+50 straipsnis Tam tikrų DI sistemų tiekėjams ir diegėjams taikomos skaidrumo pareigos
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50 straipsnis Tam tikrų DI sistemų tiekėjams ir diegėjams taikomos skaidrumo pareigos
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1. Apžvalga
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Reguliavimas |
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50 straipsnis 1.
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Tiekėjai užtikrina, kad DI sistemos, kurių paskirtis – tiesiogiai sąveikauti su fiziniais asmenimis, būtų suprojektuotos ir sukurtos taip, kad atitinkami fiziniai asmenys būtų informuojami apie tai, kad jie sąveikauja su DI sistema, nebent fiziniam asmeniui, kuris yra pagrįstai informuotas, pastabus ir nuovokus, tai būtų akivaizdu, atsižvelgiant į aplinkybes ir naudojimo kontekstą. Ši pareiga netaikoma DI sistemoms, kurias pagal teisės aktus leidžiama naudoti siekiant nustatyti nusikalstamas veikas, užkirsti joms kelią, jas tirti ir už jas patraukti baudžiamojon atsakomybėn, taikant atitinkamas trečiųjų šalių teisių ir laisvių apsaugos priemones, nebent tomis sistemomis leidžiama naudotis visuomenei pranešimo apie nusikalstamą veiką tikslais.
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50 straipsnis 2.
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DI sistemų, įskaitant bendrosios paskirties DI sistemas, kuriomis sugeneruojamas sintetinis judamo ar nejudamo vaizdo arba garso ar tekstinis turinys, tiekėjai užtikrina, kad DI sistemos išvediniai būtų pažymėti kompiuterio skaitomu formatu ir kad būtų galima atpažinti, jog jie yra sugeneruoti dirbtinai arba manipuliuojant. Tiekėjai užtikrina, kad jų techniniai sprendimai būtų veiksmingi, sąveikūs, pagrįsti ir patikimi, kiek tai techniškai įmanoma, atsižvelgiant į įvairių rūšių turinio ypatumus ir ribotumus, įgyvendinimo sąnaudas ir visuotinai pripažintus pažangiausius metodus, kurie gali būtų atspindėti atitinkamuose techniniuose standartuose. Ši pareiga netaikoma, jei DI sistemomis atliekama pagalbinė standartinio redagavimo funkcija arba iš esmės nepakeičiami diegėjo pateikti įvesties duomenys ar jų semantika, arba kai tai leidžiama pagal teisės aktus siekiant nustatyti nusikalstamas veikas, užkirsti joms kelią, jas tirti ar už jas patraukti baudžiamojon atsakomybėn.
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50 straipsnis 3.
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Emocijų atpažinimo sistemos arba biometrinio kategorizavimo sistemos diegėjai informuoja fizinius asmenis, kuriems šios sistemos taikomos, apie jų veikimą, o asmens duomenis tvarko laikydamiesi atitinkamai reglamentų (ES) 2016/679 bei (ES) 2018/1725 ir Direktyvos (ES) 2016/680. Ši pareiga netaikoma DI sistemoms, naudojamoms biometriniam kategorizavimui ir emocijų atpažinimui, kurias pagal teisės aktus leidžiama naudoti siekiant nustatyti nusikalstamas veikas, užkirsti joms kelią, jas tirti ir už jas patraukti baudžiamojon atsakomybėn, taikant atitinkamas trečiųjų šalių teisių bei laisvių apsaugos priemones ir laikantis Sąjungos teisės.
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50 straipsnis 4.
