+26 artikla Suuririskisten tekoälyjärjestelmien käyttöönottajien velvollisuudet
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26 artikla Suuririskisten tekoälyjärjestelmien käyttöönottajien velvollisuudet
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1. Yleiskatsaus
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26 artikla 1.
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Suuririskisten tekoälyjärjestelmien käyttöönottajien on toteutettava asianmukaiset tekniset ja organisatoriset toimenpiteet varmistaakseen, että ne käyttävät tällaisia järjestelmiä niiden mukana seuraavien käyttöohjeiden mukaisesti 3 ja 6 kohdassa säädetyllä tavalla.
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26 artikla 2.
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Käyttöönottajien on annettava ihmisen suorittama valvonta tehtäväksi luonnollisille henkilöille, joilla on tarvittava pätevyys, koulutus ja valtuudet, sekä annettava tarvittavaa tukea.
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26 artikla 3.
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Edellä 1 ja 2 kohdassa säädetyt velvollisuudet eivät rajoita muiden unionin tai kansallisesta lainsäädännöstä johtuvien käyttöönottajien velvollisuuksien soveltamista eivätkä käyttöönottajan vapautta järjestää omat resurssinsa ja toimintansa tarjoajan ilmoittamien ihmisen suorittamien valvontatoimien toteuttamiseksi.
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26 artikla 4.
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Siltä osin kuin käyttöönottaja valvoo syöttötietoja, käyttöönottajan on varmistettava, että syöttötiedot ovat merkityksellisiä ja riittävän edustavia suuririskisen tekoälyjärjestelmän käyttötarkoituksen kannalta, sanotun kuitenkaan rajoittamatta 1 ja 2 kohdan soveltamista.
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26 artikla 5.
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Käyttöönottajien on seurattava suuririskisen tekoälyjärjestelmän toimintaa käyttöohjeiden perusteella ja tarvittaessa ilmoitettava asiasta tarjoajille 72 artiklan mukaisesti. Jos käyttöönottajilla on syytä katsoa, että suuririskisen tekoälyjärjestelmän käyttöohjeiden mukainen käyttö voi johtaa siihen, että kyseinen tekoälyjärjestelmä aiheuttaa 79 artiklan 1 kohdassa tarkoitetun riskin, niiden on ilman aiheetonta viivytystä ilmoitettava asiasta tarjoajalle tai jakelijalle ja asianomaiselle markkinavalvontaviranomaiselle ja keskeytettävä kyseisen järjestelmän käyttö. Jos käyttöönottajat ovat havainneet vakavan vaaratilanteen, niiden on myös välittömästi ilmoitettava kyseisestä vaaratilanteesta ensin tarjoajalle ja sen jälkeen tuojalle tai jakelijalle sekä asianomaisille markkinavalvontaviranomaisille. Jos käyttöönottaja ei pysty tavoittamaan tarjoajaa, 73 artiklaa sovelletaan soveltuvin osin. Tätä velvoitetta ei sovelleta niiden tekoälyjärjestelmien käyttöönottajien arkaluonteiseen operatiiviseen tietoon, jotka ovat lainvalvontaviranomaisia. Niiden käyttöönottajien osalta, jotka ovat rahoituslaitoksia, joihin sovelletaan niiden sisäisiä hallintojärjestelyjä tai -prosesseja koskevia vaatimuksia unionin rahoituspalvelulainsäädännön nojalla, ensimmäisessä alakohdassa esitetty seurantavelvoite katsotaan täytetyksi, kun noudatetaan asiaankuuluvan rahoituspalvelulainsäädännön mukaisia sisäisiä hallintojärjestelyjä, -prosesseja ja -mekanismeja koskevia sääntöjä.
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26 artikla 6.
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Suuririskisten tekoälyjärjestelmien käyttöönottajien on säilytettävä kyseisen suuririskisen tekoälyjärjestelmän automaattisesti tuottamat lokitiedot siltä osin kuin tällaiset lokitiedot ovat heidän hallinnassaan, suuririskisen tekoälyjärjestelmän käyttötarkoitukseen nähden asianmukaisen ajanjakson ajan, kuitenkin vähintään kuuden kuukauden ajan, jollei sovellettavassa unionin tai kansallisessa lainsäädännössä, erityisesti henkilötietojen suojaa koskevassa unionin oikeudessa, toisin säädetä. Käyttöönottajien, jotka ovat rahoituslaitoksia, joihin sovelletaan niiden sisäisiä hallintojärjestelyjä tai -prosesseja koskevia vaatimuksia unionin rahoituspalvelulainsäädännön nojalla, on säilytettävä lokitiedot osana asiakirjoja, jotka säilytetään asiaankuuluvan unionin rahoituspalvelulainsäädännön nojalla.
