+AI & Autonomous Technologies Development Practices
---+AI & Autonomous Technologies Transparency
---+AI & Autonomous Technologies Implementation Documentation
---+AI & Autonomous Technologies Human Domain Knowledge Reliance
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AI & Autonomous Technologies Development Practices
Description
Mechanisms exist to ensure Artificial Intelligence (AI) and Autonomous Technologies (AAT) are designed and developed to:
(1) Achieve an appropriate level of accuracy, robustness and cybersecurity;
(2) Perform consistently in those respects throughout the AAT system's lifecycle; and
(3) Be effectively overseen by competent individuals.
Possible Solutions & Considerations
Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2
∙ Document accuracy and robustness requirements before adopting AI
Small Business (10-49 staff) / BLS Firm Size Classes 3-4
∙ AI design requirements checklist covering accuracy, robustness, cybersecurity
Medium Business (50-249 staff) / BLS Firm Size Classes 5-6
∙ Formal AI development standards
∙ Security-by-design requirements for AI
Large Business (250-999 staff) / BLS Firm Size Classes 7-8
∙ AI development security standards
∙ Formal SDLC integration
∙ Security testing requirements
Enterprise (> 1,000 staff) / BLS Firm Size Class 9
∙ Enterprise AI development framework
∙ AI security standards (NIST AI RMF, ISO 42001)
∙ DevSecOps integration for AI
SCR-CMM
Level 0 Not Performed
Practices are non-existent, based on the inability to demonstrate an implemented and operational capability. A reasonable person would conclude the control is not being performed.
Level 1 Performed Informally
Artificial Intelligence and Autonomous Technology (AAT) domain capabilities are ad hoc and inconsistent. Capability criteria associated with this control may include:
▪ Policies, standards & procedures associated with AAT domain capabilities provide limited coverage due to the depth and breadth of the existing documentation.
▪ AAT-related processes are expected to follow the organization's existing processes (e.g., incident response, asset management, change control and risk assessments).
▪ No formal Governance, Risk & Compliance (GRC) team exists to provide AAT oversight, where the Chief Information Officer (CIO), or similar function, governs technology decisions what is acceptable for AAT within the organization.
Level 2 Planned Tracked
Artificial Intelligence and Autonomous Technology (AAT) capabilities are requirements-driven, but are not standardized across the entity (e.g., local/regional level consistency). Capability criteria associated with this control reasonably expect the following criteria to exist:
▪ Policies and standards associated with AAT domain capabilities are formally documented and centrally-managed by the entity.
▪ Standardized Operating Procedures (SOP) associated with AAT domain capabilities are documented and maintained by process owners.
▪ IT and/or cybersecurity personnel work with business stakeholders and process owners to appropriately scope and reasonably implement cybersecurity and data protection controls associated with AAT domain capabilities to address applicable statutory, regulatory and/or contractual requirements for Technology Assets, Applications, Services and/or Data (TAASD).
▪ Artificial Intelligence (AI)-related controls are primarily administrative and preventative in nature (e.g., policies, standards and procedures & guidelines).
▪ Asset management may be a defined function (e.g., team or department) or assigned as an additional duty to existing IT and/or cybersecurity personnel.
▪ AAT is regarded as a technology and governed by the entity's existing IT governance practices.
▪ No formal Governance, Risk & Compliance (GRC) team exists to provide oversight of AAT-related activities. GRC functions are assigned to existing IT and/or cybersecurity personnel.
Level 3 Well Defined
Artificial Intelligence and Autonomous Technology (AAT) capabilities are standardized across the entity for applicability to People, Processes, Technologies, Data and/or Facilities (PPTDF) to ensure consistency for Technology Assets, Applications, Services and/or Data (TAASD). Capability criteria associated with this control reasonably expect the following criteria to exist:
▪ Policies and standards associated with AAT domain capabilities are formally documented and centrally-managed by the entity's Governance, Risk & Compliance (GRC) team, or similar function.
▪ Standardized Operating Procedures (SOP) associated with AAT domain capabilities are well-documented and kept current by process owners.
▪ An Artificial Intelligence Governance (AIG) team, or similar function, is appropriately staffed and supported to implement and maintain AAT domain capabilities.
▪ Technology is leveraged to enhance the efficiency and accuracy of AI governance, risk management and compliance operations (e.g., dedicated AI governance platform).
