The Chinese government recently cut off international access to a significant portion of the country’s public data—including contracts, patents, scientific conference proceedings, dissertations, and statistical information. Coverage has attributed the disappearance of some of this data to reports by think tanks that leveraged such data to highlight, among other findings, how the People’s Liberation Army hoped to access and weaponize American-designed semiconductors.
This ongoing situation is unfortunate for numerous reasons, not least because the research we conduct at Georgetown’s Center for Security and Emerging Technology (CSET) using Chinese data has consistently been recognized as accurate, balanced, and responsible. More importantly, locking down data and preventing responsible researchers who rely on publicly available materials (often called “open source”) from understanding China is a strategic mistake for the People’s Republic. Allowing global access only to unsatisfactory data may lead to unsatisfactory outcomes for everyone.
China likely cares more about controlling its message than the accuracy of U.S. analysts’ work. Chinese Communist Party (CCP) leaders have for decades limited foreigners’ access to domestic news and information to try to control global narratives about their country. But this latest expansion of the Great Firewall does little to boost China’s image, and it could strengthen the influence of foreign analysts who present one-sided perspectives on the country.
By denying international researchers open-source information, China is pulling the rug out from under analysts worldwide who are committed to providing policymakers with a holistic understanding of China’s science and technology policies. In the current, strident climate of U.S.-China competition, the loudest voices already drown out those who deliver nuanced, evidence-based assessments. This latest move by the CCP could inadvertently amplify the perspectives of professionals who are obligated to emphasize contingencies and prevent worst-case-scenarios—and, worse yet, those who offer policymakers opinions without solid evidentiary grounding.
U.S. policymakers must seek ways to counter China’s authoritarian domestic and foreign policies, some of which violate fundamental human rights, international law, and commercial norms. But overestimating risk based on one-sided assessments of China’s capabilities and intentions could spark excessive spending to counter perceived threats, diverting funds from other important priorities. The already-strained U.S.-China relationship could deteriorate further, obliterating opportunities to collaborate on shared challenges—and potentially escalating economic or security crises. Lack of open-source data could lead analysts to exaggerate Beijing’s economic, technological, and ideological threats, harming global relations. A lack of data-led decision-making could lead to misguided “decoupling” and protectionist policies that intensify the atmosphere of mutual mistrust and suspicion.
When policy discourse is dominated by hyperbolic voices and risk assessments stemming from miscalculations, misperceptions, or suppression of challenging evidence, poor outcomes result, as history shows: The Maginot Line, a series of French fortifications built in the 1930s to deter a German invasion, focused too intently on one particular risk, the threat of direct attack along France’s border with Germany. Instead, Germany skirted the line and invaded through Belgium. The Three Mile Island nuclear meltdown in 1979 illustrates how a single data point in a crisis can lead to transformative policy shifts. Though the incident caused no immediate deaths or injuries, the resulting public and regulatory reaction shaped the trajectory of U.S. nuclear energy adoption. Risks also can be intentionally inflated based on bad data or when policymakers select a narrow subset of data to support a particular conclusion: In the run-up to Operation Iraqi Freedom, Baghdad’s reported acquisition of 100,000 high-strength aluminum tubes for purported use in gas centrifuges was a key data point; the risk this data supposedly supported was later found to be overinflated.
Of course, none of these examples of risk assessments were either uncomplicated or free from confusion—nor were competing concerns in each case unwarranted. Rather, what they illustrate is how policymaking, especially in times of tension, can be improved by responsibly using reliable data to inform understanding and perception. By barring international access to its data, the CCP is putting its global competitors in precarious positions where they may be more likely to assume the worst when it comes to evaluating Chinese policy decisions in high-consequence scenarios.
China may also be further damaging its own standing as a global leader with data restrictions that hinder collaborations between Chinese and international researchers. This will likely impede progress in various fields and undermine China’s global competitiveness. Lack of transparency may erode trust with the international community, hampering cooperation on border-leaping challenges like pandemics, global warming, economic stability, and safe deployment of emerging technologies such as artificial intelligence. China’s opacity may deter foreign investors, limiting access to vital capital and technological expertise. It could also impair China’s ability to better participate in the establishment of international norms and agreements and act as a responsible global stakeholder, pushing it closer to North Korea, Russia, and other states known to routinely promote false narratives deliberately to align with their own interests. China is a global research leader with reach and influence, and these scenarios do not serve its interests or those of the global scientific and technical communities.
The CCP should immediately reconsider its decision to restrict international access to open-source data—both for its own interests and the global community’s benefit.
As for the United States, a balanced policy approach that continuously monitors both threats and opportunities using analytical capabilities that account for the nuances and complexities of the U.S.-China relationship is key. Accurately calibrating risk assessments requires significant investment into infrastructure, datasets, and other resources, and supporting the rich open-source research ecosystem will be important for best positioning the United States amid strategic and research competition. When China closes doors that can lead to better communication, understanding, and de-escalation, as it has done in restricting data access, U.S. policymakers should look for open windows by facilitating research and methodologies that offer a comprehensive understanding of risk and enable better policy decisions.
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