用可量化的指标让企业智能变得可审计、可追责。
Operationalising Extended Cognition: Formal Metrics for Corporate Knowledge and Legal Accountability
- 将企业知识定义为动态能力，通过信息获取效率和输出可靠性衡量。
- 提出连续的企业知识度量 $S_S(φ)$ 与总体认知能力指数 $/mathcal{K}_{S,t}$。
- 把算法决策纳入法律知识标准，助力企业问责制落地。
企业责任依赖于对企业主观意图（mens rea）的认定，传统上由人类代理人推断。然而，随着生成式AI日益介入企业决策，这一假设正面临挑战。基于扩展认知理论，我们主张企业知识应被重新定义为一种动态能力，可通过信息获取流程的效率和输出结果的验证可靠性来衡量。本文构建了一个形式化模型，捕捉部署复杂AI或信息系统企业的认知状态，提出连续的企业知识度量 $S_S(φ)$，整合计算成本与统计验证误差率。由此推导出知识谓词 $ extsf{K}_S$ 和企业整体认知能力指数 $ extcal{K}_{S,t}$。进一步将这些量化指标映射至法律中的实际知识、推定知识、故意视而不见及轻率等标准。本研究为创建可测量、可诉诸司法的审计成果提供路径，使算法时代的企业心智可追踪、可问责。
原文摘要 · Abstract (English)
Corporate responsibility turns on notions of corporate \textit{mens rea}, traditionally imputed from human agents. Yet these assumptions are under challenge as generative AI increasingly mediates enterprise decision-making. Building on the theory of extended cognition, we argue that in response corporate knowledge may be redefined as a dynamic capability, measurable by the efficiency of its information-access procedures and the validated reliability of their outputs. We develop a formal model that captures epistemic states of corporations deploying sophisticated AI or information systems, introducing a continuous organisational knowledge metric $S_S(φ)$ which integrates a pipeline's computational cost and its statistically validated error rate. We derive a thresholded knowledge predicate $\mathsf{K}_S$ to impute knowledge and a firm-wide epistemic capacity index $\mathcal{K}_{S,t}$ to measure overall capability. We then operationally map these quantitative metrics onto the legal standards of actual knowledge, constructive knowledge, wilful blindness, and recklessness. Our work provides a pathway towards creating measurable and justiciable audit artefacts, that render the corporate mind tractable and accountable in the algorithmic age.
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