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Fair prediction with disparate impact: a study of bias in recidivism prediction instruments

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Certifying and Removing Disparate Impact

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Equality of Opportunity

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Automated Experiments on Ad Privacy Settings: A Tale of Opacity, Choice, and Discrimination

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Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment

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Classifying without discriminating

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Decision Theory for Discrimination-Aware Classification

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Measuring discrimination in algorithmic decision making

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On the (im)possibility of fairness

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The Statistical Physics of Learning (in a nutshell):News from the stoneage of neural networks

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Using t-closeness anonymity to control for non-discrimination

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Using t-closeness anonymity to control for non-discrimination

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Bias and Fairness in Large Language Models: A Survey

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Towards a standard for identifying and managing bias in artificial intelligence

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FA*IR: A Fair Top-k Ranking Algorithm

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50 Years of Test (Un)fairness: Lessons for Machine Learning

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Auditing large language models: a three-layered approach

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The Fallacy of AI Functionality

Raji, I. D., Kumar, I. E., Horowitz, A., & Selbst, A. (2022) · 2022 ACM Conference on Fairness Accountability and Transparency · doi:10.1145/3531146.3533158 · Cited by 251 · see citing works

Five sources of bias in natural language processing

Hovy, D., & Prabhumoye, S. (2021) · Language and Linguistics Compass · doi:10.1111/lnc3.12432 · Cited by 298 · see citing works

Fairness in recommender systems: research landscape and future directions

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An empirical characterization of fair machine learning for clinical risk prediction

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Fairness in rankings and recommendations: an overview

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The Forgotten Margins of AI Ethics

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Algorithmic fairness datasets: the story so far

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A survey on interpretable reinforcement learning

Glanois, C., Weng, P., Zimmer, M., Li, D., Yang, T., Hao, J., & Liu, W. (2024) · Machine Learning · doi:10.1007/s10994-024-06543-w · Cited by 138 · see citing works

Policy advice and best practices on bias and fairness in AI

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AI auditing: The Broken Bus on the Road to AI Accountability

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Escaping the Impossibility of Fairness: From Formal to Substantive Algorithmic Fairness

Green, B. (2022) · Philosophy & Technology · doi:10.1007/s13347-022-00584-6 · Cited by 100 · see citing works

Fairness in Ranking, Part II: Learning-to-Rank and Recommender Systems

Zehlike, M., Yang, K., & Stoyanovich, J. (2022) · ACM Computing Surveys · doi:10.1145/3533380 · Cited by 93 · see citing works

Public procurement of artificial intelligence systems: new risks and future proofing

Hickok, M. (2024) · AI & SOCIETY · doi:10.1007/s00146-022-01572-2 · Cited by 81 · see citing works

Information Retrieval

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How do we assess the trustworthiness of AI? Introducing the trustworthiness assessment model (TrAM)

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MAAT: a novel ensemble approach to addressing fairness and performance bugs for machine learning software

Chen, Z., Zhang, J. M., Sarro, F., & Harman, M. (2022) · ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) · doi:10.1145/3540250.3549093 · Cited by 74 · see citing works

Trustworthy human-AI partnerships

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Conceptualising fairness: three pillars for medical algorithms and health equity

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Meta Balanced Network for Fair Face Recognition

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Evaluation Gaps in Machine Learning Practice

Hutchinson, B., Rostamzadeh, N., Greer, C., Heller, K., & Prabhakaran, V. (2022) · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · doi:10.1145/3531146.3533233 · Cited by 75 · see citing works

Sustainable AI and the third wave of AI ethics: a structural turn

Bolte, L., & van Wynsberghe, A. (2024) · AI and Ethics · doi:10.1007/s43681-024-00522-6 · Cited by 62 · see citing works

You reap what you sow: On the Challenges of Bias Evaluation Under Multilingual Settings

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Investigating Practices and Opportunities for Cross-functional Collaboration around AI Fairness in Industry Practice

Deng, W. H., Yildirim, N., Chang, M., Eslami, M., Holstein, K., & Madaio, M. (2023) · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · doi:10.1145/3593013.3594037 · Cited by 57 · see citing works

Fair ranking: a critical review, challenges, and future directions

Patro, G. K., Porcaro, L., Mitchell, L., Zhang, Q., Zehlike, M., & Garg, N. (2022) · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · doi:10.1145/3531146.3533238 · Cited by 61 · see citing works

Data justice

Dencik, L., & Sánchez‐Monedero, J. (2022) · Internet Policy Review · doi:10.14763/2022.1.1615 · Cited by 59 · see citing works

