## Tomorrow’s Electricity

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**Canonical URL:** [Tomorrow’s Electricity](https://www.imf.org/en/publications/fandd/issues/2024/12/book-review-tomorrows-electricity-chris-wellisz)

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## Bibliographic details
- Authors: CHRIS WELLISZ
- Published: December 3, 2024

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### Summary of the book reviewed
- Title reviewed: Technology and the Rise of Great Powers: How Diffusion Shapes Economic Competition by Jeffrey Ding.
- Publication details noted in the review: Princeton University Press, Princeton, NJ, 2024, 320 pp., $29.95.
- Central claim highlighted: broad adoption and diffusion of general-purpose technologies (GPTs) across many sectors—not dominance in a few “leading” industries—drives long-run economic growth and determines which nations rise to global prominence.

### Evidence and historical findings
- Critique of the leading sectors theory:
  - Leading sectors theory holds that first-mover advantage in disruptive, pioneer industries (examples cited: consumer electronics, semiconductors, chemicals, steel, motor vehicles) yields global economic dominance.
  - Jeffrey Ding disputes this theory, arguing it fails to explain how innovation translates into sustained, economy-wide growth.
- Historical examples used to support diffusion thesis:
  - Britain: cotton production surged after the spinning jenny and the water frame, but the textile industry accounted for only a small portion of subsequent increases in productivity, industrial production, and per capita GDP.
  - Britain’s Industrial Revolution success attributed to widespread mechanization of industry and adoption of the factory system (GPT diffusion), not only breakthroughs in iron or cotton textiles.
  - United States: the invention of the electrical generator in 1871 did not lead to widespread electrification of industry until decades later, illustrating slow diffusion.
  - Japan: despite technological pacesetting in the 1980s, Japan experienced economic stagnation in the 1990s, suggesting a technological lead does not guarantee long-term dominance.
- Key conceptual contrast:
  - “GPT infrastructure” (education, training, deep pools of engineering skills, broad-based adoption) vs. flashy, concentrated investments in frontier innovation.

### Policy implications and recommendations
- For policymakers in countries competing over AI and other GPTs (examples discussed: China and the United States):
  - Rethink emphasis on monopolizing frontier research and development; a sole focus on R&D may be misplaced.
  - Prioritize building GPT infrastructure:
    - Expand technology training for less-skilled workers so they can embed the next GPT throughout the economy.
    - Strengthen education and training systems to cultivate large pools of engineering skills.
  - Recognize that no single country can monopolize a GPT such as artificial intelligence; diffusion and broad adoption matter more than exclusive control of frontier innovation.
- Suggested strategic shift: from securing the high ground in innovation to investing in systems that enable economy-wide diffusion of technologies.

### Key quotations and formulations preserved
- “It is the broad adoption of technology across the economy that drives growth, not leading industries.”
- “GPT infrastructure, not the flashy efforts to secure the high ground in innovation, will decide which nation owns the future.”

*Source: F&D Magazine review “Tomorrow’s Electricity” by CHRIS WELLISZ, December 2024; review of Technology and the Rise of Great Powers by Jeffrey Ding (Princeton University Press, Princeton, NJ, 2024, 320 pp., $29.95).*

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- **Tomorrow’s Electricity**
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_Source: https://www.imf.org/en/publications/fandd/issues/2024/12/book-review-tomorrows-electricity-chris-wellisz_