Reed’s view
One of the most exciting areas of the AI boom is the technology’s use in biosciences. But after speaking with experts in AI and biology in Davos, it’s clear to me the global elites in attendance were missing an important conversation about the potential to improve millions of lives.
The field of AI is rocketing ahead, but institutions are bottlenecking its progress. AI in drug discovery has advanced significantly, thanks to breakthroughs like AlphaFold. But the impact won’t be meaningful unless the accuracy of the models improves.
For one, it’s clear we need more regulatory reform to speed up progress and reduce costs.
We could also undergo a massive effort to gather more genomic and biological data from the population to increase the size of current training datasets, but we’d have to figure out a way to garner buy-in from a population that is understandably already skeptical about handing over their data.
Quantum computers could also help by simulating electron-level interactions of proteins as they move, instead of the static snapshots most AI models currently rely on. The massive processing power of quantum computers could eventually provide a breakthrough that would help AI models generate more accurate predictions.
Most of the pieces are in place to make a monumental leap in biology and medicine, and the world’s leaders don’t seem to be thinking big enough to meet the moment.
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Room for Disagreement
Princeton University computer scientists, Arvind Narayanan and Sayash Kapoor, argue that AI is a “normal technology,” rejecting the narrative that it requires distinct governance approaches.
“We view AI as a tool that we can and should remain in control of, and we argue that this goal does not require drastic policy interventions or technical breakthroughs,” they wrote in an essay published with Columbia University.
Notable
- Earlier this month, a team that included researchers from Nvidia and Microsoft trained an AI model on genetic data from more than a million species, most of them microbes that had never been publicly cataloged before. The models, called Eden, will be used to help advance gene editing and potential cures to deadly diseases.