Explaining models: an empirical study of how explanations impact fairness judgment
Proceedings of the 24th International Conference on Intelligent User Interfaces, pp. 275-285, 2019.
empirical studies explanation fairness machine learning
Ensuring fairness of machine learning systems is a human-in-the-loop process. It relies on developers, users, and the general public to identify fairness problems and make improvements. To facilitate the process we need effective, unbiased, and user-friendly explanations that people can confidently rely on. Towards that end, we conducted ...更多