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Article 12 Record-Keeping

Article 12

Record-keeping

1.   High-risk AI systems shall technically allow for the automatic recording of events (logs) over the lifetime of the system.

2.   In order to ensure a level of traceability of the functioning of a high-risk AI system that is appropriate to the intended purpose of the system, logging capabilities shall enable the recording of events relevant for:

(a)

identifying situations that may result in the high-risk AI system presenting a risk within the meaning of Article 79(1) or in a substantial modification;

(b)

facilitating the post-market monitoring referred to in Article 72; and

(c)

monitoring the operation of high-risk AI systems referred to in Article 26(5).

3.   For high-risk AI systems referred to in point 1 (a), of Annex III, the logging capabilities shall provide, at a minimum:

(a)

recording of the period of each use of the system (start date and time and end date and time of each use);

(b)

the reference database against which input data has been checked by the system;

(c)

the input data for which the search has led to a match;

(d)

the identification of the natural persons involved in the verification of the results, as referred to in Article 14(5).

Corresponding Recitals

(66)

Requirements should apply to high-risk AI systems as regards risk management, the quality and relevance of data sets used, technical documentation and record-keeping, transparency and the provision of information to deployers, human oversight, and robustness, accuracy and cybersecurity. Those requirements are necessary to effectively mitigate the risks for health, safety and fundamental rights. As no other less trade restrictive measures are reasonably available those requirements are not unjustified restrictions to trade.
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(71)

Having comprehensible information on how high-risk AI systems have been developed and how they perform throughout their lifetime is essential to enable traceability of those systems, verify compliance with the requirements under this Regulation, as well as monitoring of their operations and post market monitoring. This requires keeping records and the availability of technical documentation, containing information which is necessary to assess the compliance of the AI system with the relevant requirements and facilitate post market monitoring. Such information should include the general characteristics, capabilities and limitations of the system, algorithms, data, training, testing and validation processes used as well as documentation on the relevant risk-management system and drawn in a clear and comprehensive form. The technical documentation should be kept up to date, appropriately throughout the lifetime of the AI system. Furthermore, high-risk AI systems should technically allow for the automatic recording of events, by means of logs, over the duration of the lifetime of the system.
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