IEEE 7000
IEEE Standard for addressing ethical concerns during system design
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Framework Domains (5)
IEEE 7000: AI Accountability & Oversight
Human oversight and accountability for AI (IEEE 7000)
| Code | Title |
|---|---|
| IEEE7000-16 | Human oversight mechanisms |
| IEEE7000-17 | Accountability framework for AI systems |
| IEEE7000-18 | AI incident reporting and response |
| IEEE7000-19 | Regulatory compliance for AI |
| IEEE7000-20 | Third-party AI audit requirements |
IEEE 7000: AI Data Governance
Governing data used in AI systems (IEEE 7000)
| Code | Title |
|---|---|
| IEEE7000-11 | Training data quality and governance |
| IEEE7000-12 | Data bias assessment and mitigation |
| IEEE7000-13 | Data provenance and lineage tracking |
| IEEE7000-14 | Privacy protection in AI training data |
| IEEE7000-15 | Data retention for AI models |
IEEE 7000: AI Risk Management
Managing risks associated with AI systems (IEEE 7000)
| Code | Title |
|---|---|
| IEEE7000-01 | AI risk identification and assessment |
| IEEE7000-02 | AI system categorization by risk level |
| IEEE7000-03 | Bias detection and mitigation |
| IEEE7000-04 | AI model validation and testing |
| IEEE7000-05 | Ongoing AI risk monitoring |
IEEE 7000: AI Safety & Security
Ensuring AI system safety and security (IEEE 7000)
| Code | Title |
|---|---|
| IEEE7000-21 | AI system robustness and resilience |
| IEEE7000-22 | Adversarial attack protection |
| IEEE7000-23 | AI model security and integrity |
| IEEE7000-24 | Safe AI deployment procedures |
| IEEE7000-25 | AI system lifecycle management |
IEEE 7000: AI Transparency & Explainability
Ensuring transparency in AI decision-making (IEEE 7000)
| Code | Title |
|---|---|
| IEEE7000-06 | AI system documentation requirements |
| IEEE7000-07 | Algorithmic transparency measures |
| IEEE7000-08 | Explainability requirements for high-risk AI |
| IEEE7000-09 | User notification of AI interactions |
| IEEE7000-10 | Record-keeping for AI decisions |
Maps to 580 other frameworks
Frequently Asked Questions
What is IEEE 7000?
IEEE 7000 is a compliance framework from International with 5 domains and 25 controls. IEEE Standard for addressing ethical concerns during system design It is used by organisations to establish and maintain compliance with industry standards and regulatory requirements.
How many controls does IEEE 7000 have?
IEEE 7000 has 25 controls organised across 5 domains. The largest domains are IEEE 7000: AI Accountability & Oversight (5 controls), IEEE 7000: AI Data Governance (5 controls), IEEE 7000: AI Risk Management (5 controls). Each control defines specific requirements that organisations must implement to achieve compliance.
What frameworks does IEEE 7000 map to?
IEEE 7000 maps to 580 other compliance frameworks. The top mapping partners are Australia AI Ethics Framework (52% coverage), China AI Regulations (52% coverage), EU AI Act (52% coverage). Use our comparison tool to explore control-level mappings between frameworks.
How do I get started with IEEE 7000 compliance?
Start your IEEE 7000 compliance journey by running a self-assessment on our platform to identify your current compliance posture. Our AI advisory can answer specific questions about IEEE 7000 requirements, and cross-framework mapping helps you leverage existing controls from other frameworks you may already comply with. Create a free account to access all 25 controls and track your progress.
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