In a recent interview with the New York Times, Brookings Institution artificial intelligence (AI) expert Kyle Chan argued that “China is running a different kind of race” when it comes to AI.^[1] While the United States pursues cutting-edge breakthroughs in the quest for general artificial intelligence, China focuses on what Chan called AI “diffusion.” What is diffusion – and why does it matter? As political scientist Jeffery Ding puts it, diffusion is simply the widespread adoption of new technologies.^[2] Yet much of our AI diffusion discourse focuses on strategic international diffusion: semiconductor export controls on competitors, allies adopting American AI stacks, and so on.^[3] As former National Security Advisor Jake Sullivan and Tal Feldman put it, “The contest [between the United States and China] is more about diffusion, embedding American systems abroad before rivals can spread their own.”^[4] To be sure, strategic international diffusion has a number of advantages, as Denny Center Student Fellow Rai Masoud details.^[5] However, if Washington wants to compete with Beijing, it must also prioritize consumer-focused domestic diffusion.

China’s Approach to Domestic Diffusion

As Chan points out, this approach to diffusion has long been a priority for the Chinese. As early as 2017, China released its “New Generation Artificial Intelligence Development Plan,” which detailed AI’s promise for the average Chinese citizen.^[6] The plan outlined how AI could facilitate self-driving vehicles and improve rail systems. These predictions have aged well. Last September, China rolled out their “AI+” initiative. Before addressing AI’s strategic advantages, the document’s first claim is that “We should harness AI to enhance public services, improve people’s quality of life and provide solutions for issues concerning people’s livelihood.”^[7] China has done just that. Consider two striking examples:

1. Many shops use AI-powered “smile to pay” terminals, which allow consumers to purchase their goods simply by smiling at a camera.^[8]
2. In Hangzhou, DeepSeek’s “City Brain” program uses AI to make traffic more efficient. Reportedly, it detects 92% of traffic incidents and has increased traffic speeds by 15%.^[9]

In short, China is using AI to improve day-to-day life for the average Chinese citizen.

The United States is not doing nearly as well in this regard. In May, Microsoft released its Q1 Global AI Diffusion Report.^[10] A team of researchers measured the percentage of the working age population using generative AI in 147 countries. Despite being one of the two biggest players in AI development, the United States came in 21st in the world with only 31.3% of the working age population using AI. That number is strikingly low. (In the UAE, it’s 70.1%.) The share of the working-age population using AI isn’t the only way to assess domestic diffusion, either. As Chan points out:

In the larger cities in China, you might see autonomous delivery robots dealing with package deliveries, food deliveries. In a restaurant, you might see a waiter robot bringing your food. This is not super, super widespread yet, but it’s starting to come about. Hotels, rather than having room service be delivered by a person pushing a cart coming up the elevator, it might be a delivery robot. You have, of course, self-driving cars. You might even have drone delivery for coffee or food.^[11] Whatever reasons Beijing has for pursuing this approach, it is not a response to democratic pressure. But for Washington, this approach to diffusion might be crucial to maintain American AI competitiveness.

America’s Need for a Similar Approach

Many Americans have understandable concerns about AI. One of the biggest is the data centers that are essential to our AI stack. Data centers can be loud and unattractive. They also use massive amounts of municipal water and electricity, which can drive up utility costs.

Another common concern is that AI will create massive job loss. This is a possibility industry leaders have long predicted. In 2025, Anthropic CEO Dario Amodei forecasted that AI would wipe out half of all entry-level white-collar jobs within five years.^[12] A June Reuters/Ipsos poll found that over half of Americans fear that they or someone in their household will lose their job because of artificial intelligence.^[13]

The third most-cited concern is AI’s impact on the education of young people. The Brookings Institution’s 2026 “A New Direction For Students In An AI World” report finds that using AI in education can “undermine children’s foundational development” and that “the damages it has already caused are daunting.”^[14] The concern about AI’s educational impact isn’t limited to K-12 schooling, either. As recent Stanford graduate Theo Baker put it in his recent New York Times op-ed, “Cheating has become omnipresent. I don’t know a single person who hasn’t used A.I. to get through some assignment in college.”^[15]

