Truth be told, this is not an uncommon take among AI leaders. On 60 Minutes last year, Demis Hassabis, co-founder of Google DeepMind, declared that “we can cure all disease with the help of Al… maybe within the next decade or so, I don’t see why not.” Actually, there’s a big reason why not: human nature. An estimated 80% of chronic diseases and premature deaths are not driven by our genes, but by the way we live: what we eat, how much we move, how we sleep, how we manage stress and stay socially connected.
It’s true AI can accelerate drug discovery and personalize nudges for our daily behaviors, but it can’t “cure all disease” while ignoring human nature, free will, and how we live. The view among those currently working to lower the disease burden is considerably less utopian than in AI. It’s unrealistic, and it sets the expectations for AI too high.
It’s hype.” “Cancer is not one disease. It is more than 200 distinct diseases, all with different causes, biology and mechanisms,” explains Dr. Catherine Young, a Senior Fellow at the Harvard T.H.
Chan School of Public Health. In 2000, on the heels of the first sequencing of human DNA, Francis Collins, then-director of the Human Genome Project, predicted that “in another 20, 25 years we should be able to prevent or cure most cases of cancer, of diabetes, of heart disease, of multiple sclerosis, of asthma.” And yet, here we are, 26 years later, facing a growing epidemic of chronic diseases. Daphne Koller, CEO of the AI-driven drug development company insitro, calls it the “magic wand” assumption.
It points to a larger problem: we are too often focused solely on improving the machines, and too rarely focused on investing energy and resources in improving humans. In 2024, Amodei wrote about the limiting factors that stand in the way of AI transforming the world for the better: “speed of the outside world,” “need for data,” “intrinsic complexity,” “physical laws” and “constraints from humans.” Of those, I would argue that the constraints imposed by humans will be the ultimate limiting factor. That is why I believe the greatest risk we face is that AI will get better but humans won’t.
We need the same relentless focus on helping humans tap into their better selves and achieve better health outcomes through healthier daily behaviors as we have on helping the machines achieve better frontier models.
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