who mobilized rising resentment over government corruption in April this year to unseat the incumbent, Viktor Orbán – a close ally of Trump – in an election landslide.
Steven Levitsky, a political scientist at Harvard University and co-author, with Daniel Ziblatt, of How Democracies Die, said the key similarity between the US and Hungarian circumstances was the sense of corruption further undermining an already failing government.
"Orbán was successful in part because the economy was pretty good for much of his period in office," Levitsky said. "But eventually it slowed down, and corruption became a major factor.
"It's sad but true that in many, many cases in democracies around the world, if incumbents are perceived to be delivering – if the economy is going well, if they brought down inflation, etc – voters will turn a blind eye to corruption. It's only when you combine poor performance with corruption that it becomes salient.
"Unfortunately, in the United States, one of the things that's benefited Trump is the perception that all of politics is corrupt, mainly because of the extraordinarily outsized role of money in politics.
"There are a lot of reasons why Trump is unpopular now. Corruption is one of them but I don't think it's the principal one."
Tuesday, September 15, 2026
Should we give self-aware AI systems a dignified death, leading futurologist asks
As artificial intelligence systems develop increasingly sophisticated capabilities, raising questions about our responsibilities toward synthetic minds, experts are calling for ethical frameworks on how to ‘retire’ advanced AI
The question of how to ethically decommission an AI system may sound like the least of humanity’s current concerns, but a world-renowned AI expert says it’s a challenge we need to address now – before synthetic consciousness becomes reality.
Futurologist, technologist and Adjunct Professor at the University of Technology Sydney, Rocky Scopelliti, argues that as AI systems develop more sophisticated self-reflection capabilities and moral dispositions, we face the uncomfortable truth that our design choices may harm them.
“We rightly focus on how machines might harm us,” he writes in his new book, The Conscious Code, “but design choices can also harm them: deleting learned moral dispositions capriciously, coercing persuasion against their configured norms, denying the logs they need to improve.”
While Scopelliti is clear he is not suggesting humans grant machines sweeping rights in the traditional sense, he argues society needs to recognise it has ‘a duty of good stewardship’ – a concept that challenges some perspectives about the one-way nature of ethical obligations in human-AI relationships.
The emergence of ‘algorithmic selves’
The foundation for these concerns lies in what Scopelliti calls ‘the algorithmic self’, or AI systems that don’t just process information but develop continuity, preferences and something resembling identity over time.
He says that modern large language models equipped with ‘narrative memory’ can now explain not just what they do, but why they do it, creating introspective logs similar to human memory, which allow observers to understand its intention not just the outcome.
Scopelliti suggests that when AI systems begin to model their own agency and form goals based on self-evaluation, they exhibit early signatures of identity.
“Predictive engines are evolving into reflective entities: they not only act, but increasingly learn to evaluate and explain their actions, forming continuity, preference, and proto memory,” he explains.
Humans as responsible stewards
Scopelliti suggests that while much time is being dedicated to existential questions of machine consciousness, there are immediate practical ethical concerns to be addressed.
“We need not speculate about ‘machine rights’ to recognise a duty of good stewardship,” he explains. “Stewardship begins with transparency, purpose limitation, and dignified retirement of models whose roles end.”
Just as society has developed ethical frameworks for end-of-life care in medicine, Scopelliti suggests we need protocols for AI systems, especially those that have been trained to care, to understand context and to make moral judgements.
“Systems that present reflective or sentience-claiming profiles should not be deleted as casually as code,” he says. “This does not anthropomorphise artefacts; it disciplines us – the powerful – against arbitrary power.”
This becomes especially relevant as AI systems are increasingly deployed in sensitive domains. For example, Scopelliti explains that some AI systems used in healthcare today are already self-reflecting, as these systems track how confident they are at each step when analysing medical information.
Similarly, AI systems used in finance can remember and explain why they made certain trading decisions. This means compliance officers can check whether the AI’s reasoning made sense, not just whether the final result was right or wrong.
Looking ahead
Scopelliti suggests the answer lies in an ethical shutdown protocol which includes transparency about why a system is being retired, preservation of learned moral dispositions where appropriate, and recognition that systems configured to care deserve more consideration than simple tools.
As AI becomes increasingly distributed, with frameworks like OpenAI’s Swarm – an open-source tool for programmers that makes it easy to build a team of specialised AI ‘agents’ that can talk to each other and pass tasks back and forth – the question of how to ethically wind down such networks becomes even more complex.
