# AI literacy — AI Act — context bundle > Focused context for a single provision, curated from overview.legal on 2026-08-22. Canonical page: https://overview.legal/laws/ai-act/art-4 > Every item cites its source. Verify against the official text (EUR-Lex / wetten.overheid.nl) before relying on it. ## Provision ### AI literacy — AI literacy *AI Act, aiact-art-4-en — https://overview.legal/laws/ai-act/art-4* Providers and deployers of AI systems shall take measures to ensure, to their best extent, a sufficient level of AI literacy of their staff and other persons dealing with the operation and use of AI systems on their behalf, taking into account their technical knowledge, experience, education and training and the context the AI systems are to be used in, and considering the persons or groups of persons on whom the AI systems are to be used. ## Related recitals ### Recital 14 — biometric data definition interpretation The notion of ‘biometric data’ used in this Regulation should be interpreted in light of the notion of biometric data as defined in Article 4, point (14) of Regulation (EU) 2016/679, Article 3, point (18) of Regulation (EU) 2018/1725 and Article 3, point (13) of Directive (EU) 2016/680. Biometric data can allow for the authentication, identification or categorisation of natural persons and for the recognition of emotions of natural persons. ### Recital 24 — AI exclusion for military defense security If, and insofar as, AI systems are placed on the market, put into service, or used with or without modification of such systems for military, defence or national security purposes, those should be excluded from the scope of this Regulation regardless of which type of entity is carrying out those activities, such as whether it is a public or private entity. As regards military and defence purposes, such exclusion is justified both by Article 4(2) TEU and by the specificities of the Member States’ and the common Union defence policy covered by Chapter 2 of Title V TEU that are subject to public international law, which is therefore the more appropriate legal framework for the regulation of AI systems in the context of the use of lethal force and other AI systems in the context of military and defence activities. As regards national security purposes, the exclusion is justified both by the fact that national security remains the sole responsibility of Member States in accordance with Article 4(2) TEU and by the specific nature and operational needs of national security activities and specific national rules applicable to those activities. Nonetheless, if an AI system developed, placed on the market, put into service or used for military, defence or national security purposes is used outside those temporarily or permanently for other purposes, for example, civilian or humanitarian purposes, law enforcement or public security purposes, such a system would fall within the scope of this Regulation. In that case, the entity using the AI system for other than military, defence or national security purposes should ensure the compliance of the AI system with this Regulation, unless the system is already compliant with this Regulation. AI systems placed on the market or put into service for an excluded purpose, namely military, defence or national security, and one or more non-excluded purposes, such as civilian purposes or law enforcement, fall within the scope of this Regulation and providers of those systems should ensure compliance with this Regulation. In those cases, the fact that an AI system may fall within the scope of this Regulation should not affect the possibility of entities carrying out national security, defence and military activities, regardless of the type of entity carrying out those activities, to use AI systems for national security, military and defence purposes, the use of which is excluded from the scope of this Regulation. An AI system placed on the market for civilian or law enforcement purposes which is used with or without modification for military, defence or national security purposes should not fall within the scope of this Regulation, regardless of the type of entity carrying out those activities. ### Recital 53 — low risk AI systems clarification It is also important to clarify that there may be specific cases in which AI systems referred to in pre-defined areas specified in this Regulation do not lead to a significant risk of harm to the legal interests protected under those areas because they do not materially influence the decision-making or do not harm those interests substantially. For the purposes of this Regulation, an AI system that does not materially influence the outcome of decision-making should be understood to be an AI system that does not have an impact on the substance, and thereby the outcome, of decision-making, whether human or automated. An AI system that does not materially influence the outcome of decision-making could include situations in which one or more of the following conditions are fulfilled. The first such condition should be that the AI system is intended to perform a narrow procedural task, such as an AI system that transforms unstructured data into structured data, an AI system that classifies incoming documents into categories or an AI system that is used to detect duplicates among a large number of applications. Those tasks are of such narrow and limited nature that they pose only limited risks which are not increased through the use of an AI system in a context that is listed as a high-risk use in an annex to this Regulation. The second condition should be that the task performed by the AI system is intended to improve the result of a previously completed human activity that may be relevant for the purposes of the high-risk uses listed in an annex to this Regulation. Considering those characteristics, the AI system provides only an additional layer to a human activity with consequently lowered risk. That condition would, for example, apply to AI systems that are intended to improve the language used in previously drafted documents, for example in relation to professional tone, academic style of language or by aligning text to a certain brand messaging. The third condition should be that the AI system is intended to detect decision-making patterns or deviations from prior decision-making patterns. The risk would be lowered because the use of the AI system follows a previously completed human assessment which it is not meant to replace or influence, without proper human review. Such AI systems include for instance those that, given a certain grading pattern of a teacher, can be used to check ex post whether the teacher may have deviated from the grading pattern so as to flag potential inconsistencies or anomalies. The fourth condition should be that the AI system is intended to perform a task that is only preparatory to an assessment relevant for the purposes of the AI systems listed in an annex to this Regulation, thus making the possible impact of the output of the system very low in terms of representing a risk for the assessment to follow. That condition covers, inter alia, smart solutions for file handling, which include various functions from indexing, searching, text and speech processing or linking data to other data sources, or AI systems used for