You can re-watch the session of Javier Campos now! A few subjects Javier Campos covers in his session:
- Classical fallacy: just because your model does not use gender (or any other protected attribute) it is not enough to guarantee fairness on those attributes
- Ways to introduce unfairness in an unintended way
- Explainability and fairness: explaining a model does not guarantee fairness- (“Fairwashing”)
- Metrics and Trade-off’s in designing robust, explainable and faired algorithms: Pareto curves and the costs of fairness
- The future of fairness