Technology toolkits
Along with guidance documents and PowerPoint, enterprises need toolkits that can actually parse the datasets, models, and code to identify the underlying biases and provide practical ways to address these concerns. The following subsections explain some such tools and libraries that offer these capabilities.
Microsoft Fairlearn
Microsoft Fairlearn24 is an open source Python library to assess and improve the fairness of ML models, and it has a wide range of algorithms to compare and mitigate bias in predictive models, as well as visualization tools to explore and analyze model performance. Fairlearn is designed to help data scientists and developers build more equitable and inclusive ML models by providing them with the tools to measure and address unfairness in their models. The library is part of Microsoft’s RAI efforts and is freely available for use by anyone.
Figure 5.4: The Fairlearn toolkit
In Chapters 8 and 9, we...
