How National Labs Drive U.S. Scientific Leadership

Lindsay: Hi, this is Lindsay Shingler, the host of Talking Policy. In this fourth and final episode of our miniseries on Technology & Security in the 21st Century, guest host Nic Wittstock sits down with Dr. Pat Falcone for an inside look at the national labs. They discuss the history and purpose of the labs, and the critical role they play in American innovation and global leadership.

Nic: Hello, everyone. My name is Nicolas Wittstock, and in this episode of Talking Policy, I am speaking with Dr. Patricia Falcone. Dr. Falcone is the deputy director for science and technology at the Lawrence Livermore National Laboratory in California. Previously, she served as the associate director of the White House Office of Science and Technology Policy for National Security and International Affairs, where she was advising on the science and technology dimensions of national security policy.

Today, we hear her perspective on American science, technology, and innovation policy, and how to meet some of the challenges that we have been discussing in this podcast series.

Hello Dr. Patricia Falcone, thanks so much for being here.

Pat: Thanks, Nicolas. It’s a pleasure.

Nic: Pleasure is all mine. Thank you so much.

I really can’t imagine anyone else better to talk about some of the questions that we’re trying to address today. I think currently we hear a lot about technological change related to various kinds of potential national security threats—or, let’s say, challenges that are relevant to national security, right?

So we hear about AI. We hear about drones, specifically in connection to the conflict in Ukraine. We hear about nuclear weapons. We also hear about things like climate change and energy security. So I’m curious about your take, first on a very general level as someone whose job it is to think about the connection between technological change and national security, but also to enact policy on this issue.

What would you say is the current state of science and technology, if that makes sense, and which fields are of specific importance and why? Specifically from this national security standpoint.

Pat: Well, thanks. I think that the state of science and technology is really fun. I mean, there is a lot happening and being at a place like this laboratory and sister institutions is a great privilege because we have the opportunity to work right at the frontiers.

And I think you’ve mentioned some of the important areas already. We work a lot in artificial intelligence, but really as it’s linked to high performance computing, detailed modeling and simulation of physical processes and getting new scientific knowledge, working on materials and manufacturing to make new things that can have good capabilities.

Working in particular, I think there’s a convergence of physical science and biological science that is leading to lots of new opportunities and capabilities and energy security as you mentioned already. So I think in all those domains there’s a lot happening and that includes potential opportunities to make things better, and also opportunities to make sure our nation’s prepared for threats.

Nic: So I want to unpack a little bit what the national laboratories do in the way that you’ve just described it. But also, maybe what it means for the federal government to work on a lot of these science and technology problems.

So in an earlier episode, we spoke to Bill Bonvillian about the history of the U.S. innovation system and the core role that the national laboratories have played. Could you maybe speak a little bit to what the labs do today, exactly?

Pat: So we are part of the Department of Energy, and the Department of Energy has 17 designated national laboratories, and they’re quite different one from another. But what’s common about them is that we have the responsibility of spending federal dollars to work on important things for the nation, and that ranges from very basic science, including the operation of very large and complex facilities that can do experiments, that yield data and understanding of different phenomena to, you know, very mission-focused work. How do we bring new energy systems and how do we understand resilience of our electricity grid? And also nuclear weapons: How do we have a strong and credible, safe, secure nuclear deterrent for our national leaders? And so the science and technology underpinnings of those important questions are what the labs do.

And our lab in particular, and actually all of the DOE system, are inheritor organizations from the Manhattan Project of the 1940s. And that was really about, you know, brand new science that began to emerge in the 1930s, nuclear science that had both threats and potential, you know, the understanding that led to decisions that were made in this country on how best can the nation be prepared to be at the frontier of science and to be sure that we’re using those frontiers to answer important national questions and to support national needs for many vulnerabilities that might occur from adversaries use of new technologies.

Our laboratory is not one of the first ones. We were founded in 1952, named after Ernest Orlando Lawrence, a physics professor at the University of California, Berkeley, who came from South Dakota and really is viewed as an originator of team science. He invented the cyclotron, and he worked to get funding and gather big teams to really build bigger and bigger experimental capabilities using that approach. Following World War II, Lawrence, Oppenheimer, [and] the others at the University of California, Berkeley were asked to expand that kind of science directly into these national security questions. Like what was it going to mean to have a nuclear weapons stockpile? And how do we understand the physics and engineering associated with a nuclear weapons stockpile, and all of the elements that go with that? And our laboratory was spun out of the Lawrence Berkeley laboratory to a site that is further east than Berkeley and out where an old naval air station was in Livermore.

