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.

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empirical studies explanation fairness machine learning

摘要

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

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