🧠 Towards FAIR AI: A Survey of Regional Trends and Knowledge Graph-Enhanced Bias Mitigation

This work is part of the research initiative "Towards FAIR AI: A Survey of Regional Trends and Knowledge Graph-Enhanced Bias Mitigation."

Authors: Abhash Shrestha, Tek Raj Chhetri, Sanju Tiwari

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📘 Overview

This study provides a regional perspective on fairness, accountability, and transparency in AI (FAIR), highlighting geographic disparities and presenting a structured review of methods using Knowledge Graphs (KGs) for mitigating bias in AI systems.

Dashboard

• Link: https://cairnepal.github.io/algorithmic-bias-survey/

🧩 Focus Areas

• 📍 Regional analysis of FAIR AI research and policy
• 🌐 Integration of Knowledge Graphs for context-aware bias detection and correction
• 🔄 Survey of state-of-the-art approaches in bias mitigation
• 💡 Opportunities and challenges for global South and underrepresented regions

📄 Citation

If you use this work, please cite it as:

@misc{shrestha2025towards,
  title={Towards FAIR AI: A Survey of Regional Trends and Knowledge Graph-Enhanced Bias Mitigation},
  author={Shrestha, Abhash and Chhetri, Tek Raj and Tiwari, Sanju},
  year={2025},
  howpublished={\url{https://cair-nepal.org}}, 
}

📜 License

This project is licensed under the Apache License 2.0.