Concern 817 · Working draft · editorial review in progress
Conformity assessments
A conformity assessment checks whether a covered AI system meets specified legal requirements before use or sale; the concern is whether the assessment is meaningful and appropriate to the system.
Understanding the concern
An assessment may examine documentation, risk controls, data practices and testing. Depending on the legal route, parts can be performed internally or require an outside body. The process is therefore not always an independent government test of each model or each answer it produces.
The EU framework provides different assessment routes for different systems. Think of inspecting a building before opening: the inspection concerns defined requirements and the intended use, not every future event. A substantial change can affect whether the earlier assessment still applies. People need clarity about who assessed the system, what evidence was considered and what the result covers.
An example
A product advertises that it passed an assessment, but the assessed version differs from the one now making decisions.
Illustrative unless identified as a documented case.
Words in plain English
- AI
- Software that learns patterns from examples or uses rules to perform tasks such as recognizing images or generating text. It can make mistakes and does not understand every situation as a person would.
- Model
- The learned part of an AI system. It uses patterns found during training to produce an answer or prediction.
- EU
- The European Union, a group of European countries with shared institutions and some shared laws.
Evidence and its limits
Assessment routes and dates vary. This explanation is not a claim that all high-risk AI requires the same third-party certification.
European Commission AI Act Service Desk · Legislative explanation
Article 43: Conformity assessment ↗ (opens in a new tab)Different assessment routes, including internal control and third-party routes. Read alongside current amendments and application dates.
Broader frameworks and background
These resources provide context. They do not establish every claim in this concern.
A question to discuss
Which version and intended use were assessed, and how are later changes handled?
Keep track of different views, what needs checking, and any next step in your own discussion notes.
Open discussion notes →Principles for the conversation
Before you finish · reflect together
Virtues and principles to consider
Virtues are qualities we practice in how we treat people and make choices. They are not scores for judging someone. Use these ideas to explore what a thoughtful response could look like.
Accountability
Accountability means being answerable for decisions and taking responsibility for repair. It requires more than saying that the software made the choice.
Name the person or team responsible, keep useful records, and give them authority to correct problems. Make the route to a complaint clear to the people affected.
Ask together: Who will answer for the outcome and help put things right?
Prudence
Prudence means using careful judgment before and during action. It balances worthwhile opportunities with the need to avoid harm that could have been anticipated.
Start with a limited trial, set stopping points, and prefer choices that can be undone when uncertainty is high. Review what happens rather than assuming the original plan remains sound.
Ask together: What is a careful next step, and when should we stop or change course?
Unity
Unity means working toward shared purposes while making room for real differences. It does not require everyone to have the same experience, beliefs, or opinion.
Look for a goal people can share, then explore disagreements about how to reach it. Make sure quieter or less powerful voices can influence the result.
Ask together: What purpose can we share while respecting our differences?
Editorial ratings
These are editorial judgments from the register, not measured probabilities or predictions about your situation.
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