Good morning everybody. My name is John Hamre, and I'm the president at CSIS. My role here is entirely ornamental; I'm only here to render honors to Michael Kratsios and to say thank you to him. You all ought to know he's a recidivist. You know, thank God he's back in government. He had a very distinguished tenure in the first Trump administration and decided he'd even do it again. We're really fortunate to have him here.
Navin Girishankar, who heads our economic security and technology division, is going to make a formal introduction, but I wanted to take a moment to help everyone here appreciate the really important nature of what we're going to talk about today and celebrate, I should say. You know, you think about the US government and the legal structure around the government—it goes back 250 years. So we have a Department of Agriculture, we've got a State Department, we've got a Treasury Department. Now we have a Defense Department, but it used to be a War Department. All this stuff goes back 250 years, and so the government is structured to deal with things in those stovepipes, in those columns. But when you get some profoundly new technology like artificial intelligence, it just cuts across everything. You cannot have a single department take the lead on designing a policy for a government for a brand-new thing. This is the hardest thing a democracy does, and the only way to make that happen is to have it done in the president's office.
And then when it's a science issue, a technology issue, it has to be led by the most competent and capable people we have, who both are credible in the science world and also understand government. That's why they asked Mr. Kratsios to head up OSTP. Personally, I think we need a science department, overdue, but then you've got to take stuff away from other departments and that's where it gets too hard. So, this is a remarkable feat to see a very coherent product, a framework, because the hard work is in front of us now. But this framework would not be possible in our system of government that goes back 250 years if we didn't have OSTP, and we celebrate the fact that you're leading it. Michael, thank you. Let me turn to Navin Girishankar for the introduction.
Well, thank you, Dr. Hamre, and really delighted that you all can be here. A very, very warm welcome to Director Kratsios for coming and spending his time here, and for some of his team who briefed us this morning. I would just add we have a department focused on economic security and technology issues, and I think it's very, very clear that AI is everybody's business. The ambition and at the same time the specificity of the plan are really quite striking, and we're going to hear a lot more about it today. I will simply say that Director Kratsios, for those who don't know, is director of the White House Office of Science and Technology Policy and senior adviser to the president. He's the key force and one of the key forces behind this action plan, and so this is the right conversation to have at this moment, a very consequential one.
And in his previous incarnation in the previous Trump administration, he was the Chief Technology Officer for the United States and also acting Under Secretary of Defense for Research and Engineering—a long history of public service. I would simply say I read the plan, we're studying it, we're trying to understand it better. I'm reminded of the Emerson quote: "Do the thing and you will have the power." And I think when you think of the execution agenda that's ahead of us, I do hope every success for this plan and am very interested in understanding the particulars. There's no better person to have this conversation with Director Kratsios than Greg Allen. I believe they worked together in the past, but Greg is our senior researcher on AI, all things AI, and this is going to be a very interesting conversation. Director, very much welcome your presence here. Thank you.
To be clear, they're clapping for you, not for me. So, thank you all. I'm Greg Allen. You heard Navin say that Michael and I had the privilege of working together. It's more accurate to say that I was like an insect in the Department of Defense and he was kind enough to take an interest in my work from time to time from his previous perch in the Office of Science and Technology Policy. I'm reminded of what former Secretary of Defense Ash Carter, the late Ash Carter, said in his memoirs about the US political appointee system. He said about 25% of political appointees are just completely out of their depth and it was a mistake to put them in the job, 50% sort of muddle through, and 25% really nail it. I knew from the first meeting I had with Director Kratsios that he was in that best 25% who really nail it. And we are grateful and privileged that he decided to return to public service because he did have attractive alternative options, and yet he forsook those for the sake of the country.
One of the benefits of his choosing to do that is what we're going to talk about here today: the AI Action Plan and the three AI executive orders and the Trump administration's AI agenda for this second Trump administration. I could try and talk about what's in these plans and what's important, but who cares what I think? I think we'd all rather hear it from Michael. So to just sort of level set for the rest of the conversation—and we're going to get into the weeds here—what is in these orders that we all should be paying attention to?
