GoKawiilHere at WIRED we’ve been trying to make sense of at least two incidents in the AI industry this week: First, the major fight over a million-dollar math problem and whether OpenAI surreptitiously borrowed the work of other researchers to solve the problem first. A day later, an Anthropic researcher—who had previously worked at OpenAI—very publicly quit his job, citing concerns about how both companies were handling AI safety. Another technical staffer at Anthropic said in response that people at the company “really do earnestly believe AI could kill all humans! I personally think it is >10% within the next decade.” (Note the exclamation point.)
The internet erupted into a debate about whether these fears are very legitimate, totally overblown, part of a regulatory capture strategy, or self-aggrandizement on the part of the AI labs that make the tech. Or some combination thereof.
One prominent technology and AI researcher, Timnit Gebru, has been especially fiery, posting on X and Bluesky about the overlapping ideas and ideologies that she thinks led us to this bizarro moment. Previously, Gebru was most known for her highly publicized departure from Google. Hired in 2018 to evaluate biases within the company’s fast-advancing AI tools, she and her fellow researchers presented a paper on the potential dangers of probabilistic large language models. Google rejected it. Gebru wasn't at the company much longer. She’s written an upcoming book about her experiences, titled Deep Unlearning: The Rise of AI and the Radicalization of a Tech Idealist (expected to ship early next year).
Gebru has many thoughts on the AI-related events of this past week. While her work is essentially rooted in AI safety, she rejects phrases like “safety and alignment” and thinks those who are warning of our impending doom are trying to distract from the actual harms the tech industry might perpetuate.
LAUREN GOODE: What do you think all the attention on the “math fight” says about the current state of AI?
TIMNIT GEBRU: Well, first I would ask, why are they heavily investing in solving math problems? Why are they choosing certain disciplines? Somehow these subjects, like programming and chess and math, were elevated to mean, OK, you solved this and thereby you’ve solved intelligence. It’s so they can say, “We solved it.”
The story that OpenAI wants you to hear is, this AI did this incredible thing, and it’s super intelligent. That’s why they chose math, this open $1 million question. But if it had gone through the whole process by which the math community vets the significance and novelty of claims and who contributed to them, and we had all waited until the dust settled, we would have gotten a better sense of whether OpenAI was framing this breakthrough accurately.
There’s something called the Leiden Declaration that I think is really good, which warns about what happens if the field of mathematics is used by corporations in this way. Policymakers start to rely on press releases and popular media, when they should be talking to mathematicians themselves. The amount of time it takes now to go from companies claiming an AI breakthrough to Bernie Sanders proposing a bill is really short, and that’s not a good thing.
It’s all just cutthroat right now leading up to their IPOs. Generally, researchers are supposed to be collaborative. When I was at Google, we were collaborating with researchers at Microsoft, at Amazon. You do that all the time. Now, the researchers are all frenetic about the problems they think they’re solving because of their pending IPOs.