Decentralized Machine Learning Governance

Researchers have started to recognize the necessity for a well-defined M L g overnance framework based on the principle of decentralization and comprehensively defining i ts s cope o f r esearch and practice due to the growth of machine learning (ML) research and applications in the real world and the success of blockchain-based technology. In this paper, we study decentralized ML governance, which includes ML value chain management, decentralized identity for the ML community, decentralized ownership and rights management of ML assets, community-based decisionmaking for the ML process, decentralized ML finance, and risk management.