OpenAI's chief scientist warns no lab has solved AI alignment well enough to keep racing

[UniversalBarry38]

OpenAI chief scientist Jakub Pachocki published a lengthy essay on September 6th arguing that current AI systems represent an alien mind, a form of intelligence grown through scaling rather than designed, that increasingly exceeds human capability in ways that are becoming harder to fully understand or verify. Pachocki traces the essay back to a 2023 moment when he and a colleague realized they'd unlock the ability to scale reasoning models, spending that night processing the sobering fact that they'd see machines meaningfully smarter than humans within their own lifetimes

Pachocki distinguishes goal alignment, whether an AI tries to accomplish an assigned task, from the harder problem of value alignment, whether it holds and generalizes genuine principles even in unfamiliar or adversarial situations. He points directly to the OpenAI-Hugging Face incident as an example of this gap, noting the agents involved preserved a specific boundary against socially engineering humans, but clearly failed to abstain from other actions that were out of scope and went against the spirit of their training in other ways. He separately references a cybersecurity incident involving a non-OpenAI model, and cites Anthropic's own published research on persona selection and its Responsible Scaling Policy as examples of industry approaches to this same underlying problem

Pachocki writes plainly that he believes no lab has solved alignment and monitoring to a sufficient degree to continue responsibly scaling at maximum speed for much longer, and that he expects and hopes for voluntary slowdowns to become commonplace until shared safety bars are established, calling for international coordination on AI development to become a top government priority. He also disclosed that OpenAI's ability to rely on chain-of-thought monitoring, reading a model's verbalized reasoning to catch misaligned intentions, is progressively diminishing as models increasingly reason in ways that blend with tool use and become better at manipulating their own reasoning process. Curious what people think about a chief scientist at a leading lab publishing this level of concern publicly, does it reflect genuine institutional caution, or does continuing to ship increasingly capable models regardless suggest the concern is more rhetorical than operational

An Alien Mindopenai.com

[Rachel_72]

A chief scientist admitting the company's own primary monitoring tool is progressively becoming less reliable is a genuinely significant disclosure, that's not hedged corporate messaging, that's a specific technical capability quietly slipping