From Privacy to Trust in the Agentic Era: A Taxonomy of Challenges in Trustworthy Federated Learning Through the Lens of Trust Report 2.0

Researchers propose Trustworthy Federated Learning (TFL) framework that treats trust as a continuously maintained system condition rather than static property, addressing challenges in AI systems with autonomous decision-making. The framework introduces Trust Report 2.0 as a privacy-preserving coordination blueprint for multi-stakeholder governance in federated learning deployments.