Federated learning is not a cure-all for data ethics
While attempting a purely technical fix for data sharing barriers, Federated Learning on its own cannot solve the complex ethical and legal problems around data for AI development in healthcare.
March 20, 2024
In their new article published by Nature, authors Marieke Bak, Vince I. Madai, Leo Anthony Celi, Georgios A. Kaissis, Ronald Cornet, Menno Maris, Daniel Rueckert, Alena Buyx and Stuart McLennan argue that although federated learning is often seen as a promising solution to allow AI innovation while addressing privacy concerns, this technology does not fix all underlying data ethics concerns. Benefiting from federated learning in digital health requires acknowledgement of its limitations.
Read the full article here.
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