For Heads-of · Practitioner
Inadequate explainability for affected individuals
An AI-driven decision materially affecting a person can't be explained to them in a way they can meaningfully understand or challenge.
- high
- transparency
- explainability
- individual-rights
How it happens
A decision is generated by a model complex enough that even the team operating it can't produce a plain-language reason for a specific outcome, so when an affected individual asks why, the honest answer is that no one really knows.
Why it matters
Explainability isn't a nice-to-have UX feature here, it's the mechanism that makes the right to contest a decision meaningful; without it, oversight and appeal rights exist in name only.
Mitigating controls
The controls that address this risk, ranked by effectiveness.
Automated decision-making safeguards
Process guaranteeing a right to human review, an ability to contest, and a documented rationale for any solely-automated decision with significant effect.
AI transparency and disclosure labelling
Consistent, visible labelling of AI-generated content and AI-driven interactions across every surface a person might encounter them.
Framework and clause references
| Framework | Clause | Title |
|---|---|---|
| EU AI Act | Article 14 | Human oversight |
| UK General Data Protection Regulation | Article 22 | Automated individual decision-making, including profiling |
Related resources
The external sources behind this risk, from the Resources library.