Chapter 1: What is the main topic discussed in this episode?
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President Trump signed an executive order aimed at limiting state-level regulation of AI. The move is supported by tech leaders who have argued local rules could stifle innovation. We're joined by David Sachs, the White House AI and Crypto Czar, or Senior Advisor. David, I think it's a really good place to start.
In your work with the president in consulting and advising on the formulation of this executive order, What was the problem that you were trying to solve for? And what is it that you said to the president about why this EO was the right approach to focus on state level laws? Ed, thanks for having me.
The problem that we see is that you've got 1,000 different bills going through state legislatures right now to regulate AI, and over 100 measures have already passed. Some of these bills are contradictory, and you've got 50 different states running in 50 different directions.
That type of compliance regime is going to be very hard for small companies and startups, especially innovators, to comply with. And so what we need is a single federal or national framework for AI regulation. And that's what the president has supported. And by the way, he supported this for a long time. If you go back to his July speech on AI, he called for a single national framework then.
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Chapter 2: What is the significance of Trump's executive order on AI?
That's important. We want to respect copyright. We want to preserve the ability of local communities to choose what infrastructure is in their communities. We're not seeking to preempt the states in any of those areas. This is an important set of principles that we have put forth. At the same time, the EO provides for a number of tools that can be used to push back on excessive state regulation.
Ed, let me just illustrate why I think this is so necessary. What we're really talking about here is regulation of AI models and algorithms. Think about how an AI model is developed. You can have developers in one state or multiple states writing the code. It can then be trained in a data center in another state.
You then can have inference happen in another state, and the entire service is provided over the internet using national telecommunications infrastructure. So you're dealing there with at least four different states, and all of them can lay claim to regulating those AI models. And those regulations can be in contradiction with each other. Even Democrat governors have admitted this is a problem.
So just the other day, Kathy Hochul, the governor of New York, basically said that she might prefer to enact California's SB53, which is a regulation that they just passed in California, rather than the bill that her own assembly gave her, the RAISE Act. Because she sees that, wait, do we really want to create this patchwork of different regulations?
So even Democrat governors are realizing this is a problem, and if they all run in different directions, then we're going to end up with a patchwork or a mishmash of regulations that are impossible for companies to comply with. What the president is calling for here is just common sense.
We want to get to a single national framework of compliance as opposed to 50 states running in different directions.
Meanwhile, Cathy Hochul actually is getting a bit of criticism perhaps for narrowing and what some are saying is bowing down to business. David, I'm really interested in how you oppose that view because there is anxiety in the population, AI versus jobs, AI versus energy bills.
How are you giving them the sense that we haven't seen federal government and indeed now state governments just handing over the reins to big tech billionaires as people call them?
Right. No, I understand there's a lot of fear out there about AI and job loss specifically. And a lot of those fears have been drummed up. Let me just say on the job loss question, because I think this is really important, that Yale just released a study. And it showed that in the 33 months after the launch of ChatGPT, there was no discernible disruption to the U.S. job market. None.
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Chapter 3: How does David Sacks describe the current state of AI regulations?
It's been quite the opposite. It's been job gains. David, final one on the EO, if I may. What this EO allows for, is it the sort of hope that it will lead to the DOJ suing states like New York and California? And if that's the case, the president and the administration's confidence that you'd win them?
Well, that is one of the tools that is in the EO, is that the DOJ has been tasked to form a litigation task force that would have the ability to push back on excessively burdensome state laws, laws that may be unconstitutional, violate the First Amendment, things like that. By the way, the DOJ already had that power. So this is not a novel power.
But what's being done here in this EO is we're marshalling all the resources of the federal government behind the strategy of the president to create a national framework. Now, in terms of what laws we go after, that's a decision that has been made. We haven't decided whether California and New York should be targets in that way.
The one that I think is probably the most excessive is this Colorado law that seeks to prohibit algorithmic discrimination. What that basically says is that if an AI model has a disparate impact on a protected group, then that model is violating the law. Model developers, by the way, have no idea how to comply with this because they're not aware of all the downstream uses of their model.
Chapter 4: What challenges do state-level regulations pose for AI innovation?
If a business decides to use an AI model in a hiring decision, for example, That business is already on the hook for discrimination, so how would the model developer know that it was being used in that way? But what Colorado is trying to do there is get their ideology inserted into the model. That's very concerning to us.
We think there's a First Amendment issue there, but look, we haven't made any decisions in terms of how that litigation task force will be used.
David, briefly, all of this is set in the context of US versus China and are deemed to run forward on AI development. Meanwhile, it's been a busy week and H200s might indeed be able to get to China. How many do you think you'll do in volumes? And what do you think the appetite is of China to buy NVIDIA's more sophisticated chips?
Well, it's interesting. I just saw an article that said that China was rejecting the H-200. So apparently they don't want them. And I think the reason for that is they want semiconductor independence. The same way that the United States wanted to be energy independent, they want to be semiconductor independent. So they're rejecting our chips.
And that's part of the calculation that goes into the decision of what we... authorized to be sold to China. The U.S. policy has always been that we don't allow the leading-edge chips, and we're not. This H200 chip was state-of-the-art a couple of years ago, but now it's been superseded by the newer Blackwell architecture and the Rubin architecture that's coming out next year.
So this is now a lagging chip, not a leading chip. But what you see is China is not taking them because they want to prop up and subsidize Huawei. They want to create a national champion. And that was part of our calculation of selling
Not the best, but lagging chips to China is you can take market share away from Huawei, but I think the Chinese government's figured that out, and that's why they're not allowing them.
David Sachs, we always wish we had more time. White House, AI, and crypto czar, we thank you for joining us today on The Executive Order. The forces shaping markets and the economy are often hiding behind a blur of numbers. So that's why we created The Big Take from Bloomberg Podcasts, to give you the context you need to make sense of it all.
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