We Need a Cure for AI Health Hype

“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!).”

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. “Diabetes, Alzheimer’s, heart disease—we don’t have cures for any of those common diseases,” says cardiologist Dr. Eric Topol. “To think that in the next five or 10 years new drugs are going to change everything, there’s no precedent for that. 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. “Scientists who study cancer rarely talk about ‘curing cancer’ because it’s nothing more than an empty slogan.”

As Amy Dockser Marcus writes for The Information, we’ve been here before. 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. “Hundreds of years into modern medicine,” she writes, “our understanding of most human disease, and much of healthy physiology, is best captured by the parable of the blind men and the elephant; in this case, a really huge elephant.”

The current debate about whether AI can cure all diseases is more than a tempest in a GPTeapot. 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. And I'm not alone.

“If for every dollar and every minute that we invest in developing artificial intelligence, we also invest in exploring and developing our own minds, it will be okay,” suggests Yuval Harari in his book 21 Lessons for the 21st Century. “But if we put all our bets on technology, on AI, and neglect to develop ourselves, this is very bad news for humanity.”

As we work to realize all the possibilities of AI, the bottleneck that will hold us back from maximizing its benefits will be what it has always been throughout human history: human nature. That is why I believe the greatest risk we face is that AI will get better but humans won’t.