Well, first off, thank you, Greg, for having me. Thank you, CSIS, for putting all this together. I was very excited and lucky to work with you in the first administration. For those of you who don't know, Greg played an extraordinarily integral part in launching the first AI efforts at the Pentagon, and the things that we talk about today—JAIC and CDAO and everything that's happened there—it all started because of this guy here. So he's a real patriot and made a huge impact on the way we think about AI and national security.
For me, last week I think was a big week for the United States, for the president, and for the future of artificial intelligence in this country. The journey, I think, to getting to the action plan actually started in the first Trump administration, in Trump 45. At that time, AI was not on the cover of every newspaper. It was not something everyone was talking about. Most think tanks here in Washington didn't have people like Greg Allen writing about AI or talking about it. It was just an issue that was kind of out there and percolating. And we have to give a lot of credit to President Trump, who signed the first executive order in the history of the United States on artificial intelligence in February of 2019, and he set the first national strategy and launched the American AI Initiative. Again, this was at a moment when ChatGPT didn't exist, when most people, when they thought about AI, were not thinking about chatbots or anything like that.
It was a very prescient moment where we realized that the US had to lead in this. The main pillar or thrust of that initial national strategy that we had then was all around research and development leadership, and how we can turbocharge the research ecosystem so that the US can be the home for the next great technological discoveries. The president then went on to announce a doubling of AI spending. And then fast-forward a few years later, and all of this great research and all this great effort that we put together as a country to work on AI sort of came to bear with the launch of ChatGPT, and then we were off to the races.
The country kind of endured four years during the Biden administration where there was a real philosophical discussion happening in Washington about the future of AI regulation, and more importantly, a very intense conversation around the hypothetical risks associated with this technology. If we go back to that era and we think of the first order, the first hearings that were happening on the Hill, there was a lot of debate about how much should we regulate, how much should we not regulate, and whether or not we as a country need to be really scared about this technology. In my sort of 30,000-foot estimation or summarization of how the previous administration thought about these issues, fear was what led almost all of their policy decisions. It was something that was captured and manifested in the Biden AI executive order. This was, I believe, the longest executive order that President Biden signed during his term. It set very weird, arbitrary limits around pre-deployment testing of AI models, and it created sort of this fear in the AI community that the government was going to come down and overly regulate this technology.
When we came into office, we needed to really turn the page on that. We realized that the US has to lead in this technology. Our national security and our economic security—our success there is so reliant on our ability to lead in AI, and we had to put together a plan in order to deliver on that. So the president on day one signed an executive order rescinding the Biden executive order, and three days later, on January 23rd, he signed a new executive order directing me, the National Security Advisor, and our senior adviser for AI, David Sacks, to come up with the new AI Action Plan.
Sorry for the background, but here we are with the plan. And I think what I found most exciting about the last six months was the level of engagement and participation from the broader American community on what we should be doing and thinking. I remember you've done a couple of podcasts, and whenever you describe OSTP, I always love the way you think about it: we're sort of this wonky policy office that not a lot of people have heard of, but we have great experts, we do important things. One of the things we do is we put out RFIs, and we put out an RFI for the community to say, "Hey, we're doing this AI Action Plan. We want America to win in AI. What should we be doing?" And I always thought, "Who even checks what an RFI from this office no one's really heard of is? What's going to happen?" We got 10,000 responses. We had an insane number of responses from all walks of life in the United States. We had Hollywood stars reacting and sending letters, we had obviously AI companies, we had big financial services companies, we had civil society. So it really showed that there was an intense interest in participating in this project. We ingested all those, and ultimately the plan came out.
To quickly summarize it—and I want to get into the conversation—essentially there's three primary pillars with the overarching theme that America has to win the AI race. As I said before, as a country, we have to have the most dominant technological stack in the world, and that's critically important for our national economic security. In order to do that, we have to do three things. The first is we have to lead on innovation. We have to continue to be the home for the next great technological discoveries in AI. That means creating a regulatory environment that can allow these technologies to thrive in the United States, give certainty to our AI companies that they can continue to innovate, provide opportunities for small businesses and new startups to be able to innovate in AI without being scared of state-level laws, for example, and also continue to invest in the very critical R&D associated with the next discoveries. We have to apply that AI to all sorts of things. We've seen today AI is extraordinarily good—or large language models are very good—at coding, for example. There's a lot more we can do in scientific discovery, in biologics, that we need to continue to work on.
