§6 · Lane 2 — AI Audit and Accountability

Auditing LLMs — A Three-Layered Approach a board-ready LLM audit checklist

Mökander, Schuett, Kirk, Floridi (2024) · AI & Ethics 4

Academic Tier 1 Lane 2 DOI
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Bibliographic data

Title
Auditing Large Language Models: A Three-Layered Approach (Mökander, Schuett, Kirk, Floridi, 2024)
Authors / Issuing body
Jakob Mökander (Oxford Internet Institute + Princeton CITP), Jonas Schuett (Centre for the Governance of AI + Goethe University Frankfurt), Hannah Rose Kirk (Oxford Internet Institute), Luciano Floridi (Oxford Internet Institute + Bologna)
Venue / Publisher
AI and Ethics 4 (2024) 1085-1115. Received Feb 2023; accepted April 2023; published May 2023 (volume year 2024).
Year
2024
Designation
Academic
Licence
Refer to publisher for full licence terms.

How to cite

Mökander, Schuett, Kirk, Floridi (2024). Auditing Large Language Models: A Three-Layered Approach (Mökander, Schuett, Kirk, Floridi, 2024). AI and Ethics 4 (2024) 1085-1115. Received Feb 2023; accepted April 2023; published May 2023 (volume year 2024).. https://doi.org/10.1007/s43681-023-00289-2.

Proposes a three-layered audit blueprint for large language models — governance audits (of providers' organisational accountability structures and quality management systems), model audits (of LLM capabilities and limitations between pre-training and release), and application audits (of products built on LLMs, covering legal compliance and impact).

Why it matters for NETEVO

Auditing Large Language Models: A Three-Layered Approach (Mökander, Schuett, Kirk and Floridi, 2024) proposes three coordinated audit layers — governance audits of provider accountability structures and quality-management systems, model audits of LLM capabilities and limitations between pre-training and release, and application audits of products built on LLMs, covering legal compliance and impact — and argues that the three layers must operate as a single instrumented loop rather than as independent activities.

The layers are interconnected, not siloed. Output from one audit becomes input to the next: governance findings inform model audits, model-limitation reports shape application audits, and application-layer operational logs feed back into the governance layer. This is the audit-side mirror of the integrated-management-system thesis the Integrated Management Systems Practical Guide establishes — one engineered system, multiple normative regimes, observed end-to-end.

Governance audits live at the management-system level. The paper places software development processes and quality management systems squarely inside the governance-audit layer — the same surface on which the Law-to-Code Methodology operates. AS ISO/IEC 42001 provides the management-system shell; this paper supplies the audit-side application.

Ex-ante and ex-post assessment together. The paper argues against audit-as-snapshot and for audit as a continuous, telemetry-driven activity. Continuous audit presupposes controls that emit evidence: an executable control produces the telemetry a continuous audit consumes, where a paper policy does not. The five institutional-arrangement archetypes the paper proposes for who audits whom also map cleanly onto Australia's emerging AI assurance landscape.

Where NETEVO applies this

Who acts on this

Reading this usually means something has forced the question — a listing, an audit finding, a procurement questionnaire, a regulator's letter. The role pages below set out what NETEVO does about it, including where we would tell you not to engage.