The Program on Geopolitics, Technology, and Governance (GTG) examines how emerging technologies—including artificial intelligence, quantum computing, and smart devices—are redefining power, economies, and policies worldwide. Our research addresses the complex challenges these advances pose for international security, and how governments, businesses, and individuals adapt to shifting landscapes of risk and opportunity.
Artificial intelligence is reshaping economies, security, and governance worldwide, raising urgent questions about how to distribute its benefits equitably while managing risks. GTG examines how democracies can leverage AI innovation to advance shared prosperity and security, with particular attention to infrastructure requirements, Global South perspectives, and mechanisms for international cooperation.
Related projects:
AI for Peace
This research initiative investigates how the United States and its allies and partners can leverage their comparative advantages in AI innovation to equitably distribute the benefits of AI while incentivizing trustworthy deployment. The research focuses on three key areas:
Infrastructural requirements for deploying AI at scale for countries at all levels of economic development and multilateral, multi-stakeholder mechanisms for meeting those requirements.
Global South perspectives on promising use cases for AI and governance approaches for facilitating AI deployment while managing risks.
Prospects and options for international collaborations to address cross-border security, environmental, and other externalities.
The Future of Decision-Making Project (FODM) is a multi-year, interdisciplinary research initiative examining how emerging technologies—particularly artificial intelligence and advanced decision-support systems—are reshaping human decision-making in high-stakes domains such as national security, defense, and crisis management. Rather than focusing solely on technological capability, the project centers on the human dimension: how judgment, responsibility, and accountability evolve as machines increasingly inform, shape, or constrain human choices. The project brings together scholars and practitioners from academia, government, and industry to develop empirically grounded, policy-relevant insights into the future of human-machine decision systems.
GEOPOLITICS OF TECHNOLOGY
Emerging technologies are becoming central to great power competition and regional security dynamics. GTG examines how technological advantages translate into geopolitical leverage, how U.S. strategy can balance competition with innovation and alliance partnerships, and how technology is reshaping power dynamics across critical regions like East Asia.
GTG's annual conference and ongoing research initiative brings together leading regional experts, policymakers, and industry leaders to examine how technological developments are reshaping geopolitical dynamics across East Asia. The research focuses on critical technology supply chains—particularly semiconductors—regional responses to U.S.-China competition, and opportunities for multilateral cooperation on technology governance.
CHINA & DIGITAL COMPETITION
China's rapid digital development and distinct governance approaches have profound implications for global markets, security, and technology standards. GTG analyzes Chinese technology policy and corporate strategies through original-language sources, providing insights into how China's digital trajectory shapes international competition and governance debates.
The DigiChina project, led by Graham Webster, enhances understanding of China's digital policy developments through translating and analyzing Chinese-language sources. Since 2017, DigiChina has published translations of primary sources, contextual explanation, and analysis on China’s technology policy landscape, covering topics including the Cybersecurity Law regime, data governance, artificial intelligence, and China’s official push for greater technological independence.
CYBERSECURITY & INTERNATIONAL COOPERATION
Effective governance of technology challenges requires sustained dialogue and cooperation across borders. GTG facilitates Track II exchanges with international partners, building relationships and shared understanding that can lay groundwork for broader policy cooperation on cybersecurity and technology governance issues.
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Crop productivity is potentially affected by several air pollutants, although these are usually studied in isolation. A significant challenge to understanding the effects of multiple pollutants in many regions is the dearth of air quality data near agricultural fields. Here we empirically estimate the effect of four key pollutants (ozone (O3), particulate matter (PM), sulfur dioxide (SO2), and nitrogen dioxide (NO2)) on maize and soybean yields in the United States using a combination of administrative data and satellite-derived yield estimates. We identify clear negative effects of exposure to O3, PM, and SO2 in both crops, using yields measured in the vicinity of monitoring stations. We also show that while stations measuring NO2 are too sparse to reliably estimate a yield effect, the strong gradient of NO2 concentrations near power plants allows us to more precisely estimate NO2 effects using satellite measured yield gradients. The presence of some powerplants that turn on and others that shut down during the study period are particularly useful for attributing yield gradients to pollution. We estimate that total yield losses from these pollutants averaged roughly 5% for both maize and soybean over the past two decades. While all four pollutants have statistically significant effects, PM and NO2 appear more damaging to crops at current levels than O3 and SO2. Finally, we find that the significant improvement in air quality since 1999 has halved the impact of poor air quality on major crops and contributed to yield increases that represent roughly 20% of overall yield gains over that period.
