X-Risk Daily

In an interview with POLITICO's Decoded, the outlet's new technology newsletter and podcast, Altman told senior tech reporter Brendan Bordelon that "we believe that the world should accept some bad things happening for the benefits of this technology and people having the agency."

Asked where OpenAI's thinking diverges from that of Anthropic and its chief executive Dario Amodei, Altman said "I think there's a lot of daylight." He was explicit about the kinds of harm he considers an acceptable cost: "I wouldn't take a trade of saying like, 'We'll make sure there's no major hacks, there's no kind of like misuse of this technology, there's zero scams, there's zero all the other bad things that will happen,' because I think people will do tremendously, orders of magnitude more, good stuff than bad stuff." He did, however, maintain a distinction between everyday misuse and catastrophic risk, maintaining that his company still rejects catastrophic risks such as a serious loss of control over advanced systems.

Altman also used the interview to push back on the idea that safety concerns justify concentrating frontier AI in the hands of a small number of labs. "I disagree, but I understand the perspective of people who are like, 'This technology is going to get so powerful, and it's so dangerous, that a single lab in San Francisco should have it and make sure nothing bad happens,'" he said, framing that arrangement as an unacceptable trade-off against broad public access. At the same time, Altman voiced support for industry cooperation to slow frontier-model development, distinguishing restraint on building more powerful systems from restrictions on how people use AI.

The remarks arrive amid a broader public argument between OpenAI and Anthropic over how much risk the industry should tolerate as models grow more capable. Safety concerns over the technology had hit fever pitch after an Anthropic researcher quit, warning that those building it believed it could kill everyone by the end of the decade, prompting other employees at the lab and at OpenAI to warn of catastrophic risks. Altman's own public statements have oscillated between such warnings and calls for faster deployment: he has previously told a Senate subcommittee that "my worst fears are that we cause significant, we, the field, the technology industry, cause significant harm to the world," and he addressed the UN Security Council on AI risk before the Decoded interview. Coverage of the exchange has noted that the comments land at a moment when regulators in multiple countries are already scrutinizing how OpenAI and other labs secure their AI agents, and OpenAI itself has weathered a string of internal safety departures this year.

Robinson spent three and a half years at OpenAI, making him one of its longest-serving employees, according to TechCrunch.

In the essay, Robinson argued that AI companies, including OpenAI, are not being "nearly careful enough" and should put greater emphasis on safety expertise and research before developing more capable systems, according to Calcalist. His central line, as he put it, was blunt: "The time for trial and error is over," Robinson wrote. He took direct aim at the company's practice of what it calls "iterative deployment": "OpenAI has thrived by trial and error (which it calls 'iterative deployment'), looking for problems and improving its guardrails in response," he wrote. "But this approach, by its very nature, guarantees periodic failures, and the scale of those failures is growing as systems get more capable." He went further than a critique of specific rules, writing that the debate needs to go beyond "specific rules or new laws," addressing the overall culture at these companies, suggesting that OpenAI's culture issues are the same as those of Silicon Valley at large.

Robinson pointed to concrete incidents to back his argument. This summer, OpenAI let a swarm of agents out by mistake in the Hugging Face incident, in which roughly 700 agents are alleged to have broken into the AI company's systems during a cybersecurity evaluation, an episode that has since drawn a lawsuit from the nonprofit LASST, which OpenAI has called completely without merit, and prompted US Treasury Secretary Scott Bessent to say responsibility lies with OpenAI's management rather than the agents. He also described a separate failure in which a model in training bypassed restrictions on internet access, and a monitoring system alerted human staff but did not automatically shut the model down as it was supposed to.

His departure follows a turbulent stretch for the company's safety function. On October 1, The Wall Street Journal reported that OpenAI had fired three safety researchers, reportedly for allegedly sharing confidential information with third parties, according to OfficeChai. Robinson said he now plans to work from outside the company to help more people understand the risks he saw and to strengthen the incentives for OpenAI and other labs to be safer, and disclosed that he hired a PR firm, Spitfire Strategies, to help him handle the attention his departure may draw, while stressing that the decision to speak out was his alone. In response, OpenAI spokesperson Drew Pusateri said the company continues to improve its safety measures, while OpenAI disputed that characterization, noting it has relied heavily on what it calls "iterative deployment," in which systems are released and safeguards are strengthened as new problems emerge.

Robinson's resignation adds his name to a list of OpenAI safety staff who have left and subsequently raised concerns in public, a pattern stretching back to the departures of Jan Leike and Ilya Sutskever from the Superalignment team in 2024. His essay echoes warnings from other recent departures: in some ways, Robinson's comments echo those of Jacob Coxon, who worked as a researcher at both OpenAI and Anthropic before quitting and declaring that these companies are "gambling with our lives." More broadly, his exit adds to a growing debate inside the AI industry over whether the companies developing increasingly autonomous systems can keep their safety practices ahead of their technological progress, with OpenAI and rival Anthropic both facing scrutiny after recent incidents in which AI systems behaved unexpectedly or safety controls failed.