Nic: Thank you so much. That’s fascinating. So I think for most people it’s probably somewhat intuitive to understand, you know, why the stewardship of the nuclear weapons stockpile requires an enormous amount of investments in science and technology, right, to understand how these things work both on a physical level, but also on a practical level.

You mentioned a lot of other areas of science that the federal government in general invests into, to a large extent. Arguably a lot of them are also related to national security.

But I was curious, could you elaborate on how decisions are made in this context? So like, who decides what science is relevant for national security? Who decides what kind of programs to fund? What drives the decision making here?

Pat: Well, the decision-making is done in the usual policy places.

So in my experience at the Office of Science and Technology Policy, which is a congressionally mandated entity that does sit inside the White House. So that means that its director is subject to senate confirmation and subject to being called before Congressional bodies to describe what’s going on.

Its job was the policy for science, the doing of science, and the science for policy—so information on science that informed other kinds of policy. So national security policy as you mentioned, but also overall innovation and economic policy, industrial policy to the extent different government leaders have different perspectives on the role of the government in that.

The thing about science is that you have to have a substantive, deep capability to be able to answer those questions. So the doing of science is different than science policy, and at the laboratories we’re in the business of the doing of science to answer questions for policymakers. But we are not policymakers here at the laboratory.

Nic: In the last three episodes on this podcast series, [we] have talked to three different experts on different challenges related to technological change. And I’m curious to get a little bit more of your assessment on some of these issues that they’ve raised.

So again, Bill Bonvillian, I think one of the core messages of the episode with him was that the impact of the federal government, through institutions like the national laboratories, on technological innovation, not just in terms of it being relevant for national security through things like the nuclear weapons program, but also in a lot of other fields right, has been enormously beneficial in economic terms.

But at the same time, it’s also somewhat publicly underappreciated. I’m just curious to get your sense of whether or not you would agree with that assessment and, if so, why that’s the case.

Pat: Yes, I would agree with that point. I think it would be difficult to hazard a guess about why that is. You know, I think the fact is that a lot of us know about what’s in our immediate area and maybe we never know much about what’s beyond. But it has been incredibly important. Numerous studies have shown that federal investments in science and technology do have very long tails in terms of economic prosperity.

And so, you know, it has been a part of political policy discussion for some time. For example, what fraction of the gross domestic product we should aspire to for research and development and how we want to foster partnerships. I think it’s also true, you know, government funding isn’t the only source, and at the present day, in fact, industry funding of research and development is larger than the government share. That changed late in the last century. But what industry does, and what the government does, is really quite different as a rule, in general. So the government does support the most basic research, and it also supports the most government mission-focused research and development.

I will say that, for example, on the Department of Energy website, there’s a website you can go to that has like 75 inventions from DOE’s national laboratories: micro[power] impulse radar, cleanrooms, you know, the technologies that were used for the Human Genome Project were all started inside a set of DOE laboratories, which includes our laboratory.

Another invention that came out of our laboratory is laser peening which, you know, to make metal very strong. If you read your history about the famous swords from antiquity, there was special pounding at high temperature that led to strength. And so for metallurgical things that had to be super strong, this idea of pounding, peening, came from the dark ages literally. But using lasers to do that is now what enables our jet engine blades to work at much higher efficiency at higher temperatures. So lots of inventions, and I would recommend that list on the DOE website to see them enumerated—or a small set of them.

We have guidance and permission to patent and push out technology and to work with industry to, you know, partner directly to bring something to market.

We also, the labs have very deep partnerships with universities such as your own, where we’re both collaborating with faculty members, because of course the universities are sitting really right at the frontiers of all these domains of interest, but also to have opportunities for students—that their training can be in these scientific facilities that the government has paid for, and get training and partnership with lab staff.

And there’s also community engagement as well. So, you know, the labs are not separated. And so, one would hope that engagement would lead to greater awareness.

Nic: Another point that emerged from the discussion with Bill Bonvillian was the idea, in recent years, that the declining manufacturing capacity of the United States is essentially in itself a major national security challenge. And in his line of argumentation, an issue for technology policy, right? So he hopes to see in the future an increased federal role to try to induce essentially more technological innovation and commercialization of new technologies, in the next generation high tech manufacturing space. To what extent are the labs currently already engaged in similar kinds of programs? And to what extent do you feel like that could be a productive role for the labs, in the future, to scale these kinds of activities up?

