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Working Papers

As IDE scholars' projects progress, they share early-stage research through working papers that offer insights into their findings and methodology.

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Working Papers Crashing Waves vs. Rising Tides: Preliminary Findings on AI Automation from Thousands of Worker Evaluations of Labor Market Tasks

Apr 2026

Neil Thompson | Research Scientist, MIT Sloan School of Management and CSAIL

Martin Fleming | Research Scientist, IDE

Matthias Mertens | Research Scientist at Future Tech

Brittany Harris | Data Analyst, CSAIL

Wensu Li | Postdoctoral Associate

Adam Kuzee

Harry Lyu

Jonathan Rosenfeld

Meiri Anto

 

The authors propose that AI automation is a continuum between: crashing waves where AI capabilities surge abruptly over small sets of tasks, and rising tides where the increase in AI capabilities is more continuous and broad-based.

Working Papers Economics of Human and AI Collaboration: When is Partial Automation More Attractive than Full Automation?

Mar 2026

Wensu Li | Postdoctoral Associate

Neil Thompson | Research Scientist, MIT Sloan School of Management and CSAIL

Martin Fleming | Research Scientist, IDE

Atin Aboutorabi

Harry Lyu

Kaizhi Qian

Brian C. Goehring

 

This paper develops a unified framework for evaluating the optimal degree of task automation. Moving beyond binary automate-or-not assessments, we model automation intensity as a continuous choice in which firms minimize costs by selecting an AI accuracy level, from no automation through partial human-AI collaboration to full automation.

Working Papers Ray of Hope? China and the Rise of Solar Energy

Mar 2026

John Van Reenen | Professor, London School of Economics

Ignacio Banares-Sanchez

Robin Burgess

David Laszlo,

Pol Simpson

Yifan Wang

Do industrial policies that promote clean energy offer a “ray of hope”, increasing a country’s growth and welfare, whilst simultaneously reducing carbon emissions? This paper examines whether the impact of Chinese solar subsidies whose implementation by city-regions went alongside massive expansion of the sector and a dramatic fall in global solar prices.

Working Papers Chaining Tasks, Redefining Work: A Theory of AI Automation

Jan 2026

John Horton | Associate Professor, MIT Sloan School of Management

Peyman Shahidi | Ph.D. Candidate

Brendan Lucier | Microsoft Research

Nicole Immorlica | Yale University, Microsoft Research

Mert Demirer | MIT

 

This paper develops a model that predicts that (1) AI-executed steps co-occur in chains, (2) dispersion of AI-exposed steps lowers AI execution at the job level, and (3) adjacency to AI-executed steps increases the likelihood that a step is AI-executed.

Working Papers The Latent Role of Open Models in the AI Economy

Nov 2025

Frank Nagle | Research Scientist

Daniel Yue

 

The result uncovered in this working paper suggest that closed model dominance reflects powerful drivers beyond model capabilities and price – whether switching costs, brand loyalty, or information frictions – with the economic magnitude of these hidden factors proving far larger than previously recognized, reframing open models as a largely latent, but high-potential, source of value in the AI economy.