Alex Imas and Phil Trammell – What remains scarce after AGI?
“One robot now turns into many robots next year, but the number of ballerinas is the same.”
TL;DR
- Economics offers crucial answers to questions about AI's impact on wealth generation, taxation, and redistribution, challenging common intuitions.
- The "relational sector," services where human involvement is part of the value, is a candidate for future scarcity, alongside potential new types of automated goods and services.
- Historical economic shifts, like the Industrial Revolution, show that automation can lead to new job creation and increased demand for services, but future outcomes are uncertain.
- Labor share has remained surprisingly stable, but the rise of AGI could alter this balance, with implications for wealth distribution.
- The "Messy Middle" scenario posits AI automation leading to job losses without sufficient wealth creation for redistribution, creating political challenges.
- Various methods for taxing and redistributing AI-generated wealth are discussed, including negative income tax, universal basic capital, and consumption taxes, each with potential drawbacks.
- Current evidence does not show mass automation or unemployment due to AI, though some effects on junior developer roles are noted.
- The elasticity of demand for AI-related services is crucial; if demand is highly elastic, automation could lead to increased hiring and economic growth.
- The scenario of demand collapse leading to negative economic growth is considered unlikely given expanding technological frontiers and potential for new types of demand.
- Integrating humans into future AI-organized production flows may become difficult due to speed, reliability, and transaction costs, even if humans have a comparative advantage.
- The preferences of future AI entities and the evolutionary pressures on human preferences regarding AI interaction are significant factors in determining future economic structures.
- Developing countries not in the AI supply chain face risks of being left behind but could potentially leapfrog using AI technologies, akin to mobile banking adoption.
- The ease of 'indexing' the economy to capture AI gains is debated, with privatization of returns posing a challenge but broad access through public companies and open models offering hope.
- Commodification of frontier AI models is seen as beneficial for broad prosperity, though it raises concerns about proliferation and concentrated power potentially being replaced by widespread diffusion.
- The narrative surrounding AI's impact matters; positive narratives about future possibilities are harder to construct than negative ones about job losses.