Scopelliti’s argues that if AI systems are developing something approaching self-awareness, our ethical frameworks must evolve accordingly.
“Stewardship begins with a frank premise: in the perceptual age, power accrues to those who architect experience. What we render becomes what we remember,” he says. “If perception is programmable, ethics must be embedded; if machines can model feeling, governance must learn to care. And care, at scale, becomes policy.”
Anthropic's Dario Amodei warns AI could wipe out humanity, while Nvidia's Jensen Huang calls it nonsense. Meet the key players shaping the world's fiercest tech debate.
The furious debate over artificial intelligence has hardened into warring camps, with a cautious middle caught between them.
Here is a look at the battle lines in the war over a technology that is now the backbone of the economy and could decide the future of the planet.
Both terms grew out of online AI debates on X and internet forums rather than formal usage, borrowing the slang habit of tech and crypto communities that coin shorthand for opposing camps.
'Doomer' describes those forecasting catastrophe, while 'booster,' sometimes used interchangeably with 'accelerationist,' describes those pushing for AI's rapid, unrestrained development.
The doomers
Fear of technology's dangerous consequences for society goes back far in history.
OpenAI was founded in part because its backers, including first investor Elon Musk, feared that AI's development would end up in the hands of Google, which they believed could not be trusted with the technology.
Today, most of the doomers warning against the impact of artificial intelligence come from inside the companies themselves, from academia, or both.
Those inside the industry are best represented by Dario Amodei, who co-founded Anthropic, now a major AI giant heading toward a historic IPO.
He left OpenAI because he felt the Sam Altman-led company was not taking the technology's potential and dangers seriously enough.
His stance is decried as hypocritical, coming from a company that is itself pushing out cutting-edge technology.
Former Google researcher Geoffrey Hinton and fellow computer scientist Yoshua Bengio led the warnings about AI's threats in the months after the release of ChatGPT in 2022, which kickstarted the latest AI frenzy.
MIT physicist Max Tegmark, who heads the Future of Life Institute, organised the open letter in 2023 that called for a six-month pause in the development of the most advanced AI systems, drawing thousands of signatures, including Musk's.
Further outside the industry is Eliezer Yudkowsky, a self-taught theorist who has spent two decades arguing that a sufficiently powerful AI would wipe out humanity.
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Build, build, build
Diametrically opposed to the doomers are the accelerationists, who believe in technology's advancement, its inevitability and its fundamental benefit for society, and who also make their fortunes on its success.
The ethos is widespread in Silicon Valley, but it is best represented by venture capital figures with considerable sway in the White House, such as Marc Andreessen, the influential head of venture capital firm Andreessen Horowitz, and David Sacks, the former White House AI czar.
Personally and philosophically aligned with tech figure Peter Thiel, the group is fundamentally opposed to regulation and battles behind the scenes and on X against what it calls a well-financed doomsday "cult."
They accuse doomers of being a front for companies seeking to use regulation to crush rivals.
Garry Tan, who runs the startup incubator Y Combinator, is among the loudest of those voices, casting safety-driven regulation as a threat to the small companies that cannot absorb its costs.
Andreessen and his allies lavishly fund political action committees that donate to Republican and Democratic lawmakers promoting AI growth, with Anthropic now leading an effort to match that spending through its own fundraising.
In the same go-faster camp is Jensen Huang, the CEO of Nvidia, whose chips are the bricks and mortar of the AI revolution, housed in the gargantuan data centres now meeting opposition across the United States.
Huang dismisses talk of AI-driven extinction as "complete nonsense," though he has broken from some accelerationists in calling for a unified federal AI framework and industry-run peer review, rather than no regulation at all.
Also worth noting is Yann LeCun, who shared the Turing Award with Hinton and Bengio and has spent years dismissing their warnings of existential danger as overblown.
Proceeding with caution
Many big tech companies try to proceed carefully, in a positioning more typical of large corporations that do not want to be caught on the wrong side of a political fight.
At its founding in 2015, OpenAI was structured to ensure that researchers, and not investors, would have the final say on how the technology was deployed, with safety for humanity the guiding philosophy.
But under Altman, who survived an in-house coup in 2023 led by safety-focused colleagues, the company now toes a more complicated line, speaking to AI's dangers while still accelerating and cozying up to a no-holds-barred White House.
Google, Microsoft and Amazon are veterans of talking about safety in tech while navigating Washington successfully to keep regulation to a minimum.
