IEEE 7000
IEEE Standard for addressing ethical concerns during system design
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Framework Domains (21)
Assurance
| Code | Title |
|---|---|
| IEEE7000-EXT | External Review and Assurance |
Concept
| Code | Title |
|---|---|
| IEEE7000-5.1 | Concept Exploration |
Culture
| Code | Title |
|---|---|
| IEEE7000-CULT | Organisational Culture and Training |
Documentation
| Code | Title |
|---|---|
| IEEE7000-DOC | Ethical Process Documentation |
Governance
| Code | Title |
|---|---|
| IEEE7000-GOV | Governance and Roles |
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 | Monitoring in Operation |
| IEEE7000-12 | Decommissioning and Disposal |
| 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 | Validation of Ethical Outcomes |
Integration
| Code | Title |
|---|---|
| IEEE7000-INTEG | Integration with System Engineering |
Lifecycle
| Code | Title |
|---|---|
| IEEE7000-12 | Decommissioning and Disposal |
Measurement
| Code | Title |
|---|---|
| IEEE7000-MEAS | Measurement and Improvement |
Operations
| Code | Title |
|---|---|
| IEEE7000-11 | Monitoring in Operation |
Requirements
| Code | Title |
|---|---|
| IEEE7000-7 | Ethical Requirements Definition |
Risk
| Code | Title |
|---|---|
| IEEE7000-8 | Ethical Risk Identification |
| IEEE7000-8.1 | Ethical Risk Analysis |
| IEEE7000-8.2 | Ethical Risk Treatment |
Stakeholders
| Code | Title |
|---|---|
| IEEE7000-5.2 | Stakeholder Identification |
| IEEE7000-5.3 | Stakeholder Engagement |
Traceability
| Code | Title |
|---|---|
| IEEE7000-7.1 | Value-Based Requirements Traceability |
Transparency
| Code | Title |
|---|---|
| IEEE7000-9 | Transparency and Communication |
Validation
| Code | Title |
|---|---|
| IEEE7000-10 | Validation of Ethical Outcomes |
Values
| Code | Title |
|---|---|
| IEEE7000-6 | Ethical Values Elicitation |
| IEEE7000-6.1 | Value Prioritisation |
Your Compliance Coverage
If you comply with IEEE 7000, you already cover:
EU AI Act
31%
13 controls mapped
Compare →Brazil AI Framework
31%
13 controls mapped
Compare →China AI Regulations
31%
13 controls mapped
Compare →+ 591 more: Australia AI Ethics Framework (31%), Singapore AI Governance Framework (31%)
See all 594 mapped frameworks ↓Maps to 594 other frameworks
Frequently Asked Questions
What is IEEE 7000?
IEEE 7000 is a compliance framework from International with 21 domains and 45 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 45 controls organised across 21 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 594 other compliance frameworks. The top mapping partners are EU AI Act (31% coverage), Brazil AI Framework (31% coverage), China AI Regulations (31% 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 45 controls and track your progress.
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