Fairness in machine learning: A survey

Cited by (646)

Items 401–500 of 646

1. A Case Study of the FRIA Project: Supporting Human Evaluation of an AI-Based Hiring System
   Lucilla Gatt, Ilaria Amelia Caggiano, Maria Cristina Gaeta, Emiliano Troisi, Maria Teresa Lo Conte, Roberto Trasarti, Roberta Savella, Marco Di Cristo, Francesca Pratesi · 2025 · Lecture notes in computer science
2. FairPrompt: Efficient Multi-Objective Prompt Optimization for Fairness Testing in Conversational AI Systems
   Zunaira Shafqat, Atif Aftab Ahmed Jilani, Nigar Azhar Butt, Shafiq Ur Rehman, Muhammad Usman Khalid, Volker Gruhn · 2025 · IEEE Access
3. FLClustering: A Fair and Robust Federated Learning Approach in Heterogeneous Environments
   Li Lin, Wei Shen, Chi-Ho Song, Shuai Ma · 2025 · IEEE Transactions on Computational Social Systems
4. Fairness in Machine Learning: A Review for Statisticians
   Xianwen He, Yao Li · 2025 · Journal of the American Statistical Association
5. A Generative Agentic AI Framework for Analysis and Debiasing of Datasets and Machine Learning Models
   Jayana Nirmani Gunaweera, Lakshitha Gunasekara, Hasanka Dileesha Rajapakse · 2025 · Annual Conference of the IEEE Industrial Electronics Society (IECON)
6. FairRegBoost: An End-to-End Data Processing Framework for Fair and Scalable Regression
   Nico Lässig, Melanie Herschel · 2025 · ACM International Conference on Information and Knowledge Management (CIKM)
7. An optimization-based algorithm for fair and calibrated synthetic data generation
   Jan Pablo Burgard, João Vitor Pamplona, Maria Eduarda Pinheiro · 2025 · Computers & Operations Research
8. Predictive hermeneutics: bias, culture, and the predictive mind
   Jennifer J. Devereaux · 2025 · Phenomenology and the Cognitive Sciences
9. Multi-criteria Decision Analysis as a tool for post-processing bias mitigation in machine learning algorithms
   Guilherme Lima Correa, Betania Silva Carneiro Campello, Leonardo Tomazeli Duarte · 2025 · Computers & Industrial Engineering
10. Assessing the Role of Sensitive Attributes in Adversarial Debiasing
    Diego Minatel, Antonio Rafael Sabino Parmezan, Vinicius M. A. Souza, Solange O. Rezende · 2025
11. Artificial Intelligence Research as a Continuous Clinical Service
    Yixi Xu, Rahul Dodhia, Juan M. Lavista Ferres, William B. Weeks · 2025 · Mayo Clinic Proceedings Digital Health
12. Human-centered Sequential Load Restoration in Transmission Networks using Reinforcement Learning
    Kasra Mazarei Saadabadi, Hamidreza Nazaripouya, Alfredo A. Martinez‐Morales · 2025
13. Is Diversity a Meaningful Metric in Fairness Testing?
    Kazuki Funamoto, Takashi Kitamura, Shingo Takada · 2025 · Proceedings of the ... ACM-IEEE International Symposium on Empirical Software Engineering and Measurement/International Symposium on Empirical Software Engineering and Measurement
14. Inference-Time Rule Eraser: Fair Recognition via Distilling and Removing Biased Rules
    Yi Zhang, Dongyuan Lu, Jitao Sang · 2026 · IEEE Transactions on Multimedia
15. LIME-EC: an Agnostic Approach to Quantifying Model Interpretability using Explanation Clustering
    Cassio Soares Carvalho, Júlio C. B. Mattos, Marilton Sanchotene de Aguiar · 2025 · International Conference on Soft Computing & Machine Intelligence (ISCMI)
16. Confronting Challenges of the Neuro-Symbolic AI (NSAI) in Human-Centered Computing (HCC), Healthcare, Education and Research, Emphasizing Ethics and Safety- an Interdisciplinary Qualitative Survey
