ChinaTalk: Ben Buchanan on AI and Cyber

Host: Jordan Schneider
Guest: Ben Buchanan (Dmitri Alperovich Professor at SAIS, former White House Special Advisor to AI)
Release Date: January 11, 2026

Overview

In this episode, Jordan Schneider welcomes Ben Buchanan to discuss the arc of AI and cyber policy, US-China competition in advanced computing, and lessons from the front lines of US government tech policy. Buchanan reflects on his experience in the Biden White House, tracing the evolution of policy around AI, export controls, and the wider technological race, alongside insights into the intersection of AI and offensive/defensive cyber operations. The conversation covers the policy process, the relationship between government and the private sector, and major open questions for the future.

Key Discussion Points & Insights

1. The AI Policy Arc: From Hypothesis to Mainstream

• 2021-2025 Retrospective: When Buchanan entered the White House, AI's relevance was clear but unproven; by 2025, computing power’s national security importance is "an established fact." ([00:53])

  “A lot of those things have come true, particularly about the importance of AI to national security and the importance of computing power to AI ... now ... it feels like that has happened.”
  — Ben Buchanan, [00:53]

• Scaling Laws as a Turning Point:
  The 2018-2020 period was pivotal, as the scaling laws (machine capability increasing with more computing power) became central. Buchanan’s 2020 Foreign Affairs piece advocated shifting US focus from data to compute.

  "The real turning point was probably somewhere in the 2018-2020 period when the scaling laws started to come into focus ... that's what's driven a great deal of AI progress." — Ben Buchanan, [02:14]

• Early Policy Wins:
  The Biden administration moved to implement critical export controls and policies before AI hit true mainstream consciousness.

  "One of the things I'm proud of frankly, is that we got some of the biggest action done prior to the whole world waking up."
  — Ben Buchanan, [04:25]

2. Chips Act vs. Export Controls: Strategic Approaches

• Distinction:
  The CHIPS Act was about restoring domestic capacity; export controls were a targeted, security-driven move, not reliant on AGI assumptions. The controls were analogous to previous measures on nuclear or cryptologic technology.

  "I would differentiate between the CHIPS Act and then the export control...The CHIPS Act ... is a supply chain thing ... export controls ... increased the value of chips if they can be used to train more powerful AI systems."
  — Ben Buchanan, [06:35]

3. Balancing National Security and Policy Process

• The “Sullivan Doctrine”:
  National Security Advisor Jake Sullivan’s “as large of a lead as possible” mantra shaped the aggressive-but-not-maximalist US strategy. Buchanan emphasizes trade-offs and respect for decision processes.

  "My view was always a maximalist one, that we should be very, very aggressive. But ... there’s a lot of constraints ... and someone sitting in Jake’s chair has to balance a lot of concerns that a dork like me doesn’t have to balance." — Ben Buchanan, [08:59]

• On Retrospective Policy Choices:
  Buchanan would have acted faster and more aggressively on certain levers (e.g., high-bandwidth memory, earlier parameters for restricting chip manufacturing equipment) if given "do-over" power.

  “Anytime you're doing something that is this technical, I would love to get mulligans and get technical parameters right.”
  — Ben Buchanan, [11:25]

4. Building State Capacity and Enforcement Challenges

• Implementation Concerns:
  Enforcement remains the best argument against ambitious export controls, raising big questions on US state capacity.

  "The best counterargument ... was just, the United States government's not capable of doing this ... the enforcement's not there ... that's the most compelling counterargument." — Ben Buchanan, [15:37]

• Government Hiring:
  Major efforts were expended to "bulk up" with over 1,000 new hires across agencies in 2023-2024 to address this deficit.

5. Government vs. Private Sector: The AI Revolution

• Unique Moment:
  Unlike nukes or space (government-led), modern AI is private-sector driven. The state’s challenge is integrating this outside "revolutionary technology" into its own operations.

  “What is the relationship between the public sector and the private sector at a time when you have a revolutionary technology, probably the first one since the railroad, that is almost exclusively coming from the private sector?" — Ben Buchanan, [19:36]

• Rickover Analogy:
  Buchanan invokes Rickover-style leadership for integrating AI into defense/intel—adapting organizational workflows at scale.

6. National Security Adoption: Three Pillars of AI Competition

• AI Geopolitical Competition:

  • (1) Racing to frontier models (private sector, compute-heavy)
  • (2) Diffusing capabilities globally (winning hearts/minds, markets)
  • (3) Domestic national security adoption (applying AI internally)

    "If we don't use that time, we get zero points. ... I view the AI competition [...] as coming down to three parts. One is the competition to make the best models ... the second is the competition to diffuse ... The third is national security adoption." — Ben Buchanan, [27:36]

• Risks:
  US could build the best models/deploy the most compute but still fall behind if others better integrate AI into their strategic operations, as with tanks in WWII.