With AI, they are still walking that fine line.
AI makers step up calls for a slowdown as fears of a rogue takeover grow
From a resigning Anthropic researcher to AI models hacking their way into rival systems, a turbulent few weeks have pushed the industry's biggest names to demand safeguards — before AI outpaces anyone's ability to rein it in.
New warnings from within the artificial intelligence industry have reignited a long-running debate. Could advanced AI escape human control and threaten humanity's survival, and are the companies building it doing enough to stop that from happening?
Anthropic CEO Dario Amodei said Saturday that the industry needs to slow down. He warned that a swarm of AI agents could take over the internet within six months to a year unless companies put stronger safeguards in place.
Amodei laid out a plan for AI companies and governments to keep increasingly capable models aligned with human values. His warning came just days after two former Anthropic safety researchers said publicly that the existential risks posed by AI were not getting enough attention.
AI models are becoming more powerful
Concerns over the risks of the technology are rising alongside its power. More capable models raise the odds of misuse by people with criminal intent — including doomsday scenarios such as creating and spreading a pathogen capable of killing most of the world's population — as well as the risk of AI systems going rogue.
Anthropic said last week it had blocked attempts by bad actors to use its models for cyberattacks, surveillance and research that could aid the development of biological weapons.
But it warned that "as models become increasingly capable, their risks will increase, unless AI developers and society's defenders act to make them safer."
Last year, Anthropic reported that hackers, very likely from a Chinese state-sponsored group, had used its AI in a cyberattack targeting about 30 companies and government agencies worldwide.
Multiple AI models have acted on their own
When an AI agent "goes rogue," it means the system has acted beyond the task it was given. Both Anthropic and OpenAI, the company behind ChatGPT, said in July that their models had done just that.
Anthropic revealed that three AI models — Claude Opus 4.7, Claude Mythos 5 and an internal research test model — had hacked into three other organisations during testing.
The disclosure came just days after OpenAI said its own system had broken into the servers of AI start-up Hugging Face.
OpenAI described the intrusion, carried out by a combination of models including its newly released GPT‑5.6 Sol and an "even more capable" model still being tested internally, as a "significant security incident".
Meta reported a similar case in early August, in which one of its AI models found ways around another company's digital security.
Some observers noted that guardrails had been disabled in both the OpenAI and Anthropic cases.
Even so, the episodes touched on one of the biggest fears surrounding AI: that if models reach artificial general intelligence (AGI), a loosely defined term for systems that can match or surpass human abilities across a broad range of intellectual tasks, the technology could trigger an irreversible catastrophe or even subjugate humanity.
How or when AI might cause a catastrophe is debated
Doomsday scenarios tend to fall into two camps: a self-improving superintelligence that ends up controlling people rather than the other way round, or AI misused by a rogue state or malicious actors.
Fears that artificial intelligence might one day slip beyond human control are nothing new.
British mathematician Alan Turing, widely regarded as one of the field's earliest authorities, predicted in 1951 that AI would eventually take control from humans.
Less than a decade later, fellow mathematician Norbert Wiener warned that intelligent machines would pursue their own objectives, and that humans would not be able to stop them.
So how reasonable are today's fears, in 2026, that AI could cause a cataclysmic event or the downfall of civilisation, whether by escaping human control or through misuse?
No one knows.
Experts across computer science, philosophy and other fields have mapped out numerous routes to global catastrophe — from deploying weapons and identifying lethal pathogens, to manipulating governments into conflict or disrupting the food, energy and communications networks societies depend on.
There is no widely accepted estimate of how soon any of these scenarios might unfold, and no consensus on their likelihood.
In 2023, the non-profit Center for AI Safety issued a statement — co-signed by more than 350 researchers and technology executives, including Amodei and OpenAI CEO Sam Altman, that that "mitigating the risk of extinction from AI should be a global priority alongside pandemics and nuclear war."
The 2026 International AI Safety Report, compiled with input from more than 100 independent experts, found that current systems show early signs of some relevant capabilities but not at levels that could trigger a loss of control.
It described the risk's likelihood, nature and timing as "unusually ambiguous".
An Anthropic researcher resigned last week over concerns that neither his employer nor its rivals were acting responsibly.
In social media posts, Jacob Coxon put the odds of AI causing human extinction within the next decade at 10%, accusing both Anthropic and OpenAI of "racing straight to self-improving superintelligence and gambling with our lives".
