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.
Show moreStarting year
2025
Granted funding
Alexander Jung
498 000 €
Funder
Jane and Aatos Erkko Foundation
Call
Other information
Funding decision number
A835
Themes
Tekniikka
Keywords
113 Tietojenkäsittely ja informaatiotieteet