UPSC Relevance- Covers GS-3 (Economy, Technology, Employment, Inequality, Governance).
Why in News
Artificial Intelligence (AI) pioneer and Nobel Laureate Geoffrey Hinton recently sounded a warning in the Financial Times: AI could lead to widening economic inequality, where a small section of society becomes significantly richer, while the majority of people see stagnant or declining incomes.
- This warning has revived the debate around “Engels’ Pause”, a historical phenomenon observed during the Industrial Revolution where technological progress boosted overall production but wages for workers remained stagnant for decades.
- Hinton’s statement draws attention to the socioeconomic risks of rapid AI adoption, highlighting that AI-driven automation may disproportionately benefit capital owners and tech companies, leaving ordinary workers behind.
Background: What is Engels’ Pause?
Concept-The term “Engels’ Pause” was coined by Oxford economist Robert Allen, inspired by Friedrich Engels’ observations of 19th-century Britain. It describes a period when:
- Industrial output and productivity surged due to technological innovation.
- Workers’ wages stagnated, failing to rise in proportion to overall economic growth.
- Income inequality widened, concentrating wealth among factory owners and capitalists.
Historical Context
- During Britain’s Industrial Revolution, often called the “workshop of the world,” ordinary workers gained very limited welfare improvements, despite enormous economic growth.
- It was only later, through labour reforms, trade unions, and the emergence of welfare policies, that the benefits of industrialisation became more widely shared.
Relevance Today
- Artificial Intelligence (AI) can be seen as a modern general-purpose technology (GPT), similar to:
- Steam engines
- Electricity
- The Internet
- Like past GPTs, AI has the potential to increase productivity and growth, but in the short term may cause job displacements, wage stagnation, and inequality before its benefits spread broadly.
Analysis: Signs of a Modern Engels’ Pause in the AI Era
1. Productivity Gains but Stagnant Wages
- In Philippines’ call centres, the introduction of generative AI copilots increased worker productivity by 30–50%.
- While firms enjoyed cost savings and higher output, workers’ wages remained flat, and workloads often intensified.
- Rising inflation further erodes real incomes, mirroring the wage stagnation of 19th-century Britain during the Industrial Revolution.
2. Rising Costs of Complements
- To fully benefit from AI, workers need access to cloud computing, large datasets, reskilling programs, and certifications.
- These requirements create “digital survival costs”, similar to how rising food prices in 19th-century Britain disproportionately affected workers’ purchasing power.
3. Unequal Distribution of Gains
- According to PwC, AI could add $15.7 trillion to global GDP by 2030.
- However, the benefits are likely to concentrate in the U.S., China, and a few tech giants controlling foundational AI models.
- The IMF (2024) reports that 40% of jobs worldwide are exposed to AI, with advanced economies facing high-skilled task substitution, further deepening inequality.
4. Job Displacement and Task Transformation
- Healthcare: AI-assisted diagnostics and AI-powered hospitals (e.g., Tsinghua University projects) are replacing routine tasks.
- Education, finance, and public management: Routine administrative and repetitive tasks are increasingly automated.
- Governance: Countries are adapting, e.g., Albania appointed the world’s first AI Minister to manage AI policy and regulation.
Challenges in the AI Era
1. Wage Inequality
- Skilled workers, tech entrepreneurs, and capital owners capture the majority of AI-driven gains.
- Ordinary workers may see stagnant or declining wages, worsening income inequality globally.
2. Governance Gap
- Weak global regulations exist for AI models, algorithms, and data usage.
- This allows data monopolies and tech giants to dominate AI development, concentrating economic and political power.
3. Access Divide
- AI infrastructure, including high-performance computing, large datasets, and cloud services, is concentrated in a few countries.
- Developing nations and smaller firms may struggle to compete, exacerbating global inequities.
4. Reskilling Burden
- Workers need to invest in reskilling, certifications, and continuous learning to stay relevant.
- High costs and limited access may exclude vulnerable groups, deepening social inequality.
5. Democratic Backsliding
- Job losses and economic insecurity could fuel social unrest, populism, and political polarization.
- Public distrust in institutions may rise if AI benefits are perceived as concentrated among elites, undermining democratic stability.
Way Forward: Escaping the AI Engels’ Pause
1. Skills and Human Capital
- Continuous reskilling is crucial to ensure workers benefit from AI rather than being displaced.
- Singapore’s SkillsFuture program provides education credits for lifelong learning, helping citizens adapt to changing technology.
- AI-focused universities like MBZUAI in Abu Dhabi are training the next generation of AI-ready professionals, building a skilled workforce globally.
2. Redistribution of AI Gains
- Policymakers can implement measures to share AI-generated wealth more broadly:
- Robot Taxes: Taxing companies that replace human labour with AI to fund social welfare and reskilling initiatives.
- Universal Basic Income (UBI) pilots in Europe and the UK provide a financial safety net for displaced workers.
- Philanthropic initiatives, such as the Chan-Zuckerberg Foundation, aim to ensure AI benefits reach underprivileged populations.
3. AI as a Public Good
- Treat compute resources and large datasets as public utilities to avoid monopolization.
- Support open-source and public AI models (e.g., K2Think.ai, Apertus) to democratize access and prevent concentration of power among a few corporations or nations.
4. Global Governance
- Establish global regulatory frameworks for AI under bodies like the UN, IMF, and G20.
- Ensure inclusive policymaking with participation from the Global South, preventing AI from becoming a tool of digital colonialism.
- Promote ethical AI standards that balance innovation, equity, and accountability worldwide.
Conclusion
The Engels’ pause teaches us that productivity revolutions do not automatically translate into welfare revolutions. Without proactive policies, AI may widen inequality, stall wage growth, and trigger social unrest. Yet, unlike the 19th century, today’s societies possess stronger welfare systems, faster tech diffusion, and democratic institutions.
Thus, the AI Engels’ pause need not be prolonged if governments:
- Invest in reskilling,
- Redistribute AI rents, and
- Treat AI infrastructure as a public good.
In essence, the challenge is not AI itself, but the political economy of how its benefits are shared. Progress delayed will mean progress denied.
Upsc mains practice question-
Q.The emergence of Artificial Intelligence (AI) has the potential to create a modern Engels’ pause, where productivity gains may not translate into broad-based welfare. Discuss the concept of Engels’ pause, its relevance in the AI era, and suggest policy measures to ensure inclusive growth.(15 marks, 250 words)