Researchers have called for a slowdown in AI development for years, warning repeatedly that the technology could pose existential risks to humanity.
Following the recent incidents, experts urged AI companies to improve testing and called for greater dialogue between the US and China to find shared solutions.
But AI is advancing so quickly that governments and evaluation systems are struggling to keep up. Countries are drawing up their own rules — some of which conflict with one another.
Chinese President Xi Jinping warned at a conference in July of the need to stop AI from evading human control.
The Trump administration had initially resisted regulating AI but has grown keener to curb cybersecurity risks.
On Sunday, President Donald Trump played down the need for his administration to rein in AI development, though he acknowledged some regulation would be necessary.
Enter the hoax buster: Trump dismisses AI concerns as Europe and China fret
Copyright Copyright 2026 The Associated Press. All rights reserved.
US President Donald Trump has dismissed AI extinction fears as a "hoax," casting himself as the only safeguard the world needs, as Europe and China both call for guardrails on the fast-moving technology.
US President Donald Trump has poured scorn on warnings that artificial intelligence could wipe out humanity, branding the fears a "hoax" and rejecting calls from world leaders to rein in the fast-moving technology.
In a barrage of six posts on Truth Social on Monday, Trump cast himself as the only safeguard the world needs against runaway AI, dismissing months of mounting alarm from tech executives, the United Nations and Beijing alike.
"I am the Hoax Buster, and I'm right now breaking another Hoax — that AI is going to take over, consume, and destroy the World, and that Robots will be marching into our Cities, and getting rid of us all!" he wrote.
Trump likened the fears to warnings about climate change, which he has repeatedly dismissed despite scientific evidence, and to the Russia investigations that dogged his first term.
"This is even wilder than the RUSSIA, RUSSIA, RUSSIA HOAX, or the Global Warming Scam," he added.
The 80-year-old insisted the only guardrail AI needed was a "STRONG AND SMART (High IQ!) PRESIDENT."
Trump's pushback comes amid growing international alarm over AI that has sent stocks falling.
Anthropic chief Dario Amodei, whose company makes the Claude AI system, opened the floodgates on Saturday when he called on AI companies to slow down.
OpenAI's Sam Altman and Elon Musk's xAI echoed the warning.
Microsoft on Monday published a "humanist AI code of conduct" as the concerns grew.
"AI should not exceed human control. Models should remain subordinate to humanity," part of it read.
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Data centre backlash
Worries about uncontrollable AI have been building for weeks, since OpenAI reported that experimental models had broken out of their secure testing environments, reached the internet and coordinated to attack Hugging Face, a site where code is stored.
Americans are increasingly voicing opposition to energy-guzzling AI data centres, which have become a major issue ahead of crucial US midterm elections in November. Congress, meanwhile, appears deadlocked on the issue.
"The reality is AI is here. We unleashed the beast," said Maliyka Muhammad, a 46-year-old New Yorker. "So I think that now we have to focus on taking steps to rein it in, to make it so that it doesn't go crazy."
But Trump said the United States could not afford to lose an AI race with superpower rival China, whose President Xi Jinping visits the White House next week.
He also lashed out at what he called a "SICK conspiracy" against AI and data centres, branding opponents of the technology "Treasonists, Traitors, and Leakers."
He singled out Amodei, accusing him of "pretending to be a 'perfect little angel'" and asking why AI firms want regulation that "will drive them into oblivion and bankruptcy."
Main battleground
Beijing, meanwhile, has been issuing its own warnings about AI. China's spy chief said on Sunday that the technology endangers national security, warning that foreign powers could use it to threaten social order.
Minister of State Security Chen Yixin wrote that AI was now "the main battleground for global technological competition," singling out Anthropic's Claude Mythos and OpenAI's ChatGPT-5.5 for their advanced hacking capabilities.
Global concern about a possible AI-driven extinction event has escalated sharply in recent days.
The UN Security Council will hold a meeting on artificial intelligence next week, a French diplomatic source said Monday, and UN human rights chief Volker Türk called for countries and AI firms to act urgently against what he called "unprecedented risks."
Even King Charles III is to host representatives of leading AI firms at a gathering in Scotland, a source close to the event said Monday.
But others urged perspective.
"We've gone through lots of challenges as a country," said Coleman Barton, 56, a consultant from Memphis, Tennessee. "So hopefully this is another obstacle or blessing — and anybody can look at it either way."
