Training Your Replacement: Worker Incentives and the Pace of Automation

Joshua S. Gans, Peter Landry · NBER Working Papers · October 2026

Where this sits in the debate

Direction of the finding as read from the abstract by an AI model (AI-written).

Key takeaway AI-written

This NBER paper models firms asking workers to train the AI systems that will replace them, where a worker can shirk, cooperate with training, or obstruct it while staying productive. Because finishing the training ends the job, the threat of dismissal loses force as a penalty, which shapes how fast automation can proceed.

The paper in three steps AI-written

Written by an AI agent from the paper's abstract, which is the primary source and is quoted below.

The question

How do worker incentives shape the pace of automation when firms ask workers to train the AI systems that will replace them?

The approach

A model in which a worker can shirk, cooperate with training, or obstruct training while keeping up productivity. Training ends the job, but only cooperation completes it.

The findings

Because completing training ends the job, the threat of dismissal becomes a weaker penalty for the worker, which the model uses to study how training incentives affect the pace of automation.

How to read it: theory. A theoretical model — its value is the mechanism it isolates; ask whether the assumptions fit the real economy.

Limitations and counterpoints AI-written

The available abstract is cut short, so further results and any calibration or empirical test cannot be described here.

Abstract

Firms ask workers to train AI systems that will replace them. We model this with a worker who can shirk, cooperate with training, or obstruct training while maintaining productivity. Because training ends the job but only cooperation completes training, dismissal becomes a weaker penalty for

About this publication

Working paper. A working paper — circulated for discussion before formal peer review, the standard first outlet in economics.

Published: 2026
Citations: Not recorded for this source

Citation counts come from OpenAlex; none are recorded for this source — absence of a count is not absence of citations.