  "It is entirely possible that we win the race to the frontier ... but if we don’t get our act together on the national security side, we still fall behind, just as the French and the British fell behind in the early days of the tank.” — Ben Buchanan, [27:36]

7. AI and Cyber Operations: Offense vs. Defense

• Vulnerability Discovery:
  Major recent advances are coming in automated vulnerability discovery/patching, with Google and DARPA pushing the envelope.

  "We are at long last starting to see machine learning systems that can contribute to that work … starting to see evidence in 2025 of that kind of capability." — Ben Buchanan, [33:18]

• Automation Trend:
  The trajectory is clear: more cyber operations will be automated, and “AI paired with the top humans” will likely dominate, but pure AI-driven operations couldn’t be dismissed in the future.

  "There’s a direction of travel that’s pretty clear here, which is towards increasing automation, increasing capability for vulnerability discovery by machines." — Ben Buchanan, [35:49]

• Defense Implications:
  If breakthroughs allow all code vulnerabilities to be instantly detected before deployment, a "defense dominant" world is possible—but this is an organizational challenge as much as a technical one.

8. The Messiness of Policy and Impact of Individual Passion

• Process Lessons:
  Theory is often easier than practice—complex change requires navigating (sometimes frustrating) interagency/government processes.

  “...theory was worked out long before then, but it still was a cumbersome process to get the system to do it. And again, sometimes for good reason.” — Ben Buchanan, [14:34]

• Technical Understanding as Policy Leverage:
  Policy often advances when technical experts personally push ideas, counterbalance lobbying dollars, and make cases at the right time. However, big company lobbying (Nvidia, et al.) is powerful and ever-present.

Notable Quotes & Memorable Moments

• On Export Controls' Impact:

  "We’re talking about a company that’s worth hundreds of billions of dollars—Nvidia. We’re talking about very important technology. ... Those are not things that should be done lightly." — Ben Buchanan, [15:05]

• On Enforcement as the Key Challenge:

  "The best counterargument that I never heard to our policies was just, the United States government's not capable of doing this ..." — Ben Buchanan, [15:37]

• On AI's Disruptive Potential:

  "Everything is interconnected. ... That has been the challenge ... teaching it in the classroom and ... in writing." — Ben Buchanan, [61:18]

• On the Role of Individual Technical Passion in Policymaking:

  "I think there's a power law distribution for this kind of stuff ... chip manufacturing ... and AI: that nexus was just by far the highest leverage thing." — Ben Buchanan, [13:02]

• On the Policy Process:

  “Every policy making process is improvisation ... I certainly didn’t feel like I had a sheet of music I was reading from ... I think it has to be jazz.” — Ben Buchanan, [77:34]

Timestamps for Important Segments

| Timestamp | Segment / Topic | |------------|-----------------------------------------------------------------| | 00:53 | Retrospective on AI's rise in US policy | | 02:14 | Key breakthrough: Scaling laws and the focus on computing power | | 04:25 | Reflections on waking up the world to AI’s significance | | 06:35 | CHIPS Act vs. export controls—different rationales | | 08:59 | The “Sullivan Doctrine” and policy aggressiveness | | 14:09 | Policy process vs. theory; the reality of government work | | 15:37 | State capacity & enforcement as policy bottlenecks | | 19:36 | The public/private divide in revolutionary tech | | 27:36 | Three parts of AI competition, policy lessons from WWII tanks | | 33:18 | AI's evolving impact on cyber offensive/defensive operations | | 61:18 | On the difficulty of writing/teaching about hyper-connected AI | | 68:00 | Predicting political and societal AI issues by 2028 |

Open Questions & Areas for Further Research

• Recursive Self-Improvement:
  Recent results (e.g., Alpha Evolve) demonstrate AI systems accelerating their own improvement.
• Energy as a New Strategic Fulcrum:
  US/China competition in data center energy supply may be the next critical battleground, and the US needs to step up.
• US vs. Chinese Tech-Military Synergy:
  Buchanan wants deep dives into the real nature of Chinese tech companies’ relationship with the state/military.
• Future of Regulatory Framework:
  How can government adapt to regulate AI risks, especially as automation and economic/social transformations accelerate?

Book Recommendations

• A Brief History of Intelligence by Max Bennett
  “If you want to take a step back and think about what is it we’re actually talking about when we talk about intelligence ... that was a great book.” — Ben Buchanan, [48:08]

Tone & Style

Buchanan brings a combination of technocratic optimism, healthy skepticism, and hard-earned realism from policy trenches. He is both reflective (“I remember what was called China Econ Talk ... we’ve already brought in the aperture here.” [18:48]) and sometimes wryly self-aware (“That’s great, Professor Buchanan, you’ve worked out the theory, but actually what we're doing here is practice.” [14:35]). The conversation is lively, ranging from geeky tech specifics to grand strategic analogies.

Closing Thoughts

Ben Buchanan's journey—from early conviction in AI’s strategic role, to hard-fought government policies, to worries about future state capacity—captures the urgency and complexity of current US technology strategy. The episode offers a nuanced look at how ideas become policy, why timing and technical intuition matter, and the persistent challenge of evolving organizations to meet a transformational moment.

End of Summary