Year: 2025
Type: report
Abstract: How much can AI accelerate progress in different research fields?This paper shows that three features-the share of research tasks AI performs, the productivity of AI at those tasks, and the strength of bottlenecks-are key determinants of AI's implications in any area, from cancer therapeutics to software design.The model maps changes in AI capabilities to research outcomes, quantifies the "marginal returns to intelligence," and shows how AI can shift returns to R&D investment.Concepts like superintelligence, Powerful AI, and Transformative AI are further engaged and disciplined.Finally, the framework sets a measurement agenda linking AI benchmarks to field-specific opportunities for accelerating progress.
DOI: 10.3386/w34312
Author: Benjamin F. Jones
Institutions: Northwestern University, National Bureau of Economic Research
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funder: National Science Foundation
OpenAlex ID: W4414867103