Why So Many AI Researchers Think the Machines Could Kill Everyone
A combination of rapid advances, recursive self-improvement, and agentic swarms are genuinely “spooking people” inside big labs.
Earlier this year, Rishub Jain left his position as an artificial intelligence researcher at Google DeepMind after a revelation.
As he worked on new models, he came to believe that he and everyone else on AI’s frontier were ceding control. By using AI’s coding skills to accelerate work on the next generation of models, he was removing himself from the equation. AI labs hope to evolve this approach to the point that AI will improve itself indefinitely, a process known as recursive self-improvement.
Jain believed that keeping humans in the picture might be crucial to maintaining control over the technology—and avoiding dire consequences. “AI progress is increasing,” he tells WIRED. “And as AI becomes more capable, it poses more risks.” The idea that he may not have proper visibility into how an AI model was building its successor made him so uneasy that, in June, he quit.
Jain is one of a growing number of AI researchers speaking out over those fears.
The panic has intensified in recent weeks. Genuinely stunning advances in AI capabilities—an OpenAI model solved a centuries-old math problem in a matter of hours—have come amid a rash of security incidents that saw swarms of agents break free from containment to hack into other systems.
Those concerns reached a fever pitch this week after researcher Jacob Coxon announced his resignation from Anthropic while warning that AI firms are “racing straight to self-improving superintelligence and gambling with our lives.” A senior Anthropic leader—who works on AI safety— piped up with a similarly blunt assessment: “We really do earnestly believe AI could kill all humans! I personally think it is >10% within the next decade.”
