arXiv AI By Nathalie Baracaldo, Nicolas Mello, Kush R. Varshney, Heiko Ludwig, Kate Soule, David Cox

Granite.Trust Policy Tools: Shareable, Actionable Policies for Generative AI Applications

Read the original on arXiv AI →

Granite.Trust Policy Tools introduces a YAML-based Actionable Policy schema that specifies what content a generative AI model can or cannot produce, allowing exception-based governance. It also offers a synthetic data generation pipeline to create policy-aligned training data and a suite of tools for defining and enforcing these policies throughout the AI lifecycle. The tools and example policies are open source, enabling organizations to tailor safety policies to their specific risks and regulatory contexts.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

arXiv AI
Jun 19

Deontic Policies for Runtime Governance of Agentic AI Systems

arXiv:2606. 19464v1 Announce Type: new Abstract: Autonomous agentic AI systems driven by Large Language Models (LLMs) introduce a new class of security, privacy, and compliance challenges: an agent that can invoke tools, manipulate data, install software, and coordinate with peer agents across organizational boundaries must be constrained not just by authentication and access control, but by the full structure of enterprise governance.

By Anupam Joshi, Tim Finin, Karuna Pande Joshi, Lalana Kagal