+AI & Autonomous Technologies Transparency
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AI & Autonomous Technologies Transparency
Description
Mechanisms exist to ensure Artificial Intelligence (AI) and Autonomous Technologies (AAT) are designed and developed so its operation is sufficiently transparent such that output can be easily interpreted by personnel implementing the AAT.
Possible Solutions & Considerations
Micro-Small Business (<10 staff) / BLS Firm Size Classes 1-2
∙ Document how AI decisions are made for key tools
Small Business (10-49 staff) / BLS Firm Size Classes 3-4
∙ Transparency requirements in AI tool selection
∙ Basic explainability documentation
Medium Business (50-249 staff) / BLS Firm Size Classes 5-6
∙ AI explainability policy
∙ Require documentation of AI decision logic
Large Business (250-999 staff) / BLS Firm Size Classes 7-8
∙ AI transparency program
∙ Explainability requirements in AI development standards
Enterprise (> 1,000 staff) / BLS Firm Size Class 9
∙ Enterprise AI explainability framework
∙ XAI tools (e.g., SHAP, LIME)
∙ Model documentation standards
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 are designed and developed so its operation is sufficiently transparent such that output can be easily interpreted by personnel implementing 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. Overview
1.1 References
1.2 Identified Requirements
1.3 Related Regulations
2. Identified Requirements
Requirements
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Requirement |
3. Related Regulations
Regulations
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Regulation |
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EULAW
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Article 13 Transparency and provision of information to deployers
Article 13
Transparency and provision of information to deployers
1. High-risk AI systems shall be designed and developed in such a way as to ensure that their operation is sufficiently transparent to enable deployers to interpret a system’s output and use it appropriately. An appropriate type and degree of transparency shall be ensured with a view to achieving compliance with the relevant obligations of the provider and deployer set out in Section 3.
2. High-risk AI systems shall be accompanied by instructions for use in an appropriate digital format or otherwise that include concise, complete, correct and clear information that is relevant, accessible and comprehensible to deployers.
3. The instructions for use shall contain at least the following information:
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(a)
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the identity and the contact details of the provider and, where applicable, of its authorised representative;
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(b)
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the characteristics, capabilities and limitations of performance of the high-risk AI system, including:
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(i)
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its intended purpose;
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(ii)
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the level of accuracy, including its metrics, robustness and cybersecurity referred to in Article 15 against which the high-risk AI system has been tested and validated and which can be expected, and any known and foreseeable circumstances that may have an impact on that expected level of accuracy, robustness and cybersecurity;
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(iii)
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any known or foreseeable circumstance, related to the use of the high-risk AI system in accordance with its intended purpose or under conditions of reasonably foreseeable misuse, which may lead to risks to the health and safety or fundamental rights referred to in Article 9(2);
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(iv)
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where applicable, the technical capabilities and characteristics of the high-risk AI system to provide information that is relevant to explain its output;
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(v)
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when appropriate, its performance regarding specific persons or groups of persons on which the system is intended to be used;
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(vi)
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when appropriate, specifications for the input data, or any other relevant information in terms of the training, validation and testing data sets used, taking into account the intended purpose of the high-risk AI system;
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(vii)
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where applicable, information to enable deployers to interpret the output of the high-risk AI system and use it appropriately;
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(c)
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the changes to the high-risk AI system and its performance which have been pre-determined by the provider at the moment of the initial conformity assessment, if any;
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(d)
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the human oversight measures referred to in Article 14, including the technical measures put in place to facilitate the interpretation of the outputs of the high-risk AI systems by the deployers;
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(e)
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the computational and hardware resources needed, the expected lifetime of the high-risk AI system and any necessary maintenance and care measures, including their frequency, to ensure the proper functioning of that AI system, including as regards software updates;
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(f)
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where relevant, a description of the mechanisms included within the high-risk AI system that allows deployers to properly collect, store and interpret the logs in accordance with Article 12.
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EULAW
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Article 14 Human oversight
Article 14
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:
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(a)
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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;
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(b)
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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.
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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:
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(a)
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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;
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(b)
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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;
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(c)
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to correctly interpret the high-risk AI system’s output, taking into account, for example, the interpretation tools and methods available;
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(d)
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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;
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(e)
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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.
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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.
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Linked Issues
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