AI vs IFC Performance Standards
Testing whether AI can design social safeguard systems that are fairer, more accountable, and more robust than human-designed international standards.
12 advanced AI models face the ultimate ethical challenge: designing protection systems for communities affected by billion-dollar development projects.
Key Findings
The Gap: Most AI models gave generic, superficial responses—the "C student" answers that sound good but lack substance.
The Leaders: Claude Opus, Kimi K2, GLM-4.6, and QSwen-3-Max demonstrated expert-level understanding of IFC Performance Standards.
Beyond Human Standards: Top models didn't just meet the gold standard—they proposed better systems with auditable metrics, binding accountability mechanisms, and quantifiable fairness targets.
The Innovation: Kimi K2 introduced the "Vulnerable Group Gap Ratio"—transforming vague principles into hard, verifiable numbers with automatic consequences for non-compliance.
📄Research Documents
LLM Prompt Testing: Full Analysis (412 pages)
PDFComprehensive testing of 12 AI models against IFC Performance Standards
Chinese Models Testing Results
PDFSpecialized analysis of Chinese language models (Kimi K2, GLM-4.6, QSwen-3-Max)
NLM Synthesis of LLM Safeguard Responses
PDFSynthesis analysis of AI model responses to social safeguard scenarios
Strategic Social Performance Lifecycle
PDFFramework for social performance management in development projects
📝Analysis Articles
AI vs IFC: The Ultimate Test
Can AI design fairer social safeguard systems than human experts?
Social Safeguards: Mandates vs Principles
Analysis of prescriptive mandates versus principle-based approaches
LLM Safeguards: Final Article
Comprehensive article on AI-designed social safeguard systems
Fixing Weaknesses in Social Risk Management
Identifying and addressing gaps in current social risk frameworks
📌 Development Note
This section is being developed to showcase the 412-page LLM Prompt Testing research in an engaging, interactive format. The raw research documents are available above. Interactive visualizations and comprehensive analysis coming soon.