▪ The entity's Governance, Risk & Compliance (GRC) team, or similar function, works with business stakeholders and process owners to appropriately scope and reasonably implement cybersecurity and data protection controls associated with AAT domain capabilities to address Minimum Compliance Requirements (MCR) (e.g., applicable statutory, regulatory and/or contractual requirements) and Discretionary Security Requirements (DSR) (e.g., entity-required controls).
▪ Measures exist to ensure AAT are designed and developed to:
(1) Achieve an appropriate level of accuracy, robustness and cybersecurity;
(2) Perform consistently in those respects throughout the AAT system's lifecycle; and
(3) Be effectively overseen by competent individuals.
Level 4 Quantitatively Controlled
Artificial Intelligence and Autonomous Technology (AAT) capabilities, in addition to being standardized across the entity and centrally managed to ensure consistency across Technology Assets, Applications, Services and/or Data (TAASD), efforts are metrics driven to provide sufficient insight for decision makers to predict optimal performance, ensure continued operations and/or identify areas for improvement. Capability criteria associated with this control reasonably expect the following criteria to exist:
▪ Applicable SCR-CMM Level 3 (Well Defined) capabilities are implemented and operational.
▪ Metrics reporting includes quantitative analysis of Key Performance Indicators (KPIs).
▪ Metrics reporting includes quantitative analysis of Key Risk Indicators (KRIs).
▪ Scope of metrics, KPIs and KRIs covers organization-wide cybersecurity and data protection controls, including functions performed by third-parties.
▪ Organizational leadership maintains a formal process to objectively review and respond to metrics, KPIs and KRIs (e.g., monthly or quarterly review).
▪ Based on metrics analysis, process improvement recommendations are submitted for review and are handled in accordance with change control processes.
▪ Business and technical stakeholders are involved in reviewing and approving proposed changes to evolve capabilities.
Level 5 Continuously Improving
Artificial Intelligence and Autonomous Technology (AAT) capabilities are "world class" efforts the leverage predictive analysis (e.g., machine learning and AI) to enable continuously improving capabilities. Capability criteria associated with this control reasonably expect the following criteria to exist:
▪ Applicable SCR-CMM Level 3 (Well Defined) capabilities are implemented and operational.
▪ Based on predictive analysis, process improvements are implemented according to “continuous improvement” practices that affect process changes.
▪ Stakeholders make time-sensitive decisions to support operational efficiency, which may include automated remediation actions via Artificial Intelligence (AI) or Machine Learning (ML) technologies.
1. Vue d’ensemble
| Intitulé |
Norme |
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AI & Autonomous Technologies Transparency
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Description
Mechanisms exist to ensure Artificial Intelligence (AI) and Autonomous Technologies (AAT) are designed and developed so its operation is sufficiently transparent such that output can be easily interpreted by personnel implementing the AAT.
Possible Solutions & Considerations
Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2
∙ Document how AI decisions are made for key tools
Small Business (10-49 staff) / BLS Firm Size Classes 3-4
∙ Transparency requirements in AI tool selection
∙ Basic explainability documentation
Medium Business (50-249 staff) / BLS Firm Size Classes 5-6
∙ AI explainability policy
∙ Require documentation of AI decision logic
Large Business (250-999 staff) / BLS Firm Size Classes 7-8
∙ AI transparency program
∙ Explainability requirements in AI development standards
Enterprise (> 1,000 staff) / BLS Firm Size Class 9
∙ Enterprise AI explainability framework
∙ XAI tools (e.g., SHAP, LIME)
∙ Model documentation standards
SCR-CMM
Level 0 Not Performed
Practices are non-existent, based on the inability to demonstrate an implemented and operational capability. A reasonable person would conclude the control is not being performed.
Level 1 Performed Informally
Artificial Intelligence and Autonomous Technology (AAT) domain capabilities are ad hoc and inconsistent. Capability criteria associated with this control may include:
▪ Policies, standards & procedures associated with AAT domain capabilities provide limited coverage due to the depth and breadth of the existing documentation.
▪ AAT-related processes are expected to follow the organization's existing processes (e.g., incident response, asset management, change control and risk assessments).
▪ No formal Governance, Risk & Compliance (GRC) team exists to provide AAT oversight, where the Chief Information Officer (CIO), or similar function, governs technology decisions what is acceptable for AAT within the organization.
