Oversight of A.I.: Principles for Regulation — Full Hearing Transcript · 2023-07-25 · primary
Themes: Closed vs. Open Split · Safety Debate
Capable models should be required to pass pre-release testing, binding open weights and closed APIs alike.
However, private action is not enough. This risk and many others, like it requires a systemic policy response. We recommend three broad classes of actions. First, the US must secure the AI supply chain in order to maintain its lead while keeping these technologies out of the hands of bad actors. This supply chain runs from semiconductor manufacturing equipment to chips, and even the security of AI models stored on the servers of companies like ours. Second, we recommend a testing and auditing regime for new and more powerful models similar to cars or airplanes.
Oversight of A.I.: Principles for Regulation — Full Hearing Transcript · 2023-07-25
Third, we should recognize the science of testing and auditing for AI systems is in its infancy. It is not currently easy to detect all the bad behaviors in the AI system is capable of without first broadly deploying it to users, which is what create the risk. Thus, it is important to fund both measurement and research on measurement to ensure a testing and auditing regime is actually effective funding. NIST and the National AI Research Resource are two examples of ways to ensure America leads here.
Oversight of A.I.: Principles for Regulation — Full Hearing Transcript · 2023-07-25
Yes. I think it's really important because when we put open source out there for something that could be dangerous, which is a tiny minority of all the code that's open source, essentially we're opening the door to all the bad actors. And as these systems become more capable, bad actors don't need to have very strong expertise, whether it's in bio weapons or cybersecurity in order to take advantage of systems like this. And they don't even need to have huge amounts of compute either to take advantage of systems like this.
Oversight of A.I.: Principles for Regulation — Full Hearing Transcript · 2023-07-25
Releasing model weights raises the risk of catastrophic misuse, because guardrails cannot be applied and usage cannot be monitored once the weights are out.
I agree with all of that. I will add a few things. One, one concern I have is that even if companies use watermarking and especially because there's now several open source versions to train LLMs or use them, including model weights that have been made available to the global community. We also need to understand how things can go wrong on that front. In other words, people are not all going to obey that law. And one important thing I'm concerned about is one can take a pre-trained model, say by, by a company that made it public, and then without huge computing resources.
Oversight of A.I.: Principles for Regulation — Full Hearing Transcript · 2023-07-25
I think the path that things are going in terms of the scaling of, of open source models, I think it's going down a very dangerous path. And if the, if again, if the path continues, I think we could get to a very dangerous place. I think it's worth saying some things on open source models that are clear to all the experts, but I want to make sure is, is understood by, by this committee, which is when, when you control a model and you're deploying it, you have the ability to moderate usage. It might be misused at one point, but then you can alter the model.
Oversight of A.I.: Principles for Regulation — Full Hearing Transcript · 2023-07-25
So I just like to add a couple of points. I agree with everything the other witness had said. So one issue is being able to trace the provenance of from the, the output that is problematic through to which model was used to create it through to where did that model come from. And a second point is about liability.
Oversight of A.I.: Principles for Regulation — Full Hearing Transcript · 2023-07-25
A coordinated slowdown is worth pursuing even at the cost of advantage, because uncoordinated speed is the greater risk.
Well, I mean, one immediate fix is to avoid releasing more of these pre-trained large models. That's the thing that governments can do, because right now, very few companies, including, you know, the seven you, you brought last week can do that. And so that's a place where government can act.
Oversight of A.I.: Principles for Regulation — Full Hearing Transcript · 2023-07-25
Thank you. I don't think you'll find much disagreement with that proposition. But to have American workers do those jobs, we need to train them. And you all in some sense, because you're all teachers, you're all professors are engaged in that enterprise. Mr. Amodei, I don't know whether you can be called still a professor, but probably not. I was never a Professor <laugh>, but we need to train workers to do these jobs, and for those who want to pause, and some of the experts have written that we should pause AI development I don't think it's gonna happen.
Oversight of A.I.: Principles for Regulation — Full Hearing Transcript · 2023-07-25
Safety and innovation trade off against one another: what makes a model safer makes it less capable or less widely available, so pushing on one goal costs ground on the other.
So on the one hand, access to AI data is a good thing for research, but on the other hand the same open models can create risks just because they are open. Senator Hawley and I as an example of our cooperation road to meta about an AI model that they released to the public, you are familiar with it, I'm sure Lama they put the first version of LAMA out there with not much consideration of risk. And it was leaked, or it was somehow made known. The second version had more documentation of its safety work. But it seems like meta or Facebook's business decisions may have been driving its agenda.
Oversight of A.I.: Principles for Regulation — Full Hearing Transcript · 2023-07-25
Now, regulation is often said to stifle innovation, but there is no real trade-off between safety and innovation. An AI system that harms human beings is simply not good ai. And I believe analytic predictability is as essential for safe AI as it is for the autopilot on an airplane. This committee has discussed ideas such as third party testing, licensing, national agency and international coordinating body, all of which I support. Here are some more ways to, as it said, move fast and fix things. First, an absolute right to know if one is interacting with a person or a machine.
Oversight of A.I.: Principles for Regulation — Full Hearing Transcript · 2023-07-25
I don't think, I mean, there are many areas where there's important trade offs. I don't think this is one of them. I think such requirements make sense. I mean, to give a little of our experience in, you know, red teaming for these biological harms, you know, we've had to work on, you know, piloting a responsible disclosure process. I think that's less about reporting to the public, more about making the other companies aware. But, you know, the two things are similar to each other.
Oversight of A.I.: Principles for Regulation — Full Hearing Transcript · 2023-07-25
Yes. So I think… I, for one, think that makes a lot of sense. I mean, the, the way I would think about it is, you know, in the, in the testing and auditing regime that, that we've all, we've all discussed, you know, the, the best case is if all of these dangers that we're talking about don't happen in the first place, because we run tests that detect the, the dangers, and there's, there's basically, there's basically prior restraint, right?
Oversight of A.I.: Principles for Regulation — Full Hearing Transcript · 2023-07-25
Building national AI capacity on sovereign infrastructure is sound policy for smaller countries, not merely a way to sell deployments.
That’s what's sad about that scenario is that would be the best case scenario, right? I mean, if there's an invasion of Taiwan, the best we could hope for is maybe all of their capacity, or most of it gets sabotaged, and maybe the whole world has to be in the dark for however long. That's the best case scenario. The point I'm trying to make is, I think your point, Mr. Amodei about securing our supply chains is absolutely critical, and thinking very seriously about decoupling efforts, strategic decoupling efforts, is absolutely vital at every point of the supply chain that we can.
Oversight of A.I.: Principles for Regulation — Full Hearing Transcript · 2023-07-25
Well, it's good because here's, I think what would be terrible to see is this new technology that is built by foreign workers, not American workers. That seems like the same old story we've heard for 30, 40 years in this country, where we're told, oh, no, American workers, they cost too much. They're American workers, they're just too demanding American workers. They don't have the skills, so we're gonna outsource it. We're gonna give it to other foreign workers. Then you mistreat the foreign workers, then you don't pay the foreign workers. And then who benefits from it?
Oversight of A.I.: Principles for Regulation — Full Hearing Transcript · 2023-07-25
I'm glad that you're charting a different course Mr. Amide, and certainly we wanna hold that, hold you to that. But I, I think it's vital that as we continue to look at, at how this technology's developing, that we actually push for what, I mean, what's wrong with having a, a technology that actually employs people in the United States of America and pays them well, I mean, why should an American workers and American families protected by our labor laws benefit from this technology? I, I don't think that's too much to ask.
Oversight of A.I.: Principles for Regulation — Full Hearing Transcript · 2023-07-25
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