Direct and Indirect Discrimination Prevention Methods
Integrity signals
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Techniques in discrimination-aware data mining attempt to define fairness and statistically assess it, assure it, or get closer to it.
“Techniques in discrimination-aware data mining attempt to define fairness (primarily in reference to anti-discrimination law [29]) and statistically assess it, assure it, or get closer to it [64, 32, 23].”
From Fairness and Accountability Design Needs for Algorithmic Support in High-Stakes Public Sector Decision-Making (2018) · cites this paper as [32]
Cites
Classifying without discriminating
Kamiran, F., & Calders, T. (2009) · 2009 2nd International Conference on Computer, Control and Communication · doi:10.1109/ic4.2009.4909197 · Cited by 409 · see citing works
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'It's Reducing a Human Being to a Percentage': Perceptions of Justice in Algorithmic Decisions
Binns, R., Van Kleek, M., Veale, M., Lyngs, U., Zhao, J., & Shadbolt, N. (2018) · Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3173574.3173951 · Cited by 691 · see citing works
“Pr epr in t correct discrimination in data mining exist, these are aimed at data scientists implementing systems rather providing information to the individual decision-subjects affected by them [3, 59, 29, 23, 28].”
BackgroundVeale, M., Van Kleek, M., & Binns, R. (2018) · Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3173574.3174014 · Cited by 490 · see citing works
“Techniques in discrimination-aware data mining attempt to define fairness (primarily in reference to anti-discrimination law [29]) and statistically assess it, assure it, or get closer to it [64, 32, 23].”
Backgroundde Laat, P. B. (2018) · Philosophy & Technology · doi:10.1007/s13347-017-0293-z · Cited by 251 · see citing works
Operationalising ethics in artificial intelligence for healthcare: a framework for AI developers
Solanki, P., Grundy, J., & Hussain, W. (2023) · AI and Ethics · doi:10.1007/s43681-022-00195-z · Cited by 157 · see citing works
“A number of techniques that can be employed to prevent discrimination during data cleaning are outlined in [161].”
BackgroundBerendt, B., & Preibusch, S. (2014) · Artificial Intelligence and Law · doi:10.1007/s10506-013-9152-0 · Cited by 44 · see citing works
- Authors
- Hajian, S., & Domingo-Ferrer, J.
- Affiliations
- Universitat Rovira i Virgili (ES)
- Corresponding author
- Hajian, Sara
- ORCID
- Hajian, Sara
- Venue
- Studies in Applied Philosophy, Epistemology and Rational Ethics
- Publisher
- Springer Berlin Heidelberg
- Published
- 2013
- Pages
- 241-254
- ISSN
- 2192-6255 (ISSN-L)
- 2192-6263
- OpenAlex
- W2226176641
- Cited by
- 27
- References
- 1
- Citations by year
- 2025: 4 · 2024: 3 · 2022: 1 · 2021: 1 · 2020: 2 · 2019: 3 · 2018: 5 · 2017: 2 · 2016: 4 · 2014: 2
- FWCI
- 3.44
- Type
- book chapter
- Language
- en
- Open access
- closed
- Licence
- Locations
- Studies in applied philosophy, epistemology and rational ethics (publishedVersion)
- Topics
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Social Sciences › Law › Discrimination and Equality Law
- Keywords
- discrimination prevention, direct discrimination, indirect discrimination, anti-discrimination, biased training data, evaluation metrics, fairness in decision-making
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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