    Aniqa Afzal · 2025 · IEEE Smart World Congress (SWC)
17. A Systematic Review on Human Roles, Solutions, and Methodological Approaches to Address Bias in AI
    Amal Hashky, Eric D. Ragan · 2026 · ACM Computing Surveys
18. A data-centric approach to detecting and mitigating demographic bias in pediatric mental health text
    Julia Ive, Paulina Bondaronek, Vishal Yadav, Daniel Santel, Tracy A. Glauser, Jeffrey Robert Strawn, Greeshma A. Agasthya, Jordan Tschida, Sanghyun Choo, Mayanka Chandrashekar et al. · 2026 · Communications Medicine
19. The emerging relevance of relational justice within algorithmic fairness research: a systematic literature review
    Laila Wegner, Marie Mirsch, Carmen Leicht-Scholten · 2026 · AI and Ethics
20. A Neurosymbolic Approach to Counterfactual Fairness
    Xenia Heilmann, Chiara Manganini, Mattia Cerrato, Leonhard Kestel, Vaishak Belle · 2026 · Neurosymbolic Artificial Intelligence
21. Ethical and Governance Challenges of AI in Accounting
    Ibrokhimjon U. Tursunaliev, Mukaddas Sh. Ergasheva, Dildora Jahongir qizi Khaydarova, Hilolaoy O. Egamberdiyeva · 2026 · Advances in computational intelligence and robotics book series
22. Strategies for mitigating artificial intelligence bias in healthcare: a systematic review
    Kais Gadhoumi, Rashaud Senior, Sijia Wei, Leila Ledbetter, Michael D. Green, Bethany D Bonner, Yvonne Mosley, Katie Seidler, Kristle Green, D M Lee et al. · 2026 · JAMIA Open
23. Artificial intelligence and decision support in applied ecology
    Elmontaserbellah Ammar, Aashna Sharma, Tom August, Jake Emmerson Bicknell, Katherine L. Boughey, Carolyn E. Dunford, Don A. Driscoll, Sicily Fiennes, Javier Lopatin, Melanie Hartley et al. · 2026 · Journal of Applied Ecology
24. Intelligent and inclusive EEG-driven authentication for gender fairness and cognitive impairment
    Toan Quoc Nguyen, Chenhan Zhang, Linh Le, David Williams King, Long Tuan Vo, Juliette Murris, Shiyao Zhang, Nghia Duong Trung · 2026 · Intelligence & Robotics
25. Towards a fair and transparent early warning system for identifying students at risk of academic failure
    Mohamed El Jihaoui, Oum El Kheir Abra, Khalifa Mansouri · 2026 · Frontiers in Education
26. FairRF: Multi-Objective Search for Single and Intersectional Software Fairness
    Giordano d’Aloisio, Max Hort, Rebecca Moussa, Federica Sarro · 2026 · ACM/IEEE International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)
27. Fairness Across Fields: Comparing Software Engineering and Human Sciences Perspectives
    Lucas Valença, Ronnie de Souza Santos · 2026 · ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE)
28. Improving Individual Fairness in Fuzzy Classifiers via Evolutionary Multi-Objective Optimization
    Takeru Konishi, Naoki Masuyama, Yusuke Nojima · 2026 · IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
29. Navigating fairness in artificial intelligence-based prediction models: theoretical constructs and practical applications
    Siri Lise van der Meijden, Yuqing Wang, Madelena Y. Ng, M. Sesmu Arbous, Bart F. Geerts, Ewout Willem Steyerberg, Tina Hernandez‐Boussard · 2026 · The Lancet Digital Health
30. Challenges in medical algorithmic fairness
    Anand Srinivasan, Durga Vahini Sritharan, Sanjay Aneja, Ilana B. Richman · 2026 · JNCI Cancer Spectrum
