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

论文概要

研究领域: ML
作者: Edward C. Cheng, Jeshua Cheng, Alice Siu
发布时间: 2026-10-24
arXiv: 2610.30445

中文摘要

能够自主决策的 AI 智能体在安全、对齐、问责与人类监督方面带来重大挑战。现有的人在环（HITL）与负责任 AI 方法提供了重要基础，但多数仍碎片化地散落在系统设计、治理与运行部署各环节。本文提出三支柱（3P）模型与框架，通过透明、问责与可信来构建安全可信赖的 AI 智能体：框架定义了一条演化路径——以渐进验证、结构化人类监督与可审计的运行控制引入更高的智能体自主性；并进一步说明该模型如何支撑智能体生命周期监控、决策可追溯、升级管理与人在 agentic 企业环境中的人机协作。通过把监督原则与运行机制结合，所提框架为部署既保持与人类意图对齐、又能受控迈向更高自主性的 AI 智能体提供了实践基础。

原文摘要

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.

自动采集于 2026-10-24

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