https://taxonomy.eticas.ai/risk/fitness-for-purpose
Maturity: emerging
The system has not been validated against the problem it is intended to solve, or is deployed for a task or context beyond the one it was validated for. Covers the ex ante question (was this designed and validated for this problem?) and its enforcement in deployment; whether the system actually succeeds at the task in operation is task-performance (Reliability).
This subcategory is emerging. It has not yet been validated through established assessment methods.
Also known as: Fitness for purpose · Task success
System type: ADM and LLM systems
Lifecycle stages: Pre Processing, In Processing, Post Processing
Status. Each mapping shows what it rests on. Reviewed means a reviewer has confirmed the mapping against the concept’s current definition and the framework edition the taxonomy currently references; when the only confirmation is that of the person who wrote the mapping, it reads Reviewed (author’s confirmation). Outdated means it was reviewed, but the concept’s definition has changed since, so the review has to be repeated. The other statuses mean that no review has been recorded yet. Inherited mappings have been in the taxonomy since before v5.7.0 and are unchanged. They carry no record of who made them or how, and some were checked by hand when the taxonomy first published its mappings. Agent-proposed mappings come from a review carried out by AI agents, which read the framework’s text and the concept’s definition and agreed on the relation; no person has confirmed them yet. Provisional mappings were made without access to the framework’s text. Unreviewed mappings are older mappings whose target or relation was revised in v5.7.0, and any other mapping without a review. Mappings to a superseded edition of a framework are not shown: where the provision continues, they are carried to the current edition. Mappings a review has changed or rejected are not shown.
| Framework | Reference | Status |
|---|---|---|
| ISO/IEC 42001:2023 — AI Management System | A.9.4 Intended use of the AI system | Agent-proposed |
| ISO/IEC 42001:2023 — AI Management System | A.6.2.4 AI system verification and validation | Agent-proposed |
| ISO/IEC 42001:2023 — AI Management System | A.6.2.2 AI system requirements and specification | Agent-proposed |
| NIST AI Risk Management Framework (AI 100-1) | MAP 3: AI capabilities, targeted usage, goals, and expected benefits and costs compared with appropriate benchmarks are understood. | Agent-proposed |
| NIST AI Risk Management Framework (AI 100-1) | MEASURE 2.5: The AI system to be deployed is demonstrated to be valid and reliable. Limitations of the generalizability beyond the conditions under which the technology was developed are documented. | Agent-proposed |
| NIST AI Risk Management Framework (AI 100-1) | MAP 3.3: Targeted application scope is specified and documented based on the system’s capability, established context, and AI system categorization. | Agent-proposed |
| NIST AI Risk Management Framework (AI 100-1) | MANAGE 1.1: A determination is made as to whether the AI system achieves its intended purposes and stated objectives and whether its development or deployment should proceed. | Agent-proposed |
Source: HRA project taxonomy