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Aequitas: A Bias and Fairness Audit Toolkit
[article]
2019
arXiv
pre-print
Recent work has raised concerns on the risk of unintended bias in AI systems being used nowadays that can affect individuals unfairly based on race, gender or religion, among other possible characteristics. While a lot of bias metrics and fairness definitions have been proposed in recent years, there is no consensus on which metric/definition should be used and there are very few available resources to operationalize them. Therefore, despite recent awareness, auditing for bias and fairness when
arXiv:1811.05577v2
fatcat:azzzplwjh5gwtgp6iwulqvmghe