This checklist provides a practical tool for organizations to assess their implementation progress across the Seven-Layer RAGF Governance Architecture. Each layer is broken down into specific implementation items that can be evaluated on a simple scale.
Instructions: For each item, assess your organization’s current implementation status using the following scale:
✅ Implemented — Fully implemented and operational
⚠️ Partial — Partially implemented or in progress
❌ Not Started — Not yet implemented or not started
N/A — Not applicable to your organization
Layer 1: Righteousness Foundation
Purpose: To establish the fundamental values, principles, and ethical commitments that anchor all subsequent governance activities.
Section 1.1: Core Values
#
Implementation Item
Implemented
Partial
Not Started
N/A
1.1.1
The organization has defined its commitment to the Five Pillars of AI Righteousness (Integrity, Justice, Stewardship, Wisdom, Beneficence)
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1.1.2
The Five Pillars have been translated into specific ethical principles relevant to the organization’s AI activities
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1.1.3
Executive leadership has visibly and actively committed to the righteousness governance initiative
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1.1.4
The righteousness vision has been communicated across the organization
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1.1.5
A formal Righteousness Charter or equivalent document exists
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Section 1.2: Leadership Commitment
#
Implementation Item
Implemented
Partial
Not Started
N/A
1.2.1
Leadership demonstrates visible commitment to righteous AI through public statements and actions
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1.2.2
Leadership has allocated sufficient resources (budget, personnel, tools) for AI governance
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1.2.3
Leadership participates in regular AI governance reviews
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1.2.4
Leadership holds themselves and others accountable for AI righteousness
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1.2.5
Leadership models righteous behavior in AI-related decisions
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Section 1.3: Organizational Awareness
#
Implementation Item
Implemented
Partial
Not Started
N/A
1.3.1
Employees can articulate the organization’s AI righteousness principles
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1.3.2
AI righteousness principles are included in onboarding and training
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1.3.3
Regular communication about AI righteousness occurs across the organization
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1.3.4
Employees feel empowered to raise righteousness concerns
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1.3.5
There is a shared understanding of righteousness across teams and departments
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Layer 2: Policy and Process
Purpose: To translate foundational values into actionable policies, procedures, and governance structures.
Section 2.1: AI Governance Policies
#
Implementation Item
Implemented
Partial
Not Started
N/A
2.1.1
Written AI governance policies exist and are accessible
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2.1.2
Policies operationalize the Five Pillars in the context of AI development and deployment
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2.1.3
Data governance policies are in place
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2.1.4
Algorithmic fairness policies are in place
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2.1.5
Transparency and explainability policies are in place
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Section 2.2: Governance Structures
#
Implementation Item
Implemented
Partial
Not Started
N/A
2.2.1
Clear roles and responsibilities for AI governance are defined
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2.2.2
A governance board or committee oversees AI governance
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2.2.3
An AI ethics committee provides ethical guidance
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2.2.4
A compliance function monitors AI governance
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2.2.5
A risk management function identifies and manages AI risks
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Section 2.3: Procedures and Workflows
#
Implementation Item
Implemented
Partial
Not Started
N/A
2.3.1
Procedures for implementing governance policies are documented
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2.3.2
Workflows for AI governance activities are established
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2.3.3
Employees understand and follow established procedures
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2.3.4
Procedures are reviewed and updated regularly
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2.3.5
Procedures include clear escalation paths
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Layer 3: Map and Analyze
Purpose: To identify, inventory, and analyze AI systems and their associated risks from a righteousness perspective.
