Sarah Kreps on AI, Drones, Guardrails, and the New National Security
John L. Wetherill Professor Sarah Kreps directs Cornell’s Tech Policy Institute and studies the intersection of technology, international politics, and national security.
An MQ-9 Reaper flies over the Nevada Test and Training Range in 2020. Photo by Airman 1st Class William Rio Rosado, U.S. Air Force, public domain.
Every era has a technology that appears to change the rules. Drones promised precision and distance. Cyber blurred the line between war and disruption. Artificial intelligence now sits at the center of nearly every national security debate, carrying with it both extraordinary possibility and the familiar temptation to overstate what any technology can do.
Sarah Kreps has built a career studying that tension. A former Air Force officer trained at MIT and now a professor at Cornell, she approaches new technologies with a historian’s caution and an empiricist’s patience. The question is not whether technology matters. It plainly does. The harder question is how governments, militaries, and societies can absorb new tools without surrendering judgment to them.
That is especially urgent on the battlefield, where phrases like “human in the loop” can sound reassuring until they meet the realities of pressure, uncertainty, and uneven human behavior. Kreps argues that the guardrails matter, but so does the evidence behind them. How do people actually use AI decision-support systems? When do they override them? When do they defer? And how much do policymakers really know about those interactions?
This conversation is about technology, but it is also about intellectual discipline: how to avoid hype, how to ask better questions, how to work across fields, and why sustained reading may become a serious advantage in a world designed to fragment attention.
This interview has been edited for clarity and length.
From the Archive · originally published in The Pathway Blog, January 2026.
Technology Disrupting National Security
Benjamin Wolf: I’d love to begin by asking: when you look across your work at the intersection of technology and national security, what is the core question you keep coming back to, and why does it feel urgent right now?
Sarah Kreps: A lot of people ask what the through-line is for my work. Broadly, it is the way technology is changing — sometimes disrupting — national security.
The motivation comes from my background in the military. I was in the Air Force. I did my training at MIT. So these ideas — technology and national security — are very much embedded in how I think about things. I’ve worked on everything from drones to cyber to AI to nuclear weapons.
I have a book coming out on these questions about how technology has disrupted national security. In it, I try to pattern-match, to think about hype cycles, the tech optimists and the tech pessimists, and position myself in ways that are historically and empirically grounded.
The reason it feels important now is that what is “relevant” keeps changing. In each moment, a different technology seems scary and disruptive. I’m trying not to offer simple solutions, but to frame questions: what can we, as a society and as a national security establishment, do to temper the excesses of technology while harnessing the opportunities?
Usable Evidence, Not Just Persuasion
BW: You have moved between institutions and audiences: academia, law and policy communities, and public-facing writing. How do you decide who you are speaking to on a given project, and what changes when the audience changes?
SK: I have never thought of myself as trying to persuade anyone. I would frame it instead as bringing insights to audiences that are in a position to protect society and take advantage of opportunities.
Sometimes that is members of society: how can they guard against disingenuous AI? Sometimes it is militaries: how can they take advantage of drones but guard against others’ use of drones? Sometimes it is government: how do we develop institutions that protect, for example, in a nuclear security context?
Too often, both sides engage in hyperbole, either tech solutionism or tech pessimism, tech doomerism. Often the answer is somewhere in between. What I’m trying to do is make sense of an appropriate equilibrium, not persuasion so much as providing evidence that helps clarify the problem.
From Environmental Security to “Bombs and Bullets”
BW: If I’m not mistaken, you studied environmental studies and public policy as an undergrad. What led you into the military and eventually into the work you do now?
SK: I grew up in the D.C. area, so I was always marinating in public policy questions and national security. My dad worked for the Department of Energy in the nuclear space. So I was always interested in some version of security.
As an undergrad and master’s student, that took the form of environmental security. I did a lot of work on environmental engagement. But as I did ROTC training, and especially once I was in the military, I pivoted to what people might call “hard” national security, or what folks in the business refer to as the “bombs and bullets” side of security.
Part of that was the era: Kosovo, 9/11, and then Iraq. These were big military engagements. My work in the military was developing new intelligence, surveillance, and reconnaissance systems.
It seemed to me there were big questions within the military that did not always have the analysis. You had practitioners without the analytics, and analysts without the military experience. My background allowed me to bridge those audiences in ways most people cannot, either because they do not have the credibility or because they do not have the experience.
