Lecture 14.1
AI and Worker Adaptability
AI and Worker Adaptability
Manning & Aguirre (2025)
- AI exposure varies widely across occupations — but exposure ≠ job loss
- Workers in high-exposure occupations often have strong adaptive capacity (education, earnings, transferable skills)
- ~6.1 million workers face both high AI exposure and low adaptive capacity — mostly in clerical and administrative roles
- The risk is concentrated, not evenly spread
Discussion: Who Bears the Risk?
Manning & Aguirre find that many highly AI-exposed workers are relatively well-positioned to adapt. Does that reassure you, or does it raise new concerns?
The Washington Post interactive maps the jobs most affected. Which occupations surprised you? What patterns did you notice?
How does the concept of adaptive capacity change how we should think about AI-driven displacement compared to earlier waves of automation (e.g., the China Shock)?
Discussion: Politics and Policy
The 6.1 million most vulnerable workers are concentrated in clerical and administrative roles. What does that tell us about who is likely to bear adjustment costs — and who isn’t?
Should government intervene, and if so, how? Consider:
- Social insurance (unemployment, retraining)
- Industrial or technology policy
- Regulating the pace of AI adoption
Does the political economy of AI disruption look different from trade-induced job loss? Why or why not?