“It is currently hodgepodge”: Examining AI/ML Practitioners’ Challenges during Co-production of Responsible AI Values

Varanasi, R. A., & Goyal, N. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3580903 · Cited by 52 · see citing works

Harnessing human and machine intelligence for planetary-level climate action

Debnath, R., Creutzig, F., Sovacool, B. K., & Shuckburgh, E. F. (2023) · npj Climate Action · doi:10.1038/s44168-023-00056-3 · Cited by 53 · see citing works

Fairness and justice through automation in China's smart courts

Papagianneas, S., & Junius, N. (2023) · Computer law & security review · doi:10.1016/j.clsr.2023.105897 · Cited by 60 · see citing works

On the Moral Justification of Statistical Parity

Hertweck, C., Heitz, C., & Loi, M. (2021) · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · doi:10.1145/3442188.3445936 · Cited by 49 · see citing works

Algorithmic individual fairness and healthcare: a scoping review

Anderson, J. W., & Visweswaran, S. (2024) · JAMIA Open · doi:10.1093/jamiaopen/ooae149 · Cited by 43 · see citing works

Responsible data management

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Inherent Limitations of AI Fairness

Buyl, M., & Bie, T. D. (2022) · Communications of the ACM · doi:10.1145/3624700 · Cited by 44 · see citing works

EXplainable Artificial Intelligence (XAI) for facilitating recognition of algorithmic bias: An experiment from imposed users’ perspectives

Chuan, C., Sun, R., Tian, S., & Tsai, W. S. (2024) · Telematics and Informatics · doi:10.1016/j.tele.2024.102135 · Cited by 37 · see citing works

A Systematic Review of Ethical Concerns with Voice Assistants

Seymour, W., Zhan, X., Coté, M., & Such, J. M. (2023) · Proceedings of the AAAI/ACM Conference on AI Ethics and Society · doi:10.1145/3600211.3604679 · Cited by 41 · see citing works

A Systematic Review of Fairness, Accountability, Transparency, and Ethics in Information Retrieval

Bernard, N., & Balog, K. (2023) · ACM Computing Surveys · doi:10.1145/3637211 · Cited by 43 · see citing works

Algorithmic decision-making in financial services: economic and normative outcomes in consumer credit

Sargeant, H. (2022) · AI and Ethics · doi:10.1007/s43681-022-00236-7 · Cited by 47 · see citing works

Towards learning trustworthily, automatically, and with guarantees on graphs: An overview

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Out of Context: Investigating the Bias and Fairness Concerns of “Artificial Intelligence as a Service”

Lewicki, K., Lee, M. S. A., Cobbe, J., & Singh, J. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581463 · Cited by 30 · see citing works

Towards user-oriented privacy for recommender system data: A personalization-based approach to gender obfuscation for user profiles

Slokom, M., Hanjalic, A., & Larson, M. (2021) · Information Processing & Management · doi:10.1016/j.ipm.2021.102722 · Cited by 31 · see citing works

Disambiguating Algorithmic Bias: From Neutrality to Justice

Edenberg, E., & Wood, A. (2023) · Proceedings of the AAAI/ACM Conference on AI Ethics and Society · doi:10.1145/3600211.3604695 · Cited by 35 · see citing works

AI and discriminative decisions in recruitment: Challenging the core assumptions

Seppälä, P., & Małecka, M. (2024) · Big Data & Society · doi:10.1177/20539517241235872 · Cited by 56 · see citing works

FairRankVis: A Visual Analytics Framework for Exploring Algorithmic Fairness in Graph Mining Models

Xie, T., Ma, Y., Kang, J. L., Tong, H., & Maciejewski, R. (2021) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2021.3114850 · Cited by 30 · see citing works

Multi-disciplinary fairness considerations in machine learning for clinical trials

Chien, I., Deliu, N., Turner, R. E., Weller, A., Villar, S. S., & Kilbertus, N. (2022) · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · doi:10.1145/3531146.3533154 · Cited by 31 · see citing works

From fair predictions to just decisions? Conceptualizing algorithmic fairness and distributive justice in the context of data-driven decision-making

Kuppler, M., Kern, C. A., Bach, R. L., & Kreuter, F. (2022) · Frontiers in Sociology · doi:10.3389/fsoc.2022.883999 · Cited by 30 · see citing works

Competing narratives in AI ethics: a defense of sociotechnical pragmatism

Watson, D., Mökander, J., & Floridi, L. (2024) · AI & Society · doi:10.1007/s00146-024-02128-2 · Cited by 36 · see citing works

