+AI & Autonomous Technologies Oversight Measures

AI & Autonomous Technologies Oversight Measures

Description

Mechanisms exist to ensure Artificial Intelligence (AI) and Autonomous Technologies (AAT) oversight measures are commensurate with the:
(1) Assessed risk(s);
(2) Level of autonomy; and
(3) Context of use.

Possible Solutions & Considerations

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

∙ Match oversight intensity to AI tool risk level

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

∙ Tiered oversight based on AI risk assessment

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

∙ Formal oversight measures proportionate to AI risk level

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

∙ Risk-tiered AI oversight program
∙ Automated oversight for low-risk AI

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

∙ Enterprise risk-tiered AI oversight framework
∙ Automated monitoring for low-risk
∙ Intensive human review for high-risk

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, risk assessments, etc.).
▪ 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, 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 oversight measures are commensurate with the:
(1) Assessed risk(s);
(2) Level of autonomy; and
(3) Context of 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.

1. Übersicht

1.1 Referenzen

1.2 Identifizierte Anforderungen

1.3 Related Regulations

2. Identifizierte Anforderungen

Anforderungen

3. Related Regulations

Regulations
EULAW Article 14 Human oversight

Article 14

Human oversight

1.   High-risk AI systems shall be designed and developed in such a way, including with appropriate human-machine interface tools, that they can be effectively overseen by natural persons during the period in which they are in use.

2.   Human oversight shall aim to prevent or minimise the risks to health, safety or fundamental rights that may emerge when a high-risk AI system is used in accordance with its intended purpose or under conditions of reasonably foreseeable misuse, in particular where such risks persist despite the application of other requirements set out in this Section.

3.   The oversight measures shall be commensurate with the risks, level of autonomy and context of use of the high-risk AI system, and shall be ensured through either one or both of the following types of measures:

(a)

measures identified and built, when technically feasible, into the high-risk AI system by the provider before it is placed on the market or put into service;

(b)

measures identified by the provider before placing the high-risk AI system on the market or putting it into service and that are appropriate to be implemented by the deployer.

4.   For the purpose of implementing paragraphs 1, 2 and 3, the high-risk AI system shall be provided to the deployer in such a way that natural persons to whom human oversight is assigned are enabled, as appropriate and proportionate:

(a)

to properly understand the relevant capacities and limitations of the high-risk AI system and be able to duly monitor its operation, including in view of detecting and addressing anomalies, dysfunctions and unexpected performance;

(b)

to remain aware of the possible tendency of automatically relying or over-relying on the output produced by a high-risk AI system (automation bias), in particular for high-risk AI systems used to provide information or recommendations for decisions to be taken by natural persons;

(c)

to correctly interpret the high-risk AI system’s output, taking into account, for example, the interpretation tools and methods available;

(d)

to decide, in any particular situation, not to use the high-risk AI system or to otherwise disregard, override or reverse the output of the high-risk AI system;

(e)

to intervene in the operation of the high-risk AI system or interrupt the system through a ‘stop’ button or a similar procedure that allows the system to come to a halt in a safe state.

5.   For high-risk AI systems referred to in point 1(a) of Annex III, the measures referred to in paragraph 3 of this Article shall be such as to ensure that, in addition, no action or decision is taken by the deployer on the basis of the identification resulting from the system unless that identification has been separately verified and confirmed by at least two natural persons with the necessary competence, training and authority.

The requirement for a separate verification by at least two natural persons shall not apply to high-risk AI systems used for the purposes of law enforcement, migration, border control or asylum, where Union or national law considers the application of this requirement to be disproportionate.

Linked Issues

Issuelinks
is related to Annual
is related to relative Control Weighting = 09
is related to Process
is related to Protect
is related to SCRM Focus Tier 2 OPERATIONAL
is related to SCRM Focus Tier 3 TACTICAL
blocks Inability to maintain individual accountability
blocks Improper assignment of privileged functions
blocks Privilege escalation
blocks Unauthorized access
blocks Lost, damaged or stolen asset(s)
blocks Loss of integrity through unauthorized changes
blocks Business interruption
blocks Data loss / corruption
blocks Reduction in productivity
blocks Information loss / corruption or system compromise due to technical attack
blocks Information loss / corruption or system compromise due to non‐technical attack
blocks Loss of revenue
blocks Cancelled contract
blocks Diminished competitive advantage
blocks Diminished reputation
blocks Fines and judgements
blocks Unmitigated vulnerabilities
blocks System compromise
blocks Inability to support business processes
blocks Incorrect controls scoping
blocks Lack of roles & responsibilities
blocks Inadequate internal practices
blocks Inadequate third-party practices
blocks Lack of oversight of internal controls
blocks Lack of oversight of third-party controls
blocks Illegal content or abusive action
blocks Inability to investigate / prosecute incidents
blocks Improper response to incidents
blocks Ineffective remediation actions
blocks Expense associated with managing a loss event
blocks Inability to maintain situational awareness
blocks Third-party cybersecurity exposure
blocks Third-party physical security exposure
blocks Third-party supply chain relationships, visibility and controls
blocks Third-party compliance / legal exposure
blocks Use of product / service
blocks Reliance on the third-party
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