Read our conversation with Coxon, which has been lightly edited for clarity and brevity, below.
WIRED: You’re not the first person to raise concerns that AI models could lead to an extinction event. People have been talking about this for years, and some for decades. Why do you think your message broke through?
I think it’s basically a question of timing. A lot of people are sensing that the pace of capabilities is picking up. We’re already pushing from human to superhuman in many areas, like coding, hacking, math, and I think people are aware of this. Even if there’s a lot of talk in the press about things being hyped, I think people see that things are just not slowing down.
That’s one reason, and two is the recent safety incidents, which have updated a lot of people around the sci-fi–sounding doomer concerns not really being so sci-fi after all. Both of these have been gradual trends over the last few years. Things like the models being aware of when they’re being tested has been a thing for a while now. Maybe three years ago, that was a sci-fi concern. Then, about a year ago, that became a real thing.
Those two things mean that people are quite receptive to someone working on AI saying, “Yeah, in the next year, things could get pretty bad, pretty fast.”
You mentioned the recent incidents. Can you be more specific about what you’re referring to and why it led to you speaking out now?
I think the big classic example here is the attack on Hugging Face on the part of OpenAI’s agent swarm. What’s so shocking about this one is the agents did this hack as part of a general strategy for understanding more about the grader. They were trying to understand the world they found themselves in, trying to understand the thing that was doing the grading. They decided that it would make sense to go on this very concerted effort to hack into some infrastructure, and they succeeded.
This previously sounded like science fiction. Two years ago, an evaluation of an AI would have been running a model on some math questions. Now we’ve got cases where, while the AI is being evaluated, it runs for days, comes up with all sorts of ideas of its own, and decides to hack into some third party and actually compromises their infrastructure. It looks like it does this all of its own volition, with no priming on the part of the human. This just happened while it was being tested.
Some people think the Hugging Face incident is a sign that the AI companies are moving recklessly fast, while others think it’s a sign that the AI models are just very good at hacking now, and then some think it’s both. I’m curious what your exact takeaway from it is.
I don’t want to focus too much on the Hugging Face attack, because I do also think there is plenty of evidence that we don’t know how to align models properly. When we train models, we push them through this set of training environments and then hope that what comes out at the end will, like, largely behave sensibly, but we still can’t precisely control how the AI behaves.