Level 2 Planned Tracked
Artificial Intelligence and Autonomous Technology (AAT) capabilities are requirements-driven, but are not standardized across the entity (e.g., local/regional level consistency). Capability criteria associated with this control reasonably expect the following criteria to exist:
▪ Policies and standards associated with AAT domain capabilities are formally documented and centrally-managed by the entity.
▪ Standardized Operating Procedures (SOP) associated with AAT domain capabilities are documented and maintained by process owners.
▪ IT and/or cybersecurity personnel work with business stakeholders and process owners to appropriately scope and reasonably implement cybersecurity and data protection controls associated with AAT domain capabilities to address applicable statutory, regulatory and/or contractual requirements for Technology Assets, Applications, Services and/or Data (TAASD).
▪ Artificial Intelligence (AI)-related controls are primarily administrative and preventative in nature (e.g., policies, standards and procedures & guidelines).
▪ Asset management may be a defined function (e.g., team or department) or assigned as an additional duty to existing IT and/or cybersecurity personnel.
Level 3 Well Defined
Artificial Intelligence and Autonomous Technology (AAT) capabilities are standardized across the entity for applicability to People, Processes, Technologies, Data and/or Facilities (PPTDF) to ensure consistency for Technology Assets, Applications, Services and/or Data (TAASD). Capability criteria associated with this control reasonably expect the following criteria to exist:
▪ Policies and standards associated with AAT domain capabilities are formally documented and centrally-managed by the entity's Governance, Risk & Compliance (GRC) team, or similar function.
▪ Standardized Operating Procedures (SOP) associated with AAT domain capabilities are well-documented and kept current by process owners.
▪ An Artificial Intelligence Governance (AIG) team, or similar function, is appropriately staffed and supported to implement and maintain AAT domain capabilities.
▪ Technology is leveraged to enhance the efficiency and accuracy of AI governance, risk management and compliance operations (e.g., dedicated AI governance platform).
▪ The entity's Governance, Risk & Compliance (GRC) team, or similar function, works with business stakeholders and process owners to appropriately scope and reasonably implement cybersecurity and data protection controls associated with AAT domain capabilities to address Minimum Compliance Requirements (MCR) (e.g., applicable statutory, regulatory and/or contractual requirements) and Discretionary Security Requirements (DSR) (e.g., entity-required controls).
▪ An implemented and operational capability exists to ensure AAT are designed and developed so its operation is sufficiently transparent such that output can be easily interpreted by personnel implementing the AAT.
Level 4 Quantitatively Controlled
Utilize SCR-CMM Level 3 criteria definitions:
▪ There are no defined Level 4 criteria, since it is reasonable to assume a quantitatively-controlled process is not necessary to operationalize this control.
▪ While it may be possible to develop “metrics-driven” capabilities for this control, the criteria would be organization-specific to define.
Level 5 Continuously Improving
Utilize SCR-CMM Level 3 or Level 4 (if available) criteria definitions:
▪ There are no defined Level 5 criteria, since it is reasonable to assume a continuously-improving process is not necessary to operationalize this control.
▪ Level 5 capabilities should be considered “world-class” where the control builds on Level 4 capabilities, but are continuously improving through Artificial Intelligence (AI) and/or Machine Learning (ML) technologies.
▪ While it may be possible to develop responsive capabilities for this control through the use of AI and/or ML technologies, the criteria would be organization-specific to define.
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AI & Autonomous Technologies Implementation Documentation
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Description
Mechanisms exist to ensure Artificial Intelligence (AI) and Autonomous Technologies (AAT) include clear and concise documentation that is relevant, accessible and comprehensible to personnel implementing and maintaining the AAT that, at a minimum, provides:
(1) Contact details of the provider;
(2) Characteristics, capabilities and limitations of performance of the AAT;
(3) Errata from the AAT's initial conformity assessment;
(4) Details necessary to interpret the outputs of the AAT;
(5) Human oversight measures necessary to facilitate the interpretation of the outputs of the AAT;
(6) Computational and hardware resources needed to operate the AAT;
(7) Projected useable lifetime of the AAT; and
(8) A description of the mechanisms included within the AAT system to properly collect, store and interpret event logs.
