Top Economists on AI · 2021-2026
What are the Nobel & Clark laureates saying about AI?
All Nobel laureates in Economics and all Clark Medalists searched for AI-related papers published 2021-2026, in NBER or top-five journals. Below: 55 papers from 18 laureates, clustered into 5 themes.
📚 Browse by Cluster
👤 Top Contributors
29 of the 55 papers (~53%) come from just two authors: Susan Athey and Daron Acemoglu. They have effectively defined the AI-economics research frontier.
🧭 Reading Paths
Don't have time to read all 55? Here are curated paths through the literature:
For Acemoglu's pessimistic case
Simple Macroeconomics of AI → Tasks Automation Wage Inequality → Pro-Worker AI → Knowledge Collapse
For Athey's methodological revolution
Deep Learning for Economists (Dell) → Stable Learning → CAREER → LABOR-LLM → AEA Presidential Address
For AI policy & antitrust
Athey-Morton Competition → Tirole Digital Dystopia → Tirole Fair Gatekeeping → Milgrom Algorithmic Mechanism Design
For AI as research tool
Dell Deep Learning for Economists → Sargent Sources of AI → Shleifer GPT Measurement → Hansen DL Climate
For AI in development
Stiglitz/Korinek Globalization → Kremer weather forecasts → Duflo AI ECG India
For optimist vs pessimist macro
Nordhaus Economic Singularity (optimist 2021) → Acemoglu Simple Macro (pessimist 2024) → Andrews Markets Believe? (markets agnostic 2025)
📋 Methodology
Five parallel research agents searched all Nobel laureates in Economics (1969-2024) and all Clark Medalists (1947-2023), looking for papers published 2021-2026 where AI/ML/automation/algorithms is the core substantive topic (not merely an econometric method). Sources: NBER working papers, top-five journals (AER/QJE/JPE/REStud/Econometrica), AEJ series, key ML venues (NeurIPS/AISTATS/JEDC). Most pre-2000 laureates are deceased; among living laureates, only ~18 had AI-core papers in the window. 5 papers are flagged "borderline" — included with caveat (3 are non-peer-reviewed but substantive; 2 are AI-as-method rather than AI-as-topic).