We’re Missing a Moral Framework of Justice in Artificial Intelligence: On the Limits, Failings, and Ethics of Fairness. Le Bui, M. & Noble, S. U. In Dubber, M. D., Pasquale, F., & Das, S., editors, The Oxford Handbook of Ethics of AI, pages 0. Oxford University Press, July, 2020. ![We’re Missing a Moral Framework of Justice in Artificial Intelligence: On the Limits, Failings, and Ethics of Fairness [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex This chapter assesses the concepts of fairness and bias in artificial intelligence research and interventions. In considering the explosive growth, emergence of, and investment in high-profile AI fairness and ethics interventions within both the academy and industry—alongside the mounting and proliferating calls for the interrogation, regulation, and, in some cases, dismantling and prohibition of AI—it contests and questions the extent to which such remedies can address the original concerns and problems they are designed to address. Indeed, many community organizations are organizing responses and challenging AI used in predictive technologies—facial-recognition software and biometrics technologies—with increasing success. Ultimately, the canon of AI ethics must interrogate and deeply engage with intersectional power structures that work to further consolidate capital in the hands of the elites and that will undergird digital informational systems of inequality: there is no neutral or objective state through which the flows and mechanics of data can be articulated as unbiased or fair.
@incollection{le_bui_were_2020,
title = {We’re {Missing} a {Moral} {Framework} of {Justice} in {Artificial} {Intelligence}: {On} the {Limits}, {Failings}, and {Ethics} of {Fairness}},
isbn = {978-0-19-006739-7},
shorttitle = {We’re {Missing} a {Moral} {Framework} of {Justice} in {Artificial} {Intelligence}},
url = {https://doi.org/10.1093/oxfordhb/9780190067397.013.9},
abstract = {This chapter assesses the concepts of fairness and bias in artificial intelligence research and interventions. In considering the explosive growth, emergence of, and investment in high-profile AI fairness and ethics interventions within both the academy and industry—alongside the mounting and proliferating calls for the interrogation, regulation, and, in some cases, dismantling and prohibition of AI—it contests and questions the extent to which such remedies can address the original concerns and problems they are designed to address. Indeed, many community organizations are organizing responses and challenging AI used in predictive technologies—facial-recognition software and biometrics technologies—with increasing success. Ultimately, the canon of AI ethics must interrogate and deeply engage with intersectional power structures that work to further consolidate capital in the hands of the elites and that will undergird digital informational systems of inequality: there is no neutral or objective state through which the flows and mechanics of data can be articulated as unbiased or fair.},
urldate = {2023-04-10},
booktitle = {The {Oxford} {Handbook} of {Ethics} of {AI}},
publisher = {Oxford University Press},
author = {Le Bui, Matthew and Noble, Safiya Umoja},
editor = {Dubber, Markus D. and Pasquale, Frank and Das, Sunit},
month = jul,
year = {2020},
doi = {10.1093/oxfordhb/9780190067397.013.9},
pages = {0},
}
Downloads: 0
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