Empirical observation of negligible fairness–accuracy trade-offs in machine learning for public policy

Scikit-learn: Machine Learning in Python

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Inherent trade-offs in the fair determination of risk scores

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Mitigating bias in algorithmic hiring: evaluating claims and practices

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

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A comparative study of fairness-enhancing interventions in machine learning

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Beyond prediction: using big data for policy problems

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Do We Know Who Will Drop Out?: A Review of the Predictors of Dropping out of High School: Precision, Sensitivity, and Specificity

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Classification with Fairness Constraints: A Meta-Algorithm with Provable Guarantees

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Risk, Race, and Recidivism: Predictive Bias and Disparate Impact

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A Machine Learning Framework to Identify Students at Risk of Adverse Academic Outcomes

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An Empirical Study of Rich Subgroup Fairness for Machine Learning

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Why is my classifier discriminatory?

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The cost of fairness in binary classification

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On Formalizing Fairness in Prediction with Machine LearningPreprint

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Crowdsourcing City Government: Using Tournaments to Improve Inspection Accuracy

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“Who, when, and why: a machine learning approach to prioritizing students at risk of not graduating high school on time,”

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Predictive Analytics for Retention in Care in an Urban HIV Clinic

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Case study

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Predictive Modeling for Public Health

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People with Complex Needs and the Criminal Justice System

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Using machine learning to help vulnerable tenants in New York city

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Crowdsourcing City Government: Using Tournaments to Improve Inspection Accuracy

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Reducing Incarceration through Prioritized Interventions

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Affordable Housing and Health

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dssg/peeps-chili: Cleanup and KDD Explorations Materials

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dssg/peeps-chili: Release for trade-offs submission

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Towards a standard for identifying and managing bias in artificial intelligence

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It’s Just Not That Simple: An Empirical Study of the Accuracy-Explainability Trade-off in Machine Learning for Public Policy

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Algorithmic fairness in business analytics: Directions for research and practice

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Model Multiplicity: Opportunities, Concerns, and Solutions

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A translational perspective towards clinical AI fairness

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Capable but Amoral? Comparing AI and Human Expert Collaboration in Ethical Decision Making

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Strategies to improve the impact of artificial intelligence on health equity: scoping review

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A scoping review and evidence gap analysis of clinical AI fairness

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The Role of Human Managers within Algorithmic Performance Management Systems: A Process Model of Employee Trust in Managers through Reflexivity

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Human visual explanations mitigate bias in AI-based assessment of surgeon skills

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Implementing equitable and intersectionality‐aware ML in education: A practical guide

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Fairness and bias correction in machine learning for depression prediction across four study populations

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What we owe to decision-subjects: beyond transparency and explanation in automated decision-making

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Causal Fairness Analysis: A Causal Toolkit for Fair Machine Learning

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Protein Function Analysis through Machine Learning

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Translating intersectionality to fair machine learning in health sciences

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Reviewing wireless broadband technologies in the peak smartphone era: 6G versus Wi-Fi 7 and 8

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Ethical Redress of Racial Inequities in AI: Lessons from Decoupling Machine Learning from Optimization in Medical Appointment Scheduling

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Identifying and mitigating algorithmic bias in the safety net

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Cross-Institutional Transfer Learning for Educational Models: Implications for Model Performance, Fairness, and Equity

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Sliding Window-Based Machine Learning for Environmental Inspection Resource Allocation

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Arbitrariness and Social Prediction: The Confounding Role of Variance in Fair Classification

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Survey on Blockchain-Enhanced Machine Learning

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The Possibility of Fairness: Revisiting the Impossibility Theorem in Practice

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

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Bias Reducing Multitask Learning on Mental Health Prediction

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The Privacy-Bias Tradeoff: Data Minimization and Racial Disparity Assessments in U.S. Government

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A Novel Approach for Fair Principal Component Analysis Based on Eigendecomposition

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An intelligent multi-agent system for last-mile logistics

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Investigating fairness in machine learning-based audio sentiment analysis

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Fair Risk Algorithms

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Mitigating Algorithmic Bias Through Probability Calibration: A Case Study on Lead Generation Data

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Algorithmic Social Injustices: Antecedents and Mitigations

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An Empirical Comparison of Bias Reduction Methods on Real-World Problems in High-Stakes Policy Settings

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Metaverse: Evolving role in healthcare delivery and implications

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Reconciling the Accuracy-Diversity Trade-off in Recommendations

