Fairness Measures

Datasets and software for detecting algorithmic discrimination

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The risen prevalence of automated decision-making process is increasing the risk associated with models that can potentially discriminate against disadvantaged groups. The Fairness Measures Project contributes to the development of fairness-aware algorithms and systems by providing relevant datasets and software.

You may find here a series of datasets we have collected and/or prepared. These datasets are from various fields and applications (e.g., finance, law, and human resources). We also provide common fairness definitions in machine learning. In addition, you can find a few fairness algorithms, both in the area of ranking and classification.

We would love to hear your comments and suggestions, please contact Meike Zehlike for any feedback you may have.


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