Sam Altman's WARNING To The Government On AI

In a historic moment On Capitol Hill.

OpenAI CEO Sam Altman, alongside other tech leaders, testified before the US Senate to discuss the future of artificial intelligence, its rapid rise, and America's role in shaping it. It's absolutely incredible. Sam Altman painted a powerful vision, one where AI could be bigger than the Internet and where America must lead or risk falling behind. In this video, I'm going to break down the opening statement, why it matters and what it tells us about where AI is headed next.

What happened with the Internet, we have happen again. I believe this will be at least as big as the Internet, maybe bigger. That needs to happen for that to happen. Investment in infrastructure is critical. I believe the next decade will be about abundant intelligence and abundant energy. Making sure that those that America leads in, both of those, that we are able to usher in these dual revolutions that will change the world we live in, I think in incredibly positive ways is critical. I got to go to Abilene, Texas yesterday where we're building out what will be the largest AI training facility in the world. It's coming along beautifully. Super exciting to see. We need a lot more of that. There's a whole sort of AI factory, like a supply chain of energy chips, standing up, data centers, building the racks and more. We've got to do that really well in the US so that we can continue to innovate, continue to lead and continue to sort of shape this.

And so, yeah, in the first clip there, we can clearly see that Sam Altman is talking about ensuring that the entire AI stack is met. So that entire AI stack, the, you know, knowledge, the chips, the energy, the. Those things actually affect each other more than you might think. And it's really important that those things are truly, truly kept in leadership by.

America because of course, as you know.

Many other countries can develop their own AIs. It's not like nukes where there might be certain regulations around it. Anyone can freely develop their AI system. Of course, there is probably just a talent shortage at the moment.

And so it's important that, you know.

America ensures that it's building the ship stack, the energy stack, and of course, getting the talent so that they can stay ahead in this AI race.

And so this is where we actually get to talk about how the AI race needs to be won by the.

United States and how this is quite.

Different to the other races. And basically the fact that we must beat China because they are not behind at all. As we recently discussed with the video, where Jensen Huang, the CEO of Nvidia, clearly said that Nvidia are looking at everything and they can see that China are not behind. I mean like a quarter of all AI researchers are Chinese. And these guys have serious, serious talent when it comes to producing some of the best models on the planet.

So what I hear there is something pretty similar to the races we've won before. Nuclear energy, for example, you know, the Germans and Austrians really led the innovation around that. But we won the race because we put a massive government effort collaborating with our universities and others to win that race. Space, you know, the Soviets put the first satellite up, put the first man in space. But we won the space race because we adopted a framework to ensure that we won. Aviation, automobiles, et cetera. So what I hear from you is you do need support from our government, but you also need the government to stay out of your way so you can innovate and win this race. How do we incentivize companies to do business here in America to make sure we win this race in America? And America leads not just China, but other non actors too? I mean, I think that the scariest thing about AI from a capability standpoint is doesn't have to be a state actor to win this race. It's not like nuclear energy, it's not like space technology. I mean a non state actor could just as easily win this race and wield more power than anyone else. So how do we encourage innovators investment to happen here in America to ensure we win this race? Mr. Ellman, you want to start?

We were honored to announce back in January project Stargate, a $500 billion investment, investment in United States infrastructure that is now well underway. As I mentioned, getting to see it yesterday in Abilene, the first site was incredible. We need a lot more of that. We need certainty on the ability to build out this entire supply chain, build the data centers, permit the electricity. We'd love to bring chip production here, network production here, server rack production here. And I think the world does want to invest. We have a lot of global investment flowing into the US to do this. We also to make sure that other countries are able to build with our technology, use our models and sort of like be in our orbit and you know, use US diffusion of technology here. So that's really important. We need to make sure that the highest skilled researchers that want to come work at US companies can come here and do that. We need to, we need to make sure that companies like OpenAI and others have legal clarity on how we're going to operate. Of course there will be rules, of course there need to be some guardrails. This is, is a very impactful technology, but we need to be able to be competitive globally. We need to be able to train, we need to be able to understand how we're going to offer services and sort of where the rules of the road are going to be. So clarity there. And I think an approach like the Internet, which did lead to flourishing of this country in a very big way, we need that again.

And so one of the things that I don't think a lot of people think about, and I really don't think they care, but I'm still including it here because I think the tides are changing a little bit in how we discuss this issue. So AI is a little bit different when it comes to privacy because most users actually freely share their data and their personal information with these models. And I don't think most people realize.

That, you know, your data, it's actually.

Going into ChatGPT and oftentimes they're actually training on those models. So I would say that, you know, privacy is something potentially to be concerned about, depending on the company that it is. Meta particularly doesn't have the best track record. And with data becoming more scarce, and I mean human data due to like the dead Internet theory where AI generated content is just proliferating social media, I think it's important to understand that.

I was going to ask you, Mr. Altman, how can we provide consumers with more control over how their data is used by AI companies while preserving the utility of the AI system? So how do you get more privacy and still get the benefits?