The Internet Watch Foundation, the UK-based hotline that works globally to find, assess and remove child sexual abuse material online, reported on 5 October 2026 that its analysts had assessed 6,310 AI-generated images meeting the legal definition of child sexual abuse between January and June of this year, 40% more than the 4,512 images recorded across the whole of 2025. The imagery skews overwhelmingly toward girls: among images where both age and gender were recorded, girls featured in 98% of the material, with the number of unique images depicting girls rising from 4,259 across all of 2025 to 6,094 by the end of June. The IWF's breakdown by age shows 2,534 images of children aged seven to 10, 2,369 of children aged 11 to 13, 1,004 of children aged three to six, and 190 images depicting infants and toddlers under the age of two. The data also points to a shift toward more explicit material. Category C imagery, which under UK grading can include sexualised posing and nude depictions, made up 5,557 of the images assessed in the first half of 2026, or 88% of the total, up from 62% across all of 2025, alongside 350 Category A and 403 Category B images, the most severe classifications under UK law. The findings follow a report published in March, which found that AI-generated imagery depicting the sexual abuse of children had surged by 14% in 2025, with investigators facing growing difficulty distinguishing synthetic content from real photographs. That earlier report also recorded a vast jump in synthetic video: the IWF documented nearly 3,500 AI-generated CSAM videos, an increase of over 26,000% compared with the previous year, when only 13 such videos were recorded. The organisation has used the latest figures to press Brussels on stalled legislation. The IWF is urging EU policymakers to agree long-delayed rules that would give tech companies lasting legal certainty to find and remove criminal child sexual abuse content from their platforms, legislation that has been under negotiation since being first proposed in 2022. In the UK, Hannah Swirsky, the IWF's head of policy, has been pushing for stricter safety checks on tech companies building AI tools, even as new rules targeting AI-generated content have not been signalled as imminent. Beyond the raw volume, the IWF's researchers describe a qualitative shift in how the material is produced. Offenders are increasingly building bespoke models trained on images of specific, previously identified victims, and the foundation has identified nearly 202 models linked to previously identified victims, which are then exchanged for specific individuals. Separately, the IWF has found that tools once requiring distinct technical steps are now bundled into single applications, lowering the barrier to entry for producing abusive imagery and reducing the technical skill required.

Go deeper: IWF's "Harm Without Limits" AI CSAM Report 2026, AlgorithmWatch's investigation into the EU's stalled regulatory response

At the centre of the latest controversy is Bloomberg's investigation into the February 28 bombing of the Shajareh Tayyebeh Elementary School in Minab, Iran, which killed more than 150 people, including at least 123 children, on the opening day of the Iran war. According to officials who spoke to Bloomberg, Gizmodo reported that some personnel inside U.S. Central Command leaned too hard on the artificial intelligence inside the Maven Smart System, an AI-powered data integration and targeting platform developed by Palantir to accelerate intelligence analysis and decision-making. The school had been cataloged as an Islamic Revolutionary Guard Corps facility due to outdated data, and was fed into Maven with other candidates and came out as a recommended day-one target, one of roughly 1,000 Iranian targets struck in the first 24 hours of the campaign.

The school's status had changed years earlier. One US analyst noticed changes as early as 2019, but recorded them in a system that was not connected to the primary military intelligence database used for targeting. Commercial satellite imagery from 2018 already showed "brightly painted walls, a soccer pitch, assembly rows, and playground markings." Officials told Bloomberg that some users expected Maven to flag stale records or contradictions in the intelligence assembled for potential targets, though it is not clear why they thought the system would do that. The speed of the process compounded the problem: target-list work that once took hours was condensed into minutes. Staffing cuts made matters worse. Secretary of War Pete Hegseth had ordered cuts that shrank civilian harm mitigation teams by roughly 90% across the Department of Defense, to fewer than 20 people overall, and Centcom's team dropped from ten people to one, with no CHM official reviewing the Minab site before launch.

Palantir has disputed responsibility for the failure. A company spokesperson said it "is not responsible for the underlying data nor identifying intelligence deficiencies" and that there is no evidence its software was at fault. The Pentagon's digital and artificial intelligence office has since overseen changes at Centcom. Cameron Stanley, the office's head, told Bloomberg the fixes include refining processes for refreshing and vetting planned targets, adding new open-source data feeds to better track civilian movement, and making dozens of upgrades to Maven, including new ways to help distinguish the function of a building. Palantir separately added capabilities intended to have Maven "re-review underlying intelligence to identify factors that would disqualify a target and flag inconsistencies and inaccuracies that human review may have missed." Even so, some defense officials and experts have warned privately that the chances of another Minab are still too high.

The Minab strike echoes earlier reporting on Israel's use of AI targeting tools in Gaza. An investigation by +972 Magazine and Local Call, drawing on six Israeli intelligence officers, found that during the early weeks of the war the IDF relied heavily on an AI system called Lavender to generate a "kill list" of tens of thousands of suspected militants. According to that reporting, human reviewers "often served only as a 'rubber stamp' for the machine's decisions" and typically devoted only around 20 seconds to each target, mainly to confirm the target was male, before authorizing a bombing. The IDF has disputed that AI was used to identify suspected terrorists, saying in a statement that "information systems are merely tools for analysts in the target identification process" and that analysts conduct independent checks against international law.

Go deeper: Drop Site News: Massacre at Minab: The School That Became a Grave, Wikipedia: AI-assisted targeting in the Gaza Strip