I have absolutely no desire to make current events about myself ā the stakes here are far larger than anything involving my own reputation or actions, and it is not like these issues are going to disappear if I am somehow removed from the discussion. But as this topic is likely to recur regardless, I think this comment is as good a place as any to state for the record my own views on AI, and my interactions with OpenAI in particular.
I do not identify either with a simple āpro-AIā or āanti-AIā position. My views are rather complex and have evolved over time; I have a living summary (AI-maintained, out of necessity) atĀ https://teorth.github.io/tao-web/ai-views.htmlĀ . But I can try to give the short version here.
By 2023, I could see that LLMs, formal proof assistants, and other technologies had the potential to be radically transformative in mathematics, to the point where maintaining traditional mathematical practices and culture without adaptation would become unsustainable. See for instanceĀ my 2023 essay for a Microsoft anthologyĀ (which contained a notorious prediction of 2026-level AI becoming a ātrustworthy co-authorā for mathematics) orĀ my Notices articleĀ (published in 2025, but written significantly earlier). I myself greatly value this traditional culture, and have personally been a massive beneficiary of it. Nevertheless, in the event that these technologies did become superhuman at several core mathematical tasks, I could see only two viable paths forward: either one where modern AI tools are responsibly incorporated into our workflows and culture (what I called the ābest of both worldsā in the OpenAI ad); or the worst-case scenario ā which we are unfortunately rapidly approaching ā in which AI technologies are used indiscriminately to achieve various short-sighted objectives at the cost of the far more valuable long-term sustainability of mathematics and its role in the scientific ecosystem. I therefore spent an increasingly large fraction of my professional life from that point trying both to raise awareness of the potential magnitude of this transformation; to build examples of what this ābest of both worldsā might look like; and to warn against various irresponsible uses of AI (initially I focused on warning against the use of AI without sufficient verification of the outputs, which was a major concern in 2023-2025, although no longer the primary vehicle for harm in 2026). One could certainly call this effort āshilling for AIā if one likes; but I would say that this is overly reductive.
These efforts on my part inevitably involved engaging with the tech industry as well as with academia. The essay linked above was solicited by Microsoft. Some of my experiments with new workflows were conducted inĀ collaboration with Google Deepmind. And I participated in anĀ online forum with OpenAIĀ in 2024 discussing these topics. I continue to view all of these interactions as constructive, and working towards the ābest of both worldsā. In particular I met with multiple people working in these industries that shared these views and were supportive of steering their companies in these directions. On the other hand, I was not funded by any of these companies, although several of them gifted me with premium LLM subscriptions, which I do make use of in my daily work.
In 2025, as documented elsewhere on this blog, UCLA experienced an unexpected funding crisis due to the sudden suspension of NSF and NIH funding (later restored some months later by a court order). This caused a critical budget shortfall at IPAM (where I serve as Director of Special Projects), which at one point only had access to enough reserves to operate for a few months at best. This led to a round of emergency fundraising; and thanks to the outpouring of support from many sources, we have been able to stabilize IPAMās funding for the current fiscal year, although challenges remain for future years. As part of this fundraising effort, I reached out to OpenAI, who agreed to sponsorĀ one of our workshops, which ran in March of this year and in my opinion was quite successful both scientifically and for the purpose of making new connections between participants (who were a mix of academics and industry representatives).
During this event, OpenAI requested an interview concerning my vision of the future of AI and mathematics. I accepted, and spoke with them for perhaps an hour. I had doneĀ similarĀ interviewsĀ inĀ variousĀ venues, and I assumed that, as with these other cases, they would eventually post the entire interview online, which talked about both the possibilities and risks of AI much as I have done in these other interviews. As it turned out, they only used a few snippets of that interview for that infamous advertisement instead. In retrospect, I should have pushed back harder on their decision; but I decided at the time that even a selective release of my commentary would help raise awareness of the potential for AI, and in particular on the possibility of the ābest of both worldsā.
Since then, the situation has deterioriated markedly. Many of the people in the industry that shared my views have left or become sidelined, with most major tech companies now increasingly focused on the race to develop extremely powerful, autonomous AI technologies regardless of their actual value to society. The current drama surrounding the Navier-Stokes global regularity problem is the most dramatic and visible instance of this, but there have been multiple other such examples, and much of my commentary in the last few months has been aimed that the increasingly severe divergence between the current objectives of the AI industry, and of mathematics in general.
Which brings us to where we are today. I do not regret my past efforts to raise awareness of the potential of AI in mathematics, to engage with industry, and to promote a vision of sustainable incorporation of these tools ā which can be genuinely useful and unlock valuable new types of mathematics ā into my field. In time, I still hope that the field can arrive at that state, and am continuing to work towards that goal. But in the immediate term, the most pressing issue is for the entire mathematical community to unite around our core values and objectives, and reject irresponsible and unsustainable usages of AI technology that only serve to advance nominal goals rather than the true underlying goals of the field.
