IIEP UBA-CONICET

Seminario de Investigación | Does generative AI narrow education-based productivity gaps? Evidence from a randomized experiment
2026-04-08 13:00 - 17:00 (America/Argentina/Buenos_Aires) | UBA Córdoba, Av. Córdoba 2122, Buenos Aires, Ciudad Autónoma de Buenos Aires, 1425, Argentina
Seminario de Investigación del IIEP
Does generative AI narrow education-based productivity gaps? Evidence from a randomized experiment
Expositor | Guillermo Cruces | UDESA

Abstract
Does generative artificial intelligence (AI) reinforce or reduce productivity differences across workers? Existing evidence largely studies AI within firms and occupations, where organizational selection compresses educational heterogeneity, leaving unclear whether AI narrows productivity gaps across individuals with substantially different levels of formal education. We address this question using a randomized online experiment conducted outside firms, in which 1,174 adults ages 25–45 with heterogeneous educational backgrounds complete an incentivized, workplace-style business problem-solving task. The task is a general (not domain specific) exercise, and participants perform it either with or without access to a generative-AI assistant. Unlike prior work that studies heterogeneity within relatively homogeneous worker samples, our design targets the between–education-group productivity gap as the primary estimand. We find that AI increases productivity for all participants, with substantially larger gains for lower-education individuals. In the absence of AI access, higher-education participants outperform lower-education participants by 0.548 standard deviations; with AI access, this gap falls to 0.139 standard deviations, implying that generative AI closes about three quarters of the initial productivity gap. We interpret this pattern as evidence that generative AI narrows effective productivity differences in task execution by relaxing cognitive constraints that are more binding for lower-education individuals, even though underlying skill differences remain, as reflected in persistent education gaps in task performance and in a follow-up exercise without AI assistance.

Co autores Diego Fernandez Meĳide, Sebastian Galiani, Ramiro H. Galvez, Maria Lombardi

Lugar | FCE-UBA | Aula Olivera
