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A Framework for Fairness: A Systematic Review of Existing Fair AI Solutions
[article]
2021
arXiv
pre-print
In a world of daily emerging scientific inquisition and discovery, the prolific launch of machine learning across industries comes to little surprise for those familiar with the potential of ML. Neither so should the congruent expansion of ethics-focused research that emerged as a response to issues of bias and unfairness that stemmed from those very same applications. Fairness research, which focuses on techniques to combat algorithmic bias, is now more supported than ever before. A large
arXiv:2112.05700v1
fatcat:cax4fds475cbzioqat2bidgkba