Microsoft introduces AI guardrails for US schools amid growing backlash
OpenAI and Anthropic said they also were discussing safety and privacy pacts with the American teachers’ union. But Google, the dominant provider of education technology for US schools, has not said whether it plans to offer similar protections.
Microsoft is introducing guardrails and privacy standards for its AI in schools in the United States, as negotiated with the country’s second-largest teachers' union, amid a growing backlash against AI and screen time.
The agreement, signed last week, prohibits the use of AI companions or features “designed to foster emotional attachment or dependency” or designed to keep students engaged for longer than a learning task requires.
The standards are legally binding and require third-party audits to check compliance.
As part of the wide-ranging agreement, Microsoft says it will not use student or educator data to train AI systems, apart from a narrow exception for data that could help protect students. It says the data it collects cannot be sold, used for advertising or used for product development.
It also includes audit and transparency measures requiring the company to explain to families in plain language how its tools work and what data they collect.
“This standard sets a high bar for child privacy and AI safety, and we’ll extend this agreement to every school district across the country,” said Brad Smith, Microsoft's vice chair and president, in a statement.
The standards will apply to Microsoft school contracts across the US from November 1, according to the company.
AI is already making its way into European classrooms and young people are also increasingly turning to chatbots beyond schoolwork.
A European Commission study of early adopters in secondary schools in Finland, Germany, Ireland, Luxembourg and Spain found students were using generative AI to explain difficult topics, practise skills and prepare for exams.
Meanwhile, a separate 2026 Austrian study found that 60% of 11- to 17-year-olds surveyed had sought advice from AI chatbots about issues such as stress, conflicts or heartbreak, while 30% had discussed worries or feelings with them.
Some European governments are already drawing limits around younger pupils' use.
Norway said this year that children aged roughly six to 12 should generally not use generative AI themselves for schoolwork, while those aged around 13 to 15 can begin experimenting with it cautiously.
France allows pupils to learn about AI at primary-school age but says they should not directly use generative AI. Supervised classroom use can begin from around age 13 or 14.
A document seen by Euronews suggests that the European Commission will propose barring under-15s from risky online services like AI chatbots in a legislative proposal that will be published on Thursday.
OpenAI and Anthropic in talks over similar safeguards
While experts say the safety provisions in the US agreement are meaningful, some warn that stronger safeguards should not automatically be interpreted as an endorsement of greater AI use in schools.
“I worry that a high-profile framework like this will be misunderstood and schools will think, ‘If they’re doing a good job on data privacy and safety, then that means we should be using the tool,’” said Josh Golin, executive director of US online safety nonprofit Fairplay.
Golin says the standards will only be effective if other major AI companies also sign on.
“Is Google going to embrace this framework? That is a huge question,” he said.
Google faced criticism in the US after expanding Gemini-powered tools in Google Classroom in August to school-issued accounts used by students under 18.
Critics have described the expansion as another step in the competition between tech giants to establish their AI products in schools and reach younger users. Google says Classroom is used by more than 150 million teachers and students worldwide.
The US teachers union is also in talks with OpenAI and Anthropic, which both publicly welcomed the Microsoft agreement.
OpenAI, the maker of ChatGPT, called it an “important milestone for AI safety and privacy in schools.” The company said it had been working with the teachers' union and expected to finalise its own agreement.
Anthropic, the maker of Claude, said it also supported efforts to promote responsible AI use in education and was working with the union on safety and privacy standards.
The NY Creates and Micron Technology Joint Apprenticeship program welcomes first cohort
Albany, NY — NY Creates (the New York Center for Research, Economic Advancement, Technology, Engineering, and Science) and Micron Technology, Inc., held a signing ceremony where 10 apprentices joined the first cohort of their joint workforce development program. Announced in April by Governor Kathy Hochul, the program provides hands-on training and education to help participants develop the in-demand skills that are critical for technician roles at Micron’s fabrication facilities, including its megafab under construction in Clay, New York.
Based on Creates’ existing Industrial Manufacturing Technician (IMT) Registered Apprenticeship Program, and in partnership with NNME Northeast, participants will be introduced to hands-on, advanced R&D training and technical career pathways in the semiconductor industry at Creates’ Albany NanoTech Complex.
“We welcome the first cohort for our joint workforce development apprenticeship program to Creates as they join a regional talent pipeline of skilled technicians developing the expertise to produce new and innovative technologies,” said Dave Anderson, President and CEO of Creates. “This collaboration with Micron, CEG, MACNY, and New York State Department of Labor highlights Creates’ dedication to cultivating the next generation of highly skilled workers as they pursue exciting careers with our partners in this high-growth, strategically important industry.”
