Ethical AI MY – Reference Release v1.0

Open, Auditable, Non-Mandatory Reference for Ethical AI in Malaysia

Prinsip Teras

Repositori ini adalah Open, Auditable, Non-Mandatory Reference untuk tadbir urus AI bertanggungjawab di Malaysia. Setiap komponen boleh disemak secara terbuka, setiap keputusan mempunyai jejak audit yang lengkap, dan penggunaan adalah pilihan bebas komuniti.

Prinsip	Maksud
Open	Kod dan dasar terbuka untuk semua
Auditable	Setiap perubahan mempunyai audit trail
Non-Mandatory Reference	Rujukan, bukan standard wajib

Pematuhan: ONSA 2025 | CPC | RMC (berkuat kuasa 1 Jun 2026)
Direktif HITL aktif — manusia sentiasa dalam kawalan.

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Overview

Ethical AI MY is a comprehensive, publicly available reference for responsible and ethical artificial intelligence development and deployment in Malaysia. This repository provides:

• Ethical Framework – Core principles and values guiding AI development
• Governance Model – Non-centralized structure for distributed decision-making
• Security Standards – Risk management and protective protocols
• Community Guidelines – Code of conduct and collaborative principles
• Attribution Framework – Recognition and transparency mechanisms

This is a reference document, not a mandate. It is offered as guidance for stakeholders who wish to align their AI initiatives with ethical principles.

Acknowledgment: This reference aligns with initiatives by ONSA 2025, CPC, dan RMC MCMC in advancing responsible AI governance in Malaysia.

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Governance Diagram

┌─────────────────────────────────────────────────────────────┐
│         ETHICAL AI MY - Non-Centralized Governance          │
├─────────────────────────────────────────────────────────────┤
│                                                              │
│  ┌──────────────┐    ┌──────────────┐    ┌──────────────┐  │
│  │  Ethical     │    │  Governance  │    │  Security    │  │
│  │  Framework   │────│  Model       │────│  Standards   │  │
│  └──────────────┘    └──────────────┘    └──────────────┘  │
│         │                   │                     │          │
│         └───────────────────┼─────────────────────┘          │
│                             │                                │
│                    ┌────────▼────────┐                       │
│                    │ Non-Centralized │                       │
│                    │ Decision Making │                       │
│                    └────────────────┘                        │
│                             │                                │
│         ┌───────────────────┼───────────────────┐            │
│         │                   │                   │            │
│    ┌────▼────┐         ┌────▼────┐        ┌────▼────┐       │
│    │ Orgs    │         │ Dev     │        │Research │       │
│    │         │         │Teams    │        │         │       │
│    └─────────┘         └─────────┘        └─────────┘       │
│                                                              │
│  Principles: Autonomy • Alignment • Transparency •          │
│  Accountability • Stakeholder Voice                          │
│                                                              │
└─────────────────────────────────────────────────────────────┘

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Hard Policy Documents

1. ETHICS.md – Ethical Framework

Fundamental principles guiding AI development:

• Fairness – Equitable outcomes across stakeholders
• Transparency – Clear documentation of decisions
• Accountability – Responsibility for behavior
• Privacy – Protection of personal data
• Benefit – Positive societal contribution

2. GOVERNANCE.md – Governance Model

Non-centralized governance structure:

• Autonomous stakeholder decision-making
• Alignment through shared principles
• Distributed review and oversight
• Transparent escalation processes
• Community-driven evolution

3. SECURITY.md – Security Standards

Technical and operational security:

• Data protection protocols
• Access control frameworks
• Incident response procedures
• Vulnerability management
• Continuous assessment

4. CODE_OF_CONDUCT.md – Community Standards

Guidelines for participation:

• Respectful communication
• Reporting mechanisms
• Conflict resolution
• Diversity commitment
• Consequence framework

5. ATTRIBUTION.md – Recognition Framework

• Contributor acknowledgment
• Citation standards
• Intellectual property recognition
• Historical record maintenance

