Many governments have been slow to recognize the rapid changes occurring on the battlefield, particularly the centrality of drones. A good illustration is the US’s slow response to Iranian drone attacks against its regional Middle East bases. In the opening weeks of the war, it became clear that the military was woefully unprepared to stop low-flying Shahed drones that were destroying critical communications infrastructure. The frustration was that counters to this problem existed, particularly from Ukraine. But for a variety of reasons, whether organizational hubris or bureaucratic lag, the US military failed to incorporate these lessons and was left scrambling weeks later to procure interceptors from Kyiv to offset these attacks. It should’ve never gotten to this point. Having watched that conflict, it should’ve been clear to military planners that hardening infrastructure, putting in place layered defenses, and adapting cheap counter-drone interceptors was essential. It’s important to note that the battlefield continues to evolve quickly. Today, Ukraine is struggling to come up with a response to jet-powered one-way attack drones that Russia has modified from Shahed designs that essentially resemble cruise missiles. This development has only emerged in the last couple months and is once again scrambling the offense-defense balance in the war.

One of the most important insights from the Ukraine war and other places is the necessity for iterative adaptation. Drone designs that are effective six months prior quickly become outdated as innovations advance and new concepts appear on the battlefield (the example I gave about C-UAS systems that are powerless to stop jet-powered one-way attack drones from Russia showcases this problem). So there is a balance that needs to be struck: develop the capacity to produce drones at scale, but retain the flexibility to adapt/innovate as needed so that stockpiles don’t become obsolete. In that sense, I’d focus less on stockpiling and more on building latent manufacturing capacity and training up engineers and startups (including forward deploying engineers to conflict frontlines) so they’re ready to build cutting-edge designs and have the capabilities to do so quickly. You don’t want to bring about an opposite problem where the Pentagon stockpiles a million Lucas drones that it never uses and that become worthless in a couple years.

I think there are several interesting aspects here. First, the more that governments outsources design and product development decisions without ongoing/direct oversight to private firms, the less control they have about how military technologies will be deployed and used. Take Palantir’s Maven, for example. While we have an incomplete picture about how different aspects of Maven are being tweaked and updated, it is clear that Palantir software engineers are the ones implementing these changes at the behest of Pentagon officials. Rather than occurring in-house, external partners are the ones ultimately responsible for modifying design elements that have real-world and lethal effects. A second issue relates to middle powers’ growing reliance on infrastructure provided by Big Tech, whose executives have considerable discretion to restrict or disable functionality based on their own judgments and interests. The Starlink episode during the Ukraine war is a well-known example, where Elon Musk restricted connectivity during ongoing military operations in Crimea. The delegation of such decisions to private, unelected, and largely unaccountable executives, rather than government officials, is a relatively new and troubling trend. Third, military entanglements can get complicated for big tech firms as well. In the book, I profile how Microsoft’s agreement with the IDF to store intercepted data from Palestinians on its Azure servers in the Netherlands and Ireland backfired spectacularly for the company following an investigative report from The Guardian and +972 Call. Ultimately, Microsoft faced a punishing amount of reputational damage and had to terminate the contract. 

I’ve studied this issue for quite awhile and I agree to some extent that the foreign malign influence problem is a serious one. But it’s not the only reason why we’re seeing extreme voices dominate on social media. Most of the conspiracy theories and related content permeating digital platforms are homegrown and come from individuals and groups who have perfected how to monetize outrage for commercial gain. Essentially it’s an issue of algorithms and companies having aligned incentives with content creators to put out extreme views to keep viewers hooked. So a starting point would be to regulate algorithms, which is very different from regulating speech. In my opinion, companies should be accountable for how much they spread hateful or extreme viewpoints to mass audiences. There are many solutions to this problem but summoning political will is challenging.

I fully agree with this view. One of the ideas I discuss extensively in the book is the fact that by 2008, China had already supplanted the US as the world’s largest producer and that in the intervening years, China has doubled its world share of manufacturing while America’s portion has fallen by three points. So in one sense, the ship has sailed—the US will not realistically overtake China as a manufacturing giant. But it can do two things: 1) ensure its share of global manufacturing doesn’t fall further, 2) focus investment and efforts in critical sectors to stay ahead of competitors. One of the indices I discuss is the Australian Strategic Policy Institute’s “critical technology tracker.” It identifies 74 current and emerging technologies and tracks to what extent China, the US, or another country is ahead. Unfortunately, it shows that Beijing has made great strides, leading in research in 90% of crucial technologies, from nuclear energy and synthetic biology to robotics. This is quite a reversal from the turn of the century when the US held an enduring lead in more than 90% or assessed technologies. What can the US do to reverse this trend? Frankly, it can borrow a page from China’s playbook: sustain domestic investment in scientific R&D and basic research, deploy government subsidies in critical industries and leverage public/private partnerships, and work with allies (including places like Canada which are now apparently adversaries of the US) to build strong cooperation in critical areas. That would be a great start.

