Alexander Honkala

I disagree with Dario on most things, but this is spot on: “At this point, saying that AI will cure cancer is more a cliché than it is inspiring, and most people think it is deceptive. The thing that will work is actually curing cancer.” The thing that frustrates me is that some people often draw a straight line from smarter models → cures, without acknowledging how much infrastructure is missing in between. We’ve still got a lot of work to do, people. The regulatory bottleneck gets a lot of attention. But the bigger bottleneck may be that in many places, we’re lacking the right biological data. AI can’t reason its way to cures if we haven’t generated the data required to understand the disease in the first place. Ironically, that’s why I’m most bullish on AI making dramatic progress in cancer first: decades of investment have produced extraordinary datasets across genomics, pathology, imaging, clinical outcomes, and more. For complex chronic diseases, much of that infrastructure simply doesn’t exist yet. The good news is that many companies (including @ChronicleBioAI) are racing to build it. But model intelligence and biological infrastructure are going to have to scale together. I really do believe AI can cure all diseases but only if we build the infrastructure to translate intelligence into cures at the same pace that models improve (which is a high bar!). Otherwise, we risk having superintelligent AI with an incomplete picture of human biology, and delay that promise by years.

2/2 Second, on the messaging around AI.  I do not agree that my messaging has been disproportionately negative.  In fact it has been about equally balanced between risks and benefits: I’ve written one major essay about each, and even in interviews where I discuss the risks, I make sure to frequently mention the incredible benefits as well as proposing possible solutions to the risks (short clips from my interviews that end up on social media tend to be disproportionately negative, as that gets clicks).  In fact, I wrote Machines of Loving Grace because I didn’t feel the AI industry was painting an inspiring enough picture of how the technology could radically transform the world for the better.  The bulk of the essay is devoted to refuting skepticism of AI’s potential in health and biology, and showing why I think it will actually be possible to cure most human disease in ~5-10 years, as crazy as it may sound to ordinary people and frankly to biologists as well (I used to be one!).  And, if you read my most recent essay (Policy on the AI Exponential), I discuss concrete proposals for how to streamline the FDA process to make sure the deluge of AI-accelerated drugs isn’t slowed down by the regulatory process.  I feel the urgency here: I lost my father to Hepatitis C only a few years before the development of direct-acting antivirals (sofosbuvir), which cure 95% of patients and probably would have cured him. I do agree that the public has a negative view of AI (and that this is a big problem), but I don’t think it is primarily caused by me or any other AI leader warning about AI’s risks.  I think it is fundamentally a crisis of trust.  I think that ordinary people don’t trust companies, governments, or the tech industry and always suspect that we are cooking up some new way to screw them over.  The causes of this go back decades and AI is just the latest iteration of it.  I don’t think that a glitzy marketing campaign with a positive spin (which some have advocated that Anthropic do) is the way to win back that trust — at this point, saying that AI will cure cancer is more a cliche than it is inspiring, and most people think it is deceptive.  The thing that will work is *actually curing cancer*.  I think by far the most accurate criticism of AI companies including Anthropic is that we haven’t yet delivered on our big promises to benefit the world.  That is totally on us, and I think it’s the criticism you should be making, instead of all this stuff about messaging and marketing. We are however doing our best to fix this: Anthropic is ramping up its efforts very quickly in biology and medicine, and we hope to have incredible results in the coming years and some early glimmers in the coming months.  When we’ve actually accomplished something real, the whole world will hear about it, as loudly as possible, you have my word on that.  But until then I don’t want to make empty promises, and in the meantime I feel compelled to speak honestly about the very real risks of AI and how to address them.  Honesty is the right thing on the merits, and in terms of public credibility and trust it is no worse than, and may in fact be better than, an approach that ignores or distracts from risks which people instinctively understand are real.

There’s an emerging cross-partisan consensus on individually contentious topics — that we need to re-evaluate the advances brought by post-WW2 materials and chemical engineering now that we have a much better understanding of human biology and environmental processes.

Excited to share our new @biorxivpreprint in which we demonstrate the formation and maintenance of cellular memories in melanoma during acquisition of therapy resistance - dependent on the transcription factor AP-1 biorxiv.org/content/10.1101/… (1/9)