The DOI matches its Crossref record; 48 of the 53 references it cites were found in a registry or an index.
A review of predictive policing from the perspective of fairness
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In the citing paper
“Utilizing AI fairness to address bias in risk assessment tools ensures that criminal sentencing decisions are fair [88,281].”
From AI Fairness in Data Management and Analytics: A Review on Challenges, Methodologies and Applications (2023) · cites this paper as [88]
Citations
Cites
A Survey on Bias and Fairness in Machine Learning
Mehrabi, N., Morstatter, F., Saxena, N., Lerman, K., & Galstyan, A. (2022) · ACM Computing Surveys · doi:10.1145/3457607 · Cited by 5,812
Dwork, C., Hardt, M., Pitassi, T., Reingold, O., & Zemel, R. (2012) · Proceedings of the 3rd Innovations in Theoretical Computer Science Conference · doi:10.1145/2090236.2090255 · Cited by 3,501
Fair prediction with disparate impact: a study of bias in recidivism prediction instruments
Chouldechova, A. (2017) · Big Data · doi:10.1089/big.2016.0047 · Cited by 2,159
Bellamy, R. K. E., Dey, K., Hind, M., Hoffman, S. C., Houde, S., Kannan, K., Lohia, P., Martino, J., Mehta, S., Mojsilovic, A., et al. (2018) · arXiv · doi:10.48550/arxiv.1810.01943 · Cited by 1,581
Algorithmic Decision Making and the Cost of Fairness
Corbett-Davies, S., Pierson, E., Feller, A., Goel, S., & Huq, A. (2017) · Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining · doi:10.1145/3097983.3098095 · Cited by 1,149
Fairness definitions explained
Verma, S., & Rubin, J. (2018) · Proceedings of the International Workshop on Software Fairness · doi:10.1145/3194770.3194776 · Cited by 1,124
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 · cited 1×
“Binns (2018) discusses through the lens of moral and political philosophy the de(cid:12)nitions of \fair" and \non-discriminatory" as they apply to algorithmic decision-making systems.”
BackgroundAI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias
Bellamy, R. K. E., Dey, K., Hind, M., Hoffman, S. C., Houde, S., Kannan, K., Lohia, P., Martino, J., Mehta, S., Mojsilović, A., et al. (2019) · IBM Journal of Research and Development · doi:10.1147/jrd.2019.2942287 · Cited by 884
Predictive Policing: The Role of Crime Forecasting in Law Enforcement Operations
Perry, W., McInnis, B., Price, C., Smith, S., & Hollywood, J. (2013) · doi:10.7249/rr233 · Cited by 693
Lum, K., & Isaac, W. (2016) · Significance · doi:10.1111/j.1740-9713.2016.00960.x · Cited by 611
Research works printed but not linked: 7
- Bakke E (2018) Predictive policing: the argument for public transparency. NYU Ann Surv Am L 74:131
- Chouldechova A (2017) Fair prediction with disparate impact: a study of bias in recidivism prediction instruments. Big Data 5(2):153–163 · DOI · Paper page
- Ferguson AG (2016) Policing predictive policing. Wash UL Rev 94:1109
- Hardt M, Price E, Srebro N (2016) Equality of opportunity in supervised learning. In: Advances in neural information processing systems, pp 3315–3323
- Kusner MJ, Loftus J, Russell C, Silva R (2017) Counterfactual fairness. In: Advances in neural information processing systems, pp 4066–4076
- Richardson R, Schultz J, Crawford K (2019) Dirty data, bad predictions: how civil rights violations impact police data, predictive policing systems, and justice. New York University Law Review Online, Forthcoming
- Ridgeway G (2013) The pitfalls of preduction. NIJ J 271:34–40
Cited by
Sorted by citations
Crime Prediction Using Machine Learning and Deep Learning: A Systematic Review and Future Directions
Mandalapu, V., Elluri, L., Vyas, P., & Roy, N. (2023) · IEEE Access · doi:10.1109/access.2023.3286344 · Cited by 201
“biases or lead to discrimination [74], [75].”
AI Fairness in Data Management and Analytics: A Review on Challenges, Methodologies and Applications
Chen, P., Wu, L., & Wang, L. (2023) · Applied Sciences · doi:10.3390/app131810258 · Cited by 155
A Comprehensive Survey of Deep Learning Approaches in Image Processing
Τρίγκα, Μ., & Dritsas, E. (2025) · Sensors · doi:10.3390/s25020531 · Cited by 174
Explainable AI and Law: An Evidential Survey
Richmond, K. M., Muddamsetty, S. M., Gammeltoft‐Hansen, T., Olsen, H. P., & Moeslund, T. B. (2023) · Digital Society · doi:10.1007/s44206-023-00081-z · Cited by 117
“The present article thus seeks to address limitations in previously published surveys (Alikhademi et al., 2022; Atkinson & Bench-Capon, 2019), centrally the failure to account for the heterogeneous nature of reasoning, adjudication, and administrative decision-making across legal sub-domains.”
Explainable AI for Cyber-Physical Systems: Issues and Challenges
Hoenig, A., Roy, K., Acquaah, Y. T., Yi, S., & Desai, S. S. (2024) · IEEE Access · doi:10.1109/access.2024.3395444 · Cited by 98
“Machine learning models are prone to repeating existing systemic bias from human decision-makers [25].”
Background
Metadata
- Authors
- Alikhademi, K., Drobina, E., Prioleau, D., Richardson, B., Purves, D., & Gilbert, J. E.
- Affiliations
- University of Florida (US)
- Corresponding author
- Alikhademi, Kiana
- Venue
- Artificial Intelligence and Law
- Published
- 2021-04-15
- Volume
- 30
- Issue
- 1
- Pages
- 1-17
- ISSN
- 0924-8463 (ISSN-L)
- 1572-8382
- OpenAlex
- W3155016818
- Cited by
- 167
- References
- 53
- Citations by year
- 2026: 29 · 2025: 26 · 2024: 27 · 2023: 69 · 2022: 14 · 2021: 2
- FWCI
- 35.01
- Type
- journal article
- Language
- en
- Update notices
- correction (2021-08-28)
- Open access
- closed
- Locations
- Artificial Intelligence and Law (publishedVersion)
- Funders
- NSF (1917712)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Social Sciences › Law › Artificial Intelligence in Law
- Social Sciences › Political Science and International Relations › Policing Practices and Perceptions
- Keywords
- predictive policing, algorithmic fairness, indirect discrimination, systemic bias, criminal justice, algorithmic bias, social justice
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