Nowadays we are witnessing widespread adoption of decision-making software with far-reaching societal impact, e.g., in fiels such as social welfare, criminal justice, and even health care. It is not difficult to envision that in the future most of the decisions in society will be delegated to software. As decision-making software becomes more and more widespread, a number of recent cases have evidenced the importance of ensuring software fairness. Going forward, decision-making software will be subject to more and more legal regulations as well as administrative audits.
The goal of the Libra research project is to meet these needs and develop new analyses and tools to reason about and certify fairness of decision-making software.
A prototype static analyzer for certifying fairness of feed-forward neural networks used for classification of tabular data is open-source and available on GitHub.
- Abhinandan Pal (Bachelor Student, IIIT Kalyani, India)
GPU-based Fairness Certification of Neural Networks
Research Internship (remote), 2022
- Marco Zanella (PhD Student, Università degli Studi di Padova, Italy)
Fairness of Decision Tree Ensemble Classifiers
PhD Internship, École Normale Supérieure, 2020