+Article 20 Mesures corrective et devoir d’information
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Article 20 Mesures corrective et devoir d’information

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1. Vue d’ensemble

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Article 20 1.
Les fournisseurs de systèmes d’IA à haut risque qui considèrent ou ont des raisons de considérer qu’un système d’IA à haut risque qu’ils ont mis sur le marché ou mis en service n’est pas conforme au présent règlement prennent immédiatement les mesures correctives nécessaires pour le mettre en conformité, le retirer, le désactiver ou le rappeler, selon le cas. Ils informent les distributeurs du système d’IA à haut risque concerné et, le cas échéant, les déployeurs, le mandataire et les importateurs en conséquence.
Article 20 2.
Lorsque le système d’IA à haut risque présente un risque au sens de l’article 79, paragraphe 1, et que le fournisseur prend conscience de ce risque, celui-ci recherche immédiatement les causes, en collaboration avec le déployeur à l’origine du signalement, le cas échéant, et informe les autorités de surveillance du marché compétentes pour le système d’IA à haut risque concerné et, le cas échéant, l’organisme notifié qui a délivré un certificat pour ce système d’IA à haut risque, conformément à l’article 44, en précisant en particulier la nature du cas de non-conformité et les éventuelles mesures correctives pertinentes prises.

1.1 Références

1.2 Exigences identifiées

1.3 Normes associées

2. Exigences identifiées

Exigences

3. Normes associées

Normes
SCF AI & Autonomous Technologies Risk Response

Description

Mechanisms exist to prioritize, respond to and remediate Artificial Intelligence (AI) and Autonomous Technologies (AAT)-related risks based on assessments and other analytical output.

Possible Solutions & Considerations

Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2

∙ Incident Response Plan (IRP)
∙ Artificial Intelligence (AI) / autonomous technologies governance program

Small Business (10-49 staff) / BLS Firm Size Classes 3-4

∙ Incident Response Plan (IRP)
∙ Artificial Intelligence (AI) / autonomous technologies governance program

Medium Business (50-249 staff) / BLS Firm Size Classes 5-6

∙ Integrated Security Incident Response Team (ISIRT)
∙ Legal review
∙ Steering committee
∙ Artificial Intelligence (AI) / autonomous technologies governance program

Large Business (250-999 staff) / BLS Firm Size Classes 7-8

∙ Integrated Security Incident Response Team (ISIRT)
∙ Legal review
∙ Steering committee
∙ Artificial Intelligence (AI) / autonomous technologies governance program

Enterprise (> 1,000 staff) / BLS Firm Size Class 9

∙ Integrated Security Incident Response Team (ISIRT)
∙ Legal review
∙ Steering committee
∙ Artificial Intelligence (AI) / autonomous technologies governance program

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 prioritize, respond to and remediate AAT-related risks based on assessments and other analytical output.

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.
SCF AI & Autonomous Technologies Risk Tracking Approaches

Description

Mechanisms exist to track Artificial Intelligence (AI) and Autonomous Technologies (AAT)-related risks that are difficult to assess using currently available measurement techniques or where metrics are not yet available.

Possible Solutions & Considerations

Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2

∙ Project team review
∙ Artificial Intelligence (AI) / autonomous technologies governance program

Small Business (10-49 staff) / BLS Firm Size Classes 3-4

∙ Project team review
∙ Artificial Intelligence (AI) / autonomous technologies governance program

Medium Business (50-249 staff) / BLS Firm Size Classes 5-6

∙ Project team review
∙ Legal review
∙ Steering committee
∙ Artificial Intelligence (AI) / autonomous technologies governance program

Large Business (250-999 staff) / BLS Firm Size Classes 7-8

∙ Legal review
∙ Steering committee
∙ Board of Directors (BoD)
∙ Artificial Intelligence (AI) / autonomous technologies governance program

Enterprise (> 1,000 staff) / BLS Firm Size Class 9

∙ Legal review
∙ Steering committee
∙ Board of Directors (BoD)
∙ Artificial Intelligence (AI) / autonomous technologies governance program

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).
▪ An implemented and operational capability exists to track AAT-related risks are difficult to assess using currently available measurement techniques or where metrics are not yet available.

