Age and gender distortion in online media and large language models

Authors: D Guilbeault, S Delecourt, BS Desikan

Published: 2025

Publication: Nature, 2025 - nature.com

The study highlights age-related gender bias in online media and language models, showing women are portrayed as younger than men, especially in high-status occupations, and explores how algorithms amplify these biases.

Methods: Analysis of 1.4 million images and videos from online sources and nine language models, followed by a pre-registered experiment involving participants to evaluate biases in internet content and algorithms.

Key Findings: Age and gender bias in occupational depiction across online platforms and language models, as well as its influence on beliefs and hiring preferences.

Institution: Stanford University, University of California Berkeley, University of Oxford

Research Area: AI Bias, Media Representation,Social Science

Discipline: Computational Social Science , Artificial Intelligence

Sample Size: 459 participants

Citations: 4