Chapter III · High-risk AI systems
Article 13 — Transparency and provision of information to deployers
Official text
Each paragraph records where its wording comes from. Only text reproduced unchanged from the Official Journal is authentic; consolidated text is editorial and has no legal value. Paragraphs, subparagraphs and points each have their own link.
High-risk AI systems shall be designed and developed in such a way as to ensure that their operation is sufficiently transparent to enable deployers to interpret a system’s output and use it appropriately. An appropriate type and degree of transparency shall be ensured with a view to achieving compliance with the relevant obligations of the provider and deployer set out in Section 3.
Authentic — as published in the Official Journal
High-risk AI systems shall be accompanied by instructions for use in an appropriate digital format or otherwise that include concise, complete, correct and clear information that is relevant, accessible and comprehensible to deployers.
Authentic — as published in the Official Journal
The instructions for use shall contain at least the following information:
- (a)
the identity and the contact details of the provider and, where applicable, of its authorised representative;
- (b)
the characteristics, capabilities and limitations of performance of the high-risk AI system, including:
- (i)
its intended purpose;
- (ii)
the level of accuracy, including its metrics, robustness and cybersecurity referred to in Article 15 against which the high-risk AI system has been tested and validated and which can be expected, and any known and foreseeable circumstances that may have an impact on that expected level of accuracy, robustness and cybersecurity;
- (iii)
any known or foreseeable circumstance, related to the use of the high-risk AI system in accordance with its intended purpose or under conditions of reasonably foreseeable misuse, which may lead to risks to the health and safety or fundamental rights referred to in Article 9(2);
- (iv)
where applicable, the technical capabilities and characteristics of the high-risk AI system to provide information that is relevant to explain its output;
- (v)
when appropriate, its performance regarding specific persons or groups of persons on which the system is intended to be used;
- (vi)
when appropriate, specifications for the input data, or any other relevant information in terms of the training, validation and testing data sets used, taking into account the intended purpose of the high-risk AI system;
- (vii)
where applicable, information to enable deployers to interpret the output of the high-risk AI system and use it appropriately;
- (i)
- (c)
the changes to the high-risk AI system and its performance which have been pre-determined by the provider at the moment of the initial conformity assessment, if any;
- (d)
the human oversight measures referred to in Article 14, including the technical measures put in place to facilitate the interpretation of the outputs of the high-risk AI systems by the deployers;
- (e)
the computational and hardware resources needed, the expected lifetime of the high-risk AI system and any necessary maintenance and care measures, including their frequency, to ensure the proper functioning of that AI system, including as regards software updates;
- (f)
where relevant, a description of the mechanisms included within the high-risk AI system that allows deployers to properly collect, store and interpret the logs in accordance with Article 12.
Authentic — as published in the Official Journal
The formal analysis of Article 13
Article 6 is formalised first. The remaining articles follow.
Article 13 is formalised node by node: each rule as a deontic position with its operator, each exception with its rank, each predicate resolved against the definitions in Article 3.
What members get, per article
- the rule logic: every norm as a formal position, with the defeater chain that decides which exception wins
- the competency questions and their answers, every unanswered one marked as a gap and named
- the ontology: predicates bound to AISV (AI Standardisation Vocabulary) and to the definitions they depend on, exportable as JSON-LD and OWL
- the documentation: the Article 6(4) assessment record generated from a fact set, with its derivation and the version of the law it was decided against
Built for providers claiming the 6(3) derogation, for the counsel who has to defend that claim, and for the auditor who reads it afterwards.
Access is invite-only and opening in stages. Article 6 is formalised first; the remaining articles follow.
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Commentary in preparation
The official text above is complete. The editorial layer for this article — duties, the roles bound by them, the AISV concepts that model them, and the European standards written to support them — is in preparation, in the same form as the articles already published.
See the published articles