Adam Russell & Tom Kalil: What Do We Want AI to Do for Us? | Intelligence at the Frontier 2026

Tom has crafted a lot of policy. Um, as you told me could you tell me a little bit what you did with the OSTP? Sure. Yeah, so I worked for two presidents, uh, President Clinton and, uh, President Obama. And for two different parts of the White House, the National Economic Council, which coordinates domestic and international economic policy, and the Office of Science and Technology Policy.

And when the President in the State of Union would say, "Today I'm pleased to announce that we're going to do X." Uh, my job was to try to help come up with the X's. Uh, so examples of things that I worked on, uh, were uh, the promotion of the internet in the 90s, the National Nanotechnology Initiative, which, uh, President Clinton announced in January 2000, which has resulted in $40 billion in funding for nanoscale science and engineering, getting first DARPA and then every agency the ability to do incentive prizes for up to $50 million, and then the, uh, BRAIN Initiative. Uh, where our early goal is to try to do for neuro science what the genome project did for genetics. So it was broadly interested in science, technology, and innovation.

Um, and as a direct, uh, beneficiary of the America Competes Act, that allowed, essentially, uh, incentive prize challenges for the government to put out. So rather than having to fund people to do the research, you would actually set this ambitious challenge and then people could respond. And I'm sure you all are familiar with like what what that means. Uh, but when I was at IARPA as a program manager, it was because of that work that we were able to launch, uh, you know, our first challenge, which, I think actually provided tremendous ROI. Um, that meant, obviously, that you were thinking of many different ways that the government could, uh, essentially achieve its mission, uh, without just sort of relying on sort of the standard playbook of of funding and policy.

Um, what other Well, so where you are now, like what were other, uh, sort of new mechanisms of of funding that you did in government, and what are you most excited about now? Uh, so broadly speaking, currently the US government has a widely utilized mechanism for making financial commitments that are contingent on failure. So, if you were to look at the balance sheet of the federal government, what you would see is trillions of dollars of loan guarantees. So, that is the government saying, "Hey Adam, if your business goes bankrupt, the US government uh will assume your debt obligations." So, it's an if-then statement, but the if is predicated on failure.

And so, what I think is interesting is increasing the capacity of the government, but also other institutions as well, to make financial commitments that are contingent on success. So, NASA uh when the US retired the space shuttle, the NASA had to give the Russians $50 million every time we wanted to send an astronaut to the space station. And no one thought that was a particularly good idea. So, NASA said to SpaceX, "Build us a rocket that can go to the International Space Station, deliver and retrieve cargo, and we will buy rides on the rocket, but we'll also provide you with milestone payments for intermediate progress towards that goal." During the Trump administration, the way Operation Warp Speed worked is the government said to Moderna and Pfizer, "Um if you get a if you develop a COVID vaccine which is safe and effective, then we will buy 300 million doses."

So, there's an if-then statement, but now the if is predicated on you being successful as opposed to you failing. So, you know, if I were king for a day, I would create a marketplace of outcomes that has three participants, the entity that's willing to pay, like NASA was for the Falcon 9 rocket, the team that believes that they can achieve that goal, and the investors who are backing that team. Um so, that works primarily in those instances where you can define what winning looks like. So, for example, for the DARPA self-driving car competition, the finish line was literally a finish line. There was an obstacle course.

You had to get to the end. The second time they ran it, a Stanford team won. That's right. Larry Page was at the finish line, and he promptly acquired the winning team. Uh so, that's where Waymo

Hello, Waymo. uh Google X came from. Yeah. Um I I know you've got here, but the conversation today, the ideas are just really incredible, robust. Uh you have some of these ideas well there.

Let's say uh somebody here is like deviates from what he believes like if there were an outcome that we achieve in some particular area of either yes, Jerry, or or privacy, example, how would they go about like trying to seed an idea like that in the government uh to to do this or trying to go negotiate discuss? Yeah. So, uh when I worked for President Obama, people would come visit me, and they'd say, "Tom, you're never going to believe it, but it turns out that the thing that I work on is really important." And I would say, "Gosh, I'd never heard that before. What is it that you would want the way else to do?"