The second pillar is all about infrastructure. We know that the key ingredient to driving the AI revolution is going to be our ability to create the right amount of electricity and also create the data centers that are going to need to be powered to do all of this critical inference and training. So there's a lot of actions in the plan and in the executive orders that talk about how we can unlock it. And the third pillar is all about AI exports. One of the most important things we need to do is make sure that the world is running on the American AI stack. We have the best chips, we have the best clouds, we have the best models, we have the best applications. Everyone in the world should be using our technology, and we should make it easy for the world to use it. We want everyone in the world who's developing AI to be using American software. So those are three pillars, lots of actions under them to do it, and we think by doing those three things we can win AI.
Amazing. So we're here at the Center for Strategic and International Studies, so I do want to start off on the international part of the conversation and the actions in here. But before I do that, I just want to commend one thing about the action plan, which is, as a guy who had "strategy" in his title when I was at DoD, the typical government strategy document is not a strategy document—and you have a private sector background, so I know you appreciate what I'm talking about. It's a list of nice things that they wish would happen. And this is an action plan. It's actually talking about things that we're going to do, the way in which we're going to pursue those goals, and even a willingness to accept trade-offs when we're going to do this and not that. I think that's just entirely commendable.
So on the international part, as you said, it's all about promoting AI exports. And the companion to the AI Action Plan element of this is, of course, the executive order, which is promoting the export of the American AI technology stack. This is interesting because it's not just about an approach to promoting exports; it's actually an idea for combining different elements of the technology stack and making it a unified package that the government is supporting. So what was your motivation for pursuing that as a strategy for increased exports? What was the problem you were trying to solve? Because just to put a hypothetical out there, there's a ton of demand for American technology all around the world. Somebody could make the case: why do American companies need help? The line is out the door and around the block for American AI technology. So what's the problem that you were trying to solve in this executive order and with this part of the plan?
Yeah, on the first point on the action plan, the language was extraordinarily deliberate. When we were working on this executive order during transition, there was this whole debate about: do we do another AI strategy? Is that how we turn the page on the disaster of the Biden EO or not? And I think the reality was no, we want actions. We want people to begin doing these as soon as possible. We gave ourselves a tight timeline. I know six months sounds like a long time, but in government time it's not a long time, and we really pushed hard to make sure we could get it out. We're excited about that.
The origin of the AI export idea, I think, comes back even to Trump 45, when I spent far too much time as essentially the US technology minister around the world talking to fellow ministers trying to convince them to rip and replace Huawei. I had these very, very challenging conversations where the West had technology which we perceived to be of higher quality, especially in the early years of the Huawei wars, and they still didn't want to buy it because the US just was not able to create the environment and the packages necessary to export it out. As we were thinking about this issue over the last four years, what I kept coming back to is the issue that we face today is even more serious than the telecommunications problem that generally the West faces in the Global South. If most countries around the world are running on an AI stack that isn't American and potentially one of an adversary, that's a really, really big problem.
Why I think it's so acute is that over time, the way that these models will operate on a government level is all the government data that a government has is going to be ingested into models to provide citizen services. Whether it's the way you pay your taxes, whether it's your healthcare records, whether it's small things like if you want to apply to get a permit to go to a national park for a campsite, all of this stuff is going to be part of the AI fabric. It would be a huge problem if the model that is fine-tuned to generate these AI solutions isn't from America. So we have to get out in front of it.
Why we're in a better position today than we were with the Huawei issues of the late 2010s is because we actually have a US alternative, and this time we have an alternative that is way better. We have the best stack. We have to always remember that we have the best chips, we have the best models, we have the best applications. So we're at a moment of extreme strength, and we need to be able to go out there. The world wants to run AI. They want to be able to provide AI for their people and for their citizens, and the question is: how do we meet our customers where they are?