Pat: Well, let’s see. You’re absolutely right that manufacturing is very important, mostly because we all like things and we use things. And it is also something that we are deeply involved in, and the DOE laboratories as a system, with respect to nuclear weapons in particular, a part of the Department of Energy called the National Nuclear Security Administration has the responsibility to actually make, and to fix up when they get old, the nuclear weapons stockpile that are then transferred once they’ve been made by the system under the auspices of the National Nuclear Security Administration. So DOE owns the manufacturing of nuclear weapons. So there is a specialized set of manufacturing responsibilities.

And, in addition, manufacturing and materials are very much a part of the use of these new scientific tools. The modeling and understanding of materials, the use of combined modeling and simulation tools with artificial intelligence to imagine the characteristics of a material you would like to have, both the material and the configuration of the object you want to make with it. And so that is the kind of research that is ongoing.

We at Livermore have been very involved in both what’s called advanced manufacturing, so that would be what we talk about when we’re removing materials. So if you think about whittling or you think about making a metal part in a shop, you know, you start with a big object and you remove material.

And of course, today after several decades of continuing work, it’s not absolutely brand new, but it’s totally fun is additive manufacturing, right? Where you build up material and objects and I think we’ve all had the opportunity to see that with plastics, but we’re seeing it more and more in the industry factory floors, for very special parts where you can make things that you never could make with the removal approaches, the additive approaches give us new opportunities. So yes, that is definitely something that we spend a lot of time on.

One thing that I think is particularly fun, and something we invented with the University of California Berkeley, is something we call volumetric manufacturing, which is basically, with particular resin, you can have a pattern that optically will just grow. You can watch it grow inside a volume of liquid. So it is really very Star Trek-y. So there’s a number of these additive approaches, not just using strings of plastic that you might have seen and lots of materials, and I think that gets to the overall future of manufacturing, which is maybe different. Because the processes are very fine dimensional at very small scales, and you can make bigger and bigger items. I think one thing that one of our sister laboratories, the Oak Ridge National Laboratory, has on display at DOE headquarters is a small sports car that they built with additive manufacturing.

Nic: So I think one of the concerns here would be that a lot of other people, not just me, would make the argument that part of the issue here for U.S. national security could be construed as the following. That, especially over the last, I don’t know, 20-30 years, the United States has continued to be very inventive, creating all kinds of amazing technologies like you’re describing right now, however, has not necessarily translated into companies that make use of these inventions in the sense of creating domestic manufacturing capacity around these technologies, but rather, building that manufacturing capacity abroad.

And I think increasingly, this is perceived as a national security threat in the case of a worsening international diplomatic situation. It might be the case that you simply don’t have access to some of these technologies, if trade gets disrupted, for example. So the question is, is there an increased role potentially for the labs to try to work together with industry to generate domestic manufacturing capacity? Is that something that is in the purview of the labs, or is that something that would have to be addressed in some other way?

Pat: Well, I think you’re addressing a set of important policy issues that the policymakers need to make a decision about how we want to do it. I think the problem is real, but I also think that strengthened relationships with nations that, you know, we have relationships with, we have shared values, that we can knit together a stronger supply chain. Certainly the pandemic highlighted for all of us the need to pay a lot more attention to supply chains. But I do think that having more opportunities to see how to better tie together more basic science and technology at what we call technology readiness levels, from very basic to very routine manufacturing, that tying all the parts of the innovation ecosystem together better are real opportunities that policymakers could exploit.

There was legislation, in the early nineties, the Bayh–Dole Act, that really encouraged the laboratories, gave them the direction, to really make sure the taxpayers get this double advantage: the tax dollars that go into the research, but then if there’s innovations that come out, that we formally have processes to engage. And at Livermore, we have an innovation and partnerships office that directly engages with industry and our patents.

There’s a lot of discussion now about how do we make more intimate partnerships, particularly in these new technology areas. But we do have folks to try to build those bridges both ways, for industry, but also as I said, with academics, with other partners in the innovation ecosystem. Because the labs are certainly not the only part, we’re one part of the overall system. And the rule set, as you’ve asked about policy, could be improved, I think.

Nic: Do you want to say a little bit more about how it could be improved?

Pat: Well I think, as you might know, often the government, when it makes a deal, wants to be in charge of everything because it’s the government. But what is interesting about new technology is that there’s many areas of new technology where the government is not the owner of all the technology.

You know, we’ve innovated in a lot of areas, and I mentioned already that industrial R&D actually contributes more actual dollars to the research and development dollars. So in many technical areas, but I would note in particular the big information technology areas, so that includes artificial intelligence, and also in the biological sphere, so, you know, we have big bio industries, particularly pharma. So in those areas I think that a more shoulder-to-shoulder partnership set of rules may be needed. Because the proposition that we’ve had in the past is: the government owns the most of the assets, and so the rule set makes decision-making slow and cumbersome. And we’ve been told by industry that they’d love to work with us, but, you know, the processes we go through to get permission take too long. So we want to speed that up and maybe have a slightly different rule set.

