Assigned into teams of three or four, students were given an area of strategic competition to focus on for the duration of the class, such as computing power, semiconductors, AI/machine learning, autonomy, space, and cyber security. In addition to readings, each group was required to conduct interviews with key stakeholders, with the end goal of producing a memo outlining specific policy-relevant insights about their area of focus.

But the final project was only part of the grade. The instructors also evaluated each group based on how they had used AI to form their analysis, organize information, and generate insights.

“This is not about replacing true expertise in policymaking, but it’s changing the nature of how you do it,” Volmar emphasized.
 

Expanding Students’ Capabilities

For the students, finding a balance between familiar habits and using a novel technology took some practice. 

“Before being in this class, I barely used ChatGPT. I was definitely someone who preferred writing in my own style,” said Helen Philips, an MA student in International Policy and course assistant for the class.

“This completely expanded my understanding of what AI is possible,” Philips continued. “It really opened up my mind to how beneficial AI can be for a broad spectrum of work products.”

After some initial coaching on how to develop effective prompts for the AI tools, students started iterating on their own. Using the models to summarize and synthesize large volumes of content was a first step. Then groups started getting creative. Some used AI to create maps of the many stakeholders involved in their project, then identify areas of overlap and connection between key players. Others used the tools to create simulated interviews with experts, then use the results to better prepare for actual interviews.
 

For Jackson Painter, the class provided valuable practice combining more traditional techniques for developing policy with new technology.

“I really came to see how irreplaceable the interviewing process is and the value of talking to actual people,” said Jackson. “People know the little nuances that the AI misses. But then when you can combine those nuances with all the information the AI can synthesize, that’s where it has its greatest value. It’s about augmenting, not replacing, your work.”

That kind of synthesis is what the course instructors hope students take away from the class. The aim, explained Volmar, is that they will put it into practice as future leaders facing complex challenges that touch multiple sectors of government, security, and society.

“This is a new type of policy work,” he said. “It's accelerated, and it increases the depth and breadth students can take in. They can move across many different areas and combine technical research with Senate and House Floor hearings. They can take something from Silicon Valley and combine it with something from Washington. It's an extraordinary thing.”

Real-time Innovation

For instructors Blank, Felter, and Volmar, classes like “Technology, Innovation, and Great Power Competition” — or sister classes like the highly popular “Hacking for Defense,” and the recently launched “Entrepreneurship Inside Government” — are an integral part of preparing students to navigate ever more complex technological and policy landscapes.

“We want America to continue to be a force for good in the world. And we're going to need to be competitive across all these domains to do that. And to be competitive, we have to bring our A-game and empower creative thinking as much as possible. If we don't take advantage of these technologies, we’re going to lose that advantage,” Felter stressed.

Applying real-time innovation to the challenges of national security and defense is the driving force behind the Gordian Knot Center. Founded in fall of 2021 by Joe Felter and Steve Blank with support from  principal investigators Michael McFaul and Riita Katila, the center brings together Stanford's cutting-edge resources, Silicon Valley's dynamic innovation ecosystem, and a network of national security experts to prepare the next generation of leaders.

To achieve that, Blank leveraged his background as a successful entrepreneur and creator of the lean startup movement, a methodology for launching companies that emphasizes experimentation, customer feedback, and iterative design over more traditional methods based on complex planning, intuition, and “big design up front” development.

“When I first taught at Stanford in 2011, I observed that the teaching being done about how to write a business plan in capstone entrepreneurship classes didn’t match the hands-on chaos of an actual startup. There were no entrepreneurship classes that combined experiential learning with methodology. But the goal was to teach both theory and practice.”
 

That goal of combining theory and practice is a throughline that continues in today’s Gordian Knot Center. After the success of Blank’s entrepreneurship classes, he — alongside Pete Newell of BMNT and Joe Felter, a veteran, former senior Department of Defense official, and the current center director of the GKC — turned the principles of entrepreneurship and iteration toward government.