You go back to the stack question: why did we think of it as a stack? What I generally observed over the last three or four years traveling around the world trying to get more countries to use AI is, generally a lot of countries are interested in having AI for their people, but the specifics of what that means is not necessarily always there. We have to fill in the blanks for them. We have to show them what the potential is for AI for their people and their country and their economies, and make it as easy as humanly possible for them to implement it. An American who wants to build AI, you're going to have to go to a different cloud vendor and do some trade-offs. Maybe you like GCP, maybe you like AWS, maybe you like Azure—you kind of play off each other. Then you think about the models: you go to all your model vendors and you choose a different model. Then you think about all your application vendors. For CIOs or CTOs in corporate America, that's your job—you do that, you pit them against each other and get the best price. If you're out in the world as a technology minister and you want to provide tech for your people, that's not a calculus that you do every day. We as America need to make it easy for lots of folks to understand what's available and how they can actually deploy this technology in their country. So that's kind of the thinking around it.
This is really interesting. You made the explicit comparison to Huawei, and I think one of the things that China Inc., as an approach to selling their technology stack abroad, does is they really do offer turnkey solutions and try to emphasize that aspect of it. So even though at every part of the stack America might be better, the fact that China was in this past period willing to offer the full stack, and America basically said, "If you put all of our pieces together, we promise it's way more beautiful and good, but you, the customer, have to navigate that complexity of putting all the pieces together." So is it fair to say that this approach is trying to make it easier for customers to navigate that complexity, so if they have the money to buy, we will make it simple to buy American?
Yeah, and I think it's twofold. It's not just if you have the money to buy we can make it simple because we have these packages, but more importantly, what the executive order does is it activates our development finance organizations within the USG to start prioritizing export of AI. That's the Export-Import Bank, the Development Finance Corporation (DFC). For years, these organizations have been sort of directed by Congress to work on this sort of technology race around the world, but it's not necessarily in their DNA. These development organizations for many years have been very good at doing hard-infrastructure-type projects. If you want to buy a plane, financing for a port, they know how to do that; they've done those deals over and over and over again. But we need to start building into their thought process that technology in the stack itself, from the chips and the compute all the way up to the algorithms, is what the US needs to be exporting. We need to find a way to create attractive financing packages through that.
So you're going to be building institutional capacity within these institutions to focus on that. That's amazing. So the flip side of promoting American exports is also controlling exports that we don't want to be going to the wrong places. The action plan really came very clearly and said, "We want to strengthen enforcement of AI compute export controls. We want to strengthen enforcement of semiconductor manufacturing equipment export controls." So I know that there is a needle that you're trying to thread with all these strategies, but I can forgive those who are casual observers of what the Trump administration is doing, and they would say, "Hey, there's areas where it seems like the Trump administration is relaxing export controls," for example, recently allowing exports of the Nvidia H20 chip to proceed, "but then there's these other areas where they're strengthening export control." So what is it you're trying to accomplish, and why are the basket of decisions that you've made sort of threading the needle that you're trying to thread?
Yeah. What we talk about in the report and we generally believe is that the highest-end semiconductors need to continue to be export controlled and not allowed into China. That's important for our ability to maintain our leadership in this race. The restrictions that we put on some of the supply chain behind the semiconductor manufacturing—some of these lithography machines—in the first Trump administration are probably one of the strongest actions that we ever took and most effective.
The highest return-on-investment export control in the whole story.
Absolutely. Those are still in place, and the action plan continues to contemplate whether there are other items that need to be thought about there. For us, I think that's kind of the dichotomy we see: continue to make sure that the highest-end chips are not making their way into China, and also think about the supply chain. The enforcement thing is really key, and I think we need to continue to do better as a country on being able to enforce this stuff. You can have the best export controls in the books, but if you're not able to effectively enforce them because you're resource-constrained, that's a challenge. I know Under Secretary Kesler, who runs BIS, and also Secretary Lutnick have talked about this. This is something that the Hill talks about a lot. We have to find ways to provide the tools that BIS needs to do the enforcement activities necessary.
