8 citations · 16 across the 8 of their papers we have counts for
Showing cs.AIShow all
3 papers · 1 filter
cs.AI2022
Integrating Prior Knowledge in Post-hoc Explanations
Adulam Jeyasothy, Thibault Laugel, Marie-Jeanne Lesot +2
In the field of eXplainable Artificial Intelligence (XAI), post-hoc interpretability methods aim at explaining to a user the predictions of a trained decision model. Integrating pr…
cs.AI2021
Explaining how your AI system is fair
Boris Ruf, Marcin Detyniecki
To implement fair machine learning in a sustainable way, choosing the right fairness objective is key. Since fairness is a concept of justice which comes in various, sometimes conf…
cs.AI2021
Towards the Right Kind of Fairness in AI
Boris Ruf, Marcin Detyniecki
Fairness is a concept of justice. Various definitions exist, some of them conflicting with each other. In the absence of an uniformly accepted notion of fairness, choosing the righ…