Semantic Web technologies and bias in artificial intelligence: A systematic literature review

Lobo, P. R., Daga, E., Alani, H., & Fernández, M. (2022) · Semantic Web · doi:10.3233/sw-223041 · Cited by 27 · see citing works

Fairness and Risk: An Ethical Argument for a Group Fairness Definition Insurers Can Use

Baumann, J., & Loi, M. (2023) · Philosophy & Technology · doi:10.1007/s13347-023-00624-9 · Cited by 32 · see citing works

Implementing Responsible AI: Tensions and Trade-Offs Between Ethics Aspects

Sanderson, C., Douglas, D., & Lu, Q. (2023) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn54540.2023.10191274 · Cited by 35 · see citing works

On the current and emerging challenges of developing fair and ethical AI solutions in financial services

Kurshan, E., Chen, J., Storchan, V., & Shen, H. (2021) · ACM International Conference on AI in Finance (ICAIF) · doi:10.1145/3490354.3494408 · Cited by 26 · see citing works

Politik in der digitalen Gesellschaft

Hofmann, J., Kersting, N., Ritzi, C., & Schünemann, W. J. (2019) · Politik in der digitalen Gesellschaft · doi:10.14361/9783839448649 · Cited by 29 · see citing works

Fairness and explainability in automatic decision-making systems. A challenge for computer science and law

Kirat, T., Tambou, O., Do, V., & Tsoukiàs, A. (2023) · EURO Journal on Decision Processes · doi:10.1016/j.ejdp.2023.100036 · Cited by 24 · see citing works

What is Proxy Discrimination?

Tschantz, M. C. (2022) · 2022 ACM Conference on Fairness Accountability and Transparency · doi:10.1145/3531146.3533242 · Cited by 25 · see citing works

The multisided complexity of fairness in recommender systems

Sonboli, N., Burke, R., Ekstrand, M. D., & Mehrotra, R. (2022) · AI Magazine · doi:10.1002/aaai.12054 · Cited by 24 · see citing works

Equalizing Credit Opportunity in Algorithms: Aligning Algorithmic Fairness Research with U.S. Fair Lending Regulation

Kumar, I. E., Hines, K. E., & Dickerson, J. P. (2022) · Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society · doi:10.1145/3514094.3534154 · Cited by 24 · see citing works

Counterfactually Fair Automatic Speech Recognition

Sar, L., Hasegawa‐Johnson, M., & Yoo, C. D. (2021) · IEEE/ACM Transactions on Audio Speech and Language Processing · doi:10.1109/taslp.2021.3126949 · Cited by 23 · see citing works

Academic performance prediction in a gender-imbalanced environment

Sapieżyński, P., Kassarnig, V., & Wilson, C. (2018) · doi:10.18122/b20q5r · Cited by 23 · see citing works

A comparison of approaches to improve worst-case predictive model performance over patient subpopulations

Pfohl, S. R., Zhang, H., Xu, Y., Foryciarz, A., Ghassemi, M., & Shah, N. H. (2022) · Scientific Reports · doi:10.1038/s41598-022-07167-7 · Cited by 22 · see citing works

BEAT Unintended Bias in Personalized Policies

Ascarza, E., & Israeli, A. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2115293119 · Cited by 21 · see citing works

Triangular Trade-off between Robustness, Accuracy, and Fairness in Deep Neural Networks: A Survey

Li, J., & Li, G. (2024) · ACM Computing Surveys · doi:10.1145/3645088 · Cited by 21 · see citing works

How Do We Assess the Trustworthiness of AI? Introducing the Trustworthiness Assessment Model (TrAM)

Schlicker, N., Baum, K., Uhde, A., Sterz, S., Hirsch, M. C., & Langer, M. (2022) · doi:10.31234/osf.io/qhwvx · Cited by 79 · see citing works

Macro Ethics Principles for Responsible AI Systems: Taxonomy and Directions

Woodgate, J., & Ajmeri, N. (2024) · ACM Computing Surveys · doi:10.1145/3672394 · Cited by 20 · see citing works

Specification overfitting in artificial intelligence

Roth, B., de Araujo, P. H. L., Xia, Y., Kaltenbrunner, S., & Korab, C. (2024) · Artificial Intelligence Review · doi:10.1007/s10462-024-11040-6 · Cited by 21 · see citing works

FairEd: A Systematic Fairness Analysis Approach Applied in a Higher Educational Context

Vásquez, J., Gitiaux, X., Ortega, C., & Rangwala, H. (2022) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/3506860.3506902 · Cited by 19 · see citing works

