One likely default response is I expect people to start clamoring hard for open-source bans, and depending on what happens in November 2026, they could plausibly succeed.
More generally, I expect the public to be even more anti-AI, and for politicians to sate that appetite by starting to ban open-source.
One good example of this is soft law/FUD from the federal administration:
I would guess that the Trump Administration will at some point realize that their best strategy here would be to create large amounts of regulatory risk around the use of open-weight Chinese models. You don’t need to “ban open source” (one of the dumber motifs of AI policy discussion). You just need to direct every agency to issue soft law that creates FUD. “A Federal Reserve Advisory Bulletin found that there may be backdoors in Chinese AI models.” It needn’t be that well justified. You just create enough regulatory risk that every regulated enterprise backs off. You probably don’t want to create so much regulatory risk that you scare off the hyperscalers from serving Chinese models; this will just drive startups to sketchier providers. There’s a happy middle ground here. I’d assume they will do some version of this.
Or even just floating very interventionist ideas:
it’s pretty easy to screw with open source if you’re the admin! you can mess with procurement etc as Dean mentions. but you can also call up hyperscalers and float some absurd interventionist ideas if they continue to host Chinese OS at scale. that’s the problem with the token-hungry structure of deployments compared to OS software: this all runs through extremely expensive, mostly centralised, infrastructure.
This is not that bad, but it is a problem because it crowds out misalignment concerns and also because the path the US takes is not likely to be one that favors slowing down/pausing, because the open-source AIs won’t be misaligned (most likely.), and the people in power will just see it as a security problem.
You know, I never thought about it, but it does seem possible that until the dangerous open source model is distilled, the US (and other countries) could actually proactively lean on global compute providers to not host it, driving the market price way up, if/when LLMjacking rates fall.
I wonder how long people in power will continue to see examples of misalignment and just think of it as a product or security problem? Would there be something that would nudge them towards thinking of it as a moral/ethics problem?
One likely default response is I expect people to start clamoring hard for open-source bans, and depending on what happens in November 2026, they could plausibly succeed.
More generally, I expect the public to be even more anti-AI, and for politicians to sate that appetite by starting to ban open-source.
One good example of this is soft law/FUD from the federal administration:
Or even just floating very interventionist ideas:
This is not that bad, but it is a problem because it crowds out misalignment concerns and also because the path the US takes is not likely to be one that favors slowing down/pausing, because the open-source AIs won’t be misaligned (most likely.), and the people in power will just see it as a security problem.
You know, I never thought about it, but it does seem possible that until the dangerous open source model is distilled, the US (and other countries) could actually proactively lean on global compute providers to not host it, driving the market price way up, if/when LLMjacking rates fall.
I wonder how long people in power will continue to see examples of misalignment and just think of it as a product or security problem? Would there be something that would nudge them towards thinking of it as a moral/ethics problem?