  The European Union Artificial Intelligence Act mandates clear stakeholder
responsibilities in developing and deploying machine learning applications to
avoid substantial fines, prioritizing private and secure data processing with
data remaining at its origin. Federated Learning (FL) enables the training of
generative AI Models across data siloes, sharing only model parameters while
improving data security. Since FL is a cooperative learning paradigm, clients
and servers naturally share legal responsibility in the FL pipeline. Our work
contributes to clarifying the roles of both parties, explains strategies for
shifting responsibilities to the server operator, and points out open technical
challenges that we must solve to improve FL's practical applicability under the
EU AI Act.
