Tools for addressing Fairness in ML

  • Fairmodels: Tool for bias detection, visualization, and mitigation.
  • FAT Forensics: Python toolkit for evaluating Fairness, Accountability and Transparency of AI systems
  • AI Fairness 360: IBM Research Trusted AI. Open source toolkit for examining, reporting, and mitigating discrimination and bias in ML models.

Some Venues on Explainable, Fair & Trustworthy AI

  • ACM FAccT 2021: ACM Conference on Fairness, Accountability, and Transparency
  • AIES 2021: AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society
  • FORC 2021: Symposium on Foundations of Responsible Computing
  • BIAS 2021: International Workshop on Algorithmic Bias in Search and Recommendation
  • XKDD 2020: ECML-PKDD Workshop on eXplainable Knowledge Discovery in Data Mining
  • TrustML: Bi-weekly Seminar Series of The Trustworthy ML Initiative

Projects on Explainable, Fair & Trustworthy AI