Safety Critical Labs / Documents

Every standard the
framework builds on.

The SCL AI Requirements Framework is grounded in a defined set of standards, regulations, and reference documents. Each entry below links to the official publisher. No hosted copies. Authoritative sources only.

[ Normative Standards ] 10

Applicable standards cited as normative references in the framework. Definitions, requirements, and verification methods used directly within SCL certification.

ISO/IEC Normative 22989:2022
AI Concepts and Terminology
Source of foundational definitions used throughout the framework's glossary and core AI/ML terms.
ISO/IECView source →
ISO/IEC Normative 5338:2023
AI System Lifecycle Processes
Lifecycle process model the framework's AI integration with software lifecycle is built against.
ISO/IECView source →
NIST Normative AI RMF 1.0
AI Risk Management Framework
Risk taxonomy referenced throughout the framework for AI-specific risk identification and management.
NISTView source →
RTCA Normative DO-178C
Software Considerations in Airborne Systems and Equipment Certification
Aviation software standard that SCL's AI framework sits alongside to address AI failure modes DO-178C does not cover.
RTCAView source →
ISO Normative 26262
Road Vehicles — Functional Safety
Automotive functional safety standard. The framework addresses AI failure modes ASIL decomposition cannot resolve.
ISOView source →
ISO/IEC Normative 27701:2019
Privacy Information Management Extension to ISO/IEC 27001
Source of privacy management controls referenced in AI-10 Privacy and Data Protection.
ISO/IECView source →
ISO/IEC Normative 29100:2011
Privacy Framework
Defines privacy principles and terminology that AI-10 sub-requirements align with.
ISO/IECView source →
NIST Normative Privacy v1.0
NIST Privacy Framework v1.0
Enterprise privacy risk management framework referenced in AI-10's privacy risk taxonomy.
NISTView source →
EU Normative AI Act
Regulation on Artificial Intelligence
EU AI risk tiering regulation. SCL classifications are cross-referenced with Article 6 high-risk categories.
EUView source →
IEEE Normative 1012-2016
System, Software, and Hardware Verification and Validation
Source of the four verification methods (Inspection, Analysis, Demonstration, Test) used in the framework's verification matrix.
IEEEView source →
[ Reference Documents ] 11

Informative references cited throughout the framework. Domain regulations, lifecycle standards, and supporting guidance that inform requirement interpretation.

NASA Reference NPR 7150.2D
NASA Software Engineering Requirements
Software lifecycle reference extended by the framework's AI-specific operations activities.
NASAView source →
NASA Reference STD-8739.8
Software Assurance and Software Safety Standard
Safety analysis reference for traceable, logically inspectable safety cases — one of the gaps AI-8 Explainability addresses.
NASAView source →
ISO/IEC Reference 23053:2022
Framework for AI Systems Using Machine Learning
ML framework concepts including out-of-distribution and overfitting definitions used in AI-3 and AI-6.
ISO/IECView source →
ISO/IEC Reference TR 24027:2021
Bias in AI Systems and AI-Aided Decision Making
Bias assessment guidance and source of the fairness metrics referenced in AI-2 Addressing AI Bias.
ISO/IECView source →
NIST Reference AI 600-1
AI RMF: Generative AI Profile
Source of the framework's hallucination definition (confabulation) and generative AI risk treatment.
NISTView source →
FAA Reference AI Roadmap
FAA Roadmap for AI Safety Assurance
FAA's acknowledged gap in AI certification criteria. The framework provides the precedent the roadmap will reference.
FAAView source →
EU Reference GDPR
EU General Data Protection Regulation
Personal data processing requirements referenced throughout AI-10 Privacy and Data Protection sub-requirements.
EUView source →
HHS Reference HIPAA
HIPAA Privacy and Security Rules
45 CFR 164 Subparts C and E. Protected health information requirements applied to medical AI systems.
US FederalView source →
CA OAG Reference CCPA / CPRA
California Consumer Privacy Act
Cal. Civ. Code §§ 1798.100 et seq. Consumer privacy requirements for AI systems processing California resident data.
US (CA)View source →
NIST Reference SP 800-122
Guide to Protecting the Confidentiality of PII
PII handling guidance referenced in the framework's data minimization and de-identification controls.
NISTView source →
ISO Reference 34503
Road Vehicles — Taxonomy for Operational Design Domain
ODD attribute taxonomy from the automotive domain that informs the framework's domain-agnostic ODD declaration in AI-1.0.
ISOView source →
[ Pending Verification ] 5

Cited inline within the framework but not yet clause-verified against source. Retained as informative cross-references; will be re-verified when source documents become accessible. Not normative dependencies.

RTCA Pending DO-326A
Airworthiness Security Process Specification
Aviation security process reference cited in AI-7 (Adversarial Robustness) aviation rows.
RTCAView source →
RTCA Pending DO-330
Software Tool Qualification Considerations
Tool qualification reference cited in AI-1 (Operational and Data Foundations) aviation row.
RTCAView source →
RTCA Pending DO-355
Information Security Guidance for Continuing Airworthiness
Continuing airworthiness security reference cited in AI-7.6 aviation row.
RTCAView source →
RTCA Pending DO-356A
Airworthiness Security Methods and Considerations
Aviation security methods reference cited in AI-7 (Adversarial Robustness) aviation rows.
RTCAView source →
AAMI Pending HE75
Human Factors Engineering — Design of Medical Devices
Human factors reference cited in AI-9.8 (Workload Management) medical row.
AAMIView source →
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