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%0 Conference Paper
%1 vasileva2020dark
%A Vasileva, Mariya I
%B Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
%D 2020
%K fairness subgroups subgroup algorithm machine learning bias citedby:scholar:count:2 citedby:scholar:timestamp:2021-8-8
%P 3586--3587
%T The Dark Side of Machine Learning Algorithms: How and Why They Can Leverage Bias, and What Can Be Done to Pursue Algorithmic Fairness
@inproceedings{vasileva2020dark,
added-at = {2021-08-08T22:48:25.000+0200},
author = {Vasileva, Mariya I},
biburl = {https://www.bibsonomy.org/bibtex/21d5fd3043e284079f130dabaa13d0c1e/becker},
booktitle = {Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery \& Data Mining},
interhash = {45e87242a4c781ed851644120ac271ac},
intrahash = {1d5fd3043e284079f130dabaa13d0c1e},
keywords = {fairness subgroups subgroup algorithm machine learning bias citedby:scholar:count:2 citedby:scholar:timestamp:2021-8-8},
pages = {3586--3587},
timestamp = {2021-08-08T22:48:25.000+0200},
title = {The Dark Side of Machine Learning Algorithms: How and Why They Can Leverage Bias, and What Can Be Done to Pursue Algorithmic Fairness},
year = 2020
}