I just want to commend you on this, because there's certain parts of this AI Action Plan that really do reflect the OSTP role in the interagency process and the NSC role in the interagency process. There's actions in this plan that could not have been taken at the department level. On the point about export control enforcement, something that I've been howling into the void about for years is connecting the intelligence community to the task of export control enforcement, which is a role that they had during the Cold War and then suspiciously forgot about right in the 1990s. Using the White House to actually drive that kind of connection between those various agencies, I think that's so long overdue, and I want to commend you on that.
The second thing that I was very interested to see was on the semiconductor manufacturing equipment side: a focus on components. So, not just the entire finished machines, but the key components that go into machines. Could you just elaborate on why you think that's important and what you're trying to accomplish with that focus?
Yeah. A lot of components relating to these machines are of US origin, and there are certain export control rules you can use that if there are certain components of these machines that are US, then you could sort of essentially control the whole thing. I think that opens up a lot more opportunity in thinking strategically about the types of machines and capabilities that you want to limit Chinese access to. Again, we are in a race, and what's important is that we're not necessarily cutting everything off from China. I think what we're carefully thinking about is, as we're doing these trade-offs, what do we think is most important? It continues to kind of be this balancing act. I think you saw it a bit with the H20s, but we continue again to control the highest-end things.
Great. So H20s are chips that are going to be able to be sold legally into China under the revised policy. There's also the chips that are being illegally sold to China via smuggling. The Trump administration rescinded the Biden administration's AI diffusion rule. But at least as I understand the messaging that's coming out of the department, they hated a lot of what was in the diffusion rule, such as country-level caps, but there was a focus on making sure that customers had appropriate protections in place to make sure that American intellectual property was protected, to make sure that chips that were sold weren't smuggled. So the diffusion rule was rescinded, but my understanding is there's going to be forthcoming guidance about the kind of protections that need to be in place for large-scale chip transactions to happen. President Trump, in his speech on July 23rd, said that we're going to maintain necessary protections for national security. Can you talk a little bit about where the administration is in developing what those protections are going to be? If we're going to sell these chips, how are we going to have confidence that that customer is not a Chinese front company? Because the Financial Times recently reported that in this year alone, there's over a billion dollars of Nvidia chip exports—and Under Secretary Kesler has talked about this being a problem—smuggled chips to China. Where are you in this story?
Yeah. Just to clarify on the H20, it's not a free-for-all sale. Any sale that Nvidia wants to make to China is one that's going to require an export license. BIS has said publicly that they will be evaluating each of those license applications and weighing the costs and benefits—
And the traditional restrictions of no military actors, no intelligence actors—those kinds of things will apply for those licenses.
You can imagine those would be contemplated. And then the security considerations when doing additional exports of chips around the world: I think they fall in a couple of buckets. The first thing that you think a lot about is the physical diffusion of the chips themselves. This one probably gets more airtime than it probably should. For those of you who—
have ever been to a large-scale AI data center, you know, these aren't chips I have in my pocket. We're not talking about a bag of diamonds or something. This is a massive rack that's tons in weight. You're not going to just put it on a forklift and back it into a truck or something. So, the physical diversion of the chips themselves is something that you probably could very easily and conceivably monitor and track with physically just counting: are they still there or not?
The second piece of the puzzle is around the use of these ultimate data centers to do training runs or be accessed by actors who you don't want to be. And this is where sometimes you see PRC cutouts or other companies that sort of spring up, but then want to do training runs on these machines. I think we have to remember, especially in what are we most worried about? Are we most worried about sort of small-scale sort of inference runs for some Chinese app? Probably not. What you're most worried about is large-scale runs that are for training sophisticated models that you would be worried about. And those are actually pretty easy to flag. Most people aren't doing multi-billion-dollar training runs on these training clusters. So I think between being able to have stringent and strong KYC requirements imposed on people who are operating the data centers, married with monitoring for the scale and scope of the actual training runs, I think you're able to kind of piece together and identify actors.
