By Zhou Chao Indian media has recently reported that the Indian Ministry of External Affairs stated that China and India have reached an agreement...
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Debates about national scientific and technological power tend to center on which state first generates new-to-the-world breakthroughs (innovation capacity). This essay argues that assessments of technological leadership should give greater weight to a state’s diffusion capacity, or its ability to spread and adopt innovations after their initial inception across productive processes. By Jeffrey Ding Why Diffusion Capacity? (FPRI) -- Why is it so important to distinguish between a state’s capacity to bring forth new-to-the-world inventions and its capacity to adopt innovations at scale? When there is a substantial gap between these two variables, assessments based solely on innovation capacity indicators will prove misleading because they undervalue the process by which new advances are embedded into productive processes. Specifically, a “diffusion deficit” characterizes situations when a state has a strong innovation capacity but weak diffusion capacity, which suggests that it is less likely to sustain its rise than innovation-centric assessments depict. In many cases, there is not much daylight between a state’s diffusion capacity and its innovation capacity. These two parameters can be highly correlated. After all, the state that first pioneered a new method has a first-mover advantage in the widespread adoption of that technique. In addition, absorbing innovations from international sources is difficult without the tacit knowledge embedded in the original context of technological development. Diffusion and innovation are entangled, overlapping processes. However, in some circumstances, diffusion and innovation capacity can widely diverge. Aside from innovation capacity, manyother factorscan shape a country’s adoption rate of new technologies, including institutions that incentivize technology transfer, trade openness, and human capital. The “advantages of backwardness” sometimes enable laggards to diffuse new technologies faster than the pioneering states. Confronting a world of globalized science and technology flows, even the most advanced economies must be able to intensively absorb and diffuse innovations first incubated in other countries. According to oneestimatederived from data on Organisation for Economic Co-operation and Development countries, over 90 percent of productivity improvements in these high-income countries can be attributed to knowledge that originated abroad. As a result, diffusion capacity indicators can be better predictors of a state’s long-term growth trajectory than innovation capacity indicators. The latter may be more unreliable given the uncertain, protracted pathway between a new technology’s introduction and its ultimate impact on productivity growth. To this point, onestudyfound that two standard innovation capacity indicators, research and development (R&D) intensity and patenting rates, tracked less well with subsequent changes in productivity than indicators of activities related to broadly disseminating information about new products and processes. Historical Case of a Diffusion Deficit: The Soviet Union (1950–70) To demonstrate how innovation-centric approaches can misrepresent the technological prowess of a country that faces a diffusion deficit, this essay revisits assessments of the Soviet Union’s technological capabilities in the early postwar period (1950–70). In this period, the Soviet Union shocked the world by launching the first satellite. Sputnik was just one of the many prominent Soviet scientific and technological accomplishments during this time. Scholars and policymakers converged on the view that the Soviet Union was a “rising technological juggernaut.” However, by the 1970s, with the Soviet Union in the midst of a productivity slowdown, it was clear that these assessments had significantly overestimated its scientific and technological capabilities. These mistaken evaluations were based on an innovation-centered framework. To be sure, the Soviet Union became a world leader in two key indicators of innovation capacity, R&D spending and the employment of scientists and engineers. By 1970, the Soviet Union was the global leader in R&D spending as a percentage of gross national product, outpacing the United States on thismetric. US policymakers were also preoccupied with the statistic that the Soviet Union was producing about double the number of science PhD graduates as the United States. If US assessments of Soviet technological strength were informed by diffusion capacity, they would have been much more skeptical of the Soviet Union’s ability to sustain its rise. While the Soviet Union did lead in introducing new technologies across many sectors, it trailed in diffusing these technologies across a broad range of productive processes. According to one cross-nationalassessmentof technological progress in nine domains, the Soviet Union ranked as most successful in pioneering innovations and least successful in the adoption of those innovations throughout the economy. “In no major branch of industry is the average level of Soviet technology in use on a par with that in the United States or Western Europe,”concludedone 1969 Central Intelligence Agency assessment. In sum, taking diffusion capacity seriously would have provided a more balanced assessment of the Soviet Union’s scientific and technological capabilities. Findings and Implications A diffusion-centered approach undercuts claims that China is poised to become a science and technology superpower. Standard assessments of China’s challenge to US technological leadership typically rely on innovation capacity indicators, including patents, scientific papers, and R&D spending. Yet, as my research has found, similar to the Soviet Union in the 1960s, China today faces a diffusion deficit: Its diffusion capacity trails significantly behind its innovation capacity. This finding is supported by adetailed examinationof China’s adoption of information and communications technologies (ICTs). Chinese businesses have been slow to embrace digitization, as measured by adoption rates of digital factories, industrial robots, smart sensors, and key industrial software. The International Telecommunication Union’s ICT development index provides a composite measure of the level of access to and use of ICTs in countries around the world. On this metric, China ranks eighty-third in the world, which trails the United States by sixty-seven places. In sum, while China has demonstrated some success at large-scale deployment in high-speed rail and consumer-facing applications like mobile payments, these high-profile examples run counter to the overall trend in ICT adoption. As for China’s capacity to diffuse artificial intelligence (AI) advances at scale, one important indicator is the breadth of the engineering talent pool to implement AI models in various industries. General counts of science, technology, engineering, and mathematics or computer science graduates can mislead, if the quality of such training is not taken into account. Using one baseline for an institution that can train average AI engineers—a university meets this standard if it employs at least one researcher that has published at least one paper in a leading AI conference—for the years 2020 to 2021, China was home toonly 29 universitiesthat met this standard, whereas the United States accounted for 159 such institutions. Another barrier to China’s diffusion capacity in AI is the lack of technical exchanges between industry and academia, which prevents information flows from those developing new technologies and those commercializing them. In sum, when assessments of China’s scientific and technological capabilities are rebalanced toward diffusion capacity, it is clear that China is far less likely to sustain its rise than innovation-centric measures depict (at least when it comes to technological advance as a key source of growth). This means that much of the current administration’s policy toward curbing China’s technological rise is based on a mistaken assessment that China is on the verge of becoming a scientific and technological superpower. Instead, China’s diffusion deficit suggests that the United States should spend much less time worrying about China’s potential to overtake it in leadership over foundational technologies and much more time ameliorating the risks of China as a “peaking power” facing a prolonged economic slowdown. About the author: Jeffrey Ding is a 2024 Templeton Fellow and a Senior Fellow in the Asia Program at the Foreign Policy Research Institute (FPRI). He is also an Assistant Professor of Political Science at George Washington University. Source: This article was published by FPRI
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