Papers for

it governance teams

Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.

Three-pillar framework guides safer autonomous AI agents

A Three-Pillar Governance Framework for Safe and Trustworthy AI Agents

Abstract: AI agents capable of autonomous decision-making introduce significant challenges related to safety, alignment, accountability, and human oversight. Existing Human-in-the-Loop (HITL) and responsible AI approaches provide important foundations, but many remain fragmented across system design, governance, and operational deployment. This paper presents a Three-Pillar (3P) model and framework for developing safe and trustworthy AI agents through transparency, accountability, and trustworthiness. The framework defines an evolutionary path in which increasing agent autonomy is introduced through progressive validation, structured human oversight, and auditable operational controls. We further describe how the model supports agent lifecycle monitoring, decision traceability, escalation management, and human-agent collaboration within enterprise agentic environments. By integrating oversight principles with operational mechanisms, the proposed framework provides a practical foundation for deploying AI agents that remain aligned with human intent while enabling controlled progression toward higher autonomy.

Wed 21 OctArtificial Intelligence
The gist
Autonomous AI agents that make their own decisions can be risky without proper controls. The authors propose a framework with three main parts—transparency, accountability, and trustworthiness—to help safely build and manage these agents. Their model encourages gradually giving agents more independence while keeping humans involved to check and audit decisions. This approach aims to ensure AI systems act in line with human intentions as they become more capable.
Open → 2610.30445v1