%0 Conference Paper %1 conf/fat/BuolamwiniG18 %A Buolamwini, Joy %A Gebru, Timnit %B FAT %D 2018 %E Friedler, Sorelle A. %E Wilson, Christo %I PMLR %K bias dataset evaluation gender image %P 77-91 %T Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification. %U http://dblp.uni-trier.de/db/conf/fat/fat2018.html#BuolamwiniG18 %V 81

@inproceedings{conf/fat/BuolamwiniG18, added-at = {2020-06-07T19:17:05.000+0200}, author = {Buolamwini, Joy and Gebru, Timnit}, biburl = {https://www.bibsonomy.org/bibtex/27de24cc50f640002d2d5dc0a36d97ef6/mgrueter}, booktitle = {FAT}, crossref = {conf/fat/2018}, editor = {Friedler, Sorelle A. and Wilson, Christo}, ee = {http://proceedings.mlr.press/v81/buolamwini18a.html}, interhash = {34a6b892efb2d515cdb29e9bc24efd89}, intrahash = {7de24cc50f640002d2d5dc0a36d97ef6}, keywords = {bias dataset evaluation gender image}, pages = {77-91}, publisher = {PMLR}, series = {Proceedings of Machine Learning Research}, timestamp = {2020-06-07T19:24:24.000+0200}, title = {Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification.}, url = {http://dblp.uni-trier.de/db/conf/fat/fat2018.html#BuolamwiniG18}, volume = 81, year = 2018 }