用可测量机制评估具身AI可信度，提升认证科学性
Toward Maturity-Based Certification of Embodied AI: Quantifying Trustworthiness Through Measurement Mechanisms
- 构建基于成熟度的具身AI认证框架，明确评估指标
- 以不确定性量化为例，实现可信度的可衡量评估
- 适用于无人机等高风险场景的AI系统可靠性验证
我们提出一种基于成熟度的具身AI系统认证框架，通过明确的测量机制实现可信度评估。我们认为，可认证的具身AI需要结构化的评估体系、量化评分机制，以及处理可信度评价中多目标权衡的方法。本文以不确定性量化作为示范性测量机制，通过无人飞行系统（UAS）目标检测案例展示了该方法的可行性。
原文摘要 · Abstract (English)
We propose a maturity-based framework for certifying embodied AI systems through explicit measurement mechanisms. We argue that certifiable embodied AI requires structured assessment frameworks, quantitative scoring mechanisms, and methods for navigating multi-objective trade-offs inherent in trustworthiness evaluation. We demonstrate this approach using uncertainty quantification as an exemplar measurement mechanism and illustrate feasibility through an Uncrewed Aircraft System (UAS) detection case study.
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