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DI sistemos, kuria generuojamas arba atlikus manipuliacijas gaunamas sintetinę sankaitą sudarantis judamo ar nejudamo vaizdo arba garso turinys, diegėjai atskleidžia, kad toks turinys yra sugeneruotas dirbtinai arba manipuliuojant. Ši pareiga netaikoma, kai naudojimas leidžiamas pagal teisės aktus siekiant nustatyti nusikalstamas veikas, užkirsti joms kelią, jas tirti ar už jas patraukti baudžiamojon atsakomybėn. Tais atvejais, kai turinys yra akivaizdžiai meninio, kūrybinio, satyrinio, išgalvoto ar analogiško kūrinio ar programos dalis, šioje dalyje nustatyti skaidrumo reikalavimai apima tik tokio sugeneruoto turinio ar turinio, gauto atlikus manipuliacijas, buvimo fakto atskleidimą tinkamu būdu, kuris netrukdo rodyti kūrinį ar juo mėgautis. DI sistemos, kuria generuojamas arba kuria atlikus manipuliacijas gaunamas tekstas, paskelbiamas siekiant informuoti visuomenę viešojo intereso klausimais, diegėjai atskleidžia, kad tekstas yra sugeneruotas dirbtinai arba manipuliuojant. Ši pareiga netaikoma tais atvejais, kai naudoti leidžiama pagal teisės aktus siekiant nustatyti nusikalstamas veikas, užkirsti joms kelią, jas tirti ar už jas patraukti baudžiamojon atsakomybėn arba kai DI sugeneruotam turiniui buvo taikomas žmogaus atliekamos peržiūros arba redakcinės kontrolės procesas, o fizinis ar juridinis asmuo prisiima redakcinę atsakomybę už turinio paskelbimą.
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50 straipsnis 5.
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1–4 dalyse nurodyta informacija atitinkamiems fiziniams asmenims pateikiama aiškiai ir matomai ne vėliau nei pirmosios sąveikos arba sistemos panaudojimo jų atžvilgiu metu. Informacija turi atitikti taikomus prieinamumo reikalavimus.
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50 straipsnis 6.
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1–4 dalys nedaro poveikio III skyriuje nustatytiems reikalavimams bei pareigoms ir nedaro poveikio kitoms Sąjungos ar nacionalinės teisės aktuose nustatytoms DI sistemų diegėjų skaidrumo pareigoms.
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50 straipsnis 7.
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Komisija skatina ir palengvina praktikos kodeksų rengimą Sąjungos lygmeniu, kad būtų sudarytos palankesnės sąlygos veiksmingai įgyvendinti pareigas, susijusias su turinio, kuris yra sugeneruotas dirbtinai arba manipuliuojant, aptikimu, žymėjimu ir ženklinimu. 56 straipsnio 6 dalies nustatyta tvarka Komisija, kuo labiau atsižvelgdama į Valdybos nuomonę, įvertina, ar tų praktikos kodeksų laikymasis yra tinkamas siekiant užtikrinti, kad būtų laikomasi šio straipsnio 2 ir 4 dalyse nustatytų pareigų. Jei Komisija mano, kad praktikos kodeksas nėra tinkama priemonė, ji gali priimti įgyvendinimo aktą, kuriame būtų išsamiai nustatytos bendros tų pareigų vykdymo taisyklės, laikantis 98 straipsnio 2 dalyje nurodytos nagrinėjimo procedūros.
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1.1 Nuorodos
1.2 Nustatyti reikalavimai
1.3 Susiję standartai
2. Nustatyti reikalavimai
Reikalavimai
| Šaltinis |
Reikalavimas |
3. Susiję standartai
Standartai
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Reikalavimas |
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SCF
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AI & Autonomous Technologies Output Marking
Description
Mechanisms exist to mark output from Artificial Intelligence (AI) and Autonomous Technologies (AAT) in a machine-readable format so it is detectable as artificially generated or manipulated.
Possible Solutions & Considerations
Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2
∙ Label AI-generated content when distributing it
Small Business (10-49 staff) / BLS Firm Size Classes 3-4
∙ Policy requiring labeling of AI-generated content
Medium Business (50-249 staff) / BLS Firm Size Classes 5-6
∙ Formal AI content marking policy
∙ Machine-readable metadata for AI content
Large Business (250-999 staff) / BLS Firm Size Classes 7-8
∙ AI content marking program
∙ Technical implementation of C2PA or similar standards
Enterprise (> 1,000 staff) / BLS Firm Size Class 9
∙ Enterprise AI content marking framework
∙ C2PA standard implementation
∙ Automated content marking in AI pipelines
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 mark output from AAT in a machine-readable format so it is detectable as artificially generated or manipulated.