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26 artikla 7.
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Ennen suuririskisen tekoälyjärjestelmän käyttöönottoa tai käyttöä työpaikalla käyttöönottajien, jotka ovat työnantajia, on ilmoitettava työntekijöiden edustajille ja asianomaisille työntekijöille, että heihin sovelletaan suuririskistä tekoälyjärjestelmää. Nämä tiedot on tarvittaessa annettava työntekijöille ja heidän edustajilleen tiedottamista koskevassa unionin ja kansallisessa lainsäädännössä ja käytännössä vahvistettujen sääntöjen ja menettelyjen mukaisesti.
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26 artikla 8.
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Suuririskisten tekoälyjärjestelmin käyttöönottajien, jotka ovat viranomaisia tai unionin toimielimiä, elimiä tai laitoksia, on noudatettava 49 artiklassa tarkoitettuja rekisteröintivelvollisuuksia. Jos tällaiset käyttöönottajat toteavat, että suuririskistä tekoälyjärjestelmää, jota ne aikovat käyttää, ei ole rekisteröity 71 artiklassa tarkoitettuun EU:n tietokantaan, ne eivät saa käyttää kyseistä järjestelmää ja niiden on ilmoitettava asiasta tarjoajalle tai jakelijalle.
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26 artikla 9.
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Suuririskisten tekoälyjärjestelmien käyttöönottajien on tarvittaessa käytettävä tämän asetuksen 13 artiklan mukaisesti toimitettuja tietoja noudattaakseen velvollisuuttaan tehdä tietosuojaa koskeva vaikutustenarviointi asetuksen (EU) 2016/679 35 artiklan tai direktiivin (EU) 2016/680 27 artiklan mukaisesti.
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26 artikla 10.
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Rikoksesta epäillyn tai tuomitun henkilön kohdennettua etsintää koskevan tutkinnan yhteydessä suuririskisen tekoälyjärjestelmän, joka on tarkoitettu käytettäväksi jälkikäteiseen biometriseen etätunnistukseen, käyttöönottajan on pyydettävä oikeusviranomaiselta tai hallintoviranomaiselta, jonka päätös on sitova ja johon sovelletaan tuomioistuinvalvontaa, lupaa kyseisen järjestelmän käyttöön etukäteen tai ilman aiheetonta viivytystä ja viimeistään 48 tunnin kuluessa kyseisen järjestelmän käyttöön, paitsi jos sitä käytetään mahdollisen epäillyn alustavaan tunnistamiseen rikokseen suoraan liittyvien objektiivisten ja todennettavissa olevien tosiseikkojen perusteella, sanotun kuitenkaan rajoittamatta direktiivin (EU) 2016/680 soveltamista. Kukin käyttö on rajoitettava siihen, mikä on ehdottoman välttämätöntä kyseessä olevan rikoksen tutkintaa varten. Jos ensimmäisen alakohdan nojalla haettu lupa hylätään, kyseiseen lupaan linkitetyn jälkikäteisen biometrisen etätunnistusjärjestelmän käyttö on lopetettava välittömästi ja sen suuririskisen tekoälyjärjestelmän käyttöön liittyvät henkilötiedot, jota varten lupaa haettiin, on poistettava. Tällaista suuririskistä tekoälyjärjestelmää, joka on tarkoitettu käytettäväksi jälkikäteiseen biometriseen etätunnistukseen, ei saa missään tapauksessa käyttää lainvalvontatarkoituksiin kohdentamattomalla tavalla ilman minkäänlaista yhteyttä tiettyyn rikokseen, rikosoikeudelliseen menettelyyn, todelliseen ja välittömään tai todelliseen ja ennakoitavissa olevaan rikoksen uhkaan tai tietyn kadonneen henkilön etsimiseen. On varmistettava, että päätöstä, jolla on yksittäiseen henkilöön kohdistuvia kielteisiä oikeusvaikutuksia, ei saa tehdä pelkästään tällaisen jälkikäteisen biometrisen etätunnistusjärjestelmän tuotosten perusteella. Tämä kohta ei rajoita asetuksen (EU) 2016/679 9 artiklan ja direktiivin (EU) 2016/680 10 artiklan soveltamista biometristen tietojen käsittelyn osalta. Käyttötarkoituksesta tai käyttöönottajasta riippumatta tällaisten suuririskisten tekoälyjärjestelmien kaikenlainen käyttö on dokumentoitava asianomaiseen poliisitiedostoon ja asetettava pyynnöstä asianomaisen markkinavalvontaviranomaisen ja kansallisen tietosuojaviranomaisen saataville, lukuun ottamatta lainvalvontaan liittyvien arkaluonteisten operatiivisten tietojen luovuttamista. Tämä alakohta ei rajoita valvontaviranomaisille direktiivin (EU) 2016/680 nojalla annettuja valtuuksia. Käyttöönottajien on toimitettava asianomaisille markkinavalvonta- ja kansallisille tietosuojaviranomaisille vuosittain raportit jälkikäteisten biometristen etätunnistusjärjestelmien käytöstä, lukuun ottamatta lainvalvontaan liittyvien arkaluonteisten operatiivisten tietojen luovuttamista. Raportit voidaan koota yhteen siten, että ne kattavat useamman kuin yhden käyttökerran. Jäsenvaltiot voivat unionin oikeuden mukaisesti ottaa käyttöön jälkikäteisten biometristen etätunnistusjärjestelmien käyttöä koskevaa rajoittavampaa lainsäädäntöä.
