Former Google DeepMind Researcher Joins the Fray, Warns AI Could “Kill Us All”

A former Google DeepMind researcher has warned that artificial intelligence could eventually "kill us all" and that the industry may be running out of time to prevent such an outcome, adding to a growing chorus of researchers raising alarms about the pace at which increasingly capable AI systems are being developed.

Bilal Chughtai, who worked on artificial general intelligence safety and alignment research at Google DeepMind, said Monday that he had resigned from the company because of concerns about the trajectory of AI development.

"I earnestly believe that AI has the potential to kill us all, and that we might be running out of time to avoid this outcome," Chughtai wrote on X.

Chughtai worked as a research engineer at Google DeepMind and co-authored research papers during his time at the company. His LinkedIn profile indicates that he left the company in July 2026.

His warning follows a series of stark statements from researchers at some of the world's leading AI companies, turning what was once largely an academic debate over long-term AI risks into a more public dispute over how quickly frontier systems should be developed and deployed.

Last week, former Anthropic researcher Jacob Coxon said he had resigned partly because people developing advanced AI "earnestly believe that it could kill us all by the end of the decade."

Evan Hubinger, an Anthropic scientist who has worked on AI safety research, subsequently said Coxon's characterization was accurate and estimated that there was a greater than 10% probability that AI could kill all humans within the next decade.

Those assessments are not predictions that AI will necessarily cause human extinction. Rather, they illustrate how some researchers working closest to frontier AI systems have come to assign meaningful probabilities to catastrophic outcomes, even while the timing and mechanisms remain highly uncertain.

AI Safety Moves From Research Concern to Industry Debate

Chughtai said a safe path for AI development remains possible, but argued that it will require cooperation between companies rather than an unrestricted race to build increasingly powerful systems.

"Navigating AI safely is possible, but it requires coordination to avoid this manic race between AI companies," he wrote.

"We need to pace AI development to a speed that society can handle, where emerging risks can be addressed before extreme harm is realized," he added.

The comments arrive as AI companies face a difficult competitive problem. The largest labs are investing enormous sums in computing infrastructure, talent and model development, creating strong incentives to release more capable systems before rivals do. A company that voluntarily slows development could fear losing customers, talent or technological advantage to competitors that continue moving ahead.

That dynamic is at the heart of the recent debate over whether frontier AI development should be deliberately slowed.

Anthropic CEO Dario Amodei also called for a slower pace of advanced AI development, explaining that companies and governments need more time to understand and manage emerging risks. His position received unusually broad support from rivals and other technology leaders, including OpenAI CEO Sam Altman and SpaceXAI's Elon Musk.

The convergence is notable because the companies involved remain direct competitors in the race to build sophisticated AI systems. Agreement on the need for greater caution does not necessarily mean agreement over what constitutes a safe development pace, how safety should be measured or who should have authority to impose limits.

It has also opened a broader debate over "AI doomerism," the term often used to describe warnings that sufficiently advanced AI could produce catastrophic or existential consequences.

Skeptics believe that such warnings can exaggerate uncertain future risks and potentially justify restrictions that protect established AI companies from competition. Supporters of stronger safeguards counter that the uncertainty itself is a reason to develop systems more cautiously, particularly if future models become capable of autonomous planning, self-improvement or other behaviors that researchers cannot reliably control.

Washington Takes a Different View

The warnings from AI researchers have also exposed a widening gap between parts of the technology industry and the Trump administration.

President Donald Trump has dismissed calls for greater AI regulation, describing the industry's push for regulation as a "hoax." His administration has emphasized the need for the United States to maintain its lead in AI development, particularly in competition with China.

Trump's stance has created a fundamental policy tension. The United States wants its AI companies to move quickly enough to maintain technological and economic leadership, while some of the scientists developing those systems are increasingly arguing that speed itself could become a source of systemic risk.

Chughtai's warning adds weight to that argument because it comes from someone who recently worked inside one of the world's most prominent AI research organizations on the specific problem of making advanced systems safer and more aligned with human objectives.

His departure does not establish that AI is on a path toward human extinction, nor does his assessment provide a timetable for such an outcome. But taken alongside warnings from researchers at Anthropic and calls for slower development from Amodei, it shows how concerns once confined largely to AI safety circles are becoming increasingly difficult for the industry to keep at the margins.

The major concern now hinges largely on how AI companies can coordinate on safety without sacrificing the competitive incentives that are driving the technology forward. For researchers such as Chughtai, the danger is that those incentives could push development faster than safety research, regulation, and society's ability to respond.

That is a considerably different proposition from arguing that AI development should stop. It is an argument that the speed of the race may itself become one of the risks that the industry needs to manage.