Great. Keeping with the international theme but changing gears slightly, I want to talk about regulation and governance. Vice President Vance, in his speech at the Paris AI Action Summit back in February, was pretty harshly critical of the EU AI Act and EU technology regulatory efforts that affect American companies more broadly. You know, the actions that the administration is taking are framed explicitly as a light-touch regulatory approach and really don't want to throw the baby out with the bathwater as we try and ensure safety and efficacy in AI. But at the same time, we've seen that some American companies have already announced that for their large language models, for their general-purpose AI systems, they are going to abide by the EU AI Act code of practice. So, where is the administration on its thinking about how to engage with these international AI regulatory frameworks, and does that affect anything that you're trying to accomplish in the AI action plan?
Well, the EU stuff is particularly disappointing. It's funny, if you ever look on sort of the EU Commission's Twitter, they have a lot of pride in leading the world in tech regulations, which I find amusing. And they initiated all of this effort around the EU AI Act many years ago before sort of large language models are what they are today, the way that we can evaluate them, we can think about them. They still use very sort of antiquated high-risk, low-risk buckets, all sorts of stuff. And their inability to actually implement the act itself has led to this new phase of thinking around the sort of code of conduct that they want people to agree to. And they essentially have our American companies over the barrel of a gun saying, "Look, if you don't sign up for this code of practice and this much more stringent thing we haven't really defined, it's going to come after you, which is the EU AI Act." So I think it's very unfortunate that they're using these tactics, and they have big markets so our companies want to be able to access those markets, and it's very unfortunate to kind of see it play out. I think what we try to do in the United States is be able to show that there's an alternative to that sort of precautionary-principle-driven mode of AI regulation, and that's what we're building here in the United States.
The very key fundamental distinction between the way that the Europeans view AI regulation and we do as an administration is the Europeans continue to think of it as a singular AI regulation that is sort of horizontal and crosses everything. It is just like AI rules.
Computer rules, yeah, even better way to put it. And I think the US thinks about it much more as the way that you should think about AI regulation: it needs to be use-case-, sector-specific, and risk-based in nature. So, if you think about it, the regulators at FDA who are thinking about AI-powered medical diagnostics are the ones who should be doing regulations on AI-powered medical diagnostics, not some group somewhere else in government that is doing AI regs. And the people who are doing drones or the people doing autonomous vehicles or the people doing financial services, they're the experts in regulating that industry, and you can imagine this is just like another technology that has entered into their domain. So, Department of Transportation was regulating vehicle safety, and NHTSA was regulating vehicle safety before there were even a bunch of electronics in cars, and now there are, and it just grows over time. And I think, yes, you could argue, do they have enough capacity or understanding of this new technology to keep pace? My argument is yes they do, and they will over time get better at it, and we have to push them as experts and as industry leaders to educate them on kind of where the technology is, but that's how you get good regulation.
Yeah. Keeping with the topic of regulation, there was a proposal that was originally in one of the drafts of the big beautiful bill for a 10-year moratorium on state-level AI regulation. It was ultimately not included in the final version that was passed, but there are some movements in the action plan that deal with the issue of state-level AI regulation. So, can you talk a little bit about what the mechanisms you're using are and what you're trying to achieve?
So, the President spoke about this directly in the speech where he made the point that, look, having a patchwork of regulations across the entire country just doesn't make sense and is not pro-innovation. If you're a startup and you're trying to create an AI use case and California has one law and Colorado has another one, and you're trying to figure out how you comply with both, that's really hard. If you're a large Big Tech company with a multi-trillion-dollar market cap, you probably have enough lawyers to figure it out. But the smaller guys probably can't, and it's not fair to them. And generally, that's where the administration position is: it's probably smarter to try to have, if we do have AI regs, it should be uniform across the country and essentially try to preempt states from being able to do that. How that plays out and how we're able to find consensus with the Hill remains to be determined, and we look forward to working with the Hill on all these issues. But I think the President was very clear on what the position of the administration is, that generally for being pro-innovation, you have to avoid a patchwork of state regs.