Finally, there is a broader worry that these issues – in particular job loss and educational harm – will have a downstream effect on American democracy. Recent work published in the Proceedings of the National Academy of Science found that the perception that AI is labor-replacing (rather than labor-creating) reduces democratic legitimacy and political engagement.^[16] Likewise, a 2024 report from the National Education Policy Center found that “The weight of the available evidence suggests that the current wholesale adoption of unregulated AI applications in schools poses a grave danger to democratic civil society and to individual freedom and liberty.”^[17] Taken together, the immediate concerns about data centers, job loss, and education and the prospect of AI’s impact on democracy paint a bleak picture.

These concerns have attracted the attention of legislators. Municipalities have used their land use, zoning, and utility powers to nix data centers. Data center moratorium bills have already been introduced in fourteen states.^[18] In March, Senator Bernie Sanders (I-VT) introduced S.4214 – the Artificial Intelligence Data Center Moratorium Act. While many of these bills are unlikely to pass, Gallup finds that “AI infrastructure could become an important campaign issue in local and state elections this year, and politicians who favor data centers in their area are likely taking a politically risky stance.”^[19] Legislative efforts have not been limited to the data center issue, either. Senator Marsha Blackburn (R-TN) has presented a draft of a sweeping AI bill that some think would hamper AI development through third-party audits, a duty of care on developers, and making copyrighted works not fair use for AI training under the Copyright Act of 1976.^[20] Of course, not all of these proposed bills are directly harmful to American AI competitiveness. The industry largely supported 2025’s TAKE IT DOWN Act, which criminalized distributing nonconsensual intimate images, including AI deepfakes.^[21] The important point is this. American AI discourse has largely focused on AI’s downsides. In turn, legislators have mostly focused on addressing these downsides.

Conclusion

Americans are fortunate to be able to register their concerns and have legislators respond to them. But this responsiveness is only one of many democratic values – and, without some of the other important ingredients of democracy, it could threaten American AI competitiveness. Thus, there are both substantive and prudential grounds for Washington to focus on consumer-focused domestic diffusion.

Substantively, such an approach could promote a different democratic value. It could help Americans make more informed, balanced decisions about what they want their relationship with AI to be by demonstrating its transformative potential. Consider the following possibilities:

• Public-private partnerships: DeepMind’s AlphaFold 3 model, which analyzes protein structure, is expected to revolutionize drug discovery. The model was trained on data from the Protein Data Bank, long funded by the National Science Foundation.^[22] Future partnerships could make this collaboration between the federal governments and leading AI labs even more direct. Public-private partnerships are likely best suited for “life or death” applications of AI – drug discovery, national security, and so on.^[23]
• Domestic industrial policy: Without rising to the level of public-private partnerships, direct subsidies, tax credits, and research and development (R&D) grants can incentivize companies to incorporate AI into widely-used consumer products. (Think, for example, of the “smile to pay” terminals.)
• In-house models for public services: AI can help citizens navigate difficult processes like filing taxes. As Ezra Klein puts it, “There could be an A.I. system that works through your taxes with you, grounded in both the I.R.S.’s data on your income and the most up-to-date information on the tax code. Every person could have the equivalent of a personal accountant.”^[24] On the enforcement side, the IRS is already using AI to comb through returns, which has resulted in a 12% increase in revenue in 2026.^[25] Government procurement efforts – especially at the local and state level (for example, the DMV) – could deliver user-friendly and efficient public services.

Better drug discovery, quicker shopping, more convenient public services – these applications of AI could change the lives of everyday Americans. Of course, an AI strategy that incorporates these kinds of policies wouldn’t assuage all concerns. Regardless of where public opinion eventually comes out, like any technology, our relationship with AI should come from carefully assessing its pros and cons. As Neil Postman puts it in Technopoly, “It is a mistake to suppose that any technological innovation has a one-sided effect. Every technology is both a burden and a blessing; not either-or, but this and that.”^[26] The cons are real – and obvious to many Americans. The potential pros are less obvious. This is due, in part, to the lack of government focus on consumer-centric domestic diffusion. Such an approach would allow Americans to make more informed choices about AI.