Section 3.1: AI Inventory
#
Implementation Item
Implemented
Partial
Not Started
N/A
3.1.1
A comprehensive inventory of all AI systems exists
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3.1.2
The inventory is maintained and updated regularly
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3.1.3
AI systems are classified by risk level
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3.1.4
AI systems are classified by function and data sensitivity
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3.1.5
AI systems are classified by impact level
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Section 3.2: Risk Assessment
#
Implementation Item
Implemented
Partial
Not Started
N/A
3.2.1
Data flows are mapped and understood
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3.2.2
Stakeholders are identified and engaged
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3.2.3
Risk assessments are conducted for high-impact AI systems
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3.2.4
Risks are assessed against the Five Pillars
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3.2.5
Risk assessments are documented and reviewed
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Section 3.3: Context Analysis
#
Implementation Item
Implemented
Partial
Not Started
N/A
3.3.1
The operational context of each AI system is understood
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3.3.2
The regulatory context of each AI system is understood
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3.3.3
The social context of each AI system is understood
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3.3.4
The ethical context of each AI system is understood
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3.3.5
Contextual factors are documented and reviewed
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Layer 4: Measure and Monitor
Purpose: To establish quantitative and qualitative measures of AI righteousness and to monitor performance over time.
Section 4.1: Metrics Definition
#
Implementation Item
Implemented
Partial
Not Started
N/A
4.1.1
Metrics are established for Integrity
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4.1.2
Metrics are established for Justice
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4.1.3
Metrics are established for Stewardship
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4.1.4
Metrics are established for Wisdom
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4.1.5
Metrics are established for Beneficence
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Section 4.2: RI Assessment
#
Implementation Item
Implemented
Partial
Not Started
N/A
4.2.1
RI-D assessments are conducted for developers
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4.2.2
RI-P assessments are conducted for providers
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4.2.3
RI-O assessments are conducted for the organization
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4.2.4
RI-A assessments are conducted for AI agents
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4.2.5
RI-R assessments are conducted for robots
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Section 4.3: Continuous Monitoring
#
Implementation Item
Implemented
Partial
Not Started
N/A
4.3.1
Continuous monitoring systems are in place
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4.3.2
Monitoring data is collected and analyzed
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4.3.3
Baselines are established for measurement
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4.3.4
Regular reports are produced and reviewed
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4.3.5
Monitoring results are communicated to stakeholders
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Layer 5: Manage and Control
Purpose: To implement controls, safeguards, and interventions that ensure AI systems operate within righteous boundaries.
Section 5.1: Technical Controls
#
Implementation Item
Implemented
Partial
Not Started
N/A
5.1.1
Bias detection tools are deployed
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5.1.2
Transparency mechanisms are deployed
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5.1.3
Action boundaries are enforced
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5.1.4
Security safeguards are in place
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5.1.5
Technical controls are tested and updated
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Section 5.2: Human Oversight
#
Implementation Item
Implemented
Partial
Not Started
N/A
5.2.1
Meaningful human review exists for critical AI decisions
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5.2.2
Human oversight roles are defined and staffed
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5.2.3
Human overseers are adequately trained
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5.2.4
Human-in-the-loop controls are maintained
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5.2.5
Oversight activities are documented
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Section 5.3: Incident Response
#
Implementation Item
Implemented
Partial
Not Started
N/A
5.3.1
Incident response procedures are in place
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5.3.2
Incident response teams are identified and trained
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5.3.3
Incident response procedures are tested regularly
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5.3.4
Incidents are documented and reviewed
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5.3.5
Lessons learned from incidents are incorporated
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Layer 6: Assess Impact
Purpose: To evaluate the broader impacts of AI systems on individuals, communities, and society, and to assess the effectiveness of governance activities.
