Author Launches 5-Part AI Economics Series, Probing Productivity History
Updated
Updated · Paul Krugman | Substack · Jun 7
Author Launches 5-Part AI Economics Series, Probing Productivity History
3 articles · Updated · Paul Krugman | Substack · Jun 7
Summary
A new primer opens a planned multi-part series on AI economics by centering on productivity history rather than making firm forecasts about AI’s economic effects.
5 topics frame the first installment: how economists measure technology’s impact, the postwar productivity boom, the Solow paradox, the short-lived IT payoff, and preliminary questions about AI.
The piece argues that electrification is a useful but incomplete analogy, saying AI should also be assessed against episodes such as the postwar boom and the 1990s-2000s IT surge that faded after about 10 years.
That historical lens is presented as a check on both near-term bubble claims around datacenter spending and long-run certainty about AI’s effects on productivity, jobs and wages.
Future installments are set to widen the focus from productivity to technological unemployment, income distribution and other economic consequences of AI.
AI is everywhere except the economic data. Is the promised productivity boom a myth, or just delayed?
AI promises efficiency but delivers 'brain fry.' How do we reap its benefits without burning out the human workforce?
Mass AI job loss seems inevitable. But could our aging power grids be the one thing that saves human jobs?
AI and Productivity: Quantifying Gains, Navigating Diffusion, and Shaping Policy for the Future Economy
Overview
This report explores how AI is driving a new wave of productivity, highlighting that early gains are often underestimated because major technologies like AI require large, often hidden investments before their full benefits appear. As these investments mature, productivity can surge, but current metrics may not yet capture AI’s real impact. The report shows that initial productivity improvements are concentrated in a few industries, with broader effects expected as AI adoption spreads. This pattern, explained by the Productivity J-curve, suggests that while AI’s true economic value is still emerging, significant groundwork is being laid for future growth.