So far, the policy conversation about A.I. has focused on preventing harms to the public. What if A.I. leads to mass job loss? What if it\u2019s used for surveillance? For bioweapons? What if it concentrates wealth and power in the hands of the few while acting as an agent of cognitive and social atrophy for the many? What if future systems slip out of our control or beyond our understanding?<\/p>\n
These dangers are real, or at least plausible. Policies to prevent or respond to them are essential. But there is another policy conversation that is strangely absent: How does A.I. benefit the public?<\/p>\n
The public goods of A.I. are, I recognize, not the most politically popular topic at the moment. A.I.\u2019s polling is dismal, even if its usage is exploding. Data centers are hideously unpopular and, in some jurisdictions, banned. Pope Leo XIV devoted his first encyclical to the technology\u2019s dangers. Many see the use of A.I. at all as borderline immoral \u2014 it adds demand to an overhyped, dangerous technology whose rollout needs to be slowed or perhaps even stopped.<\/p>\n
I start from a different perspective. A.I. is here. It will be used. But how it is used, for what and by whom are meaningful questions. A.I.\u2019s benefits will not emerge automatically or inevitably. It will take work to identify the problems A.I. can help the public solve and then create the data, financing and \u201ccompute\u201d \u2014 the raw processing power that A.I. systems use when queried, supplied by data centers full of specialized chips \u2014 needed to actually solve them.<\/p>\n
When A.I. is pointed at the right problem, in the right way, the results can be remarkable. An OpenAI model just disproved a conjecture that had eluded mathematicians for 80 years. A drug for pulmonary fibrosis just became the first fully A.I.-generated treatment<\/a> with proven efficacy and safety in humans. A Mayo Clinic team developed<\/a> an A.I. system that can detect pancreatic cancers on a CT scan up to three years before clinicians can see them. DeepMind\u2019s Graphcast model appears<\/a> to generate weather predictions both faster and more accurately than the supercomputer systems that are used now. The 2024 Nobel Prize in Chemistry went in part to the designers of the AlphaFold model for the quantum leap it offered in predicting protein structures.<\/p>\n The corporations buying A.I. access for themselves are not deluded. But they are finding<\/a> that you cannot solve problems just by throwing A.I. at them. It takes work to structure a problem in a way that allows A.I. to be useful, just as it took work, in previous generations, to integrate I.T. into a company or redesign a factory to take advantage of electricity.<\/p>\n The AlphaFold advance was possible only because of the Protein Data Bank, a laboriously created database of protein structures that the National Science Foundation began funding in the 1970s. No Protein Data Bank, no AlphaFold.<\/p>\n So a public agenda for A.I. needs to be more than a vague intention to toss A.I. at public problems. It starts with access, but it does not end there.<\/p>\n Still, start with access. It might begin with an actual public option for A.I.: Perhaps there should be at least one frontier-level model under direct public control. It would at least begin with the recognition that there is already more demand for compute than there is supply. That might mean buying compute for public purposes and making certain it is affordable for universities, public agencies and others.<\/p>\n The digital divide I mentioned above is already opening up into a private-public divide, where Goldman Sachs can afford colossal quantities of compute and public universities cannot. I want the public to have access to enough compute that it can unleash A.I. on hard problems.<\/p>\n But much of the A.I. capacity will remain in the private sector. So a public agenda for A.I. should also give the private sector reason to work on public problems. Like in Operation Warp Speed, the government could define the outcomes it wants \u2014 a drug, a solution \u2014 and guarantee a market if it\u2019s found and distributed equitably.<\/p>\n What kinds of public problems can A.I. solve? Look closely<\/a> at the math advance OpenAI just released, and what you\u2019ll see is that the A.I. system was able to combine two of A.I.\u2019s strengths to achieve the result: One was a vast knowledge of existing mathematics, such that it could apply a different branch of the discipline to the problem. The other was the ability to attempt possibilities that would have been too laborious for human mathematicians to try.<\/p>\n There are a lot of problems that could benefit from the sustained attention of tireless researchers with a vast knowledge of all relevant subject areas. Rare diseases, for instance, where the suffering is immense but the market for a cure is often not large enough to attract much private interest. Or hunting out<\/a> new uses for existing drugs. Or the search for new materials to extend long-term battery storage.<\/p>\n Right now, we\u2019re seeing promising pilot projects. Microsoft and the U.S. Department of Energy\u2019s Pacific Northwest National Laboratory worked together<\/a> on a project that used A.I. to analyze more than 32 million materials to discover an electrolyte that might improve lithium-ion batteries. But projects like these are a sideshow right now as the A.I. giants chase the guaranteed revenues of corporate clients. Only public funding has the possibility to bend the industry toward public problems.<\/p>\n Then there\u2019s the way A.I. could change the relationship between citizens and a government that is often maddeningly difficult to navigate. President Trump killed<\/a> the I.R.S.\u2019s Direct File program, but the technology exists now to go far beyond it: There could be an A.I. system that works through your taxes with you, grounded in both the I.R.S.\u2019s data on your income and the most up-to-date information on the tax code. Every person could have the equivalent of a personal accountant. More ambitiously, you could imagine that same L.L.M. as an entry point to government services: a kind of digital concierge to everything the government has that might help you.<\/p>\n