Section 6.1: Impact Assessment
#
Implementation Item
Implemented
Partial
Not Started
N/A
6.1.1
Social impact assessments are conducted
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6.1.2
Ethical impact assessments are conducted
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6.1.3
Environmental impact assessments are conducted
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6.1.4
Human rights impact assessments are conducted
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6.1.5
Impact assessments are documented and reviewed
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Section 6.2: Stakeholder Engagement
#
Implementation Item
Implemented
Partial
Not Started
N/A
6.2.1
Stakeholders are identified for each AI system
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6.2.2
Affected communities are engaged
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6.2.3
Stakeholder feedback is collected and incorporated
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6.2.4
Stakeholder concerns are addressed
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6.2.5
Stakeholder engagement is documented
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Section 6.3: Governance Effectiveness
#
Implementation Item
Implemented
Partial
Not Started
N/A
6.3.1
Governance activities are evaluated for effectiveness
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6.3.2
Unintended consequences are identified and documented
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6.3.3
Alignment with the Five Pillars is reviewed
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6.3.4
Lessons learned are documented
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6.3.5
Lessons learned are applied to improve governance
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Layer 7: Sustain and Improve
Purpose: To ensure that righteousness governance is not a one-time effort but a continuous, evolving practice.
Section 7.1: Review and Update
#
Implementation Item
Implemented
Partial
Not Started
N/A
7.1.1
Governance policies are reviewed regularly
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7.1.2
Governance procedures are reviewed regularly
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7.1.3
Governance controls are reviewed regularly
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7.1.4
Updates are made based on review findings
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7.1.5
Reviews are documented
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Section 7.2: Feedback and Improvement
#
Implementation Item
Implemented
Partial
Not Started
N/A
7.2.1
Feedback from measurement is incorporated
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7.2.2
Feedback from assessments is incorporated
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7.2.3
Feedback from stakeholders is incorporated
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7.2.4
Continuous improvement processes are in place
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7.2.5
Improvement is tracked and measured
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Section 7.3: Capability Development
#
Implementation Item
Implemented
Partial
Not Started
N/A
7.3.1
Training is provided to build governance capabilities
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7.3.2
Best practices are shared across the organization
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7.3.3
External best practices are monitored and adopted
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7.3.4
RGS is tracked to ensure continuous improvement
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7.3.5
Governance capabilities are evaluated and developed
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Summary Scorecard
Layer Implementation Score
Layer
Total Items
Implemented
Partial
Not Started
Score (%)
Status
Layer 1: Foundation
15
___
___
___
___%
___
Layer 2: Policy and Process
15
___
___
___
___%
___
Layer 3: Map and Analyze
15
___
___
___
___%
___
Layer 4: Measure and Monitor
15
___
___
___
___%
___
Layer 5: Manage and Control
15
___
___
___
___%
___
Layer 6: Assess Impact
15
___
___
___
___%
___
Layer 7: Sustain and Improve
15
___
___
___
___%
___
Total
105
___
___
___
___%
___
Score Calculation
Each Layer Score (%) = (Implemented Count ÷ Total Items) × 100
Overall Score (%) = (Sum of 7 Layer Scores) ÷ 7
Status Interpretation
Score Range
Status
Description
80–100%
Fully Implemented
The layer is fully implemented and operating effectively
60–79%
Proficient
The layer is largely implemented with room for improvement
40–59%
Developing
The layer is partially implemented and needs further development
20–39%
Emerging
The layer is at an early stage and needs significant improvement
0–19%
Not Started
The layer has not yet been implemented
Implementation Priority Matrix
Layer
Score (%)
Priority
Recommended Actions
Owner
Timeline
Layer 1: Foundation
___%
High/Medium/Low
___
___
___
Layer 2: Policy and Process
___%
High/Medium/Low
___
___
___
Layer 3: Map and Analyze
___%
High/Medium/Low
___
___
___
Layer 4: Measure and Monitor
___%
High/Medium/Low
___
___
___
Layer 5: Manage and Control
___%
High/Medium/Low
___
___
___
Layer 6: Assess Impact
___%
High/Medium/Low
___
___
___
Layer 7: Sustain and Improve
___%
High/Medium/Low
___
___
___
Implementation Roadmap
Phase
Layers
Focus
Timeline
Phase 1: Foundation
Layer 1, Layer 2
Establish values, policies, and governance structures
3-6 months
Phase 2: Assessment
Layer 3, Layer 4
Map AI systems, assess risks, and establish measurement