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+AI & Autonomous Technologies Human Domain Knowledge Reliance |
AI & Autonomous Technologies Human Domain Knowledge RelianceDescriptionMechanisms exist to document the extent to which human domain knowledge is employed to improve Artificial Intelligence (AI) and Autonomous Technologies (AAT) performance including:(1) Reinforcement Learning from Human Feedback (RLHF); (2) Fine-tuning; (3) Retrieval- augmented generation; (4) Content moderation; and (5) Business rules. Possible Solutions & ConsiderationsMicro-Small Business (<10 staff) / BLS Firm Size Classes 1-2∙ Document how human expertise is used to improve AI toolsSmall Business (10-49 staff) / BLS Firm Size Classes 3-4∙ Document human feedback mechanisms for AI improvementMedium Business (50-249 staff) / BLS Firm Size Classes 5-6∙ Formal policy on human domain knowledge use in AI training∙ RLHF documentation Large Business (250-999 staff) / BLS Firm Size Classes 7-8∙ AI development standards covering human knowledge integration∙ Documentation requirements Enterprise (> 1,000 staff) / BLS Firm Size Class 9∙ Enterprise AI training governance framework∙ RLHF program documentation ∙ Human feedback loop management SCR-CMMLevel 0 Not PerformedPractices 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 InformallySCR-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 TrackedArtificial 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, 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 DefinedArtificial Intelligence and Autonomous Technology (AAT) capabilities are standardized across the entity for applicability to People, Processes, Technologies, Data and/or Facilities (PPTDF) to ensure consistency for Technology Assets, Applications, Services and/or Data (TAASD). Capability criteria associated with this control reasonably expect the following criteria to exist:▪ Policies and standards associated with AAT domain capabilities are formally documented and centrally-managed by the entity's Governance, Risk & Compliance (GRC) team, or similar function. ▪ Standardized Operating Procedures (SOP) associated with AAT domain capabilities are well-documented and kept current by process owners. ▪ An Artificial Intelligence Governance (AIG) team, or similar function, is appropriately staffed and supported to implement and maintain AAT domain capabilities. ▪ Technology is leveraged to enhance the efficiency and accuracy of AI governance, risk management and compliance operations (e.g., dedicated AI governance platform). ▪ The entity's Governance, Risk & Compliance (GRC) team, or similar function, works with business stakeholders and process owners to appropriately scope and reasonably implement cybersecurity and data protection controls associated with AAT domain capabilities to address Minimum Compliance Requirements (MCR) (e.g., applicable statutory, regulatory and/or contractual requirements) and Discretionary Security Requirements (DSR) (e.g., entity-required controls). ▪ An implemented and operational capability exists to document the extent to which human domain knowledge is employed to improve AAT performance including: (1) Reinforcement Learning from Human Feedback (RLHF); (2) Fine-tuning; (3) Retrieval- augmented generation; (4) Content moderation; and (5) Business rules. Level 4 Quantitatively ControlledUtilize 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 ImprovingUtilize 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. 1. Übersicht
1.1 Referenzen1.2 Identifizierte Anforderungen1.3 Related Regulations2. Identifizierte Anforderungen
3. Related Regulations
Linked Issues
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