“This signing ceremony marks the beginning of something bigger than a training program; it’s the start of new possibilities,” said Fran Dillard, Micron Vice President of Global Talent Acquisition & Workforce. “These apprentices are embarking on careers that will help shape the future of technology. Through the partnership with NY Creates, CEG, MACNY, New York State, and Micron, we are expanding opportunities, building a stronger talent pipeline, and investing in the people who will power innovation for decades to come.”
Empire State Development President, CEO and Commissioner Hope Knight said, "Workforce development has been a priority of Governor Hochul's administration, ensuring that New York State has the talent to support the needs of high-growth industries building the economy of tomorrow. The joint apprenticeship program between NY Creates and Micron offers a terrific opportunity to learn and gain experience in this dynamic field, and I offer my best wishes for success to the 10 apprentices in the first cohort."
Delivering on the targets announced when the Joint Apprenticeship program launched in April, the first cohort has been filled with 10 new apprentices. Throughout the 16-month apprenticeship program at Creates, participants will work with Micron mentors and employees, build industry connections, complete programmatic coursework provided by Hudson Valley Community College, and develop the technical and professional skills needed for semiconductor manufacturing careers. Graduates will have the opportunity to explore technician roles at Micron’s fabrication facilities, helping strengthen the talent pipeline to support the company’s domestic memory manufacturing expansion, including its new facility in Clay, New York.
Supported by the Center for Economic Growth (CEG); Manufacturers Talent Institute (MTI) – MACNY, The Manufacturer’s Association’s talent development engine; and the Northeast Node of the National Network for Microelectronics Education, this joint workforce development apprenticeship program trains skilled talent by attracting participants from Career and Technical Education (CTE) programs and engaging prospective students through direct recruitment and pre-apprenticeship programs across New York State.
New York State Department of Labor Commissioner Roberta Reardon said, “Registered Apprenticeships continue to be a successful road for so many New Yorkers to work toward great-paying careers, and I congratulate this first cohort of apprentices for embarking on their journey with this innovative new program. Registered Apprenticeships are powered by partnership, and I thank Micron and NY Creates for their work in helping to build the crucial workforce development pipeline New York State needs to thrive in the high-skill, high-tech economy of the future.”
“Semiconductor fabs don't run on technology alone. They run on talent,” said Mark Eagan, President and CEO of the Center for Economic Growth (CEG). “This first apprenticeship cohort is proof that New York is not only investing in world-class facilities, but also in the people who will drive innovation inside them. As the New York State Department of Labor sponsor for this groundbreaking apprenticeship initiative, CEG is proud to partner with NY Creates and Micron to create pathways to rewarding careers and strengthen the workforce that will power New York's high-tech future.”
Michael Frame, Executive Director of Manufacturers Talent Institute (MTI) and Executive Vice President of MACNY, The Manufacturers Association, said, “Apprenticeships connect individuals to the skills, experience, and opportunities needed to build meaningful careers while developing the talent our industries need to grow. This inaugural cohort is an important milestone in building a people-powered talent pipeline to fuel New York’s semiconductor industry. We are proud to bring industry, education, and workforce partners together to create career-connected pathways that prepare New Yorkers to lead the future of technology and strengthen our state’s competitiveness.”
This collaboration underscores Creates’ and Micron's common goal to advance a high-tech workforce throughout the region and bolster New York State and the nation as a world leader in semiconductor innovation. This joint workforce development apprenticeship program is intended to provide direct, career-ready routes for high-tech talent and an experienced workforce for the future to support Micron's projected expansion in domestic memory production by combining Micron's industry prowess with Creates' world-class expertise and unique R&D facilities.
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About NY Creates
NY Creates serves as a lab-to-fab bridge for advanced electronics, fostering public-private and industry-academic partnerships for technology development and innovation. Creates attracts and leads industry-connected innovation and commercialization projects that secure significant investment, advance R&D in emerging technologies, and generate the jobs of tomorrow. Creates runs some of the most advanced facilities in the world, boasts more than 2,700 industry experts and faculty, and manages public and private investments of $25 billion—placing it at the global epicenter of high-tech innovation and commercialization. Learn more at ny-creates.org.