Quantification of the sector-specific financial impacts of historical global warming represents a critical gap in climate change impacts assessment. The multiple decades of county-level data available from the U.S. crop insurance program – which collectively represent aggregate damages to the agricultural sector largely borne by U.S. taxpayers – present a unique opportunity to close this gap. Using econometric analysis in combination with observed and simulated changes in county-level temperature, we show that global warming has already contributed substantially to rising crop insurance losses in the U.S. For example, we estimate that county-level temperature trends have contributed $US2017 23.9 billion – or 17% – of the national-level crop insurance losses over the 1991-2017 period. Further, we estimate that observed warming contributed approximately one third of total losses in the most costly single year (2012). In addition, analyses of a large suite of global climate model simulations yield very high confidence that anthropogenic climate forcing has increased U.S. crop insurance losses. These sector-specific estimates provide important quantitative information about the financial costs of the global warming that has already occurred (including the costs of individual extreme events), as well as the economic value of mitigation and/or adaptation options.
This essay is a part of an exchange based on Francis Fukuyama’s “Making the Internet Safe for Democracy” from the April 2021 issue of the Journal of Democracy.
Natural infrastructure such as parks, forests, street trees, green roofs, and coastal vegetation is central to sustainable urban management. Despite recent progress, it remains challenging for urban decision-makers to incorporate the benefits of natural infrastructure into urban design and planning. Here, we present an approach to support the greening of cities by quantifying and mapping the diverse benefits of natural infrastructure for now and in the future. The approach relies on open-source tools, within the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) software, that compute biophysical and socio-economic metrics relevant to a variety of decisions in data-rich or data-scarce contexts. Through three case studies in China, France, and the United States, we show how spatially explicit information about the benefits of nature enhances urban management by improving economic valuation, prioritizing land use change, and promoting inclusive planning and stakeholder dialogue. We discuss limitations of the tools, including modeling uncertainties and a limited suite of output metrics, and propose research directions to mainstream natural infrastructure information in integrated urban management.
Background: Attention deficit hyperactivity disorder (ADHD) is a widely recognized mental health problem in developed countries but remains under-investigated in developing settings. This study examines the prevalence, correlates, and consequences of ADHD symptoms among elementary school students in rural China. Methods: Cross-sectional data were collected from 6,719 students across 120 rural primary schools in China on ADHD symptoms, demographic characteristics, and academic performance in reading and math. ADHD symptoms were evaluated using the caregiver-reported ADHD Rating Scale-IV. Results: The prevalence of ADHD symptoms was 7.5% in our sample. Male students, students in lower grade levels, and students with lower cognitive ability showed a significantly higher prevalence of ADHD symptoms (ORs = 2.56, 2.06, and 1.84, respectively; p<0.05). Left-behind children showed a significantly lower prevalence of ADHD symptoms than did children who were living with their parents (OR = 0.74, p < 0.05). Adjusted regressions show that students with ADHD symptoms scored 0.12 standardized deviations lower in reading (p < 0.05) and 0.19 standardized deviations lower in math (p < 0.01). Limitations: The ADHD Rating Scale-IV is a screening scale rather than a diagnostic test. Caregiver self-report measures also may underestimate ADHD symptoms for our sample. Conclusions: ADHD is a common disorder among rural students in China and appears to be contributing to poor academic outcomes. The higher prevalence of ADHD among students with low cognitive ability also suggests that many rural children in China face multifactorial learning challenges. Taken together, the findings indicate a need for educators and policymakers in rural China to develop programs to reduce risk and support students with ADHD symptoms.
China’s economy has doubled in size every eight years since 1979, making it over 32 times bigger now then it was then and the second largest in the world today.1 Four decades of growth have ushered more than 400 million people in China into the global middle class.2 According to the World Bank, China is currently an upper middle-income country. The country is the only major economy on earth to report growth in 2020 in the wake of the coronavirus pandemic.3 What are the prospects for China to continue its spectacular economic rise and become a high-income country? In this article, we aim to draw attention to an underappreciated factor that we believe may complicate China’s continued economic ascent: hundreds of millions of poorly educated, increasingly underemployed workers hailing from China’s rural hinterland.