31. Measuring Gender Bias in Word Embeddings for Russian Language
    A.S. Pestova · 2021 · Computational Linguistics and Intellectual Technologies
32. Machine Learning Bias in Computer Vision: Why do I have to care?
    Camila Laranjeira, Virgínia Fernandes Mota, Jefersson Alex dos Santos · 2021 · SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)
33. Künstliche Intelligenz
    Frauke Rostalski, Deutschland · 2022 · Mohr Siebeck eBooks
34. UN CONCEPTO VIAJERO
    Noelia Beltramelli Gula, Camila Ferro, María Goñi Mazzitelli, Lorena Etcheverry, Martín Rocamora · 2023 · Novos Rumos Sociológicos
35. Identifying Selection Bias from Observational Data
    David Kaltenpoth, Jilles Vreeken · 2023 · Proceedings of the AAAI Conference on Artificial Intelligence
36. Towards an AutoML System for Fair Classifications∗
    Nico Lässig · 2023 · IEEE International Conference on Data Engineering (ICDE)
37. Fairer Machine Learning Through the Hybrid of Multi-objective Evolutionary Learning and Adversarial Learning
    Shenhao Gui, Qingquan Zhang, Changwu Huang, Bo Yuan · 2023 · International Joint Conference on Neural Networks (IJCNN)
38. An Ontology for Reasoning About Fairness in Regression and Machine Learning
    Jade S. Franklin, Hannah Powers, John S. Erickson, Jamie Patricia McCusker, Deborah L. McGuinness, Kristin P. Bennett · 2023 · Lecture notes in computer science
39. Fairness in Survival Outcome Prediction for Medical Treatments
    Yunqi Li, Hanxiong Chen, Lanjing Zhang, Yongfeng Zhang · 2024 · Conference on Information Sciences and Systems
40. FairerML: An Extensible Platform for Analysing, Visualising, and Mitigating Biases in Machine Learning [Application Notes]
    Bo Yuan, Shenhao Gui, Qingquan Zhang, Ziqi Wang, Junyi Wen, Bifei Mao, Jialin Liu, Xin Yao · 2024 · IEEE Computational Intelligence Magazine
41. Simulating Counterfactuals
    Juha Karvanen, Santtu Tikka, Matti Vihola · 2024 · Journal of Artificial Intelligence Research
42. Utilization of geospatial distribution in the measurement of study cohort representativeness
    Keith Feldman, Natalie J. Kane, Stacey Daniels-Young, Bruce Reed, Jessica Welch, Lauren Fitzpatrick, Mark Allan Hoffman, Andrea Bradley‐Ewing, Elin Grundberg · 2024 · Journal of Biomedical Informatics
43. Estudo experimental sobre justiça algorítmica aplicada em modelos de análise de crédito
    Tiago Almeida de Oliveira, João Batista de Oliveira, Tarcísio P. Farias, Erick W. R. Cruz, Leandro J. S. Andrade, Robespierre Pita · 2024 · Simpósio Brasileiro de Bancos de Dados (SBBD)
44. Fairness Auditing with Multi-Agent Collaboration
    Martijn de Vos, Akash Dhasade, Jade Garcia Bourrée, Anne-Marie Kermarrec, Erwan Le Merrer, Benoît Rottembourg, Gilles Trédan · 2024 · Frontiers in artificial intelligence and applications
45. Empirical Bayes Fairness in Linear Regression
    Emilio Carrizosa, Rafael Jiménez-Llamas, Pepa Ramírez‐Cobo · 2024 · Bayesian Analysis
46. Enforcing Equity in Neural Climate Emulators
    William Yik, Sam James Silva · 2025 · Geophysical Research Letters
47. Correct-by-Construction: Certified Individual Fairness through Neural Network Training
    Rui-Han Zhang, Jun Sun · 2025 · Proc. ACM Program. Lang.
48. Design and validation of a responsible artificial intelligence-based system for the referral of diabetic retinopathy patients
    Eduardo Ulises Moya-Sánchez, Abraham Sánchez-Pérez, Alejandro Zarate-Macías, Raul Nanclares, Edgar Villarreal-Padilla, Paulino Monroy Castillero, Alejandro Sánchez-Montes, Edtna Elvira Jáuregui-Ulloa, Héctor J. Moreno, Ulises Cortés · 2025 · Health Information Science and Systems
49. On The Fairness of Multitask Representation Learning
    Yingcong Li, Samet Oymak · 2023 · IEEE International Conference on Acoustics Speech and Signal Processing
50. RENATA: REpreseNtation And Training Alteration for Bias Mitigation.
    William Paul, Armin Hadžić, Neil Joshi, Philippe Burlina · 2020 · arXiv (Cornell University)
51. A Hybrid 2-stage Neural Optimization for Pareto Front Extraction
    Singh, Gurpreet, Soumyajit Sen Gupta, Matthew Lease, Clint N. Dawson · 2021 · arXiv (Cornell University)