“We realized that university students had little connection or exposure to the problems that government was trying to solve, or the larger issues civil society was grappling with,” says Blank. “But with the right framework, students could learn directly about the nation's threats and security challenges, while innovators inside the government could see how students can rapidly iterate and deliver timely solutions to defense challenges.”

That thought led directly to the development of the “Hacking for Defense” class, now in its tenth year, and eventually to the organization of the Gordian Knot Center and its affiliate programs like the Stanford DEFCON Student Network. Based at the Freeman Spogli Institute for International Studies, the center today is a growing hub of students, veterans, alumni, industry experts, and government officials from a multiplicity of backgrounds and areas of expertise working across campus and across government to solve real problems and enact change.

Prepared for Diverse Challenges

In the classroom, the feedback cycle between real policy issues and iterative entrepreneurship remains central to the student experience. And it’s an approach that resonates with students.  

“I love the fact that we’re addressing real issues in real time,” says Nuri Capanoglu, a masters student in Management Science and Engineering who took “Technology, Innovation, and Great Power Competition” in fall 2024.

He continues, “Being able to use ChatGPT in a class like this was like having a fifth teammate we could bounce ideas off, double check things, and assign to do complex literature reviews that wouldn't have been possible on our own. It's like we went from being a team of four to a team of fifty.”

Other students agree. Feedback on the class has praised the “fusion of practical hand-on learning and AI-enabled research” and deemed it a “must-take for anyone, regardless of background.”

Like many of his peers, Capanoglu is eager for more. “As I’ve been planning my future schedule, I’ve tried to find more classes like this,” he says.

For instructors like Felter and Volmar, they are equally ready to welcome more students into their courses.

“Policy is so complex now, and the stakes are so high,” acknowledged Felter. “But what we’re seeing in these classes is a passion for addressing real challenges from students who may not have otherwise thought they have a place at the table of national security or policy. That’s what we want. The best and brightest future policymakers are going to have diverse skill sets and understand how to leverage every possible tool and capability available to meet those challenges. So if you want to get involved and make a difference, come take a policy class.”

When the Department of Homeland Security’s Advisory Council announces it plan next week for overhauling how the agency combats the spread of disinformation online, its focus will be on “how to achieve greater transparency across our disinformation related work” and how to “increase trust with the public,” according to council meeting minutes released Monday.

Read more at Cyberscoop.com

Click the link for a transcript of “Spies, Lies and Algorithms with Amy Zegart."

The Origins of Spies, Lies and Algorithms

When I was a professor at UCLA, I was teaching an intelligence class. On a lark, I did a survey of my students and I asked them about their spy-themed entertainment viewing habits, as well as their attitudes towards certain intelligence topics like interrogation techniques.

What I found was there was a statistically significant correlation between their spy-themed viewing habits; people who watch the show 24 all the time were far more pro-waterboarding, among other things, than students who didn't watch spy-themed entertainment.

This got me really thinking, what do people know about espionage? Where do they get this information? And what I found is that most Americans don't know anything about the intelligence community, and when you're talking about spy agencies in a democracy, that's really problematic.

The original book was going to be more of a textbook for the class I was teaching, but as I write it, so many things started to change in the intelligence community, both politically and technologically. So with that in mind, I tried to make it forward looking to where intelligence needs to go, not just backward to where it’s been.

Who are the Spies?
 

The biggest surprise for me came from the research I did on open-source intelligence and nuclear threats. If ever there was an area you would think spy agencies would have cornered the market on intelligence, it would be nuclear threats.

But what I found is that there's a whole ecosystem of non-governmental people tracking nuclear threats around the world and actually uncovering really important things. That includes some open-source nuclear sleuths here at Stanford among my colleagues at CISAC.

The more I dug into this, the more I realized that open-source intelligence and publicly available data is the ballgame in the future of intelligence. Secrets still matter; but they matter a whole lot less than they did even ten years ago.

There is so much insight that we can glean from open-source information, but the intelligence community has to figure out better ways to connect with organizations and people who are in this ecosystem.

What are the Lies?

