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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We link industrial clusters, regional productivity and resource reallocation efficiency with geographical and sectoral disaggregated data. Based on a county-industry level panel from 1998 to 2007 in China, we find that industrial clusters significantly increase local industries' productivity by lifting the average firm productivity and reallocating resources from less to more productive firms. Moreover, we find major mechanisms through which resource reallocation is improved within clusters: (i) clusters are associated with a higher firm turnover with increased entry and exit rates simultaneously; and (ii) within clusters' environment, the dispersion of individual firm's markup is significantly reduced, indicating intensified local competition within clusters. Such results suggest that industrial clusters in China help improve regional productivity and resource allocation efficiency with intensified competition and accelerated firm dynamics. The identification issues are carefully addressed by two-stage estimations with instrumental variables and other robustness checks.
In each of the three waves of the Section 301 tariffs on Chinese imports, the US government exempted some products on the originally proposed list from additional duties. Using these exempted products as the counterfactual, we identify modest but heterogeneous impacts of the tariffs on the value of US imports from China. We find a complete pass-through for the first and second waves of tariffs. However, unlike in previous studies, we estimate a very limited tariff pass-through of the third wave of tariffs. Finally, we find little import diversion for the US and significant export diversion for China.
Low rates of vaccination, emergence of novel variants of SARS-CoV-2, and increasing transmission relating to seasonal changes and relaxation of mitigation measures leave many US communities at risk for surges of COVID-19 that might strain hospital capacity, as in previous waves. The trajectories of COVID-19 hospitalizations differ across communities depending on their age distributions, vaccination coverage, cumulative incidence, and adoption of risk mitigating behaviors. Yet, existing predictive models of COVID-19 hospitalizations are almost exclusively focused on national- and state-level predictions. This leaves local policymakers in urgent need of tools that can provide early warnings about the possibility that COVID-19 hospitalizations may rise to levels that exceed local capacity. In this work, we develop a framework to generate simple classification rules to predict whether COVID-19 hospitalization will exceed the local hospitalization capacity within a 4- or 8-week period if no additional mitigating strategies are implemented during this time. This framework uses a simulation model of SARS-CoV-2 transmission and COVID-19 hospitalizations in the US to train classification decision trees that are robust to changes in the data-generating process and future uncertainties. These generated classification rules use real-time data related to hospital occupancy and new hospitalizations associated with COVID-19, and when available, genomic surveillance of SARS-CoV-2. We show that these classification rules present reasonable accuracy, sensitivity, and specificity (all ≥ 80%) in predicting local surges in hospitalizations under numerous simulated scenarios, which capture substantial uncertainties over the future trajectories of COVID-19. Our proposed classification rules are simple, visual, and straightforward to use in practice by local decision makers without the need to perform numerical computations.
Research suggests that elements of the family environment may have significant associations with cognitive and language development outcomes. Less is known, however, about the family environment in peri-urban China, where rates of cognitive and language delay in children aged 0-3 years are as high as 51% and 54%, respectively. Using data collected from 81 peri-urban households with toddlers aged 18-24 months in Southwestern China, this study examines the associations between stimulating parenting practices, the home language environment, and parental self-efficacy, with cognitive and language development. The results indicate that stimulating parenting practices was significantly associated with cognitive development, the home language environment was significantly associated with language development, and parental self-efficacy was significantly associated with cognitive development. The implications of such findings reveal several mechanisms for supporting healthy cognitive and language development among toddlers from peri-urban China.
National Academies of Sciences, Engineering, and Medicine,
January 22, 2023
The COVID-19 pandemic spurred a rapid expansion of wastewater-based infectious disease surveillance systems to monitor and anticipate disease trends in communities.The Centers for Disease Control and Prevention (CDC) launched the National Wastewater Surveillance System in September 2020 to help coordinate and build upon those efforts. Produced at the request of CDC, this report reviews the usefulness of community-level wastewater surveillance during the pandemic and assesses its potential value for control and prevention of infectious diseases beyond COVID-19.
Between 2004 and 2010, Dr. Siegfried Hecker made seven trips to North Korea to explore ways to reduce the danger posed by Pyongyang’s advancing nuclear weapons program.
Introduction Millions of young rural children in China still suffer from poor health and malnutrition, partly due to a lack of knowledge about optimal perinatal and child care among rural mothers and caregivers. Meanwhile, there is an urgent need to improve maternal mental health in rural communities. Comprehensive home visiting programmes delivered by community health workers (CHWs) can bridge the caregiver knowledge gap and improve child health and maternal well-being in low-resource settings, but the effectiveness of this approach is unknown in rural China. Additionally, grandmothers play important roles in child care and family decision-making in rural China, suggesting the importance of engaging multiple caregivers in interventions. The Healthy Future programme seeks to improve child health and maternal well-being by developing a staged-based curriculum that CHWs deliver to mothers and caregivers of young children through home visits with the assistance of a tablet-based mHealth system. This protocol describes the design and evaluation plan for this programme.
Methods and analysis We designed a cluster-randomised controlled trial among 119 rural townships in four nationally designated poverty counties in Southwestern China. We will compare the outcomes between three arms: one standard arm with only primary caregivers participating in the intervention, one encouragement arm engaging primary and secondary caregivers and one control arm with no intervention. Families with pregnant women or infants under 6 months of age are invited to enrol in the 12-month study. Primary outcomes include children’s haemoglobin levels, exclusive breastfeeding rates and dietary diversity in complementary feeding. Secondary outcomes include a combination of health, behavioural and intermediate outcomes.
Autocratic elections are often marred with systematic intimidation and violence toward voters and candidates. When do authoritarian regimes resort to violent electoral strategies?