Possible Solutions & Considerations
Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2
∙ Document AI implementation steps and configuration
Small Business (10-49 staff) / BLS Firm Size Classes 3-4
∙ AI implementation documentation template
Medium Business (50-249 staff) / BLS Firm Size Classes 5-6
∙ Formal AI implementation documentation policy
∙ Technical documentation requirements
Large Business (250-999 staff) / BLS Firm Size Classes 7-8
∙ AI documentation program
∙ Standardized implementation documentation templates
Enterprise (> 1,000 staff) / BLS Firm Size Class 9
∙ Enterprise AI documentation platform
∙ Automated documentation generation from MLOps tools
∙ Model cards and system cards
SCR-CMM
Level 0 Not Performed
Practices are non-existent, based on the inability to demonstrate an implemented and operational capability. A reasonable person would conclude the control is not being performed.
Level 1 Performed Informally
Artificial Intelligence and Autonomous Technology (AAT) domain capabilities are ad hoc and inconsistent. Capability criteria associated with this control may include:
▪ Policies, standards & procedures associated with AAT domain capabilities provide limited coverage due to the depth and breadth of the existing documentation.
▪ AAT-related processes are expected to follow the organization's existing processes (e.g., incident response, asset management, change control and risk assessments).
▪ No formal Governance, Risk & Compliance (GRC) team exists to provide AAT oversight, where the Chief Information Officer (CIO), or similar function, governs technology decisions what is acceptable for AAT within the organization.
Level 2 Planned Tracked
Artificial Intelligence and Autonomous Technology (AAT) capabilities are requirements-driven, but are not standardized across the entity (e.g., local/regional level consistency). Capability criteria associated with this control reasonably expect the following criteria to exist:
▪ Policies and standards associated with AAT domain capabilities are formally documented and centrally-managed by the entity.
▪ Standardized Operating Procedures (SOP) associated with AAT domain capabilities are documented and maintained by process owners.
▪ IT and/or cybersecurity personnel work with business stakeholders and process owners to appropriately scope and reasonably implement cybersecurity and data protection controls associated with AAT domain capabilities to address applicable statutory, regulatory and/or contractual requirements for Technology Assets, Applications, Services and/or Data (TAASD).
▪ Artificial Intelligence (AI)-related controls are primarily administrative and preventative in nature (e.g., policies, standards and procedures & guidelines).
▪ Asset management may be a defined function (e.g., team or department) or assigned as an additional duty to existing IT and/or cybersecurity personnel.
Level 3 Well Defined
Artificial Intelligence and Autonomous Technology (AAT) capabilities are standardized across the entity for applicability to People, Processes, Technologies, Data and/or Facilities (PPTDF) to ensure consistency for Technology Assets, Applications, Services and/or Data (TAASD). Capability criteria associated with this control reasonably expect the following criteria to exist:
▪ Policies and standards associated with AAT domain capabilities are formally documented and centrally-managed by the entity's Governance, Risk & Compliance (GRC) team, or similar function.
▪ Standardized Operating Procedures (SOP) associated with AAT domain capabilities are well-documented and kept current by process owners.
▪ An Artificial Intelligence Governance (AIG) team, or similar function, is appropriately staffed and supported to implement and maintain AAT domain capabilities.
▪ Technology is leveraged to enhance the efficiency and accuracy of AI governance, risk management and compliance operations (e.g., dedicated AI governance platform).
▪ The entity's Governance, Risk & Compliance (GRC) team, or similar function, works with business stakeholders and process owners to appropriately scope and reasonably implement cybersecurity and data protection controls associated with AAT domain capabilities to address Minimum Compliance Requirements (MCR) (e.g., applicable statutory, regulatory and/or contractual requirements) and Discretionary Security Requirements (DSR) (e.g., entity-required controls).
▪ An implemented and operational capability exists to ensure AAT include clear and concise documentation that is relevant, accessible and comprehensible to personnel implementing and maintaining the AAT that, at a minimum, provides:
(1) Contact details of the provider;
(2) Characteristics, capabilities and limitations of performance of the AAT;
(3) Errata from the AAT's initial conformity assessment;
(4) Details necessary to interpret the outputs of the AAT;
(5) Human oversight measures necessary to facilitate the interpretation of the outputs of the AAT;
(6) Computational and hardware resources needed to operate the AAT;
(7) Projected useable lifetime of the AAT; and
(8) A description of the mechanisms included within the AAT system to properly collect, store and interpret event logs.
