AI resources governance with OpenDID: Strategy & Roadmap - Chacón, Lenin; Moraga, Kevin (Anais Estendidos do Latin-American Symposium on Dependable and Secure Computing (LADC), 2025)
The accelerated adoption of artificial intelligence (AI) in academia has created new demands on computing infrastructure, pushing institutions to rethink how resources are allocated. This paper proposes a governance model for fair and efficient access to university-owned GPU clusters, grounded in decentralized identity (DID) and verifiable credentials (VC). Drawing from scheduling theory in operating systems, we outline how eligibility proofs—such as GPA, coursework, or research needs—can be used to assign priority in resource queues. We present a roadmap for implementation within a Latin American university context, with an initial prototype already under development. Our approach aims to reduce friction in resource access while reinforcing institutional policies on equity and transparency. By aligning DID-based authentication with cryptographic proofs and scheduling logic, we offer a scalable strategy that could serve as a reference for other educational environments seeking responsible AI infrastructure governance.