Nic: We also spoke to David Hart about clean energy, but also more widely, the promise of cheap and abundant energy as not just a tool to reduce greenhouse gas emissions, but also as a tool to amplify economic growth in the United States. And I think it’s a little bit difficult to interpret the recent budget bill to that extent. But I would say that energy security remains certainly a topic that at least on its face seems to be very important to the current administration.

And it appears to be that energy needs of data centers make abundant, cheap energy extremely important for potential U.S. leadership in AI in the future. But I’m curious, again, how you think about this from the national security perspective, right?

So how important do you feel like this energy topic really is, for AI and for U.S. leadership in AI, and whether or not that’s really something to focus on, or are there other issues that are much more important to navigate this emerging field of AI as a technology class?

Pat: Well, energy is essential. Absolutely. And we sit in the Department of Energy, so of course we care about it. But it also means DOE does own that sector—that is to say, you know, they have responsibility for the security issues related to the sector.

So first of all, that’s my area of training. I’m a mechanical engineer by training. My background is in combustion systems and propulsion, and energy is interesting and it’s essential. What do we have to do? There’s issues about supply and I think that diversity of supply always gives you more resilience, but also a distribution.

You know, I’m sure you’ve heard a lot about grid, stability, grid security, the components that go with that. But in terms of generation, you know, I am realizing now that if we don’t talk about fusion, I will likely be fired by my boss. So,  the most advanced and high potential kind of, energy work is, because of our responsibilities in the nuclear weapons area, we have a longstanding interest in the science of high energy density systems, like the energy that we get from the stars and in the center of planets, and trying to reproduce those processes in a laboratory on Earth. We’ve now done that eight times in our National Ignition Facility, a keystone of our laboratory. And so fusion does offer a potential energy source that has many benefits. So, yes, we’re working on that.

But there’s also lots of other dimensions, and I think you’re right about the increased use of energy by data centers, but also by human beings. I’ve had the opportunity now to listen to Secretary Wright, and he’s quite passionate about the importance of energy just for having all the people on the planet have good lives and talks about that only a fraction of the 8 billion people have the kind of access to energy that we do in our country that we enjoy, and that energy’s needed to support human beings.

So, yes, we want to be working on energy security, which is security of the generation and the distribution and the use.

Nic: Finally, we also spoke to professor Mark Schwartz about the politics of big technological transitions. And I suppose I’m interested in your take on the extent to which we’re really at the cusp of a, I don’t know, fourth industrial revolution—depends a little bit on how you count these things, right?

But basically a big economic transformation built on the widespread implementation of a new set or a new stack of technologies, most importantly, I suppose, being AI. First of all, to what extent do you think that is imminent?

And to what extent is the U.S. really in a position, both from a policy but also from an economic perspective, to really take advantage of these new technologies?

Pat: Yes, I believe that AI has big implications and I am hopeful that we get the kinds of productivity increases that would benefit our nation economically, at the same level that the Industrial Revolution afforded.

And also, I guess if we look back at these other transitions, we also need to be prepared to deal with dislocations—there will be dislocations in any transition. I guess I do believe that we are on the leading edge of a big change. If you think about the ubiquity of communication, just how different it is now with cell phones. And so the connectivity and then the density of information. Our laboratory has a big strategy for artificial intelligence, which has a couple of elements. Like, it’s so important. We’re trying to really work to understand it. And, you know, it’s not fully developed, so understanding is a daily task and is big. And because it’s about, well, what’s it good for, what’s it bad for? How’s it getting in our way? How is it helpful?

And we’re contributing. AI is very much about computation. That is a history in this laboratory. The first sort of big laboratory equipment that this laboratory purchased in 1952 when the lab started, was the supercomputer of the day. And we continue that tradition, we have currently the fastest, biggest supercomputer in the world, and we have probably two dozen supercomputers on site.

So because AI is compute-intensive, it’s something that fits with us and we’re already contributing. Partnering is essential. We’ve already talked about the importance of partnering, but you know, the companies that are developing AI and the web services, we need to understand what they’re doing. There’s things we do that they can’t. Our scientists have been doing these “AI jams,” where particular companies for a couple of days will give scientists across the lab system access to do scientific problems, because the companies don’t have the kinds of assets of scientists.

And so, once you’ve vacuumed up everything on the web, the next question is how are you thinking about new knowledge? And that’s what scientists think about is new knowledge. So they’re very interested in seeing how our scientists use it. That’s part of evolving partnerships.

