Jeffrey Hinton, known as the “Godfather of AI” and a Nobel laureate, suggested that AI will greatly enrich a few people while impoverishing the rest. This concern highlights a situation called Engels’ Pause.

Background of Engels’ Pause

• Industrial Revolution: Surge in Productivity
  • During the 19th-century Industrial Revolution in Britain, industrial output and national productivity soared due to mass factory production.
• Living Standards: No improvement for Common Man
  • Despite national progress, the quality of life for ordinary workers did not improve.
• Wages and Prices: Stagnant earnings, Rising Costs
  • Wages remained stagnant, while rising food prices forced most families to spend nearly all their income on subsistence.
• Inequality: Gap between Rich and Poor Widened
  • The industrial boom dramatically increased economic and social inequality.
• Engels’ Pause: Growth Without Welfare
  • Economist Robert Allen coined the term Engels’ Pause, named after Friedrich Engels, who (alongside Karl Marx) highlighted the grim conditions of Britain’s working class during this period.

About Engels’ Pause

• Engels’ Pause is the situation where technology such as Artificial Intelligence increases national productivity , but the quality of life or wages of the common man stagnate or decline. 
• This creates a gap where the benefits of technological progress take years to reach the wider population.

Indicators of a Modern-Day Engels’ Pause in the Age of AI

• Rising Productivity, Stagnant Wages: Companies benefit greatly from AI, but worker compensation does not reflect this increase.
  • Example: Call center workers in the Philippines using AI tools saw their productivity rise by 30% to 50%, but their salaries did not increase.
  • Hidden Costs: Data centers required to run AI use massive amounts of electricity, driving up energy demand and increasing electricity bills for common people.
• Expensive Complements: AI requires expensive “complementary” services such as cloud computing, data access, cyber security, and skilled employee retention.
  • For workers, the complement is the “price of staying relevant.” 
  • Small salary increases are immediately consumed by the cost of acquiring new digital skills (e.g., coding boot camps, new certifications, continuous learning).
• Unequal Distribution of Benefits: The benefits from AI are highly concentrated and unequal. AI is estimated to contribute $15.7 trillion to global GDP by 2030.
  • Most of this profit will flow to the US and China, where major AI companies (Google Gemini, OpenAI, Deepseek) are based, exacerbating global inequality.
• Job Displacement: AI is permeating every sector, leading to job loss and disruption.
  • Examples: Doctors using ChatGPT, China opening the world’s first AI-powered hospital, and software companies laying off thousands to focus on AI. 
    • Albania appointed the first AI Minister named Diayla to oversee public procurement and combat corruption.

Government Measures to Mitigate the Pause

• Skill Transition Programs: Governments must launch programs to reskill workers.
  • Example: Singapore’s Skill Future Program provides credits to workers to learn new skills. 
    • Abu Dhabi established the MBZUAI (first AI university globally).
• Redistribution of AI Rents: The extra profits generated by AI should be redistributed
  • Example: Implementing a Robot Tax and using the revenue to fund social security measures like Universal Basic Income (UBI).
    • Experiments with UBI in the United Kingdom and the European Union, or philanthropic commitments such as the Chan-Zuckerberg Initiative, aim to channel AI gains toward public good.
• Treat AI Infrastructure as a Public Good: Like roads and electricity, AI infrastructure should be made available as a public good for the benefit of all citizens.
  • Example: The UAE’s K2 Think Tank AI is working to develop public open AI models to reduce the monopoly currently held by companies from the US and China

Reasons the Engels’ Pause Analogy May Not Fully Apply Today

• Welfare and Institutions: Modern societies have stronger welfare systems and functioning democratic institutions, even though democratic backsliding is evident in some parts of the world.
• Rapid Technology Diffusion: Technology spreads much faster today; smartphones reached billions within a decade, and AI assistants could do the same.
• Potential for Welfare Gains: AI can lower costs in health care, education, and clean energy, delivering immediate benefits if governance ensures equitable deployment.
• Policy Alignment: If innovation is matched with effective policy, the AI Engels’ pause could be shorter than its historical counterpart.

Conclusion

The challenge for AI governance is to ensure AI becomes not just a productivity revolution but a human welfare revolution. Like Engels’ Pause, its shadow may linger—but its duration depends on our choices.

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