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.
SCF Previously Unknown AI & Autonomous Technologies Threats & Risks

Description

Mechanisms exist to respond to and recover from a previously unknown Artificial Intelligence (AI) and Autonomous Technologies (AAT)-related risk when it is identified.

Possible Solutions & Considerations

Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2

∙ Artificial Intelligence (AI) / autonomous technologies governance program

Small Business (10-49 staff) / BLS Firm Size Classes 3-4

∙ Artificial Intelligence (AI) / autonomous technologies governance program

Medium Business (50-249 staff) / BLS Firm Size Classes 5-6

∙ Artificial Intelligence (AI) / autonomous technologies governance program

Large Business (250-999 staff) / BLS Firm Size Classes 7-8

∙ Artificial Intelligence (AI) / autonomous technologies governance program

Enterprise (> 1,000 staff) / BLS Firm Size Class 9

∙ Artificial Intelligence (AI) / autonomous technologies governance program

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 respond to and recover from a previously unknown AAT-related risk when it is identified.

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.
SCF Non-Conformity Oversight

Description

Mechanisms exist to identify and document instances of non-conformity with statutory, regulatory and/or contractual obligations, in order to develop appropriate risk mitigation actions.

Possible Solutions & Considerations

Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2

∙ GRC solution (e.g., SCFConnect, Cyturus, SureCloud, SimpleRisk, Ignyte, ZenGRC, Galvanize, MetricStream, Archer, etc.)

Small Business (10-49 staff) / BLS Firm Size Classes 3-4

∙ GRC solution (e.g., SCFConnect, Cyturus, SureCloud, SimpleRisk, Ignyte, ZenGRC, Galvanize, MetricStream, Archer, etc.)

Medium Business (50-249 staff) / BLS Firm Size Classes 5-6

∙ GRC solution (e.g., SCFConnect, Cyturus, SureCloud, SimpleRisk, Ignyte, ZenGRC, Galvanize, MetricStream, Archer, etc.)

Large Business (250-999 staff) / BLS Firm Size Classes 7-8

∙ GRC solution (e.g., SCFConnect, Cyturus, SureCloud, SimpleRisk, Ignyte, ZenGRC, Galvanize, MetricStream, Archer, etc.)

Enterprise (> 1,000 staff) / BLS Firm Size Class 9

∙ GRC solution (e.g., SCFConnect, Cyturus, SureCloud, SimpleRisk, Ignyte, ZenGRC, Galvanize, MetricStream, Archer, etc.)

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

Compliance (CPL) 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 CPL domain capabilities are formally documented and centrally-managed by the entity.
▪ Standardized Operating Procedures (SOP) associated with CPL 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 CPL domain capabilities to address applicable statutory, regulatory and/or contractual requirements for Technology Assets, Applications, Services and/or Data (TAASD).
▪ Compliance management controls-related controls are primarily administrative and preventative in nature (e.g., policies, standards and procedures & guidelines).
▪ Compliance management may be a defined function (e.g., team or department) or assigned as an additional duty to existing IT and/or cybersecurity personnel.
▪ External compliance requirements for cybersecurity and data privacy are identified and documented, based on applicable laws, regulations and contractual obligations.
▪ IT and/or cybersecurity perform an informal annual review of existing compliance requirements and research evolving or new requirements.

Level 3 Well Defined

Compliance (CPL) 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 CPL 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 CPL domain capabilities are well-documented and kept current by process owners.
▪ A Governance, Risk & Compliance (GRC) team, or similar function, is appropriately staffed and supported to implement and maintain CPL domain capabilities.
▪ Technology is leveraged to enhance the efficiency and accuracy of governance, risk management and compliance operations (e.g., GRC 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 CPL 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 and review instances of non-compliance with statutory, regulatory and/or contractual obligations to develop appropriate risk mitigation actions.

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.