So there's all of the standard privacy controls that companies like ours and others build and should. But there's a new area that I'd love to flag for your consideration, which is people are sharing more information with AI systems than I think they have with previous generations of technology. And the maximum utility of these systems happens when the model can get very personalized to you. So this is a wonderful thing and we should find a way to enable it. But the fact that these AI systems will get to know you over the course of your life so well, I think presents a new challenge and level of importance for how we think about privacy in the world of AI, how we're going to think about guaranteeing people privacy when they talk to an AI system about whatever's happened in their lives, how we make sure that when one system connects to another, it shares the appropriate information and doesn't share other information and that users are in control of that. I believe this will become one of the most important issues with AI in the coming years as people come to integrate this technology more into their lives. And I think it's is a great area for you all to.

And so one of the biggest issues I've been speaking about for quite some time, but I haven't really spoken about it that much recently because I just felt that most people would ignore this issue. And it's about the issue of how AI is going to fundamentally change the labor market. And this question is posed to Sam Altman, basically stating, look, of course AI is developing at breakneck speed, but how do we ensure that this doesn't just completely upend society and all of those jobs? And he does talk about the fact that, you know, jobs are going to change. But after I show you guys this clip, I want to show you guys another clip by someone who actually used to work at OpenAI. In fact, I'll probably show you this clip before I show you guys this clip because Sam Altman in this clip essentially just says that, you know, we are, you know, building tools and jobs will change. And of course that is quite true, but I really can't understand what people are going to do. Want to resist AI doing a large majority of the tasks, how society is going to function after that. And the crazy thing about this is that Daniel Kokatajo, who used to work at OpenAI, ushers the same thing.

Talk to me about how you believe leaders in your industry can help mitigate job losses or, or deal with what could, as you described it last year, major social disruption.

The thing that I think is different this time than previous technological revolutions is the potential speed. Technological revolutions have impacted jobs and the economy for a long time. Some jobs go away, some new jobs get created. Many jobs just get more efficient and people are able to do more and earn more money and create more. And that's great. Over some period of time, society can adapt to a huge amount of job change. And you can look at the last couple of centuries and see how much that's happened. I don't know. I don't think anyone knows exactly how fast this is going to go, but it feels like it could be pretty fast. The most important thing, or one of the most important things I think we can do is to put tools in the hands of people early. We have a principle that we call iterative deployment. We want people to be getting used to this technology as it's developed. We've been doing this now for almost five years, since our first product launch. As society and this technology co evolve Putting great capable tools in the hands of a lot of people and letting them figure out the new things that they're going to do and create for each other and come up with and provide sort of value back to the world. On top of this new building block we have and the sort of scaffolding of society that is I think, the best thing we can do as OpenAI and as our industry to be a sort of help smooth this transition.

The idea, we want to get to a point where AI isn't displacing work, but actually enhancing work that people are more productive and doing things that we probably can't even imagine what people will do. If we look 100 years ago, we have jobs that no one can't imagine.

And I don't think we can imagine the jobs on the other side of this. But, but even if you look today at what's happening with programming, which I'll pick because it's sort of my background and near and dear to my heart, what it means to be a programmer and, you know, an effective programmer in May of 2025 is very different than what it meant last time I was here in May of 2023. These tools have really changed what a programmer is capable of, the amount of code and software that the world is going to get. And it's not like people don't hire software engineers anymore, right? They work in a different way and they're way more productive.

And then this is where essentially Sam Altman brings into the entire scope, basically of what AI is going to do for the future. And I think it's not an exaggeration. Every day, the more research papers I read, the more videos I see, the more demos, more breakthroughs. I really do think that this stuff is not underhyped at all.

I am incredibly excited about the rate of progress, but I also am cautious and I would say, like, I don't know, I feel small next to it or something. I think this is beyond something that we all fully yet understand where it's going to go. This is, this is, I, I believe, among the biggest, maybe it'll turn out to be the biggest technological revolutions humanity will have ever produced. And I, I feel privileged to be here. I feel curious and interested in what's going to happen. But I do think things are going to change quite substantially. I think humans have a wonderful ability to adapt and things that seem amazing will become the new normal very quickly. We will figure out how to use these tools to just do things we could never do before. And I think it will be quite extraordinary. But these are going to be tools that are capable of things that we can't quite wrap our heads around. And some people call that, you know, as these tools start helping us to create next future iterations. Some people call that singularity. Some people call that the takeoff. Whatever it is, it feels like a sort of new era of human history. And I think it's tremendously exciting that we get to live through that. And we can make it a wonderful thing, but we've got to approach it with humility and some caution.

And then lastly, this is where we actually get some information on OpenAI's open source model, because of course, as you know, DeepSeek pretty much changed everything with their model and competition is certainly heating.

Up in this country.

Very helpful. Thank you. Mr. Altman. Much has been made about the Chinese open source models like Deep Seq. We spoke about that a month or two ago. A concern that I have is that accessible Chinese models promoted by the Chinese Communist Party might be an attractive option for AI application developers to build on top of particularly in developing world economies. So how important is US leadership in either open source or closed AI models?

I think it's quite important. Lead in both. We realized that we OpenAI can do more to help here. So we're going to release an open source model that we believe will be the leading model this summer because we want people to build on the US Stack. In terms of closed source models, a lot of the world uses our technology and the technology of our colleagues. We think we're in good shape there.