Prioritizing domestic diffusion could also undercut the myopic, one-sided views that focus only on AI’s downsides. Recent reporting from The New York Times finds that these views are being spread on social media by state actors from China, Russia, and Iran.^[27] This is unsurprising, given that these views, if sufficiently widespread, could harm American AI competitiveness. Taken together, consumer-focused domestic diffusion could advance an important democratic goal – a public well-informed about the pros and cons of AI – and Washington’s interest in avoiding one-sided backlash harmful to American AI competitiveness. The alignment of democratic values and strategic interests should make this approach low-hanging fruit for policymakers.

 

 

 

 

 

^[1] Kyle Chan, “China’s Not the Problem. We Are,” moderated by Ross Douthat, May 14, 2026, The New York Times, https://www.nytimes.com/2026/05/14/opinion/china-trump-ai-xi.html

^[2] Jeffery Ding, “The diffusion deficit in scientific and technological power: re-assessing China’s rise,” Review of International Political Economy 31, no. 1 (2024): 173. doi:10.1080/09692290.2023.2173633.

^[3] See, for example, the debate over the Biden administration’s Commerce Department’s “Framework for Artificial Intelligence Diffusion,” released in January of 2025, which the Trump administration’s Commerce Department rescinded in May of 2025.

^[4] Jake Sullivan, “Geopolitics in the Age of Artificial Intelligence,” Foreign Affairs, January 27, 2026, https://www.foreignaffairs.com/united-states/geopolitics-age-artificial-intelligence

^[5] Rai Masou, “Diffuse and Democratize: Rethinking U.S. AI Strategy,” The Denny Center for Democratic Capitalism, March 18, 2026, https://www.law.georgetown.edu/denny-center/blog/rethinking-ai-strategy/#_edn7.

^[6] “A [New] Generation Artificial Intelligence Development Plan,” State Council of the People’s Republic of China, effective July 20, 2017, trans. Elsa Kania, Paul Triolo, Rogier Creemers, and Graham Webster, https://www.newamerica.org/insights/full-translation-chinas-new-generation-artificial-intelligence-development-plan-2017/

^[7] “AI+ International Cooperation Initiative,” Ministry of Foreign Affairs of the People’s Republic of China, last modified September 24, 2025 18:08, https://www.fmprc.gov.cn/eng/xw/zyjh/202509/t20250924_11715960.html

^[8]  Jacob Dreyer, “Why China Is So Much Less Scared Of A.I.,” New York Times, May 9, 2026, https://www.nytimes.com/2026/05/09/opinion/ai-china-america-race.html

^[9] “Hangzhou City Brain 3.0,” Envisioning, https://www.envisioning.com/research/substrate/china__hangzhou-city-brain-30

^[10] Juan Ferres, “The state of global AI diffusion in 2026,” Microsoft, May 7, 2026, https://blogs.microsoft.com/on-the-issues/2026/05/07/the-state-of-global-ai-diffusion-in-2026/; Amit Misra et al., “Measuring AI Diffusion: A Population-Normalized Metric for Tracking Global AI Usage,” arXiv, https://doi.org/10.48550/arXiv.2511.02781

^[11] Kyle Chan, “China’s Not the Problem. We Are,” moderated by Ross Douthat, May 14, 2026, The New York Times, https://www.nytimes.com/2026/05/14/opinion/china-trump-ai-xi.html

^[12] Jeffery Sonnenfield, “The Real Job Destruction from AI Is Hitting Before Careers Can Start,” Yale Insights, May 4, 2026, https://insights.som.yale.edu/insights/the-real-job-destruction-from-ai-is-hitting-before-careers-can-start

