为军事中AI系统交战设计可解释的附带损伤评估模型
Collateral Damage Assessment Model for AI System Target Engagement in Military Operations
- 基于统一知识表示框架，融合时空与力量维度
- 通过可解释推理机制量化损伤程度与发生概率
- 适用于需可信评估的军事AI交战场景
随着人工智能在战场上的作用日益增强，确保负责任的打击行动需要对潜在附带损害进行严格评估。本文提出一种新型的军事作战中AI系统交战附带损伤评估模型。该模型采用设计科学方法论，在统一的知识表示与推理（KRR）架构下整合时间、空间和力量维度。其分层结构涵盖待打击AI系统的类别、架构组件、对应交战向量及上下文要素。同时，综合考虑传播性、严重性、可能性与评估指标，实现透明化推理的清晰表征。通过实例化演示与评估，验证了该模型作为构建负责任、可信赖智能系统的基础能力，支持对军事作战中交战所产生效应的系统性评估。
原文摘要 · Abstract (English)
In an era where AI (Artificial Intelligence) systems play an increasing role in the battlefield, ensuring responsible targeting demands rigorous assessment of potential collateral effects. In this context, a novel collateral damage assessment model for target engagement of AI systems in military operations is introduced. The model integrates temporal, spatial, and force dimensions within a unified Knowledge Representation and Reasoning (KRR) architecture following a design science methodological approach. Its layered structure captures the categories and architectural components of the AI systems to be engaged together with corresponding engaging vectors and contextual aspects. At the same time, spreading, severity, likelihood, and evaluation metrics are considered in order to provide a clear representation enhanced by transparent reasoning mechanisms. Further, the model is demonstrated and evaluated through instantiation which serves as a basis for further dedicated efforts that aim at building responsible and trustworthy intelligent systems for assessing the effects produced by engaging AI systems in military operations.
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