MLCommons Invites Feedback on Decentralized AI Policy Blueprint
MLCommons invites the ML community to contribute to the ‘Technical Policy Blueprint for Trustworthy Decentralized AI’ by providing feedback and use cases to enhance AI governance.
The Machine Learning community is invited to contribute to the ‘Technical Policy Blueprint for Trustworthy Decentralized AI’ initiative by providing feedback and use cases.
The blueprint proposes a collaborative community effort to introduce:
- Policy-as-code objects for transparent AI governance
- A Policy Engine to verify evidence and issue capability packages
- Asset Guardians to simplify verification and application of these packages
This decoupling aims to enhance transparency, auditability, interoperability, and resilience in decentralized AI systems.
For more information, email Alex Karargyris.
Tags: Decentralized AI, Technical Policy Blueprint, Trustworthy AI, Machine Learning, AI Governance, MLCommons