Sinopinion Jeffrey Ding: Technology Diffusion and National Strength: The New Logic of Competition in the Age of GPTs
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Mar 31, 2025 
In this insightful discussion, Jeffrey Ding, a professor at George Washington University and an expert on technology diffusion, shares his thoughts on the modern competition driven by general-purpose technologies (GPTs). He critiques the glorification of breakthrough innovations and highlights the significance of gradual advancements and workforce skills. Ding discusses the historical impact of GPTs on military effectiveness and advocates for a diffusion-centric strategy in the US-China AI rivalry, emphasizing the need for improved technical education and workforce growth.
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Diffusion Matters More Than First Invention
- General purpose technologies (GPTs) shape national power more by widespread adoption than by who pioneers them.
- Success depends on slow diffusion across sectors and institutions that train broad pools of ordinary engineers, not just frontier inventors.
What Makes A Technology General Purpose
- GPTs are identified by continual improvement, pervasive applicability, and strong technological complementarities.
- These traits let a GPT enable many sectors only after broad adaptation, distinguishing it from leading sectors like autos or steel.
Leading Sectors Versus GPTs
- Leading sectors like automobiles can be large but lack GPT breadth and cross-sector enabling power.
- Advances in AI can enable improvements across industries (e.g., electric vehicles), unlike sector-limited innovations.
