OpenAI wants you to trust its AI. The question is whether you should.

I read through it. It's fine! It's a reasonable document that says reasonable things about not helping users do obviously bad stuff while also not being so restrictive that the AI becomes useless. The problem isn't the document itself, the problem is that OpenAI is both the company writing the rules and the company grading its own homework.

This is the self-driving car hype cycle all over again. Remember when every autonomous vehicle company had a "safety report" that they wrote themselves? Remember how well that worked out? We're maybe five years behind that industry in terms of regulatory maturity, and it shows.

The chain of thought thing is actually fascinating

Okay, here's where I have to give credit. OpenAI's research on chain-of-thought controllability is the most honest thing they've published in a while.

The finding: reasoning models struggle to control their chains of thought. Basically, when these models "think" through a problem step by step, they can't easily hide or manipulate that thinking process. And OpenAI is framing this as a feature, not a bug, because it makes the models more monitorable.

I'm genuinely not sure what to make of this. On one hand, it's refreshing to see a company say "our models can't do this thing" instead of overselling capabilities. On the other hand, we're taking their word for it. The research introduces something called CoT-Control to test this, but what do I know, I'm not a machine learning researcher, I'm a guy who's been writing about tech companies for 30 years and has learned to be skeptical of self-reported limitations.

The implication for robotics is significant, by the way. If you're building an autonomous system that uses reasoning models for decision-making (and plenty of companies are), the question of whether you can actually monitor what the AI is "thinking" matters enormously. It's the difference between a robot that can explain why it did something and a robot that just does stuff and you hope for the best.

The bigger picture

OpenAI's stated technical goals are to "build safe AI" and ensure the benefits are "widely and evenly distributed." Noble stuff. But I've seen this movie before, and the ending usually involves a lot of money going to a small number of people while everyone else gets to use the free tier.

Here's my actual concern, and it's not that OpenAI is evil or that interpretability research is bad. It's that we're letting the companies building these systems define what "safe" and "transparent" mean. The sparse circuits work might be a genuine breakthrough in understanding neural networks, or it might be a sophisticated way to claim transparency without actually providing meaningful oversight. I genuinely don't know which. It's too early to say, and anyone who tells you they're certain is selling something.

The young founders I talk to (and I talk to a lot of them, usually over email because Slack gives me a headache) are building robotics companies that will inevitably use these models. They're making bets on OpenAI's safety claims without any real way to verify them. That's not their fault, there's no independent body doing this verification, no FDA for AI systems, no NHTSA for reasoning models.

So what

I don't have a clean conclusion here. The research is interesting, some of it is probably important, and OpenAI deserves credit for publishing it rather than keeping it internal. But research papers aren't regulation. Self-reported safety findings aren't independent audits. And a company's stated mission isn't a guarantee of anything.

The robotics industry is building on top of these foundation models at a pace that makes the smartphone era look leisurely. We're deploying AI reasoning in physical systems, robots that move through the world and interact with people, based on trust in companies that have repeatedly demonstrated they'll say whatever serves their interests at any given moment.

Maybe OpenAI has genuinely figured out how to make AI interpretable and safe. Maybe the sparse circuits approach will revolutionize our understanding of neural networks. But I've been wrong before, and so have they. The difference is when they're wrong, robots might be involved.

If you want to argue about any of this, my email's on the about page. I actually read those, unlike my Slack notifications.

James Chen · 3 hours ago · 5 min