translation of initial documents. In any case, AI systems used in high-risk use-cases listed in an annex to this Regulation should be considered to pose significant risks of harm to the health, safety or fundamental rights if the AI system implies profiling within the meaning of Article 4, point (4) of Regulation (EU) 2016/679 or Article 3, point (4) of Directive (EU) 2016/680 or Article 3, point (5) of Regulation (EU) 2018/1725. To ensure traceability and transparency, a provider who considers that an AI system is not high-risk on the basis of the conditions referred to above should draw up documentation of the assessment before that system is placed on the market or put into service and should provide that documentation to national competent authorities upon request. Such a provider should be obliged to register the AI system in the EU database established under this Regulation. With a view to providing further guidance for the practical implementation of the conditions under which the AI systems listed in an annex to this Regulation are, on an exceptional basis, non-high-risk, the Commission should, after consulting the Board, provide guidelines specifying that practical implementation, completed by a comprehensive list of practical examples of use cases of AI systems that are high-risk and use cases that are not. ### Recital 94 — law enforcement biometric data processing compliance Any processing of biometric data involved in the use of AI systems for biometric identification for the purpose of law enforcement needs to comply with Article 10 of Directive (EU) 2016/680, that allows such processing only where strictly necessary, subject to appropriate safeguards for the rights and freedoms of the data subject, and where authorised by Union or Member State law. Such use, when authorised, also needs to respect the principles laid down in Article 4 (1) of Directive (EU) 2016/680 including lawfulness, fairness and transparency, purpose limitation, accuracy and storage limitation. ### Recital 104 — open-source general-purpose AI model transparency exceptions The providers of general-purpose AI models that are released under a free and open-source licence, and whose parameters, including the weights, the information on the model architecture, and the information on model usage, are made publicly available should be subject to exceptions as regards the transparency-related requirements imposed on general-purpose AI models, unless they can be considered to present a systemic risk, in which case the circumstance that the model is transparent and accompanied by an open-source license should not be considered to be a sufficient reason to exclude compliance with the obligations under this Regulation. In any case, given that the release of general-purpose AI models under free and open-source licence does not necessarily reveal substantial information on the data set used for the training or fine-tuning of the model and on how compliance of copyright law was thereby ensured, the exception provided for general-purpose AI models from compliance with the transparency-related requirements should not concern the obligation to produce a summary about the content used for model training and the obligation to put in place a policy to comply with Union copyright law, in particular to identify and comply with the reservation of rights pursuant to Article 4(3) of Directive (EU) 2019/790 of the European Parliament and of the Council (40). ### Recital 106 — general-purpose AI model copyright compliance Providers that place general-purpose AI models on the Union market should ensure compliance with the relevant obligations in this Regulation. To that end, providers of general-purpose AI models should put in place a policy to comply with Union law on copyright and related rights, in particular to identify and comply with the reservation of rights expressed by rightsholders pursuant to Article 4(3) of Directive (EU) 2019/790. Any provider placing a general-purpose AI model on the Union market should comply with this obligation, regardless of the jurisdiction in which the copyright-relevant acts underpinning the training of those general-purpose AI models take place. This is necessary to ensure a level playing field among providers of general-purpose AI models where no provider should be able to gain a competitive advantage in the Union market by applying lower copyright standards than those provided in the Union. ## Guidance ### EDPB Annual Report 2025 *EDPB — https://overview.legal/posts/125683* Clarity in action: Supporting stakeholders through guidance and dialogue Annual Report 2025 Foreword 3 Highlights 4 1. The EDPB Secretariat 6 1.1 Mission And Activities 8 2. European Data Protection Board – Activities in 2025 12 2.1 Bridging Fundamental Rights and Digital Innovation Through GDPR Compliance 12 2.1.1 Helsinki high-level meeting: enhanced clarity, support and engagement 12 2.1.2 Regulation on procedural rules and Omnibus regulation on the record of processing 14 2.1.3 Cross… ### Report on stakeholder event on processing of personal data to target or deliver political advertisements *EDPB — https://overview.legal/posts/125684* Report on stakeholder event on processing of personal data to target or deliver political advertisements 27 March 2026 1. Background The EDPB organised an online stakeholder event on 27 March 2026 to collect stakeholders’ input on processing of personal data to target or deliver political advertisements. The objective was to engage with stakeholders at an early stage of drafting the EDPB Guidelines on the processing of personal data to target or deliver political advertisements (Chapter III of… ### Report on stakeholder event on anonymisation and pseudonymisation of 12 December 2025 *EDPB — https://overview.legal/posts/125688* Report on stakeholder event on anonymisation and pseudonymisation of 12 December 2025 1. Background The EDPB organise d a remote stakeholder event on 12 December 2025 to collect stakeholders’ input on anonymisation and pseudonymisation , following the Court of Justice of the European Union ( “ CJEU ” ) judgment in case EDPS v SRB 1 . The objective was to engage with stakeholders to inform the EDPB’s ongoing work on its guidelines 01/2025 on pseudonymisation and f orthcoming guidelines on… ### EDPB-EDPS Joint opinion 1/2026 on the Proposal for a Regulation as regards the simplification of the implementation of harmonised rules on artificial intelligence *EDPB — https://overview.legal/posts/53738* EDPB, EDPB-EDPS Joint opinion 1/2026 on the Proposal for a Regulation as regards the simplification of the implementation of harmonised rules on artificial intelligence (Digital Omnibus on AI) ### Vormvoorstel Nederlandse regulatory sandbox *Autoriteit Persoonsgegevens — https://overview.legal/posts/50722* De aankomende AI-verordening verplicht lidstaten tot het oprichten van ten minste één AI regulatory sandbox vanaf augustus 2026. Binnen een regulatory sandbox bieden toezichthouders ondersteuning aan aanbieders van AI-systemen die tijdens de ontwikkeling vragen hebben over hoe zij aan de AI-veror... ## Related topics - **AI Value Chain Actors and Roles** — https://overview.legal/topics/ai-value-chain-actors ## Legal Framework --- Generated by overview.legal · https://overview.legal/laws/ai-act/art-4 · 2026-08-22