AI Can Be Sexist and Racist — It’s Time to Make It Fair. Zou, J. & Schiebinger, L. Nature, 559(7714):324–326, July, 2018. Bandiera_abtest: a Cg_type: Comment Publisher: Nature Publishing Group Subject_term: Information technology, Society
Paper doi abstract bibtex Computer scientists must identify sources of bias, de-bias training data and develop artificial-intelligence algorithms that are robust to skews in the data.
@article{zou_ai_2018,
title = {{AI} {Can} {Be} {Sexist} and {Racist} — {It}’s {Time} to {Make} {It} {Fair}},
volume = {559},
copyright = {2021 Nature},
url = {https://www.nature.com/articles/d41586-018-05707-8},
doi = {10/gdtkwr},
abstract = {Computer scientists must identify sources of bias, de-bias training data and develop artificial-intelligence algorithms that are robust to skews in the data.},
language = {en},
number = {7714},
urldate = {2024-04-15},
journal = {Nature},
author = {Zou, James and Schiebinger, Londa},
month = jul,
year = {2018},
note = {Bandiera\_abtest: a
Cg\_type: Comment
Publisher: Nature Publishing Group
Subject\_term: Information technology, Society},
keywords = {Information technology, Society},
pages = {324--326},
}
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