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26 artikla 11.
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Sellaisten liitteessä III tarkoitettujen suuririskisten tekoälyjärjestelmien käyttöönottajien, jotka tekevät tai auttavat tekemään luonnollisiin henkilöihin liittyviä päätöksiä, on ilmoitettava luonnollisille henkilöille, että heihin sovelletaan suuririskistä tekoälyjärjestelmää, sanotun kuitenkaan rajoittamatta tämän asetuksen 50 artiklan soveltamista. Lainvalvontatarkoituksiin käytettäviin suuririskisiin tekoälyjärjestelmiin sovelletaan direktiivin (EU) 2016/680 13 artiklaa.
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26 artikla 12.
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Käyttöönottajien on tehtävä yhteistyötä asiaankuuluvien toimivaltaisten viranomaisten kanssa kaikissa toimissa, joita kyseiset viranomaiset toteuttavat suuririskisen tekoälyjärjestelmän suhteen tämän asetuksen täytäntöönpanemiseksi.
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1.1 Viittaukset
1.2 Tunnistetut vaatimukset
1.3 Liittyvät standardit
2. Tunnistetut vaatimukset
Vaatimukset
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Vaatimus |
3. Liittyvät standardit
Standardit
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Vaatimus |
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SCF
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AI & Autonomous Technologies Deployment
Description
Mechanisms exist to ensure the deployment of Artificial Intelligence (AI) and Autonomous Technologies (AAT) includes appropriate technical and organizational measures so that AAT are used in accordance with the AAT developer-provided instructions.
Possible Solutions & Considerations
Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2
∙ Deploy AI tools only for documented, approved purposes
Small Business (10-49 staff) / BLS Firm Size Classes 3-4
∙ AI deployment approval process ∙ Document intended use and technical measures
Medium Business (50-249 staff) / BLS Firm Size Classes 5-6
∙ Formal AI deployment policy ∙ Technical and organizational measures for AI deployment
Large Business (250-999 staff) / BLS Firm Size Classes 7-8
∙ AI deployment governance program ∙ Formal approval workflows ∙ Post-deployment monitoring
Enterprise (> 1,000 staff) / BLS Firm Size Class 9
∙ Enterprise AI deployment governance framework ∙ Automated deployment controls ∙ Continuous monitoring ∙ Regulatory compliance
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 ensure the deployment of AAT includes appropriate technical and organizational measures so that AAT are used in accordance with the AAT developer-provided instructions for use.
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 Oversight Functions Competency
Description
Mechanisms exist to ensure the deployment of Artificial Intelligence (AI) and Autonomous Technologies (AAT) assigns human oversight to individuals who have the necessary: (1) Competence; (2) Training; (3) Authority; and (4) Resources.
Possible Solutions & Considerations
Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2
∙ Train AI system operators on oversight responsibilities
Small Business (10-49 staff) / BLS Firm Size Classes 3-4
∙ Training program for personnel overseeing AI systems
Medium Business (50-249 staff) / BLS Firm Size Classes 5-6
∙ Formal AI oversight training program ∙ Competency requirements for AI oversight roles
Large Business (250-999 staff) / BLS Firm Size Classes 7-8
∙ AI training and certification program for oversight personnel
Enterprise (> 1,000 staff) / BLS Firm Size Class 9
∙ Enterprise AI training and certification program ∙ Role-based AI competency framework ∙ Continuous learning 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 ensure the deployment of AAT assigns human oversight to individuals who have the necessary: (1) Competence; (2) Training; (3) Authority; and (4) Resources.