Think Tanks, Interdisciplinary Work, and Real-World Questions
BW: After the military, how did your career evolve? And with fellowships and affiliations, are those things you pursued, or did they come to you through the work?
SK: Some of both.
Think tanks let you stay engaged with real-world questions. It’s not that the “ivory tower” deserves all the derision it gets, but it is certainly more insulated than the think tank community. Being involved in those conversations keeps ideas fresh.
If you look at the arc of my publications, I try to think hard about difficult national security problems. In 2009, before many people were paying attention to drones and U.S. counterterrorism, I started working on drones because I had been in that space earlier. A friend from high school, a philosopher, came to me and said, “I’ve been watching what’s happening with drones. You were in the military; you’re a political scientist. Do you want to collaborate?” So I said yes.
That is also true of my work more generally: it is interdisciplinary. That drones work was with a philosopher. My work now on semiconductor supply chains is with mechanical engineers. My AI work is with computer scientists.
In a way, it comes full circle to being an undergrad working in labs. I took a lot of hard science classes — chemistry, physics, math — so I can be credible not just in national security, but also across disciplines.
The questions that are pressing today are inherently interdisciplinary. They need voices not just from engineers or computer scientists, but also philosophers, political scientists, and people who study national security. And especially in the last few years, these have become big societal questions: AI’s impact on employment, the battlefield, the classroom. Many of them require interdisciplinary answers.
A Battlefield-Proof Guardrail, If One Exists
BW: Staying on AI: if you had to propose one realistic guardrail that could actually survive contact with modern conflict, what would it be?
SK: The important guardrail would be ensuring there is a human in the loop. But I’m not completely optimistic that it can survive contact with the battlefield.
Some of the work I’m doing right now is trying to figure out, in a data-driven way, how individuals in battlefield settings interact with AI decision-support systems. People are developing these systems and putting them out in the field, but we do not yet have great data about how people interact with them.
For example: do people respond to confidence thresholds in the same way? Are some more likely to override than others? We are often assuming one size fits all in how these systems are used, but we do not have good evidence for that.
So even saying “keep a human in the loop” is itself indeterminate, because we do not really know, within a group of ten people, whether those ten will respond similarly to the same outputs.
Grants, Rejections, and Showing Up
BW: You have certainly earned a lot of awards and grants for that kind of research. How do those processes start? How often do they work out? And how do you not get discouraged by the rejections?
SK: It is definitely a numbers game. You have to apply to a lot of things, and some will work out. Like a lot of things in life, it is about showing up over and over.
BW: When you win an award, do you already have a detailed plan for how you will implement it? Or does it adjust as you go?
SK: Part of the reason those processes are so long is that they require high-granularity thinking about what you are actually going to do. Execution is often more straightforward than idea generation.
Regulation Without Delusion
BW: When governments try to govern emerging technology, they often default to either overconfidence in rules or fatalism that rules won’t matter. What is your pragmatic middle path? How should institutions build adaptive governance without outsourcing responsibility to the technology?
SK: It is a tricky question, and I grapple with it in the book. There is no one-size-fits-all approach.
A lot depends on values. Europe is approaching this differently than the United States, which is approaching it differently than China. These regions have different values. Europe has long been more skeptical of new technologies, so the response tends to be more precautionary, even when technologies are still nascent.
We see that in the AI Act, which leans more aggressively into regulation than the U.S. The U.S. approach has been more: let evidence and data unfold so we can understand what the technology means before responding.
Policymakers face a conundrum. If you act too early, you may not understand the technology and could impede progress, for example, AI applications in medicine. But if you do not act soon enough, you risk being caught flat-footed as new threats emerge.
In AI, we have seen a lot of existential language where the reality is more ambivalent. In the U.S., it is also complicated because the U.S. has many of the tech firms. Aggressive regulation is not only about stifling technology and opportunity. It also has economic implications, because these firms are among the most thriving parts of the economy.
Certain states are taking regulation more seriously — California, New York — but what those steps can ignore is that capital and talent are mobile. They can move from state to state, country to country. In Europe, you do not have the same thriving AI tech sector in part because people come here to do the work, because they can.
Why Academia
BW: Outside your research and writing, you are also a professor at Cornell. Why did you decide to pursue academia alongside everything else, and what has been most rewarding about teaching?
SK: I went into my PhD at a place known for cultivating practitioner types — Georgetown — so I thought I wanted to go back into the policy world.
