+AI & Autonomous Technologies Ongoing Assessments

AI & Autonomous Technologies Ongoing Assessments

Description

Mechanisms exist to conduct regular assessments of Artificial Intelligence (AI) and Autonomous Technologies (AAT) with independent assessors and stakeholders not involved in the development of the AAT.

Possible Solutions & Considerations

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

∙ Information Assurance (IA) Program
∙ Artificial Intelligence (AI) / autonomous technologies governance program

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

∙ Information Assurance (IA) Program
∙ Artificial Intelligence (AI) / autonomous technologies governance program

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

∙ Information Assurance (IA) Program
∙ Artificial Intelligence (AI) / autonomous technologies governance program

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

∙ Information Assurance (IA) Program
∙ Artificial Intelligence (AI) / autonomous technologies governance program

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

∙ Information Assurance (IA) Program
∙ Artificial Intelligence (AI) / autonomous technologies governance program

SCR-CMM

Level 0 Not Performed

Practices are non-existent, based on the inability to demonstrate an implemented and operational capability. A reasonable person would conclude the control is not being performed.

Level 1 Performed Informally

Artificial Intelligence and Autonomous Technology (AAT) domain capabilities are ad hoc and inconsistent. Capability criteria associated with this control may include:
▪ Policies, standards & procedures associated with AAT domain capabilities provide limited coverage due to the depth and breadth of the existing documentation.
▪ AAT-related processes are expected to follow the organization's existing processes (e.g., incident response, asset management, change control, 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 conduct regular assessments of AAT with independent assessors and stakeholders not involved in the development 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.

1. Übersicht

1.1 Referenzen

1.2 Identifizierte Anforderungen

1.3 Related Regulations

2. Identifizierte Anforderungen

Anforderungen

3. Related Regulations

Regulations
EULAW Article 17 Quality management system

Article 17

Quality management system

1.   Providers of high-risk AI systems shall put a quality management system in place that ensures compliance with this Regulation. That system shall be documented in a systematic and orderly manner in the form of written policies, procedures and instructions, and shall include at least the following aspects:

(a)

a strategy for regulatory compliance, including compliance with conformity assessment procedures and procedures for the management of modifications to the high-risk AI system;

(b)

techniques, procedures and systematic actions to be used for the design, design control and design verification of the high-risk AI system;

(c)

techniques, procedures and systematic actions to be used for the development, quality control and quality assurance of the high-risk AI system;

(d)

examination, test and validation procedures to be carried out before, during and after the development of the high-risk AI system, and the frequency with which they have to be carried out;

(e)

technical specifications, including standards, to be applied and, where the relevant harmonised standards are not applied in full or do not cover all of the relevant requirements set out in Section 2, the means to be used to ensure that the high-risk AI system complies with those requirements;

(f)

systems and procedures for data management, including data acquisition, data collection, data analysis, data labelling, data storage, data filtration, data mining, data aggregation, data retention and any other operation regarding the data that is performed before and for the purpose of the placing on the market or the putting into service of high-risk AI systems;

(g)

the risk management system referred to in Article 9;

(h)

the setting-up, implementation and maintenance of a post-market monitoring system, in accordance with Article 72;

(i)

procedures related to the reporting of a serious incident in accordance with Article 73;

(j)

the handling of communication with national competent authorities, other relevant authorities, including those providing or supporting the access to data, notified bodies, other operators, customers or other interested parties;

(k)

systems and procedures for record-keeping of all relevant documentation and information;

(l)

resource management, including security-of-supply related measures;

(m)

an accountability framework setting out the responsibilities of the management and other staff with regard to all the aspects listed in this paragraph.

2.   The implementation of the aspects referred to in paragraph 1 shall be proportionate to the size of the provider’s organisation. Providers shall, in any event, respect the degree of rigour and the level of protection required to ensure the compliance of their high-risk AI systems with this Regulation.

3.   Providers of high-risk AI systems that are subject to obligations regarding quality management systems or an equivalent function under relevant sectoral Union law may include the aspects listed in paragraph 1 as part of the quality management systems pursuant to that law.

4.   For providers that are financial institutions subject to requirements regarding their internal governance, arrangements or processes under Union financial services law, the obligation to put in place a quality management system, with the exception of paragraph 1, points (g), (h) and (i) of this Article, shall be deemed to be fulfilled by complying with the rules on internal governance arrangements or processes pursuant to the relevant Union financial services law. To that end, any harmonised standards referred to in Article 40 shall be taken into account.

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
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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