Bias in context: What to do when complete bias removal is not an option
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Bias in context : What to do when complete bias removal is not an option. / Holm, Sune; Petersen, Eike; Ganz, Melanie; Feragen, Aasa.
In: Proceedings of the National Academy of Sciences of the United States of America, Vol. 120, No. 23, e2304710120, 2023.Research output: Contribution to journal › Letter › Research › peer-review
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TY - JOUR
T1 - Bias in context
T2 - What to do when complete bias removal is not an option
AU - Holm, Sune
AU - Petersen, Eike
AU - Ganz, Melanie
AU - Feragen, Aasa
PY - 2023
Y1 - 2023
N2 - It is widely recognized that machine learning algorithms may be biased in the sense that they perform worse on some demographic groups than others. This motivates algorithmic development to remove algorithmic bias, which in turn might lead to a hope—even an expectation—that algorithmic bias can be mitigated or removed (1). In this short comment, we make three points to qualify Wang et al.’s suggestion: 1) It may not be possible for algorithms to perform equally well across groups on all measures, 2) which inequalities count as morally unacceptable bias is an ethical question, and 3) the answer to the ethical question will vary across decision contexts.
AB - It is widely recognized that machine learning algorithms may be biased in the sense that they perform worse on some demographic groups than others. This motivates algorithmic development to remove algorithmic bias, which in turn might lead to a hope—even an expectation—that algorithmic bias can be mitigated or removed (1). In this short comment, we make three points to qualify Wang et al.’s suggestion: 1) It may not be possible for algorithms to perform equally well across groups on all measures, 2) which inequalities count as morally unacceptable bias is an ethical question, and 3) the answer to the ethical question will vary across decision contexts.
KW - Bias
U2 - 10.1073/pnas.2304710120
DO - 10.1073/pnas.2304710120
M3 - Letter
C2 - 37252997
VL - 120
JO - Proceedings of the National Academy of Sciences of the United States of America
JF - Proceedings of the National Academy of Sciences of the United States of America
SN - 0027-8424
IS - 23
M1 - e2304710120
ER -
ID: 348163796