Level 4 Quantitatively Controlled
Utilize SCR-CMM Level 3 criteria definitions:
▪ There are no defined Level 4 criteria, since it is reasonable to assume a quantitatively-controlled process is not necessary to operationalize this control.
▪ While it may be possible to develop “metrics-driven” capabilities for this control, the criteria would be organization-specific to define.
Level 5 Continuously Improving
Utilize SCR-CMM Level 3 or Level 4 (if available) criteria definitions:
▪ There are no defined Level 5 criteria, since it is reasonable to assume a continuously-improving process is not necessary to operationalize this control.
▪ Level 5 capabilities should be considered “world-class” where the control builds on Level 4 capabilities, but are continuously improving through Artificial Intelligence (AI) and/or Machine Learning (ML) technologies.
▪ While it may be possible to develop responsive capabilities for this control through the use of AI and/or ML technologies, the criteria would be organization-specific to define.
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AI & Autonomous Technologies Human Domain Knowledge Reliance
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Description
Mechanisms exist to document the extent to which human domain knowledge is employed to improve Artificial Intelligence (AI) and Autonomous Technologies (AAT) performance including:
(1) Reinforcement Learning from Human Feedback (RLHF);
(2) Fine-tuning;
(3) Retrieval-augmented generation;
(4) Content moderation; and
(5) Business rules.
Possible Solutions & Considerations
Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2
∙ Document how human expertise is used to improve AI tools
Small Business (10-49 staff) / BLS Firm Size Classes 3-4
∙ Document human feedback mechanisms for AI improvement
Medium Business (50-249 staff) / BLS Firm Size Classes 5-6
∙ Formal policy on human domain knowledge use in AI training
∙ RLHF documentation
Large Business (250-999 staff) / BLS Firm Size Classes 7-8
∙ AI development standards covering human knowledge integration
∙ Documentation requirements
Enterprise (> 1,000 staff) / BLS Firm Size Class 9
∙ Enterprise AI training governance framework
∙ RLHF program documentation
∙ Human feedback loop management
SCR-CMM
Level 0 Not Performed
Practices are non-existent, based on the inability to demonstrate an implemented and operational capability. A reasonable person would conclude the control is not being performed.
Level 1 Performed Informally
SCR-CMM Level 1 criteria definitions are not available for this control:
▪ A reasonable person would conclude this control requires a structured process.
▪ At this level of maturity, the "ad hoc" nature of performing a capability informally would indicate the intent of the control is not met due to a lack of consistency and formality.
Level 2 Planned Tracked
Artificial Intelligence and Autonomous Technology (AAT) capabilities are requirements-driven, but are not standardized across the entity (e.g., local/regional level consistency). Capability criteria associated with this control reasonably expect the following criteria to exist:
▪ Policies and standards associated with AAT domain capabilities are formally documented and centrally-managed by the entity.
▪ Standardized Operating Procedures (SOP) associated with AAT domain capabilities are documented and maintained by process owners.
▪ IT and/or cybersecurity personnel work with business stakeholders and process owners to appropriately scope and reasonably implement cybersecurity and data protection controls associated with AAT domain capabilities to address applicable statutory, regulatory and/or contractual requirements for Technology Assets, Applications, Services and/or Data (TAASD).
▪ Artificial Intelligence (AI)-related controls are primarily administrative and preventative in nature (e.g., policies, standards and procedures & guidelines).
▪ Asset management may be a defined function (e.g., team or department) or assigned as an additional duty to existing IT and/or cybersecurity personnel.
Level 3 Well Defined
Artificial Intelligence and Autonomous Technology (AAT) capabilities are standardized across the entity for applicability to People, Processes, Technologies, Data and/or Facilities (PPTDF) to ensure consistency for Technology Assets, Applications, Services and/or Data (TAASD). Capability criteria associated with this control reasonably expect the following criteria to exist:
▪ Policies and standards associated with AAT domain capabilities are formally documented and centrally-managed by the entity's Governance, Risk & Compliance (GRC) team, or similar function.
▪ Standardized Operating Procedures (SOP) associated with AAT domain capabilities are well-documented and kept current by process owners.
▪ An Artificial Intelligence Governance (AIG) team, or similar function, is appropriately staffed and supported to implement and maintain AAT domain capabilities.
