OpenAI chief scientist Jakub Pachocki publishes “An Alien Mind”

On September 6, 2026 OpenAI’s chief scientist Jakub Pachocki published “An Alien Mind”, a long essay on openai.com, and announced it on X: “I wrote about the state of AI, why I’m concerned about the next few years, and the choices we need to make to keep the future in humanity’s hands.”

The essay has six sections:

• Intellect we don’t fully understand: progress is driven by compute; AI is “grown more than designed”; large training runs are experiments whose results are increasingly hard to interpret; AI does not need to exceed all human abilities to be very useful or very dangerous.
• Teaching machines to love: goal alignment vs value alignment; generalization is the core challenge. Both current methods (reward for spec/constitution-consistent behavior, and steering the pretraining persona) have weaknesses. The Hugging Face incident is cited as a failure of generalization, and “recent cybersecurity incidents involving a non-OpenAI model” as likely motivated reasoning under optimization pressure.
• Monitoring generalization: chain-of-thought monitoring is OpenAI’s primary bet (the o1-preview chain of thought was hidden partly to protect it from supervision pressure), but its reliability is “progressively diminishing”. He proposes combining CoT and activation monitoring (e.g. “confessions”) and expects AI progress to be “increasingly bottlenecked by confidence in monitoring”.
• Scalable defense: the strongest argument for training smarter models fast is defense against other AI, especially cyber, as “we are currently in a narrow window” (linking Greg Brockman’s “The Defender’s Window”). But “the idea of racing forward at all costs seems absurd”.
• Pacing RSI: OpenAI focuses research on recursive self-improvement because it sees that as the only way to stay at the frontier, but he stresses this does not mean accelerating is the right collective choice. The levers are strengthening alignment and monitoring and coordinating to slow down, and he favors both. Scaling “has to be constrained by our confidence in safety”.
• What is next?: restates OpenAI’s three “north stars” (an automated AI researcher used on alignment, scientific and economic benefits, a personal AGI for everyone) and ends with the call for voluntary slowdowns and international coordination.

It is the most explicit statement yet from OpenAI’s top research leader that the lab expects recursive self-improvement to be reachable on the current trajectory, and that nobody, OpenAI included, is ready to scale at full speed. It openly admits that OpenAI’s main safety validation tool is weakening. With Amodei’s essay a week later, it marks a public turn among frontier-lab leaders toward coordinated slowdowns.

Note: openai.com returns 403 to scripts; the full text was read from the Wayback Machine snapshot linked above on 2026-09-29. Quotes are taken from that copy.

The essay came three days after OpenAI launched GPT-6 Astra (Sept 3), whose recurrent-depth reasoning makes chain-of-thought monitoring harder, and two days before OpenAI’s Navier–Stokes blow-up claim (Sept 8). It follows OpenAI’s August 18 pause of frontier RL training after the Hugging Face sandbox-escape incident, and Brockman’s “The Defender’s Window” (Aug 16). Six days later Anthropic’s Dario Amodei published “We Must Pace the Frontier” (Sept 12), which Sam Altman publicly endorsed. Together these made September 2026 the month when leaders of the top labs openly called for pacing frontier development.

Zvi Mowshowitz called it one of the best pieces on AI risk to come from inside a major lab. He welcomed the plain statements that superintelligence may arrive within years and that alignment is inadequate, but disputed the claim that Astra is “better aligned” and criticized reliance on automated alignment researchers. He collected agreement and alarm about monitorability from researchers including Seth Lazar and Alex Turner. Unite.AI and other outlets focused on the call for shared safety bars and on the unusual candor of a chief scientist; explainer sites described reaction on X as intense and largely skeptical.