A Mathematical Theory of Federated Learning (TRUST-FELT)

Description of the granted funding

Artificial intelligence (AI) is integral to our daily lives, influencing our job search, housing, and relationships. Many AI services are powered by federated learning (FL) systems providing tailored predictions on interests like job offers, dating, and music videos. Despite the usefulness of FL systems, there is increasing evidence for their potentially harmful effects, such as boosting addictive user behavior or even genocide.This project breaks ground for trustworthy FL, shifting the focus of current FL research towards a more human-centric perspective. Besides the computational and statistical properties of FL systems, this project emphasizes important design criteria for trustworthy AI.
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Starting year

2025

Granted funding

Alexander Jung
498 000 €

Funder

Jane and Aatos Erkko Foundation

Other information

Funding decision number

A835

Themes

Tekniikka

Keywords

113 Tietojenkäsittely ja informaatiotieteet