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Supplementary Documents

• FINAL_INTENT.md – Statement of purpose and vision
• LICENSE – Open usage terms

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Repository Structure

ethical-ai-my/
├── index.html
├── README.md (this file)
├── LICENSE
├── ETHICS.md
├── GOVERNANCE.md
├── SECURITY.md
├── ATTRIBUTION.md
├── CODE_OF_CONDUCT.md
├── FINAL_INTENT.md
├── ethical-ai-my-archive-bilingual.html
├── ethical-ai-my-diagram-monochrome-bilingual.svg
├── governance/
│   └── version.json
├── scripts/
│   ├── ensure_required_files.sh
│   ├── audit_logger.py
│   └── risk_scoring.py
├── api/
│   └── audit_api.py
└── .github/
    ├── PULL_REQUEST_TEMPLATE.md
    └── ISSUE_TEMPLATE/
        ├── bug_report.md
        └── feature_request.md

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Key Principles

✓ Non-Centralized

Distributed governance enables autonomous decision-making while maintaining alignment through shared ethical values.

✓ Auditable

All frameworks, policies, and decisions are fully documented and available for independent review and verification.

✓ Non-Mandatory

This reference is guidance and best practice, not binding regulation. Organizations are encouraged to adopt, adapt, or extend these principles.

✓ RZ1 Production Traceability

RZ1 production components now include:

• JSON audit logging (scripts/audit_logger.py)
• Risk scoring output (scripts/risk_scoring.py)
• Audit tracking API endpoints (api/audit_api.py)
• Version and traceability metadata (governance/version.json)

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Getting Started

For Developers

1. Review ETHICS.md for ethical principles
2. Study SECURITY.md for technical requirements
3. Implement according to your AI system context

For Organizations

1. Examine GOVERNANCE.md for structural models
2. Review CODE_OF_CONDUCT.md for team guidelines
3. Establish alignment with your strategy

For Researchers

1. Access complete references in documentation
2. Consult ATTRIBUTION.md for citation practices
3. Contribute findings to expand the reference

For Community Members

1. Read CODE_OF_CONDUCT.md for participation
2. Review contribution process
3. Engage respectfully in discussions

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Version Information

• Version: 1.0
• Status: Reference Release
• Release Date: 2026-06-01
• Type: Open, Auditable, Non-Mandatory Reference
• Language: English, Malay (Bilingual)

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License

This work is released under Creative Commons Attribution 4.0 International (CC BY 4.0). See LICENSE for details.

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Contributing

Contributions are welcome. Please:

1. Review CODE_OF_CONDUCT.md
2. Follow .github/PULL_REQUEST_TEMPLATE.md
3. Ensure alignment with ETHICS.md
4. Update ATTRIBUTION.md if needed

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Periodic Cross-Review and Updates

To keep this reference open, auditable, and internally consistent, the repository follows a recurring cross-review process across policy documents, static pages, and release metadata.

Scope

• Core policy documents: ETHICS.md, GOVERNANCE.md, SECURITY.md, CODE_OF_CONDUCT.md, ATTRIBUTION.md, FINAL_INTENT.md
• Public entry points: README.md, index.html, ethical-ai-my-archive-bilingual.html
• Audit and release record: RELEASE_NOTES.md, GitHub workflow logs, and pull requests

Source of Truth

• Core policy meaning is maintained in the policy documents themselves.
• Public-facing summary and repository navigation are maintained in README.md.
• Version and release-date metadata must remain aligned across README.md, index.html, ethical-ai-my-archive-bilingual.html, and the policy-document footers.

Review Cadence and Ownership

• Automated cross-review runs weekly through .github/workflows/compliance.yml and also on pushes and pull requests to main.
• Repository maintainers review workflow failures and coordinate follow-up updates.
• Contributors who change public content are expected to update every affected file in the same pull request.

Follow-Up Actions

1. Investigate any workflow failure as a content-governance issue, not only as a formatting issue.
2. Update all affected files when version, release date, or core reference wording changes.
3. Record material reference or governance updates in RELEASE_NOTES.md to preserve the audit trail.
4. Re-run validation before merge so the weekly baseline remains trustworthy.

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Support

For questions or suggestions:

• Open an issue using the provided templates
• Review existing documentation
• Engage constructively in discussions

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Ethical AI MY – Open Reference for Responsible AI Development

Last Updated: 2026-06-01