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An Engels’ pause in an AI-shaped world

29 Sep 2025 GS 3 Economy
An Engels’ pause in an AI-shaped world Click to view full image

Engels’ Pause:

  • Concept: Coined by economist Robert Allen (after Friedrich Engels).

  • 19th-century Britain:

    • Industrial output surged.

    • Wages stagnated, cost of living stayed high.

    • Inequality widened; benefits of industrialization took decades to reach the masses.

  • Technological revolutions create growth, but mass welfare may lag.

AI and a Modern Engels’ Pause

AI is seen as a General Purpose Technology (GPT) (like steam, electricity, internet).

  • Potential: Boosts productivity, lowers prediction costs (Agrawal, Gans, Goldfarb, 2018).

  • Risk: Gains concentrated among few firms/nations; broad-based welfare delayed.

Markers of a Modern Engels’ Pause

  1. Productivity rise, stagnant wages

    • Example: Call centres in Philippines → 30–50% productivity gains with AI copilots, but wages stagnant.

    • Workers face inflation, higher cost of living.

  2. Rising cost of complements

    • AI requires cloud, retraining, data, cybersecurity.

    • Workers pay high costs for coding bootcamps, certifications → digital survival expensive.

  3. Unequal global distribution

    • AI could add $15.7 trillion to GDP by 2030.

    • Benefits concentrated in US, China, few firms with foundational models.

    • IMF (2024): 40% jobs exposed to AI; inequality may deepen.

  4. Job displacement and task transformation

    • Doctors, educators, finance workers see tasks reshaped by AI.

    • Example: Tsinghua University’s AI hospital, Albania appointing world’s first AI Minister.

Policy Lessons from History

  • U.S. Gilded Age: inequality and unrest, followed by reforms (trade unions, schooling, welfare).

  • Without governance, Engels’ pause persists.

Pathways to Avoid an AI-Induced Engels’ Pause

  1. Skill transitions & education

    • Singapore’s SkillsFuture: continuous education credits.

    • MBZUAI (Abu Dhabi): world’s first AI university.

  2. Redistribution of AI rents

    • Robot taxes, Universal Basic Income (UBI).

    • Philanthropic efforts (e.g., Chan-Zuckerberg Initiative).

  3. Treat AI infrastructure as a public good

    • Compute and data must be affordable.

    • Open AI reasoning models like K2Think.ai (UAE), Apertus (Switzerland).

The Challenge Ahead

  • Optimistic view:

    • Stronger welfare systems, faster diffusion (smartphones, healthcare AI).

    • AI may deliver quicker welfare benefits than 19th-century industry.

  • Caution:

    • Risk of “macro gains but micro stagnation.”

    • Requires strong political will, equitable governance, and redistribution policies.



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