Can federated learning solve AI’s data privacy problem?: A legal analysis

• Main Authors: CHIK, Warren B., GAMPER, Florian
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Federated Learning; artificial intelligence; AI; machine learning; data sharing; AI data problem; privacy protection; GDPR; Artificial Intelligence and Robotics; Privacy Law
• Online Access: https://ink.library.smu.edu.sg/sol_research/4517; https://ink.library.smu.edu.sg/context/sol_research/article/6475/viewcontent/Federated_Learning_A_legal_analysis.pdf
• Institution: Singapore Management University

Federated learning (FL) is a method of training AI systems on different datasets without sharing data. The promise of FL is to enable AI systems to be trained on data, including personal data, while preserving data privacy and confidentiality, and thus, inter alia, facilitate compliance with data pr...