FINDHR (Fairness and Intersectional Non-Discrimination in Human Recommendation) project

In FINDHR research, technology, law, and ethics are interwoven. Our Lab is leading the cross-cultural digital ethics theme, and our partners have an expertise in a wide variety of domains ‒ e.g., data protection law, non-discrimination law; intersectional gender analysis; algorithmic fairness and explainability research; expertise on privacy and responsible data practices and models; auditing of digital services. In particular, we consult on cross-cultural product design expertise, for fair treatment of marginalised groups. We are currently exploring the socio-ethical implications of data de-biasing and fairness in synthetic data generation, and the potentials of AI-driven technologies to shape and transform the future of work.

Payal Arora
Principal Investigator

Marianna Capasso
Postdoc Researcher

Kiran Bhatia
Researcher

Celeste Tacconi
Fellow

Deepshikha Sharma
Fellow
Select Outputs

Training on Reducing AI Bias and Discrimination
- Marianna Capasso, Payal Arora, Deepshikha Sharma and Celeste Tacconi: On the Right to Work in the Age of Artificial Intelligence: Ethical Safeguards in Algorithmic Human Resource Management The Business and Human Rights Journal 2025
- Philippe de Wilde, Payal Arora, Fernando Buarque, Yik Chan Chin,
Mamello Thinyane, Stinckwich Serge, Fournier-Tombs Eleonore and Marwala
Tshilidzi. Recommendations on the Use of Synthetic Data to Train AI Models : UNU Centre, UNU-CPR, UNU Macau, 2024.