Recent proposals have argued that the best route to governing AI is to separate the technical and political parts of the problem. The idea is attractively simple yet catastrophically flawed.
Andrew Freedman, CEO and co-founder of the AI governance nonprofit Fathom, recently wrote about this idea in Transformer. He argued that independent verification organizations, working to standards defined by the government, could “insulate the facts” from the “coercive choices” that are a part of politics. But such insulation is fanciful. Vaccines, for example, are safe, but the facts have not protected them from politics. Freedman doesn’t propose any means of preventing AI testing from winding up in the same situation.
There is a certain elegance to the concept described by Fathom and Freedman, which is similar to one described in 2023 (and recently updated) by Gillian Hadfield of Johns Hopkins University and Jack Clark of Anthropic. Boiled down to its essence, the idea runs like this: (1) The government sets outcome-based safety standards; (2) The government licenses Independent Verification Organizations (IVOs); (3) AI developers opt-in to the process, which partially insulates them from certain forms of liability. If an AI developer opts-in, it must be certified by one of the IVOs licensed by the government. The Fathom proposal does not even include the Hadfield-Clark concept that an AI developer’s private regulator could impose meaningful penalties short of cutting off the regulator’s own revenue stream.. If the IVOs fail to ensure the outcome-based standards the government set, they can lose the license they were granted.