52. Fairness and Robustness of Contrasting Explanations.
    André Artelt, Barbara Hammer · 2021 · arXiv (Cornell University)
53. Introducing a Family of Synthetic Datasets for Research on Bias in Machine Learning
    William Blanzeisky, Pádraig Cunningham, Kenneth Kennedy · 2021 · arXiv (Cornell University)
54. Measure Twice, Cut Once: Quantifying Bias and Fairness in Deep Neural Networks
    Cody Blakeney, Gentry Atkinson, Nathaniel Huish, Yan Yan, Vangelis Metris, Ziliang Zong · 2021 · arXiv (Cornell University)
55. Scalable Unidirectional Pareto Optimality for Multi-Task Learning with Constraints
    Soumyajit Sen Gupta, Gurpreet Singh, Bollapragada, Raghu, Lease, Matthew · 2021 · arXiv (Cornell University)
56. Contrastive Clustering: Toward Unsupervised Bias Reduction for Emotion and Sentiment Classification
    Jared Mowery · 2021 · arXiv (Cornell University)
57. Adaptation and Generalization for Unknown Sensitive Factors of Variations
    William Paul, Philippe Burlina · 2021 · arXiv (Cornell University)
58. Increasing Trust and Fairness in Machine Learning Applications within the Mortgage Industry
    Wessel van Zetten, Guus J. Ramackers, Holger H. Hoos · 2022 · SSRN Electronic Journal
59. On Prediction-Modelers and Decision-Makers: Why Fairness Requires More Than a Fair Prediction Model
    Teresa Scantamburlo, Joachim Baumann, Christoph Heitz · 2023 · arXiv (Cornell University)
60. Fairness by design in shared-energy allocation problems
    Zoé Fornier, Vincent Leclère, Pierre Pinson · 2024 · Research Square
61. Underdiagnosis Bias of Chest Radiograph Diagnostic AI can be Decomposed and Mitigated via Dataset Bias Attributions
    Yuta Kobayashi, Haoran Zhang, Harvineet Singh, Judy Wawira Gichoya, Shalmali D. Joshi · 2024 · medRxiv
62. O Funcionamento Diferencial dos Itens na Indução de Classificadores Mais Justos
    Diego Minatel · 2024
63. The Four Artificial Intelligence Apprehension Scales: Apprehension Towards Personal AI, General AI, Institutional AI, and Large Language Models
    Ala Yankouskaya, Mohamed Basel Almourad, Magnus Liebherr, Mohammad Mominur Rahman, Sameha Ahmed Ali Alshakhsi, Raian Ali · 2026 · Research Square
64. Advancing Health Equity through Multi-Level Fairness in Health Informatics
    Souligne, Nick, Subbian, Vignesh · 2026 · arXiv
65. Multi-Fair Pareto Boosting.
    Arjun G. Roy, Vasileios Iosifidis, Eirini Ntoutsi · 2021 · arXiv (Cornell University)
66. Deep Clustering based Fair Outlier Detection
    Hanyu Song, Peizhao Li, Hongfu Liu · 2021 · arXiv (Cornell University)
67. Generalizing Fairness: Discovery and Mitigation of Unknown Sensitive Attributes.
    William Paul, Philippe Burlina · 2021 · arXiv (Cornell University)
68. Ensuring Fairness Despite Differences in Environment
    Karan Deep Singh · 2021 · York University Digital Library (York University)
69. Derechos sociales en la constitución
    Rodolfo Capón Filas · 2006 · Hispana
70. Mitigating health disparities in hospital readmission
    Shaina Raza · 2022 · Research Square
71. On the Faithfulness of Conditional Probability Estimates: A Multi-objective Approach
    William Blanzeisky, Pádraig Cunningham · 2022 · Research Square
72. Fic Graph - Quantifying Fairness with Sensitive Attribute
    Olalekan Joseph Akintande, Olusanya Elisa Olubusoye · 2023 · SSRN Electronic Journal
73. Interactive active learning for fairness with partial group label
    Zeyu Yang, Jizhi Zhang, Fuli Feng, Chongming Gao, Qifan Wang, Xiangnan He · 2023 · AI Open
74. Data Informed Decision Bias
    Prathapa Dissanayake · 2023
75. Um estudo sobre a influência de métodos imparciais de análise de componentes principais em problemas de classificação
    Felipe Tetsuo Yamada · 2021
76. FairAC: Long-term Balancing between Accuracy and Fairness in Recommender Systems Using a Multi-Objective Deep Reinforcement Learning Framework
    Mohammad Amir Rezaei Gazik, Mehdy Roayaei · 2024 · Research Square
77. A Novel Information Theoretic Objective to Disentangle Representations for Fair Classification
    Pierre Colombo, Nathan Noiry, Guillaume Staerman, Pablo Piantanida · 2023
78. The Growth and Development of Data Security Using Cryptography Algorithms and Machine Learning Algorithms
    Raja V. · 2024 · Advances in information security, privacy, and ethics book series
79. The Unfairness of ε-Fairness
    Thorsten Schmidt, Tolulope Fadina · 2024 · SSRN Electronic Journal
80. Reflexive Co-Design: A Participatory Method to Design for Socially Responsible Technology Based on Responsible Research and Innovation