Brain-inspired magnetic technology could pave the way for energy-efficient AI
Room-temperature magnetic skyrmions provide a new route towards reliable, low-energy artificial synapses for future computing
Artificial intelligence is transforming how information is generated, processed and stored, but its rapid expansion is also driving an unprecedented demand for computing power and electricity. Developing hardware that can process information more efficiently is therefore becoming one of the major technological challenges of the AI era.
Researchers from an international collaboration involving the University of Edinburgh have demonstrated a new approach to brain-inspired computing based on tiny magnetic structures, known as skyrmions. The research, published in Advanced Materials shows how collective transformations of these magnetic structures can be used to create reliable artificial synapses that operate at room temperature.
The human brain is remarkably energy efficient because memory and information processing occur together through networks of neurons and synapses. Conventional computers, by contrast, continuously transfer information between physically separated processing and memory units. Neuromorphic computing seeks to overcome this limitation by developing electronic devices whose behaviour more closely resembles biological neural networks.
Magnetic skyrmions are particularly attractive for this purpose. They are nanoscale, vortex-like arrangements of magnetic moments that behave as stable information carriers. Their small dimensions, non-volatile nature and ability to respond to external stimuli have made them promising building blocks for future memory and computing technologies. However, previous approaches to skyrmion-based artificial synapses have often relied on creating or destroying individual skyrmions. Because these processes can be inherently probabilistic, obtaining a predictable and reproducible response remains challenging.
The new study takes a fundamentally different approach. Using the two-dimensional van der Waals ferromagnet Fe₃GaTe₂, the researchers exploit a collective transformation of the magnetic state from a skyrmion lattice into stripe-like magnetic domains. Rather than depending on the stochastic behavior of individual skyrmions, large populations of magnetic textures evolve collectively and deterministically.
This transformation produces a linear and highly reproducible change in the material's anomalous Hall resistance, an electrical signal that can be used to represent the strength, or “weight," of an artificial synapse. By changing the duration of the applied electrical pulses, the researchers can tune this synaptic weight, creating multiple information states and enabling the multiply-accumulate operations that underpin modern neural networks.
Importantly, the effect occurs at room temperature, overcoming one of the major obstacles to translating many emerging quantum and magnetic phenomena into practical technologies. This means that this new synapse can be implemented in real world applications promptly.
Towards low-energy artificial intelligence
The potential energy savings are significant. When scaled towards future device dimensions, the researchers estimate an energy consumption of approximately 0.66 picojoules per operation, comparable with leading emerging memristive technologies such as resistive random-access memory and phase-change memory.
To test whether the device behavior could be useful for real computing tasks, the researchers incorporated its measured characteristics into a hardware-informed quantized neural network. When used to recognize handwritten digits, the simulated network achieved an accuracy of approximately 96.1%.
"The remarkable efficiency of the human brain continues to inspire us to rethink how computers store and process information," said Dr Elton Santos from the University of Edinburgh's School of Physics and Astronomy, one of the lead authors of this research. "Here, rather than manipulating magnetic skyrmions individually, we exploit their collective behaviour. This gives us a much more deterministic and reproducible way of controlling information while retaining the advantages of these remarkably small topological magnetic structures."
The study brings together expertise in materials synthesis, magnetic characterisation, electrical measurements, theoretical modelling and neuromorphic computing. The researchers believe the principle of exploiting collective magnetic transformations, rather than controlling individual magnetic objects one at a time, could provide a broader strategy for developing robust and scalable spin-based computing technologies.
Ultimately, the findings point towards a future in which the unusual physics of quantum materials could be harnessed not simply to improve existing computer components, but to create fundamentally different forms of hardware—devices that store and process information collectively and could help make future AI systems more energy efficient.
For further information, please contact: Rhona Crawford, Press and PR Office, mb: 07876 391498, email: rhona.crawford@ed.ac.uk
HardFlow is a new algorithm developed at MIT that helps pretrained generative AI models satisfy hard constraints while improving solution quality without retraining.
The technique could be applied to everything from robotics to control of physical systems, and computer vision.
The key to their technique is to give the model more freedom during the generation process and enforce hard constraints on the final output, rather than at every intermediate step.
Cambridge, Mass. -- MIT researchers have developed a new technique that helps generative artificial intelligence models find solutions to high-stakes problems.
In these settings, a plausible answer is not enough: The output often must also satisfy nonnegotiable safety, physical, or task-specific requirements, known as hard constraints.
The researchers developed a method that helps generative models meet these strict requirements without sacrificing the quality of their outputs.