Bias on Demand: A Modelling Framework That Generates Synthetic Data With Bias

Baumann, J., Castelnovo, A., Crupi, R., Inverardi, N., & Regoli, D. (2023) · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · doi:10.1145/3593013.3594058 · Cited by 19 · see citing works

Algorithmic Pluralism: A Structural Approach To Equal Opportunity

Jain, S., Suriyakumar, V. M., Creel, K., & Wilson, A. (2024) · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · doi:10.1145/3630106.3658899 · Cited by 19 · see citing works

“It’s Like the Value System in the Loop”: Domain Experts’ Values Expectations for NLP Automation

Showkat, D., & Baumer, E. P. S. (2022) · Designing Interactive Systems Conference · doi:10.1145/3532106.3533483 · Cited by 18 · see citing works

On (assessing) the fairness of risk score models

Petersen, E., Ganz, M., Holm, S., & Feragen, A. (2023) · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · doi:10.1145/3593013.3594045 · Cited by 21 · see citing works

FairBalance: How to Achieve Equalized Odds With Data Pre-Processing

Yu, Z., Chakraborty, J., & Menzies, T. (2024) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2024.3431445 · Cited by 16 · see citing works

Sustainable artificial intelligence-driven classroom assessment in higher institutions: Lessons from Estonia, China, the USA, and Australia for Nigeria

Ofem, U. J., & Chukwujama, G. (2024) · European Journal of Interactive Multimedia and Education · doi:10.30935/ejimed/15265 · Cited by 15 · see citing works

librec-auto: A Tool for Recommender Systems Experimentation

Sonboli, N., Mansoury, M., Guo, Z., Kadekodi, S., Liu, W., Liu, Z., Schwartz, A., & Burke, R. (2021) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3459637.3482006 · Cited by 14 · see citing works

Fairness of Academic Performance Prediction for the Distribution of Support Measures for Students: Differences in Perceived Fairness of Distributive Justice Norms

Lünich, M., Keller, B., & Marcinkowski, F. (2023) · Technology Knowledge and Learning · doi:10.1007/s10758-023-09698-y · Cited by 21 · see citing works

Dynamic Fairness-aware Recommendation Through Multi-agent Social Choice

Aird, A., Farastu, P., Sun, J. J., Štefancová, E., All, C., Voida, A., Mattei, N., & Burke, R. (2024) · ACM Transactions on Recommender Systems · doi:10.1145/3690653 · Cited by 14 · see citing works

A new era of public procurement: critical issues of procuring artificial intelligence systems to produce public services

Aboelazm, K. S. (2025) · International Journal of Law and Management · doi:10.1108/ijlma-06-2024-0208 · Cited by 17 · see citing works

A decade of gender bias in machine translation

Savoldi, B., Bastings, J., Bentivogli, L., & Vanmassenhove, E. (2025) · Patterns · doi:10.1016/j.patter.2025.101257 · Cited by 14 · see citing works

Algorithmic Social Injustices: Antecedents and Mitigations

Tanriverdi̇, H., & Akinyemi, J.-P. O. (2025) · MIS Quarterly · doi:10.25300/misq/2025/18314 · Cited by 13 · see citing works

Generative AI in higher education: Ethical and behavioral factors influencing students’ intentions to use ChatGPT

Rizun, N., Bordean, O. N., Nikiforova, A., Beleiu, I. N., & Revina, A. (2026) · Computers and Education Open · doi:10.1016/j.caeo.2026.100336 · Cited by 22 · see citing works

iFlipper: Label Flipping for Individual Fairness

Zhang, H., Tae, K. H., Park, J., Chu, X., & Whang, S. E. (2023) · Proceedings of the ACM on Management of Data · doi:10.1145/3588688 · Cited by 13 · see citing works

How to be fair? A study of label and selection bias

Favier, M., Calders, T., Pinxteren, S., & Meyer, J. (2023) · Machine Learning · doi:10.1007/s10994-023-06401-1 · Cited by 13 · see citing works

Beyond incompatibility: Trade-offs between mutually exclusive fairness criteria in machine learning and law

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Multi-agent Social Choice for Dynamic Fairness-aware Recommendation

Burke, R., Mattei, N., Grozin, V., Voida, A., & Sonboli, N. (2022) · ACM Conference on User Modeling, Adaptation and Personalization (UMAP) · doi:10.1145/3511047.3538032 · Cited by 13 · see citing works

