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[2602.20946] Some Simple Economics of AGI
Summary
This article explores the economic implications of Artificial General Intelligence (AGI), focusing on the transition from human cognition to automated execution and the challenges of verification in a rapidly evolving landscape.
Why It Matters
As AGI technologies advance, understanding their economic impact is crucial for policymakers, businesses, and society. The paper highlights the need for effective oversight mechanisms to ensure that the benefits of AGI are realized without compromising human values and responsibilities.
Key Takeaways
- The transition to AGI shifts the economic focus from intelligence to human verification capacity.
- A widening Measurability Gap poses risks of unverified deployment leading to a Hollow Economy.
- Scaling verification processes is essential to harness AGI's potential while preserving human oversight.
Economics > General Economics arXiv:2602.20946 (econ) [Submitted on 24 Feb 2026] Title:Some Simple Economics of AGI Authors:Christian Catalini, Xiang Hui, Jane Wu View a PDF of the paper titled Some Simple Economics of AGI, by Christian Catalini and 2 other authors View PDF HTML (experimental) Abstract:For millennia, human cognition was the primary engine of progress on Earth. As AI decouples cognition from biology, the marginal cost of measurable execution falls to zero, absorbing any labor capturable by metrics--including creative, analytical, and innovative work. The binding constraint on growth is no longer intelligence but human verification bandwidth: the capacity to validate, audit, and underwrite responsibility when execution is abundant. We model the AGI transition as the collision of two racing cost curves: an exponentially decaying Cost to Automate and a biologically bottlenecked Cost to Verify. This structural asymmetry widens a Measurability Gap between what agents can execute and what humans can afford to verify. It also drives a shift from skill-biased to measurability-biased technical change. Rents migrate to verification-grade ground truth, cryptographic provenance, and liability underwriting--the ability to insure outcomes rather than merely generate them. The current human-in-the-loop equilibrium is unstable: eroded from below as apprenticeship collapses (Missing Junior Loop) and from within as experts codify their obsolescence (Codifier's Curse). Unveri...