But once I got into my studies, I realized what a privilege it is to wake up every day and think about questions that are important in the real world, or at least I hope they are important. And also to educate the next generation on these issues. What better position than a university professor?
Someone from a think tank once said think tanks are great because they are universities without students. And I thought: why would you want to be at a university without students? Students are one of the best parts of my job.
I teach law students, business school students, PhD students, undergrads — the whole range. Each group thinks about these topics differently, and my interactions with them enrich the way I think about the questions.
Breadth and Better Questions
BW: As we wrap up, if a motivated undergrad wanted to contribute meaningfully to this field in the next 12 months, what are two concrete skills or habits — one analytical, one practical — that would make them more competent?
SK: I read this recently, and maybe it validates the approach I have taken, but the world today is a world suited for generalists.
Practically, I would recommend breadth. Some of the most interesting people can combine philosophy and computer science, or economics and political science. My recommendation is: don’t stovepipe yourself. Be well-versed across disciplines so you can look at problems not in silos, but as the real world presents them.
Analytically, it follows from that: learn how to ask the right questions. These aren’t falsifiable math questions. It’s about asking: how can societies, polities, and economies get the most out of new technologies without the negative externalities and risks? You try to get closer to the answer, even if there isn’t just one answer.
What She Wishes She Had Done Earlier
BW: What is a piece of career advice you wish you had taken earlier?
SK: Even though it contradicts what I said a little, I wish I had taken more math and more computer science earlier.
There is a lot of debate about whether computer scientists will become obsolete because of AI, but I think that is overblown. You need some understanding of coding to engage meaningfully with AI and to ask the right questions. I often feel like I’m outsourcing some of those parts to students.
On the other hand, that is what teams are for. Not everyone can be good at everything. The best teams bring together people who are excellent at coding with people who are excellent at other things. But yes, I would recommend that students load up on math and computer science while also engaging the bigger philosophical questions.
Why Deep Reading Still Matters
BW: One last one: if someone wants to follow a path like yours, is there any reading you would recommend?
SK: I would just recommend more reading. I lament that people are engaging more and more online and on their phones. As someone who studies technology, I’m becoming more of a Luddite, wanting to put my phone aside and read something dense.
Read a classic. Sit down with a dense novel — Dostoyevsky — something that is a slog, something that requires mental discipline. There is a lot of awareness of physical discipline, but I think mental discipline is atrophying. Our ability to sustain focus is lower, and it takes a conscious decision to retrain that part of the mind.
BW: I’ve honestly never heard that response before, and it feels right. We live in a world built around short-form video. Even platforms like Netflix and major news outlets are including clips on their platforms.
SK: The advice to read a dense book can sound out of step. But I do think that kind of mental discipline, something fewer people have, will set you apart.
BW: My computer is actually propped up on Walter Isaacson’s Steve Jobs biography right now — definitely different from Dostoyevsky, but certainly dense.
SK: Biographies are great. I love reading biographies because there is so much we can learn from people who have been successful.
And weaving insights together across different figures helps you map them onto your own personality. There is not one-size-fits-all. You read about one person, then another, and you can see, “I like this quality,” or “I hadn’t thought about that.” It becomes like a menu of skills and attributes. But how would you know that without reading deeply about people?
I read a biography of Martin Luther and found it fascinating, this figure from 500 years ago. He walked from Germany to Rome in the early 1500s. Putting yourself in a completely different time period — no trains, no modern travel — forces a mental exercise you do not get online.
What struck me was that he disrupted the status quo. We think of technology as disrupting the status quo, but that is what he did as an individual, enabled in part by technology like the printing press. Bringing those insights to the present is valuable.
And I think if I had read that book two years earlier, I would have gotten something different out of it. That is why reading is so useful. It stimulates thoughts that short-form content just won’t.
BW: Professor Kreps, I can’t thank you enough for your time. It has been an honor speaking with you today.
SK: Thank you so much, Ben.
About the guest: Sarah Kreps is the John L. Wetherill Professor in the Department of Government at Cornell University, Adjunct Professor of Law, and Director of the Cornell Brooks School Tech Policy Institute. Her work focuses on technology, international politics, and national security, including drones, AI, cyber, war finance, and military intervention. She previously served as an active-duty officer in the United States Air Force.
About The Pathway Review: The Pathway Review publishes long-form interviews with people in politics, policy, journalism, law, diplomacy, markets, and public service about the work they do and the path that brought them there.
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This interview was conducted in January 2026 and has been edited for length and clarity.