Fair Machine Learning in Healthcare: A Survey

Feng, Q., Du, M., Zou, N., & Hu, X. (2025) · IEEE Transactions on Artificial Intelligence · doi:10.1109/tai.2024.3361836 · Cited by 12 · see citing works

Uncovering Bias in Personal Informatics

Yfantidou, S., Sermpezis, P., Vakali, A. I., & Baeza-Yates, R. A. (2023) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3610914 · Cited by 13 · see citing works

On prediction-modelers and decision-makers: why fairness requires more than a fair prediction model

Scantamburlo, T., Baumann, J., & Heitz, C. (2024) · AI & Society · doi:10.1007/s00146-024-01886-3 · Cited by 13 · see citing works

Fairness in Search Systems

Yi, F., Singh, A., & Tao, Z. (2024) · Foundations and Trends® in Information Retrieval · doi:10.1561/1500000101 · Cited by 12 · see citing works

What Is Fair? Defining Fairness in Machine Learning for Health

Gao, J., Chou, B., McCaw, Z. R., Thurston, H., Varghese, P., Hong, C., & Gronsbell, J. L. (2025) · Statistics in Medicine · doi:10.1002/sim.70234 · Cited by 14 · see citing works

Ethical guidelines for the use of artificial intelligence and the challenges from value conflicts

Petersen, T. (2021) · Etikk i Praksis: Nordic Journal of Applied Ethics · doi:10.5324/eip.v15i1.3756 · Cited by 13 · see citing works

Rationing Scarce Healthcare Capacity: A Study of the Ventilator Allocation Guidelines During the COVID-19 Pandemic

Anderson, D. R., Aydinliyim, T., Bjarnadóttir, M. V., Çil, E. B., & Anderson, M. R. (2022) · Production and Operations Management · doi:10.1111/poms.13934 · Cited by 11 · see citing works

Artificial Intelligence and Cancer Control: Toward Prioritizing Justice, Equity, Diversity, and Inclusion (JEDI) in Emerging Decision Support Technologies

Taber, P. A., Armin, J. S., Orozco, G., Fiol, G. D., Erdrich, J., Kawamoto, K., & Israni, S. T. (2023) · Current Oncology Reports · doi:10.1007/s11912-023-01376-7 · Cited by 11 · see citing works

Introduction to The Special Section on Bias and Fairness in AI

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Decoding the algorithmic operations of Australia's National Disability Insurance Scheme

van Toorn, G., & Carney, T. (2024) · Australian Journal of Social Issues · doi:10.1002/ajs4.342 · Cited by 10 · see citing works

Software doping analysis for human oversight

Biewer, S., Baum, K. L., Sterz, S., Hermanns, H., Hetmank, S., Langer, M., Lauber-Rönsberg, A., & Lehr, F. (2024) · Formal Methods in System Design · doi:10.1007/s10703-024-00445-2 · Cited by 10 · see citing works

Data-Centric Factors in Algorithmic Fairness

Li, N., Goel, N., & Ash, E. (2022) · Proceedings of the AAAI/ACM Conference on AI Ethics and Society · doi:10.1145/3514094.3534147 · Cited by 12 · see citing works

Balancing Act: Evaluating People’s Perceptions of Fair Ranking Metrics

Alkhathlan, M., Cachel, K., Shrestha, H., Harrison, L., & Rundensteiner, E. A. (2024) · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · doi:10.1145/3630106.3659018 · Cited by 9 · see citing works

Recommender Systems

Castells, P., & Jannach, D. (2024) · ACM eBooks · doi:10.1145/3674127.3674131 · Cited by 9 · see citing works

Fairness Hacking: The Malicious Practice of Shrouding Unfairness in Algorithms

Meding, K., & Hagendorff, T. (2024) · Philosophy & Technology · doi:10.1007/s13347-023-00679-8 · Cited by 10 · see citing works

A note on the impossibility of "fairness".Preprint

Miconi, T. (2017) · arXiv (Cornell University) · Cited by 1 · see citing works

Revisiting Fairness Impossibility with Endogenous Behavior

Penn, E. M., & Patty, J. W. (2026) · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · doi:10.1145/3805689.3812247

Formalizing fairness

Krakovsky, M. (2022) · Communications of the ACM · doi:10.1145/3542815 · Cited by 3 · see citing works

Progress, Justness, and Fairness

van Glabbeek, R., & Höfner, P. (2019) · ACM Computing Surveys · doi:10.1145/3329125 · Cited by 42 · see citing works

Fairness without interpersonal comparisons

Gärdenfors, P. (1978) · Theoria · doi:10.1111/j.1755-2567.1978.tb00168.x · Cited by 11 · see citing works