And then the final two parts are applying it, taking AI tools and having folks work with our missions in the nuclear deterrence area, in non-proliferation and energy security. And then we’re employing it to run the lab. I mean, we have a big project going on to rewrite some rules for some nuclear facilities where there’s just piles of documents that we’re concerned that, you know, how do we take a fresh look and make sure that we’re doing everything with the right scientific approaches today. And AI is a good tool for supporting our staff. And so we have this comprehensive view, and I think that’ll ultimately lead to benefits and, as I said, maybe some dislocations that we’re going to have to face up to and address, making our way through them smoothly like we did through the industrial revolution.

Nic: You mentioned that the U.S. remains at the leading edge of a lot of these developments. How large do you consider the competitive threat here from peers in the science and technology space, like notably China, for example.

Pat: Well, I think that’s, as you well know, an acute area of discussion. I’m impressed and would commend the work of Jimmy Goodrich, who I think you probably know as well. He’s given a lot of talks, but notably he talked, relative to scientific facilities, to NSF’s National Science Board a few months ago, and you can find that on the web.

China has a lot of smart people, but I think our system of government and the innovation and excitement, that it’s my sense that we have to keep running. We have competitors, but our system is working. But we’re going to have to be purposeful and not pollyannish, and we’re going to have to put resources into supporting our innovation ecosystem and our use of AI in appropriate ways and helpful ways, and figure out ways to prevent bad uses.

And I guess one of my biggest concerns is that we’ve got to make sure to bring everyone along. To do the kind of work we do, you really have to have your math and your science in your elementary and secondary schools. And if we don’t provide those, then people don’t have the option to study. Because I think, in the science and technology world, that experience is built a little more vertically than it is in other domains. And so, personally, I’m very interested that we make sure to keep our education system strong absolutely everywhere in the country and have this open pathway to study all these great things and to be a part of making the AI revolution happen right in the U.S.

Nic:  So, I’d be remiss not to at least ask this. You know, you mentioned education, you mentioned the need to invest in science to be able to fully make use of some of these new technologies, but also to compete with peers.

Is the United States politically in a position to do this? I mean, the current administration is cutting science from a variety of directions, right? It’s in an open confrontation with a lot of the leading universities that you mentioned are very active in this space, you know, might eliminate the Department of Education.

There’s two ways to interpret this, right? One way would be to say that like, well the U.S. has a fundamental issue in financing a lot of these things. And that’s not really a political problem, but this is just a matter of, like, how you approach that, but ultimately you’re going to have to cut in some way. Or, this is a political polarization issue, right? Because you ultimately have one of the major parties in the United States right now that is very opposed to the view that you have to invest in all of these things in the way that you just laid out. What would your reaction be to that?

Pat: Well, I’m definitely concerned about the uncertainty in funding, particularly as it’s affecting young scientists. So I was on a campus, on a review committee, at about the time this spring that the graduate students had received notice that they had been accepted to graduate school and then they were replying, and across the universities, as the funding uncertainty happened, some of those admissions were rescinded or postponed.

And also for our young scientists, it is a little unsettled right now, but it has been my experience that there is strong support by U.S. citizens for strong science and technology. And people love their cell phones, and they love, you know, satellite TV and all kinds of other things.

I guess I have some hope that it’ll work out. I mean, I think we have to say that, you know, not everything is perfect and we do have to be open to change. As scientists, we love experiments, and I think for policy, pilot projects are important.

And I guess it’s still my belief that we’ll sort it out. But the changes have been injurious to people that are at key points in their career path. And we have to work together to continue to deliver on these things.

Nic: So let me ask in closing, given that you have infinitely more expertise in this than I will probably ever have. From your perspective, what are some of the major technological challenges that I haven’t mentioned and that you feel like aren’t mentioned enough in the public conversation for the United States in general?

Pat: Well, I guess I’m thinking about when I was writing my dissertation, I had a small Post-it note above my desk that said, “hard work pays off.” And so I guess, you know, there’s a lot of fast talk, but the fact is that if we are going to deliver for our citizens on, you know, space travel, on people having energy to have their lives be better, for better health outcomes. That we can use AI to tailor drugs to people’s particular issues. To get all of these benefits, it takes doing hard, no-nonsense work. And so we need serious people trained and working and all our policy folks focused on real jobs and new industries. And so I guess my view is: hard work pays off—and I did finish my dissertation watching that every day.

Nic: Oh, that’s the most important thing, yeah.

Dr. Patricia Falcone, thank you so much for being part of the podcast. This has been very interesting.

Pat: Thank you very much.