FAT Forensics: A Python Toolbox for Implementing and Deploying Fairness, Accountability and Transparency Algorithms in Predictive Systems

Python Submitted 12 September 2019 • Published 19 May 2020
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Review

Editor: @arokem (all papers)
Reviewers: @bernease (all reviews), @osolari (all reviews)

Authors

Kacper Sokol (0000-0002-9869-5896), Alexander Hepburn, Rafael Poyiadzi, Matthew Clifford, Raul Santos-Rodriguez (0000-0001-9576-3905), Peter Flach (0000-0001-6857-5810)

Citation

Sokol et al., (2020). FAT Forensics: A Python Toolbox for Implementing and Deploying Fairness, Accountability and Transparency Algorithms in Predictive Systems. Journal of Open Source Software, 5(49), 1904, https://doi.org/10.21105/joss.01904

@article{Sokol2020, doi = {10.21105/joss.01904}, url = {https://doi.org/10.21105/joss.01904}, year = {2020}, publisher = {The Open Journal}, volume = {5}, number = {49}, pages = {1904}, author = {Kacper Sokol and Alexander Hepburn and Rafael Poyiadzi and Matthew Clifford and Raul Santos-Rodriguez and Peter Flach}, title = {FAT Forensics: A Python Toolbox for Implementing and Deploying Fairness, Accountability and Transparency Algorithms in Predictive Systems }, journal = {Journal of Open Source Software} }
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Fairness Accountability Transparency Artificial Intelligence Machine Learning Software Python Toolbox

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Journal of Open Source Software is part of Open Journals, which is a NumFOCUS-sponsored project.

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ISSN 2475-9066