^[13] Jason Lange and Courtney Rozen, “Half of Americans fear AI could put someone in their household out of work, Reuters/Ipsos poll finds,” Reuters, June 10, 2026, https://www.reuters.com/business/world-at-work/half-americans-fear-ai-could-put-someone-their-household-out-work-reutersipsos-2026-06-10/

^[14] Mary Burns et al., “A new direction for students in an AI world: Prosper, prepare, protect,” Brookings Institution, January 14, 2026, https://www.brookings.edu/articles/a-new-direction-for-students-in-an-ai-world-prosper-prepare-protect/

^[15] Theo Baker, “What A.I. Did to My College Class,” New York Times, May 17, 2026, https://www.nytimes.com/2026/05/17/opinion/chatgpt-ai-college-school-graduation.html

^[16] Ben Williamson et al., “Time for a Pause: Without Effective Public Oversight, AI in Schools Will Do More Harm Than Good,” National Education Policy Center, March 5, 2024, https://nepc.colorado.edu/publication/ai

^[17] Armin Granulo et al., “Perceiving AI as Labor-Replacing Reduces Democratic Legitimacy and Political Engagement,” Proceedings of the National Academy of Sciences 123, no. 4 (2026): e2523508123. https://doi.org/10.1073/pnas.2523508123.

^[18] “Which States Are Banning Data Centers?,” National Conference of State Legislatures, last modified April 27, 2026, https://www.ncsl.org/fiscal/which-states-are-banning-data-centers

^[19] Jeffery Jones, “Americans Oppose AI Data Centers in Their Area,” Gallup, May 13, 2026, https://news.gallup.com/poll/709772/americans-oppose-data-centers-area.aspx

^[20] Kevin T. Frazier and Jennifer Huddleston, “The Latest AI Bill’s 5 Biggest Flaws,” Cato Institute, March 19, 2026, https://www.cato.org/blog/latest-ai-bills-5-biggest-flaws; Holly Fechner et al., “White House, Blackburn Introduce Visions of Comprehensive Federal AI Policy,” Covington & Burling, March 26, 2026, https://www.globalpolicywatch.com/2026/03/white-house-blackburn-introduce-visions-of-comprehensive-federal-ai-policy/

^[21] Duane Pozza et al., “Trump Signs Law Expanding Tech Platform Requirements and FTC Enforcement on Intimate AI Deepfakes and Images,” Wiley Rein, May 20, 2025, https://www.wiley.law/alert-Trump-Signs-Law-Expanding-Tech-Platform-Requirements-and-FTC-Enforcement-on-Intimate-AI-Deepfakes-and-Images

^[22] Ezra Klein, “There’s Something Else We Should Be Worrying About,” The New York Times, May 31, 2026, https://www.nytimes.com/2026/05/31/opinion/artificial-intelligence-public-good.html

^[23] For discussion of public private partnerships on AI in national security, see Karen Matthews, “Agile AI Partnerships: A Public-Private FLEXible and SMART Framework for National Security and Competitive Innovation,” Harvard Kennedy School Belfer Center for Science and International Affairs, May 2025, https://www.belfercenter.org/research-analysis/agile-ai-partnerships-public-private-flexible-and-smart-framework-national

^[24] Ezra Klein, “There’s Something Else We Should Be Worrying About,” The New York Times, May 31, 2026, https://www.nytimes.com/2026/05/31/opinion/artificial-intelligence-public-good.html

^[25] Mike Wallace, “IRS AI Agents Drive 12% Enforcement Revenue Surge With 25% Fewer Staff,” Greenback, May 7, 2026, https://www.greenbacktaxservices.com/blog/irs-ai-agents-expat-tax-implications/

^[26] Neil Postman, Technopoly: The Surrender of Culture to Technology (Vintage Books, 1993), 4-5.

^[27] Steven Myers and Dustin Volz, “China, Russia and Others Seek to Inflame Debate Over A.I. Data Centers,” NEw York Times, July 9, 2026, https://www.nytimes.com/2026/07/09/business/china-russia-ai-data-centers.html