The DOI matches its Crossref record; 37 of the 38 references it cites were found in a registry or an index.
Using sensitive personal data may be necessary for avoiding discrimination in data-driven decision models
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“Many of the methods to tackle discrimination in AI systems implicitly assume that organisations hold these sensitive data”
From Discrimination, artificial intelligence, and algorithmic decision-making (2025) · cites this paper as Žliobaitė and Custers 2016
Citations
Cites
Causality: Models, Reasoning, and Inference
Pearl, J. (2009) · doi:10.1017/cbo9780511803161 · Cited by 11,653
Barocas, S., & Selbst, A. D. (2014) · doi:10.2139/ssrn.2477899 · Cited by 3,048
Private traits and attributes are predictable from digital records of human behavior
Kosinski, M., Stillwell, D., & Graepel, T. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1218772110 · Cited by 2,829
Certifying and Removing Disparate Impact
Feldman, M., Friedler, S. A., Moeller, J., Scheidegger, C., & Venkatasubramanian, S. (2015) · Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining · doi:10.1145/2783258.2783311 · Cited by 1,827
Hassard, T. H., & Weisberg, S. (1981) · Journal of the Royal Statistical Society Series D (The Statistician) · doi:10.2307/2987575 · Cited by 1,219
(2013) · Cited by 1,126
Broken Promises of Privacy: Responding to the Surprising Failure of AnonymizationPreprint
Ohm, P. (2009) · SSRN Electronic Journal · Cited by 997
Discrimination in online ad delivery
Sweeney, L. (2013) · Communications of the ACM · doi:10.1145/2447976.2447990 · Cited by 783 · cited 1×
“Growing evidence suggests (Barocas and Selbst 2016; Kay et al. 2015; Edelman and Luca 2014; Citron and Pasquale 2014; Sweeney 2013) that decision making by inappropriately trained algorithms can discriminate people.”
BackgroundFairness-Aware Classifier with Prejudice Remover Regularizer
Kamishima, T., Akaho, S., Asoh, H., & Sakuma, J. (2012) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-33486-3_3 · Cited by 694
Discrimination-aware data mining
Pedreshi, D., Ruggieri, S., & Turini, F. (2008) · Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining · doi:10.1145/1401890.1401959 · Cited by 676
Research works printed but not linked: 1
- Citron DK, Pasquale FA (2014) The scored society: due process for automated predictions. Wash Law Rev, Vol. 89, p. 1, U of Maryland Legal Studies Research Paper No. 2014-8
Cited by
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Bias in data‐driven artificial intelligence systems—An introductory survey
Ntoutsi, E., Fafalios, P., Gadiraju, U., Iosifidis, V., Nejdl, W., Vidal, M., Ruggieri, S., Turini, F., Papadopoulos, S., Krasanakis, E., et al. (2020) · WIREs Data Mining and Knowledge Discovery · doi:10.1002/widm.1356 · Cited by 1,043
Fairness in Criminal Justice Risk Assessments: The State of the Art
Berk, R., Heidari, H., Jabbari, S., Kearns, M., & Roth, A. (2021) · Sociological Methods & Research · doi:10.1177/0049124118782533 · Cited by 988
“Under these circumstances, it is possible for a risk instrument to have predictive parity but not be well calibrated.”
BackgroundVeale, M., & Binns, R. (2017) · Big Data & Society · doi:10.1177/2053951717743530 · Cited by 512
Cheong, B. C. (2024) · Frontiers in Human Dynamics · doi:10.3389/fhumd.2024.1421273 · Cited by 445
Measuring discrimination in algorithmic decision making
Žliobaitė, I. (2017) · Data Mining and Knowledge Discovery · doi:10.1007/s10618-017-0506-1 · Cited by 272
Self-citation
Metadata
- Authors
- Žliobaitė, I., & Custers, B.
- Affiliations
- University of Helsinki (FI)
- Leiden University (NL)
- Corresponding author
- Žliobaitė, Indrė
- Venue
- Artificial Intelligence and Law
- Published
- 2016-05-07
- Volume
- 24
- Issue
- 2
- Pages
- 183-201
- ISSN
- 0924-8463 (ISSN-L)
- 1572-8382
- OpenAlex
- W2392403817
- Cited by
- 125
- References
- 38
- Citations by year
- 2026: 4 · 2025: 7 · 2024: 18 · 2023: 15 · 2022: 13 · 2021: 22 · 2020: 17 · 2019: 17 · 2018: 5 · 2017: 7
- FWCI
- 23.63
- Type
- journal article
- Language
- en
- Open access
- green
- papers.ssrn.com
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Artificial Intelligence and Law (publishedVersion)
- SSRN Electronic Journal (submittedVersion)
- Leiden Repository (Leiden University) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Physical Sciences › Computer Science › Artificial Intelligence › Explainable Artificial Intelligence (XAI)
- Social Sciences › Law › Digitalization, Law, and Regulation
- Keywords
- algorithmic discrimination, sensitive personal data, data-driven decision making, algorithmic fairness, prediction model, race, data privacy regulation, data minimization, data bias, data mining, personal data protection law
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