# Operationalising Extended Cognition: Formal Metrics for Corporate Knowledge and Legal Accountability

arXiv: https://arxiv.org/abs/2510.16193 · HTML: https://mlsanity.com/paper/2510.16193/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 53 references that are in the map.
- First posted on arXiv 17 Oct 2025.

## Builds on (most cited first, 4 of 4)

- [On Calibration of Modern Neural Networks](https://mlsanity.com/paper/1706.04599/) (2017)
- [Billion-scale similarity search with GPUs](https://mlsanity.com/paper/1702.08734/) (2017)
- [Deal or No Deal? End-to-End Learning for Negotiation Dialogues](https://mlsanity.com/paper/1706.05125/) (2017)
- [Infrastructure for AI Agents](https://mlsanity.com/paper/2501.10114/) (2025)

## Built on by (most cited first, 1 of 1)

- [Memory in the Loop: In-Process Retrieval as Extended Working Memory for Language Agents](https://mlsanity.com/paper/2607.05690/) (2026)

## Abstract (arXiv)

Corporate responsibility turns on notions of corporate textitmens 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 SS(varphi) which integrates a pipeline's computational cost and its statistically validated error rate. We derive a thresholded knowledge predicate mathsfKS to impute knowledge and a firm-wide epistemic capacity index KS,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.