Jeffrey Dingis an Assistant Professor of Political Science at George Washington University. He had connections with the EA community (e.g. here and here; I don’t know the current situation). Last month he published in Review of International Political Economy a paper, “The Diffusion Deficit in Scientific and Technological Power: Re-assessing China’s Rise”, which seems worth the attention of those who are interested in the question of whether China is becoming a science and technology superpower.
Its abstract is as follows:
Virtually all scholars recognize that scientific and technological capabilities are becoming increasingly important factors in a nation’s overall power. Unsurprisingly, debates over a possible U.S.–China power transition highlight China’s rise as a science and technology superpower. These discussions overwhelmingly center on national innovation capabilities, reflective of the bias in assessments of scientific and technological capabilities toward the generation of novel advances. This paper argues that these assessments should, instead, place greater weight on a state’s capacity to diffuse, or widely adopt, innovations. Specifically, when there is a significant gap between a rising power’s innovation capacity and its diffusion capacity, relying solely on the former results in misleading appraisals of its potential to sustain economic growth in the long run. I demonstrate this with two historical cases: the U.S. in the Second Industrial Revolution and the Soviet Union in the early post-war period. Lastly, I show that, in contrast to assessments based on innovation capacity, a diffusion-centric approach reveals that China is far from being a science and technology superpower.
So, Jeffrey argues that China is far from being a science and technology superpower because it suffers from a serious problem of diffusion deficit.
In the following recent discussion, Jeffrey first briefly explained his idea of China’s diffusion deficit and also that as applied in AI, and then he answered many related questions:
About two months ago, he made a related testimony (video starting at about 02:07:10) before the U.S.-China Economic and Security Review Commission for a hearing on “China’s Challenges and Capabilities in Educating and Training the Next Generation Workforce”.
Is China Becoming a Science and Technology Superpower? Jeffrey Ding’s Insight on China’s Diffusion Deficit
Jeffrey Ding is an Assistant Professor of Political Science at George Washington University. He had connections with the EA community (e.g. here and here; I don’t know the current situation). Last month he published in Review of International Political Economy a paper, “The Diffusion Deficit in Scientific and Technological Power: Re-assessing China’s Rise”, which seems worth the attention of those who are interested in the question of whether China is becoming a science and technology superpower.
Its abstract is as follows:
So, Jeffrey argues that China is far from being a science and technology superpower because it suffers from a serious problem of diffusion deficit.
In the following recent discussion, Jeffrey first briefly explained his idea of China’s diffusion deficit and also that as applied in AI, and then he answered many related questions:
About two months ago, he made a related testimony (video starting at about 02:07:10) before the U.S.-China Economic and Security Review Commission for a hearing on “China’s Challenges and Capabilities in Educating and Training the Next Generation Workforce”.