major AI principles recognized globally, grounded in the most authoritative sources available. I’ll pull directly from the OECD, Microsoft, Google, and other reputable frameworks so you get a complete, reliable overview.
🌍 Global AI Principles (with citations)
1. OECD AI Principles
These are the most widely adopted international AI principles, used by governments and organizations worldwide.
Core principles:
- Inclusive growth, sustainable development, and well‑being
- Human‑centered values and fairness
- Transparency and explainability
- Robustness, security, and safety
- Accountability
2. Microsoft Responsible AI Principles
Microsoft’s framework is widely used in industry and aligns with global standards.
Principles:
- Fairness
- Reliability & Safety
- Privacy & Security
- Inclusiveness
- Transparency
- Accountability
3. Google AI Principles
Google’s principles emphasize responsible innovation and global benefit.
Principles:
- Be socially beneficial
- Avoid creating or reinforcing unfair bias
- Be built and tested for safety
- Be accountable to people
- Incorporate privacy design principles
- Uphold high scientific standards
- Be made available for uses that align with these principles
4. Intelligence Community AI Ethics Principles
These apply to government and national‑security contexts.
Principles:
- Respect the law and act with integrity
- Purposeful and responsible use
- Accuracy and objectivity
- Transparency and traceability
- Security
- Accountability
📘 Summary Table
| Framework | Core Themes |
|---|---|
| OECD | Fairness, transparency, safety, accountability, human‑centered values |
| Microsoft | Fairness, safety, privacy, inclusiveness, transparency, accountability |
| Social benefit, fairness, safety, privacy, accountability | |
| Intelligence Community | Integrity, responsibility, accuracy, transparency, security |