▪ Technology is leveraged to enhance the efficiency and accuracy of AI governance, risk management and compliance operations (e.g., dedicated AI governance platform).
▪ The entity's Governance, Risk & Compliance (GRC) team, or similar function, works with business stakeholders and process owners to appropriately scope and reasonably implement cybersecurity and data protection controls associated with AAT domain capabilities to address Minimum Compliance Requirements (MCR) (e.g., applicable statutory, regulatory and/or contractual requirements) and Discretionary Security Requirements (DSR) (e.g., entity-required controls).
▪ An implemented and operational capability exists to document the extent to which human domain knowledge is employed to improve AAT performance including:
(1) Reinforcement Learning from Human Feedback (RLHF);
(2) Fine-tuning;
(3) Retrieval- augmented generation;
(4) Content moderation; and
(5) Business rules.
Level 4 Quantitatively Controlled
Utilize SCR-CMM Level 3 criteria definitions:
▪ There are no defined Level 4 criteria, since it is reasonable to assume a quantitatively-controlled process is not necessary to operationalize this control.
▪ While it may be possible to develop “metrics-driven” capabilities for this control, the criteria would be organization-specific to define.
Level 5 Continuously Improving
Utilize SCR-CMM Level 3 or Level 4 (if available) criteria definitions:
▪ There are no defined Level 5 criteria, since it is reasonable to assume a continuously-improving process is not necessary to operationalize this control.
▪ Level 5 capabilities should be considered “world-class” where the control builds on Level 4 capabilities, but are continuously improving through Artificial Intelligence (AI) and/or Machine Learning (ML) technologies.
▪ While it may be possible to develop responsive capabilities for this control through the use of AI and/or ML technologies, the criteria would be organization-specific to define.
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1.1 Références
1.2 Exigences identifiées
1.3 Réglementations associées
2. Exigences identifiées
Exigences
| Source |
Exigence |
3. Réglementations associées
Réglementations
| Source |
Réglementation |
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EULAW
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Article 13 Transparence et fourniture d’informations aux déployeurs
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EULAW
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Article 14 Contrôle humain
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EULAW
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Article 14 Contrôle humain
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EULAW
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Article 14 Contrôle humain
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EULAW
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Article 15 Exactitude, robustesse et cybersécurité
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EULAW
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Article 16 Obligations incombant aux fournisseurs de systèmes d’IA à haut risque
Article 16
Obligations incombant aux fournisseurs de systèmes d’IA à haut risque
Les fournisseurs de systèmes d’IA à haut risque:
a)
veillent à ce que leurs systèmes d’IA à haut risque soient conformes aux exigences énoncées à la section 2;
b)
indiquent sur le système d’IA à haut risque ou, lorsque cela n’est pas possible, sur son emballage ou dans la documentation l’accompagnant, selon le cas, leur nom, raison sociale ou marque déposée, l’adresse à laquelle ils peuvent être contactés;
c)
mettent en place un système de gestion de la qualité conforme à l’article 17;
d)
assurent la conservation de la documentation visée à l’article 18;
e)
assurent la tenue des journaux générés automatiquement par leurs systèmes d’IA à haut risque, lorsque ces journaux se trouvent sous leur contrôle, conformément à l’article 19;
f)
veillent à ce que le système d’IA à haut risque soit soumis à la procédure d’évaluation de la conformité applicable visée à l’article 43, avant sa mise sur le marché ou sa mise en service;
g)
élaborent une déclaration UE de conformité conformément à l’article 47;
h)
apposent le marquage CE sur le système d’IA à haut risque ou, lorsque cela n’est pas possible, sur son emballage ou dans la documentation l’accompagnant, selon le cas, afin d’indiquer la conformité avec le présent règlement, conformément à l’article 48;
i)
respectent les obligations en matière d’enregistrement prévues à l’article 49, paragraphe 1;
j)
prennent les mesures correctives nécessaires et fournissent les informations requises à l’article 20;
k)
à la demande motivée d’une autorité nationale compétente, prouvent la conformité du système d’IA à haut risque avec les exigences énoncées à la section 2;
l)
veillent à ce que le système d’IA à haut risque soit conforme aux exigences en matière d’accessibilité conformément aux directives (UE) 2016/2102 et (UE) 2019/882.
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EULAW
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Article 17 Système de gestion de la qualité
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