And that shockingly I have to say that at the time people did not have a good answer to that. So, the thought experiment that I always gave people is uh you have a meeting with uh President Obama in the Oval Office, and he says, "If you give me a good idea for, you know, whatever, AI of human censorship, then I will call a lot of climate. Uh it can be a conference call, so they can be more in the one person of all right. If that person works for you right to hit by by being directed will be something cuz I've been boss. If it's someone outside of government, I could challenge to do something.

So, you add a Now, wait. Do you have to tell me what your idea is, but in order to make your idea happen, who would I call alone ask to do? So, that that is the White House version of the Hillel Mark House. Okay. If you could call anyone, who would you call, and what would you ask them to do?

It's So, the premise of the thought experiment is that complex problems require building coalitions, and it is very difficult to build a coalition if you cannot articulate the members of the coalition and the mutually reinforcing steps that you want them to take in the form individual organization A takes action B in the pursuit of goal C. Check. Yeah, uh he mentioned the Heilmeier questions. Has anybody heard of those before? Oh, wow.

Okay. Um yeah, if you've ever been through an ARPA, uh it makes you instantly sweat. I mean, my hands are sweating here. Uh cuz the George Heilmeier was a director of DARPA who came up with what's called the catechism. There are eight fairly simple, like deceptively simple questions that essentially every program you see coming out of DARPA has to answer these questions.

And they basically load on the same factors of like, what are you trying to do? Why can't we do it now? What are the limitations? But then, who cares? What's new in your approach?

What's new in your approach? This is always the And by the way, the answer can't be uh well, I'm just smarter than everybody else. Um which rarely is the case. Um But you the story you just told is people come to you with ideas. Um one of the terms I used, which one I would use again, was harvestigate.

Like, how do you How do we How do we use ideas that are here now, but also can seize your can seize your investigate, right? What's the way for us uh to to find and identify like new new results of public goods? How How does the government do that? How should it do it? How do you do it?

Yeah, so I think one thing that is underrated is unbundling idea generation from execution.

Mhm. So, the way we usually do research funding is that we assume that the same person who has the idea should also be the person to execute the idea. And I don't think that's necessarily the case. So, I I think there are some instances where you just want a lot of ideas. And so, why why might you want to uh unbundle those?

Well, in part because the person who has the idea may not be in a position to actually execute the idea. So, for example, there are huge number of uh of opportunities at the intersection of uh AI and health where uh the you know, the the challenge is that a number of organizations are hoarding the data, right? So, you may have a researcher who could articulate, "This is what I would do if I could get access to the data, but I don't personally have the political juice necessary to make this happen, but you know, if you give me an opportunity to send my idea into someone, I can tell you uh you know, what what I think the the opportunities are. So, that's that's that's sort of one thing that I don't think that we do enough of is unbundle idea generation from execution. Interesting.

So, in in terms of the idea execution again, um or sorry, uh idea generation, um where we sit at DARPA is we are used to because there's a large budget, you're used to people coming to you, uh which makes you lazy in some cases, right? In particular, a lot of complaint, as you can imagine, is like, "Well, the talent in AI is very thin." And that's probably because the talent they see is the stuff that's going to you know, the the large tasks. Uh when you actually get out there and start hunting, you realize, "Oh, actually there's more than you think." Um what would you recommend for like a field strategist sort of approach?

Is Renaissance Philanthropy doing that? Um Yeah, so uh our vision is that in the same way that wealthy Italians fairly supported the Italian Renaissance by backing intellectual activity, today's philanthropists are positioned to support a 21st century Renaissance that is fueled by these big five bases in science, technology, and innovation. And one of the ways in which we do that is we design and launch thesis-driven funds that have uh you know, the problem