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 Data Relevance
Description
Mechanisms exist to ensure the input to Artificial Intelligence (AI) and Autonomous Technologies (AAT) is relevant to the intended purpose of the AAT.
Possible Solutions & Considerations
Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2
∙ Validate that inputs to AI tools are relevant before submitting
Small Business (10-49 staff) / BLS Firm Size Classes 3-4
∙ Policy requiring relevance checking of AI inputs
Medium Business (50-249 staff) / BLS Firm Size Classes 5-6
∙ Formal AI input validation policy ∙ Input relevance criteria documentation
Large Business (250-999 staff) / BLS Firm Size Classes 7-8
∙ Input validation controls for AI systems ∙ Automated input filtering
Enterprise (> 1,000 staff) / BLS Firm Size Class 9
∙ Enterprise AI input governance framework ∙ Automated input validation and filtering ∙ Data quality controls for 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 ensure the input to AAT is relevant to the intended purpose of 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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SCF
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AI & Autonomous Technologies Irregularity Reporting
Description
Mechanisms exist to ensure serious incidents and/or irregularities associated with the deployment of Artificial Intelligence (AI) and Autonomous Technologies (AAT) are reported without delay to the: (1) AAT provider; (2) AAT importer or distributor, if applicable; and/or (3) Local law authorities and/or governmental agency, as required.
Possible Solutions & Considerations
Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2
∙ Report serious AI incidents and irregularities to management
Small Business (10-49 staff) / BLS Firm Size Classes 3-4
∙ Incident reporting procedure for AI irregularities
Medium Business (50-249 staff) / BLS Firm Size Classes 5-6
∙ Formal AI incident and irregularity reporting policy ∙ Regulatory reporting contacts
Large Business (250-999 staff) / BLS Firm Size Classes 7-8
∙ AI incident response program with regulatory reporting integration
Enterprise (> 1,000 staff) / BLS Firm Size Class 9
∙ Enterprise AI incident management platform ∙ Automated regulatory notification ∙ Legal and compliance integration
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 serious incidents and/or irregularities associated with the deployment of AAT are reported without delay to the: (1) AAT provider; (2) AAT importer or distributor, if applicable; and/or (3) Local law authorities and/or governmental agency, as required.
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 Employees
Description
Mechanisms exist to ensure employees, including workers' representatives, are informed about Artificial Intelligence (AI) and Autonomous Technologies (AAT) deployments, prior to the use of the AAT in a production environment.
Possible Solutions & Considerations
Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2
∙ Inform employees of AI tools being used in their work
Small Business (10-49 staff) / BLS Firm Size Classes 3-4
∙ Policy requiring employee notification of AI tools affecting their work
Medium Business (50-249 staff) / BLS Firm Size Classes 5-6
∙ Formal employee notification policy for AI deployments ∙ Communication procedures
Large Business (250-999 staff) / BLS Firm Size Classes 7-8
∙ AI transparency program for employees ∙ Works council/union notification as required
Enterprise (> 1,000 staff) / BLS Firm Size Class 9
∙ Enterprise AI employee transparency framework ∙ Formal notification procedures ∙ Labor law compliance tracking
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 employees, including workers' representatives, are informed about AAT deployments, prior to the use of the AAT in a production environment.
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 Event Logging
Description
Mechanisms exist to ensure Artificial Intelligence (AI) and Autonomous Technologies (AAT) system event logging capabilities at a minimum provide: (1) Start date, start time, end date and end time for each use; (2) Database(s) against which input data has been checked by the system; (3) Input data for which the search has led to a match; and (4) Identification of individual(s) involved in the verification of the results.
Possible Solutions & Considerations
Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2
∙ Enable basic logging on AI/ML systems
Small Business (10-49 staff) / BLS Firm Size Classes 3-4
∙ Configure event logging on AI systems ∙ Define log retention periods
Medium Business (50-249 staff) / BLS Firm Size Classes 5-6
∙ Formal AI event logging policy ∙ Centralized log collection
Large Business (250-999 staff) / BLS Firm Size Classes 7-8
∙ SIEM integration for AI system logs ∙ Defined logging standards for AI platforms
Enterprise (> 1,000 staff) / BLS Firm Size Class 9
∙ Enterprise SIEM platform ∙ Standardized AI event logging schema ∙ Automated alerting for anomalous AI events
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 system event logging capabilities at a minimum provide: (1) Start date, start time, end date and end time for each use; (2) Database(s) against which input data has been checked by the system; (3) Input data for which the search has led to a match; and (4) Identification of individual(s) involved in the verification of the results.
