A new research paper introduces the TrustX Agent Risk Classification Framework (ARC), designed to assess and categorize the risks associated with internally developed agentic AI systems. The framework utilizes a twelve-dimension scoring rubric, combined with models like GPA + IAT and a five-level autonomy scale, to produce a three-tier governance output with recommended controls. An extension for coding assistants is also included to address specific risks in that domain. ARC aims to provide a structured and repeatable instrument for AI governance practitioners, risk officers, developers, and regulators. AI
IMPACT Provides a structured approach for managing risks associated with increasingly complex AI agent systems.
RANK_REASON The cluster describes a new research paper published on arXiv detailing a framework for classifying AI agent risk.
- alphaXiv
- arXiv
- CatalyzeX Code Finder for Papers
- coding assistant
- Connected Papers
- CORE Recommender
- DagsHub
- Gotit.pub
- GPA + IAT
- Hugging Face
- Influence Flower
- Litmaps
- ScienceCast
- scite Smart Citations
- TrustX Agent Risk Classification Framework
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