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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SCF
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AI & Autonomous Technologies Use Notification To Users
Description
Mechanisms exist to ensure Artificial Intelligence (AI) and Autonomous Technologies (AAT) that make decisions, or assist in making decisions, inform the people in a clear manner that they are:
(1) Utilizing an AAT solution; and
(2) Expected to validate the output for relevance and accuracy.
Possible Solutions & Considerations
Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2
∙ Inform users when AI is making or assisting decisions affecting them
Small Business (10-49 staff) / BLS Firm Size Classes 3-4
∙ User notification policy for AI-assisted decisions
Medium Business (50-249 staff) / BLS Firm Size Classes 5-6
∙ Formal user notification policy and procedures for AI decision support
Large Business (250-999 staff) / BLS Firm Size Classes 7-8
∙ AI user transparency program
∙ Automated user notifications for AI decisions
Enterprise (> 1,000 staff) / BLS Firm Size Class 9
∙ Enterprise AI user transparency framework
∙ Automated disclosure mechanisms
∙ Regulatory compliance (EU AI Act, GDPR)
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 that make decisions, or assist in making decisions, inform the people in a clear manner that they are:
(1) Utilizing an AAT solution; and
(2) Expected to validate the output for relevance and accuracy.
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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SCF
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AI & Autonomous Technologies Use Notification To Users
Description
Mechanisms exist to ensure Artificial Intelligence (AI) and Autonomous Technologies (AAT) that make decisions, or assist in making decisions, inform the people in a clear manner that they are:
(1) Utilizing an AAT solution; and
(2) Expected to validate the output for relevance and accuracy.
Possible Solutions & Considerations
Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2
∙ Inform users when AI is making or assisting decisions affecting them
Small Business (10-49 staff) / BLS Firm Size Classes 3-4
∙ User notification policy for AI-assisted decisions
Medium Business (50-249 staff) / BLS Firm Size Classes 5-6
∙ Formal user notification policy and procedures for AI decision support
Large Business (250-999 staff) / BLS Firm Size Classes 7-8
∙ AI user transparency program
∙ Automated user notifications for AI decisions
Enterprise (> 1,000 staff) / BLS Firm Size Class 9
∙ Enterprise AI user transparency framework
∙ Automated disclosure mechanisms
∙ Regulatory compliance (EU AI Act, GDPR)
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 that make decisions, or assist in making decisions, inform the people in a clear manner that they are:
(1) Utilizing an AAT solution; and
(2) Expected to validate the output for relevance and accuracy.
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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SCF
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AI & Autonomous Technologies Use Notification To Users
Description
Mechanisms exist to ensure Artificial Intelligence (AI) and Autonomous Technologies (AAT) that make decisions, or assist in making decisions, inform the people in a clear manner that they are:
(1) Utilizing an AAT solution; and
(2) Expected to validate the output for relevance and accuracy.
Possible Solutions & Considerations
Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2
∙ Inform users when AI is making or assisting decisions affecting them
Small Business (10-49 staff) / BLS Firm Size Classes 3-4
∙ User notification policy for AI-assisted decisions
Medium Business (50-249 staff) / BLS Firm Size Classes 5-6
∙ Formal user notification policy and procedures for AI decision support
Large Business (250-999 staff) / BLS Firm Size Classes 7-8
∙ AI user transparency program
∙ Automated user notifications for AI decisions
Enterprise (> 1,000 staff) / BLS Firm Size Class 9
∙ Enterprise AI user transparency framework
∙ Automated disclosure mechanisms
∙ Regulatory compliance (EU AI Act, GDPR)
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 that make decisions, or assist in making decisions, inform the people in a clear manner that they are:
(1) Utilizing an AAT solution; and
(2) Expected to validate the output for relevance and accuracy.
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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