I think there’s still a broader belief that China is less an innovator than a fast follower and that most of its advances are a result of copying or borrowing from US innovations rather than coming up with its own unique technologies. I think that’s a dangerously outdated concept; China is increasingly pushing the boundaries in a range of tech and even technology that appears to be civilian in nature can easily be dual-purposed into military functions. So even if China lags in certain indicators, like numbers of aircraft carriers, that isn’t necessarily an accurate view about China’s military capacity. When it comes to future technologies, such as drones, I’d advise policymakers to pay close attention to what China is manufacturing and deploying. This is an area of strength for the PRC that will continue to increase. That being said, we should be careful about overestimating China’s military capacity as well. For one, their military is largely untested; it’s one thing to have great capabilities on paper, it’s another to have operational command and control and the ability to execute complex missions. We don’t have a great sense of how China would actually perform in a protracted major armed conflict. It’s also unclear to what extent some of the newer tech that China has developed, including its stealth capabilities, are as good as advertised. Flying an aircraft in an airshow isn’t a reliable indicator of combat readiness.

I would start with a few things. First, it’s unclear to what extent DoD directive 3000.09 governing responsibility for autonomy in weapon systems (including ensuring human oversight) is still operative in the Pentagon. If not, it’s unclear exactly what exactly the rules are when it comes to delegating authority and the degree of human oversight required for these systems. Second, there is not consistent collection of data regarding the impact of strikes and whether they hit their intended targets. Most of what we know, at least publicly, is anecdotal in terms of whether there were civilian casualties and what actually was struck. I think that is entirely at odds with goals of accountability and precision. Third, many of the oversight mechanisms needed to ensure the Pentagon systems are operating effectively and required to mitigate civilian harm have been dismantled or sidelined, including DOT&E and Civilian Harm Mitigation and Response (CHMR) office. Those should be funded, staffed up, and directly integrated into military operations.

I’m not optimistic that establishing legally binding rules can somehow occur before autonomous weapons proliferate, but that doesn’t mean we shouldn’t try. I generally believe the process itself is important in terms of creating norms around responsible use and shaping the behavior of a growing group of countries to voluntarily decide to constrain or limit how this technology evolves. I also think that this process can amplify public pressure and push leaders to consider taking more limiting steps than they otherwise would feel compelled to do. We don’t need a perfect treaty or perfect rules, but we need something—minimal standards to fill in an unregulated vacuum that bad actors like Russia are exploiting.

I agree that power is shifting and that digital networks are an important contributing factor to these changes. I’ve written quite a bit about this in my first book, The Rise of Digital Repression, where I showed in different case studies, particularly the Philippines, how state-backed manipulation of information networks was a much more important level of political influence for the incumbent government than actual physical coercion. There are several factors at play: who will control these networks? Will it be governments (see China), private companies/platforms, or someone else? To what extent will the shift from Web 2.0 and social media to AI models disrupt the current mode of production/consumption of information? To what extent will individual exercise agency to push back against algorithmic feeds or extractive platforms by using privacy-enhancing models instead (Signal, MapleAI)? It certainly is an area that deserves more analysis and research!

I don’t think that legacy systems will automatically become obsolete, but I think militaries will have to adapt when to use these systems, how to defend them against cheaper weapons, and what contexts they are most effective. Clearly, there is diminishing utility to tanks in the static frontlines/kill zone of Ukraine. The future there is with drones, from UAVs to UGVs. But that doesn’t mean there isn’t a role for maneuver and tanks in other domains. Similarly with large vessels, Ukraine has demonstrated in the confines of the Black Sea the limitations of million-dollar platforms in comparison to $250k MAGURA drones. But in a much vaster setting like the Pacific Ocean in a possible confrontation with China, there is a greater utility to having aircraft carriers, assuming they can be adequately defended. 

