---
title: "Federated learning"
description: "Training a model across devices or sites where the data lives, sharing model updates instead of raw records."
canonical: https://aigovernanceengineer.com/glossary/federated-learning
author: "Jorge García Aibar"
license: "CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/)"
doi: https://doi.org/10.5281/zenodo.22956197
version: "0.5.0"
updated: 2026-09-24
---

# Federated learning

Training a model across devices or sites where the data lives, sharing model updates instead of raw records [1]. It limits data movement but does not by itself hide personal data, because shared updates can leak training examples.

- Developed in: [ch. 19, Privacy-enhancing technologies and their honest limits](https://aigovernanceengineer.com/bok/privacy-and-ai#privacy-enhancing-technologies-and-their-honest-limits)
- Chapters: [ch. 19, Privacy & AI](https://aigovernanceengineer.com/bok/privacy-and-ai)
- In the glossary chapter: https://aigovernanceengineer.com/bok/glossary#t-federated-learning

## Sources

[1] "Communication-Efficient Learning of Deep Networks from Decentralized Data" (McMahan et al.; federated learning; arXiv 1602.05629). arXiv. 2016-02-17. https://arxiv.org/abs/1602.05629 (verified: primary)