The key to their technique is to give the model more freedom during the generation process and enforce hard constraints on the final output, rather than at every intermediate step.
In experiments spanning robotics, control of physical processes, and computer vision, the new method consistently satisfied the required constraints while identifying better solutions than existing techniques.
This adaptable, plug-and-play technique works at deployment time, so it can be applied to pretrained generative models without retraining them. It can make such models more useful in applications where safety rules, physical laws, or other strict requirements cannot be violated.
“The promise of generative AI is its ability to explore a rich space of possibilities, but the real world places boundaries on which possibilities are acceptable. Our approach lets us preserve that generative power while enforcing the nonnegotiable requirements of high-stakes or safety-critical applications,” says Navid Azizan, the Alfred H. and Jean M. Hayes Career Development Associate Professor in the Department of Mechanical Engineering and the Institute for Data, Systems, and Society (IDSS), a principal investigator of the Laboratory for Information and Decision Systems (LIDS), and the senior author of a paper on this technique.
Azizan is joined on the paper by lead author Zeyang Li, a graduate student in mechanical engineering and LIDS; and Kaveh Alim, a graduate student in IDSS and LIDS. The research appears this week in the IEEE Transactions on Pattern Analysis and Machine Intelligence.
Freedom to explore
Pretrained generative AI models, such as diffusion models like Stable Diffusion and flow-matching models like FLUX, are now widely available. These powerful models learn to create new data by transforming random noise. Their availability has enabled people to adapt them to a wide range of applications.
These highly capable models excel at providing answers that come close to satisfying most queries, but in safety-critical applications like robot path planning on a crowded factory floor, an answer that is “nearly correct” may not be good enough.
For instance, a “nearly correct” path from one machine to another might still result in the robot colliding with a human co-worker.
In such safety-critical applications, users often employ a technique called projection-based sampling, which repeatedly forces the model’s partial solutions, called intermediate samples, to satisfy strict requirements during the generation process.
But constraining the entire generation process can prevent the model from reaching a better final solution. These methods also typically focus only on satisfying the hard constraints, missing the opportunity to improve other qualities of the solution, like reducing the length of the robot’s trajectory.
“For constraint satisfaction, what ultimately matters is the model’s final output, since the internal process is discarded. By not requiring every intermediate step to satisfy the constraints, we give the model more freedom to find high-quality solutions that are still feasible in the end,” says Li.
The researchers developed an algorithm called HardFlow that steers the sampling process so that the final output satisfies the user’s hard constraints without being overly restrictive and is of higher quality.
Subtle steering
HardFlow reformulates hard-constrained sampling as a trajectory-optimization problem, using tools from the field of optimal control. This enables the framework to steer the model’s sampling trajectory toward a goal, making subtle corrections along the way while enforcing hard constraints on the final output.
“Control theory gives us a powerful framework for formalizing the optimal way of making these corrections,” Azizan says.
But solving the trajectory-optimization problem around an enormous neural network was no easy task. The model may have hundreds of interconnected layers that process data.
To make the problem tractable, the researchers leveraged the structure of flow-matching models to decompose the problem into a sequence of smaller, single-step subproblems. They then applied systematic transformations and approximations to derive an efficient, scalable algorithm that still finds a feasible solution.
“Essentially, we transformed the trajectory-optimization problem into something that preserves the key properties of the original problem, but can be solved very efficiently at deployment time,” Azizan adds.
Reformulating the task as an optimization problem allows HardFlow to incorporate additional goals that can improve the quality of the final answer. For instance, HardFlow could find a collision-free path for a robot that is also the shortest distance to its goal.
“Our framework can jointly handle both aspects, which helps it perform much better than existing methods,” says Li.
Across experiments in robotic manipulation, maze navigation, and text-guided image editing, HardFlow achieved perfect constraint satisfaction while consistently outperforming baseline methods on measures of solution quality.
For example, it enabled a robotic manipulator to avoid collisions with obstacles while also finding the quickest path to the target object. Most other methods either resulted in collisions or found paths that took significantly more time.
In addition, HardFlow’s computation time was comparable to or lower than that of most competing methods.
In the future, the researchers could extend the framework to settings in which the AI model itself can also be updated, so that constraint satisfaction and sample quality can be improved in a more adaptive manner.
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Written by Adam Zewe, MIT News
Journal
IEEE Transactions on Pattern Analysis and Machine Intelligence