    Yuri Nakao · 2024 · SSRN Electronic Journal
81. The Fairness Stitch: A Novel Approach for Neural Network Debiasing
    Modar Sulaiman, Kallol Roy · 2024 · Acta Informatica Pragensia
82. Quantifying the Trade-Offs Between Dimensions of Trustworthy AI - An Empirical Study on Fairness, Explainability, Privacy, and Robustness
    Nils Kemmerzell, Annika Schreiner · 2024 · Lecture notes in computer science
83. A Comparative Study of Fairness and Bias in DecisionTree and Random Forest Machine Learning Models
    Swati Kashyap, Bhuvneshwari Bhuvneshwari, Sujal Mehta, Akashdeep · 2024 · International Conference on Emerging Innovations and Advanced Computing (INNOCOMP)
84. Fair overlap number of balls (Fair-ONB): an undersampling method for bias reduction based on data morphology
    José Daniel Pascual-Triana, Alberto Fernández, Paulo Nováis, Francisco Herrera · 2025 · Statistics
85. Regression Model Bias Evaluation by Estimating Conditional Densities with Gaussian Mixtures
    Wei Sun, Xuning Tang, Kuo‐Chu Chang · 2024 · International Conference on Information Fusion (FUSION)
86. FRINGE: context-aware FaiRness engineerING in complex software systEms
    Fabio Palomba, Andrea Di Sorbo, Davide Di Ruscio, Filomena Ferrucci, Gemma Catolino, Giammaria Giordano, Dario Di Dario, Gianmario Voria, Viviana Pentangelo, Maria Tortorella et al. · 2024 · Proceedings of the ... ACM-IEEE International Symposium on Empirical Software Engineering and Measurement/International Symposium on Empirical Software Engineering and Measurement
87. Fade: fairness-aware deep ensemble for quantifying uncertainty
    William Blanzeisky, Pádraig Cunningham · 2024 · Neural Computing and Applications
88. Looks Can Mislead: Feature-Based Explanations Do Not Reliably Improve Fairness of AI-Assisted Decisions
    Jakob Schoeffer, Maria De‐Arteaga, Niklas Kühl · 2025 · SSRN Electronic Journal
89. A Beam-Search Based Method to Select Classification and Imputation Methods for Fair and Accurate Data Analysis
    Dodavah Mowoh, Zhiyuan Chen · 2024 · IEEE International Conference on Big Data (BigData)
90. Bias Detection and Mitigation in Zero-Shot Spam Classification using LLMs
    Hossein Salemi, Anuridhi Gupta, Hemant Purohit · 2024 · IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA)
91. Understanding the Development, Performance, Fairness, and Transparency of Machine Learning Models Used in Child Protection Prediction: A Systematic Review
    Claudia F. Bull, Steve R Kisely, Kim Steven Betts, Yanan Hu · 2025 · SSRN Electronic Journal
92. A bias evaluation solution for multiple sensitive attribute speech recognition
    Zigang Chen, Yuening Zhou, Zhen Wang, Fan Liu, Tao Leng, Haihua Zhu · 2025 · Computer Speech & Language
93. Quantile Multi-Attribute Disparity (QMAD): An Adaptable Fairness Metric Framework for Dynamic Environments
    Dalha Alhumaidi Alotaibi, Jianlong J. Zhou, Yifei Dong, Jia Wei, Janet Ge, Fang Chen · 2025 · Electronics
94. Fairness-Preserving Implementation of Machine Learning Models
    Shahadat Uddin, Haohui Lu, Farshid Hajati · 2025 · Research Square
95. Large Language Models for Text Classification: A New Era of Accuracy and Efficiency
    Dário P. Dos Santos, Fábio Lúcio Lópes de Mendonça, João Paulo C. L. da Costa, André Luiz Marques Serrano, José Alberto Sousa Torres, Daniel Alves da Silva · 2025 · Communications in computer and information science
96. Multilingual Technologies: An Interdisciplinary Master's Program Leveraging Technology for Language
    Sigrid Schefer-Wenzl, Igor Miladinović, Dagmar Gromann · 2025 · IEEE Global Engineering Education Conference (EDUCON)
97. Accurate Numerical Prediction Strategy (NPS) based on feature weighting and soft computing techniques
    Ahmed I. Saleh, Shaimaa A. Hussien · 2025 · Knowledge-Based Systems
98. Disparities and Predictive Modeling of Foundational Learning in Somaliland: A Gender-, Location-, and School-Type-Based Analysis Using Machine Learning and Regression Approaches
    Mukhtaar Axmed Cumar, Mustafe Khadar Abdi, Abdisalam Hassan Muse, Jibril Abdikadir Ali · 2025 · Research Square
99. Model Explanations for Gender and Ethnicity Bias Mitigation in AI-Generated Narratives
    Martha O. Dimgba · 2025
100. Predicting Progression from Mild Cognitive Impairment to Alzheimer’s Using an AI-Based Multimodal Approach
     Quoc-Toan Nguyen, Nghia Duong‐Trung · 2025 · Lecture notes in computer science