Ontological Knowledge Blocks: Executable Compliance and Profile-Based Validation for Trustworthy AI Systems
The paper introduces Ontological Knowledge Blocks (OKBs) as a solution for ensuring compliance in AI systems. OKBs transform regulatory obligations into machine-checkable constraints, facilitating automated governance. The authors present prototypes demonstrating effective profile-based validation in AI-assisted scenarios.
- ▪AI-enabled services must adhere to governance obligations like transparency and accountability.
- ▪Current compliance methods are documentation-centric and do not scale well for automated systems.
- ▪The paper presents a governance infrastructure that compiles regulations into structured evidence graphs.
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Computer Science > Artificial Intelligence arXiv:2605.23297 (cs) [Submitted on 22 May 2026] Title:Ontological Knowledge Blocks: Executable Compliance and Profile-Based Validation for Trustworthy AI Systems Authors:Aasish Kumar Sharma, Julian M. Kunkel View a PDF of the paper titled Ontological Knowledge Blocks: Executable Compliance and Profile-Based Validation for Trustworthy AI Systems, by Aasish Kumar Sharma and 1 other authors View PDF HTML (experimental) Abstract:AI-enabled services deployed in critical digital infrastructure are subject to governance obligations spanning transparency, accountability, fairness, and traceability.
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