My other objection is that I feel a lot of despair when thinking in near-mode about the Plan A proposal of slowing down algorithmic progress.
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India’s leading company publishes a paper about a training dataset they used to make the user-experience for their AI smoother. The Indian regulator apparently green-lighted it, but they are known for their lenient approach. Some academics notice that the Indian model is now not just smoother to use, but it subtly feels like it’s smarter than other models, even though it doesn’t directly show on the standard benchmarks. The American AISI starts getting emails from academics, explaining that they feel like the Indian model got smarter, and that they think the paper the Indians published was too high-level to fully reconstruct what they did.
Meanwhile the American AISI is also getting emails from academics complaining about how the European AI is too biased against minorities, and how the Brazilian AI has too high persuasive capabilities, and how the compute cluster in the ocean is harming the fish. They are also tasked with defending the US companies from the totally unfair complaints coming from China and India that they are not transparent enough about their research.
The American AISI only has 200 people at this point, because they started out small, and you can’t easily grow an organization more than 2x per year. Also, 50 out of the 200 people joined because they care about the ocean cluster harming the fish. (It is true though that probably it helps a bunch that they have good AI assistants. Maybe the crux is that I don’t believe it that much that the AI assistants will solve the dysfunctionality.)
The American AISI starts a bilateral conversation with the Indian regulators, but by the time they get to anywhere, it looks like the Europeans and two American companies have already probably copied something like what the Indians did. The world clearly didn’t end, and the AIs are just a bit smoother to use now. So no one escalates to a big diplomatic fight, and they quietly accept that the Indians didn’t publish enough details this time. Everyone keeps scaling up the technique with more compute and more data.
A month later, there is a new report which indicates that some interpretability techniques show that some scheming propensities are maybe going up, maybe linked to the new technique. After another month (do you know how slow it is to do anything in a government agency?) the American AISI calls up the President, and tells him to put pressure on American companies and other world leaders to roll back the new technique. Unfortunately, the President doesn’t have much time, because the Australian PM is pressuring him to make sure no one’s AI goes along with human rights violations in an ongoing war in the Middle East. Plus, he needs to speak at an environmentalist conference about the fish. (Also, he is still the President, running the non-AI aspects of the country.)
Now the President needs to call up the other world leaders and make it clear that he is willing to go to war if needed, because this interp scheming score really shouldn’t go up (unlike last time when a bias score was going up, but after a lot of yelling, people decided it’s not worth fighting over). So the President and other world leaders (reminder: Xi is 73, Modi is 75, Trump is 80, Biden left office at 82) get together and discuss the interp results and come to an agreement.
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I think probably the sheer amount of bureaucracy still slows down algorithmic progress in the companies, and probably the government agencies pushing for safer directions and trying to ban more unsafe directions will have a non-zero correlation with actual safety. But it’s going to be a mess, and I don’t think you can slow down progress more than 2x this way, and the companies and countries that are more willing to skirt the rules will come out ahead more.
In contrast, GPUs, fabs and EUV machines are physical objects. I have much more trust in the government to competently control them and slow progress that way than through governing algorithmic progress.
My other objection is that I feel a lot of despair when thinking in near-mode about the Plan A proposal of slowing down algorithmic progress.
----
India’s leading company publishes a paper about a training dataset they used to make the user-experience for their AI smoother. The Indian regulator apparently green-lighted it, but they are known for their lenient approach. Some academics notice that the Indian model is now not just smoother to use, but it subtly feels like it’s smarter than other models, even though it doesn’t directly show on the standard benchmarks. The American AISI starts getting emails from academics, explaining that they feel like the Indian model got smarter, and that they think the paper the Indians published was too high-level to fully reconstruct what they did.
Meanwhile the American AISI is also getting emails from academics complaining about how the European AI is too biased against minorities, and how the Brazilian AI has too high persuasive capabilities, and how the compute cluster in the ocean is harming the fish. They are also tasked with defending the US companies from the totally unfair complaints coming from China and India that they are not transparent enough about their research.
The American AISI only has 200 people at this point, because they started out small, and you can’t easily grow an organization more than 2x per year. Also, 50 out of the 200 people joined because they care about the ocean cluster harming the fish. (It is true though that probably it helps a bunch that they have good AI assistants. Maybe the crux is that I don’t believe it that much that the AI assistants will solve the dysfunctionality.)
The American AISI starts a bilateral conversation with the Indian regulators, but by the time they get to anywhere, it looks like the Europeans and two American companies have already probably copied something like what the Indians did. The world clearly didn’t end, and the AIs are just a bit smoother to use now. So no one escalates to a big diplomatic fight, and they quietly accept that the Indians didn’t publish enough details this time. Everyone keeps scaling up the technique with more compute and more data.
A month later, there is a new report which indicates that some interpretability techniques show that some scheming propensities are maybe going up, maybe linked to the new technique. After another month (do you know how slow it is to do anything in a government agency?) the American AISI calls up the President, and tells him to put pressure on American companies and other world leaders to roll back the new technique. Unfortunately, the President doesn’t have much time, because the Australian PM is pressuring him to make sure no one’s AI goes along with human rights violations in an ongoing war in the Middle East. Plus, he needs to speak at an environmentalist conference about the fish. (Also, he is still the President, running the non-AI aspects of the country.)
Now the President needs to call up the other world leaders and make it clear that he is willing to go to war if needed, because this interp scheming score really shouldn’t go up (unlike last time when a bias score was going up, but after a lot of yelling, people decided it’s not worth fighting over). So the President and other world leaders (reminder: Xi is 73, Modi is 75, Trump is 80, Biden left office at 82) get together and discuss the interp results and come to an agreement.
----
I think probably the sheer amount of bureaucracy still slows down algorithmic progress in the companies, and probably the government agencies pushing for safer directions and trying to ban more unsafe directions will have a non-zero correlation with actual safety. But it’s going to be a mess, and I don’t think you can slow down progress more than 2x this way, and the companies and countries that are more willing to skirt the rules will come out ahead more.
In contrast, GPUs, fabs and EUV machines are physical objects. I have much more trust in the government to competently control them and slow progress that way than through governing algorithmic progress.