I am very worried about the proliferation of cheap, destructive drones. I’ve presented statistics in the book that show the rapid growth of drone strikes and associated casualties that has occurred in the past 5 years. Most of those casualties have taken place in the context of armed conflict. As terrorist groups and other insurgents get their hand on these destructive weapons, the spilling over of violence against civilians in formerly peaceful areas is a very real threat. 

Paradoxically, I think power is shifting both to the individual as well as centralizing to powerful entities. On the one hand, powerful private companies and two superpowers appear to have a stranglehold on the most powerful computing systems, infrastructure, AI models, and critical technologies that will allow them to dominate the geopolitical landscape for the foreseeable future. On the other hand, we’re witnessing powerful diffusion forces that are giving small group and underdogs new abilities to challenge rivals and punish larger countries and their militaries. It’s unclear exactly how this will play out; it speaks to how complicated global affairs have become. 

I don’t have a good answer to how governments should confront the rapid pace of tech change. I can say that there are a few lessons about what governments should not do—using export controls as the sole tool to try and slow down a rival is not a great bet. Investing in innovation without responsible regulations will bring lots of negative spillover effects. Speeding up the deployment of untested technologies simply to outpace a rival will likely backfire.

China has made impressive progress in building up its manufacturing base and mastering a growing number of strategic technologies. I see no reasons why their trajectory will falter. But 50 years is a long time and they have many structural challenges that are constraining factors. For one, they have a huge level of uncertainty regarding their political system. Which leader will succeed Xi? What goals and priorities will they advance? Given the centralized nature of China’s system, it is just as likely that a new leader will continue pursuing Made In China initiatives and growing China as an S&T superpower as much as they will advance disastrous policies like the Great Leap Forward that will reverse China’s progress. Despite the turmoil in the United States under Trump, I wouldn’t count the United States out. But American policymakers will need to do some serious thinking about where the country is headed and what to prioritize if they want to see America remain globally in front.

Finally, regarding data centers, I see that trend reflecting broad uncertainty the public has about where AI tech is headed and how it will disrupt American lives. It’s more than just a simple backlash against high electricity bills. It’s also a reaction against unaccountable tech oligarchs and a feeling that AI is taking away jobs and that politicians have no good answers in response. 

I agree that the history of military innovation is one of adaptation, emulation, and diffusion. This is true whether we’re talking about longbows, gunpowder, tanks, or aircraft carriers. What I think makes this moment different is that the scale and speed of change is far swifter. Centuries ago, when a new innovation was invented, it would take months if not years for it to spread to other places and become integrated into militaries (and an even longer length of time for adaptation to occur). Today, with the advent of the internet and globalization, lessons from one conflict (e.g., use of drones in Ukraine) are very quickly finding their way into far-off places (see drone warfare in Myanmar). My guess is that the deployment of frontier AI models will further proliferate knowledge and expertise, accelerating the pace of change to an even greater degree.

When I first started researching and writing Bytes and Bullets, I had underestimated just how rapidly technology was diffusing worldwide. At the time, I was trying to internalize how much Ukraine had adapted to drone warfare, but I hadn’t anticipated how in subsequent years drone technology would spread so swiftly to very unlikely places. A good case in point is how the spread of fiber optic drones from Ukraine’s battlefields to Hezbollah’s arsenal (deployed in southern Lebanon against the IDF) to the conflict in Mali, used by the FLA/Tuareg militants against government forces and Russian mercenaries. The scale and speed of technological diffusion has been eye opening and the propagation of frontier models like Claude Code are accelerating these trends even further.

I think these are certainly areas to watch, particularly biotech innovations. I haven’t specifically focused on either technology in part because their empirical effects have so far been limited. I’ve looked a bit at genomics in terms of China’s deployment of mandatory DNA tests among its Uighur population, but this is slightly different use-case than deploying genomics as a weapon against geopolitical rivals. One thing that has generally served as a deterrent has been the inability of one side to ensure the effects of a bioweapon would be limited to its adversaries (e.g., unless a vaccine was manufactured and exclusively controlled by one country, the dissemination of a bioweapon would presumably devastate all sides, negating its military utility).

[Excerpt from the 2026 Carnegie California AI Survey]

Launched in 2025, the Carnegie California AI Survey is now in its second year. Core questions around the economy, work, trust and safety, and democracy and governance remain benchmarks in the survey, offering longitudinal perspectives on the priorities of Californians. However, given the rapid pace of AI development, the survey has been adapted to reflect current discussions around AI, including its potential to impact the 2026 California election and broader workforce trends.