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Explainability

What is Explainability?

The degree to which the internal mechanics of an AI or machine learning system can be explained in human terms. Explainability is a key requirement of the EU AI Act for high-risk AI systems.

AI & Technology

Each of these is named in at least one of the same controls as explainability. The number is how many controls name both.

What the standards actually require on explainability

Requirements naming explainability across 6 standards, quoted from the control text.

Provide stakeholders with appropriate explanations of AI decisions and system behaviour.

23894-A.6 · Transparency and Explainability

Requirement defined in ISO/IEC TR 24028:2020, clause 9.3 (Explainability). See licensed source for normative text. Implementation focus is to demonstrate conformity with the obligations of this clause through the artefacts listed in evidence_requirements.

iso-iec-tr-24028-2020::9.3 · Explainability

Adopt explainability practices so the functioning of the model and how it arrives at decisions can be communicated to relevant stakeholders.

AIGE-OM-5 · Model explainability

Ensure AI decision-making processes can be explained in understandable terms relative to the risk level

AIGF-3.2 · Explainability

Per UK AI Principles: appropriate transparency + explainability + system documentation + cards + maintain transparency to users + regulators.

UKAI-4 · Transparency, Explainability, Documentation

The transparency and explainability of AI systems are necessary preconditions to ensure rights and to allow contestability. The level of transparency shall be appropriate to the context and the impact of the system.

UNESCO-PR-TRANSP · Transparency and explainability

Questions people ask about explainability

What is Explainability?
The degree to which the internal mechanics of an AI or machine learning system can be explained in human terms. Explainability is a key requirement of the EU AI Act for high-risk AI systems.
Why is Explainability important for compliance?
Explainability is a key concept in AI & Technology. Understanding explainability helps organizations meet regulatory requirements, reduce risk, and demonstrate due diligence during audits. Our compliance platform maps 686 frameworks with 311K cross-framework control mappings.
Which compliance frameworks address Explainability?
Explainability appears in the requirement text of ISO/IEC 23894:2023, ISO/IEC TR 24028:2020, ASEAN Guide on AI Governance and Ethics, Singapore AI Governance Framework, UK AI Regulation Framework. Across these standards we have identified 14 controls that name it directly, each linked to the control text on the compliance platform.
Where can I learn more about Explainability?
Explore our compliance framework pages to see how explainability applies across different standards and regulations. Our implementation guides provide step-by-step guidance, and the compliance platform offers AI-powered analysis of how this concept maps across 686 frameworks.

See how Explainability applies across compliance frameworks

Our platform maps 686 frameworks with 311K cross-framework control mappings. Explore how this concept is addressed across standards.

Written and maintained by Gerard Blokdyk, The Art of Service.