Intelligence is about deception. We don't want our enemies to understand all of our military capabilities, for example, or what our intentions are.

But I think the technology and data revolutions of the last few decades has also changed the nature of deception. It’s gone from elites deceiving elites about where their troops are, and whether they're going to attack, to mass audience deception and this disinformation-information warfare of domestic audiences like we're experiencing here in the United States.

Understanding deception, not in a pejorative sense but as an analytic frame, is critically  important to being able to gather and analyze intelligence correctly.

The Power of Algorithms in Intelligence

We're drowning in data. The amount of data on Earth is estimated to double every two years. Think about that for a minute. It's just an astounding amount of data. And it's too much for any human to deal with.

So, if intelligence is in the business of collecting or finding needles in haystacks, the haystacks are growing exponentially. The intelligence community has to use artificial intelligence and other tools to augment human analysts. AI frees up analysts to then ask questions about things like intent, which humans can figure out much better than machines.

Imagine an algorithmic red team: you have humans that are developing assessments of what is Putin going to do in Ukraine, and you've got a red team that's just algorithms aggregating data, so that you have a sort of competitive analysis between humans and machines that can make the humans better. Those are the kinds of things that intelligence agencies need to be doing much more with AI.

The China Program at Shorenstein APARC had the privilege of hosting Jude Blanchette, the Freeman Chair in China Studies at the Center for Strategic and International Studies​ (CSIS). The program, entitled "What’s ‘Communist’ about the Communist Party of China?," explored the goals and ideology of the Chinese Communist Party (CCP), as well as what they might mean for the future of China in the global community. Professor Jean Oi, William Haas Professor of Chinese Politics and director of the APARC China Program, moderated the event.

After the death of Mao Zedong in 1976, the goals of the CCP became less clear. As the country began to adopt market reforms in the 1980s and 1990s, CCP theorists were forced into contortions providing ideological justifications for policies that appeared overtly capitalist. Deng Xiaoping’s concept of “Socialism with Chinese characteristics” came to be seen as a theoretical fig leaf rather than a description of an egalitarian economic system, and by the 2000s, a consensus emerged that the CCP had completely abandoned any pretense of pursuing the Marxist vision it purported to hold. With the rise of Xi Jinping, however, the Party talks with renewed vigor about Marxism-Leninism and the goal of achieving actual, existing socialism. Has the CCP re-discovered communism?  In his talk, Blanchette discussed the abandoned and existing legacies of Mao Zedong, Marxism-Leninism, and the CCP’s vision of socialism. Watch now: 

On February 10, 2021, the China Program at Shorenstein APARC hosted Professor Oriana Skylar Mastro, Center Fellow at the Freeman Spogli Institute for International Studies​ for the virtual program "Military Competition with China: Harder to Win Than During the Cold War?" Professor Jean Oi, William Haas Professor of Chinese Politics and director of the APARC China Program, moderated the event.

As US-China competition intensifies, experts debate the degree to which the current strategic environment resembles that of the Cold War. Those that argue against the analogy often highlight how China is deeply integrated into the US-led world order. They also point out that, while tense, US-China relations have not turned overtly adversarial. But there is another, less optimistic reason the comparison is unhelpful: deterring and defeating Chinese aggression is harder now than it was against the Soviet Union. In her talk, Dr. Mastro analyzed how technology, geography, relative resources and the alliance system complicate U.S. efforts to enhance the credibility of its deterrence posture and, in a crisis, form any sort of coalition. Mastro and Oi's thought-provoking discussion ranged from the topic of why even US allies are hesitant to take a strong stance against China to whether or not Taiwan could be a catalyst for military conflict. Watch now: 

In the aftermath of the assault on the Capitol, much of the nation’s attention was focused on “why.” But another question is equally important: “What next?”

The problem the authorities faced on Jan. 6 was not an inability to respond, but failure to anticipate the threat. Going forward, counterterrorism efforts should emphasize connecting the dots in the far-right extremist universe — not a simple task, given the dispersed and fast-moving nature of the threat.

Read the rest at The New York Times