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 Registration
Description
Mechanisms exist to maintain a current registration for Artificial Intelligence (AI) and Autonomous Technologies (AAT) with the appropriate governing body, as required by statutory or regulatory requirements.
Possible Solutions & Considerations
Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2
∙ Determine whether any AI use requires registration (e.g., EU AI Act high-risk systems)
Small Business (10-49 staff) / BLS Firm Size Classes 3-4
∙ Track AI registration obligations by jurisdiction in compliance checklist
Medium Business (50-249 staff) / BLS Firm Size Classes 5-6
∙ Register high-risk AI systems with relevant authorities as required
Large Business (250-999 staff) / BLS Firm Size Classes 7-8
∙ AI registration compliance program ∙ Track registration requirements by jurisdiction
Enterprise (> 1,000 staff) / BLS Firm Size Class 9
∙ Enterprise AI regulatory compliance platform ∙ Automated registration tracking ∙ EU AI Act database registration compliance
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
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 maintain a current registration for AAT with the appropriate governing body, as required by statutory or regulatory requirements.
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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Data Protection Impact Assessment (DPIA)
Description
Mechanisms exist to conduct a Data Protection Impact Assessment (DPIA) on Technology Assets, Applications and/or Services (TAAS) that store, process and/or transmit Personal Data (PD) to identify and remediate reasonably-expected risks.
Possible Solutions & Considerations
Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2
∙ Risk Management Program (RMP) ∙ Data Protection Impact Assessment (DPIA) ∙ Privacy Impact Assessment (PIA)
Small Business (10-49 staff) / BLS Firm Size Classes 3-4
∙ Risk Management Program (RMP) ∙ Data Protection Impact Assessment (DPIA) ∙ Privacy Impact Assessment (PIA)
Medium Business (50-249 staff) / BLS Firm Size Classes 5-6
∙ Risk Management Program (RMP) ∙ Data Protection Impact Assessment (DPIA) ∙ Privacy Impact Assessment (PIA)
Large Business (250-999 staff) / BLS Firm Size Classes 7-8
∙ Risk Management Program (RMP) ∙ Data Protection Impact Assessment (DPIA) ∙ Privacy Impact Assessment (PIA)
Enterprise (> 1,000 staff) / BLS Firm Size Class 9
∙ Risk Management Program (RMP) ∙ Data Protection Impact Assessment (DPIA) ∙ Privacy Impact Assessment (PIA)
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
Risk Management (RSK) 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 RSK domain capabilities are formally documented and centrally-managed by the entity. ▪ Standardized Operating Procedures (SOP) associated with RSK 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 RSK domain capabilities to address applicable statutory, regulatory and/or contractual requirements for Technology Assets, Applications, Services and/or Data (TAASD). ▪ Risk management-related controls are primarily administrative and preventative in nature (e.g., policies, standards and procedures & guidelines). ▪ Risk management may be a defined function (e.g., team or department) or assigned as an additional duty to existing IT and/or cybersecurity personnel. ▪ Risk management processes (e.g., risk assessments) and technologies focus on protecting High Value Assets (HVAs), including environments where sensitive/regulated data is stored, transmitted and processed. ▪ IT and/or cybersecurity personnel implement and maintain a form of Risk Management Program (RMP) that provides operational guidance on how risk is identified, assessed, remediated and reported. ▪ Data/process owners are expected to self-manage risks associated with their systems, applications, services and data, based on the organization's published policies and standards, including the identification, remediation and reporting of risks. ▪ Business process owners (BPOs) are made aware of cybersecurity and data protection risk(s).
Level 3 Well Defined
Risk Management (RSK) 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 RSK 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 RSK domain capabilities are well-documented and kept current by process owners. ▪ A risk management team, or similar function, is appropriately staffed and supported to implement and maintain RSK domain capabilities. ▪ Technology is leveraged to enhance the efficiency and accuracy of risk management operations (e.g., risk management solution, GRC platform and TPRM tool). ▪ 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 RSK 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 conduct a Data Protection Impact Assessment (DPIA) on Technology Assets, Applications and/or Services (TAAS) that store, process and/or transmit Personal Data (PD) to identify and remediate reasonably-expected risks.
Level 4 Quantitatively Controlled
Risk Management (RSK) 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
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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