risk
Lack of AI explainability, documentation and disclosure
Because AI models are opaque, model cards and datasheets are missing, and AI involvement in consequential interactions is not disclosed, affected individuals cannot obtain recourse and operators cannot see failure modes, resulting in unaccountable decisions, uninformed consent, and misplaced confidence in spurious, non-causal model reasoning.
Record JSON · Open in map · Data retrieval guide
Catalog revision: 24028ffcfc2b295fa1b08ee6caa84b765f0731b321496bf4f548c49ad2177028. A connection does not establish full coverage.
Attributes
- category
- ai_governance
- domain
- AI Governance
- Governance, Policy & Oversight
- taxonomy
- nist-ai-rmf-risk
- iso-23894-ai-risk
- eu-ai-act-risk
- inherent_rating
- medium
Details
- risk_id
- ai-lack-explainability-transparency
- category
- ai_governance
- likelihood
- medium
- impact
- medium
- inherent_rating
- medium
- treatment
- mitigate
- taxonomies
- nist-ai-rmf-risk
- iso-23894-ai-risk
- eu-ai-act-risk
Source
No record-specific source URL is provided.
Connections
- UC-AI-06 — Maintain AI system technical documentation mitigates Lack of AI explainability, documentation and disclosure
- strength
- primary
- rationale
- Technical documentation supplies the model/data characteristics, limitations and datasheets the risk says are missing, letting operators see failure modes.
- UC-AI-10 — Meet transparency obligations for AI systems mitigates Lack of AI explainability, documentation and disclosure
- strength
- primary
- rationale
- Disclosing AI involvement and providing capability/limitation instructions directly addresses the non-disclosure and uninformed consent the risk names.
- UC-AI-17 — Define customer data-use and output-rights policies for AI services mitigates Lack of AI explainability, documentation and disclosure
- strength
- related
- rationale
- Published data-use and output-rights terms are part of the transparency customers rely on to understand how the AI service treats their data.
- UC-AI-15 — Fulfill general-purpose AI model provider obligations mitigates Lack of AI explainability, documentation and disclosure
- strength
- related
- rationale
- Model technical documentation and downstream information supply model cards/datasheets for GPAI.
- UC-AI-09 — Govern AI data quality, provenance, and preparation mitigates Lack of AI explainability, documentation and disclosure
- strength
- related
- rationale
- Provenance/lineage records supply the datasheets the risk says are missing, though indirect to core model opacity.