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Fairness considered aggregation mechanism for consumers and prosumers in electricity distribution networks

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Analysing and organising human communications for AI fairness assessment

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Guiding responsible AI in healthcare in the Philippines

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Fairquant: Certifying and Quantifying Fairness of Deep Neural Networks

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A Guide to Machine Learning Epistemic Ignorance, Hidden Paradoxes, and Other Tensions

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Improving Model Fairness with Time-Augmented Bayesian Knowledge Tracing

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Fairness in Online Ad Delivery

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Fairness in Contextual Resource Allocation Systems: Metrics and Incompatibility Results

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One Threshold Doesn’t Fit All: Tailoring Machine Learning Predictions of Consumer Default for Lower-Income Areas

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Socioeconomic bias in applying artificial intelligence models to health care

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Low-cost and scalable machine learning model for identifying children and adolescents with poor oral health using survey data: An empirical study in Portugal

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Does artificial intelligence improve social equity in public services? A systematic literature review on opportunities and pitfalls

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Multi-modal Machine Learning Investigation of Telework and Transit Connections

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Disciplining Deliberation: A Socio-technical Perspective on Machine Learning Trade-Offs

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Construction and Optimization of Mental Health Education Consultation Management System Based on Decision Tree Association Rule Mining

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What Constitutes a Less Discriminatory Algorithm?

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Post-processing methods for mitigating algorithmic bias in healthcare classification models: An extended umbrella review

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Fairness in Forecasting of Observations of Linear Dynamical Systems

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Formal Group Fairness and Accuracy in Automated Decision Making

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Intersectional and Marginal Debiasing in Prediction Models for Emergency Admissions

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Enhancing spatiotemporal demand prediction in transportation systems through region generation using soft clustering

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AI without borders: The rise of cross-disciplinary machine learning

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Be Intentional About Fairness!: Fairness, Size, and Multiplicity in the Rashomon Set

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SOK: Application of machine learning models in child and youth mental health decision-making

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An Anti-Subordination Approach to Fair ClassificationPreprint

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Rethinking fairness in medical imaging: Maximizing group-specific performance with application to skin disease diagnosis

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A computational social science approach to understanding predictors of Chafee service receipt

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Artificial Intelligence and Criminal Justice: A systematic review of the scientific literature

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Metric-Independent Mitigation of Unpredefined Bias in Machine Classification

Tang, Z., Lu, T., & Li, T. (2024) · Intelligent Computing · doi:10.34133/icomputing.0083 · Cited by 2 · see citing works

FATE: Learning Effective Binary Descriptors With Group Fairness

Zhang, F., Chen, C., Hua, X., & Luo, X. (2024) · IEEE Transactions on Image Processing · doi:10.1109/tip.2024.3406134 · Cited by 2 · see citing works

SoK: Unintended Interactions among Machine Learning Defenses and Risks

Duddu, V., Szyller, S., & Asokan, N. (2024) · IEEE Symposium on Security and Privacy (S&P) · doi:10.1109/sp54263.2024.00243 · Cited by 2 · see citing works

External Evaluation of Discrimination Mitigation Efforts in Meta's Ad Delivery

Imana, B., Shen, Z., Heidemann, J., & Korolova, A. (2025) · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · doi:10.1145/3715275.3732170 · Cited by 1 · see citing works

Engineering the law-machine learning translation problem: developing legally aligned models

Hanson, M., Lewkowicz, G., & Verboven, S. (2025) · Computer law & security review · doi:10.1016/j.clsr.2025.106252 · Cited by 1 · see citing works

Responsible AI for Predicting Delayed Hospital Discharge Among Older Adults: Development and Evaluation Study for Balancing Accuracy, Equity, and Explainability

Ghazalbash, S., Zargoush, M., Guilcher, S. J. T., & Kuluski, K. (2026) · JMIR Medical Informatics · doi:10.2196/83244 · Cited by 1 · see citing works

Scrutinizing Index-Based Risk Assessments: A Case Study in NYC Decision-making for Heat Emergency Management

Gosciak, J., Boyce, L., Wang, A., & Koenecke, A. (2026) · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · doi:10.1145/3805689.3812405 · Cited by 1 · see citing works

Linking convolutional kernel size to generalization bias in face analysis CNNs

Liang, H., Caro, J. O., Maheshri, V., Patel, A. B., & Balakrishnan, G. (2024) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv57701.2024.00464 · Cited by 1 · see citing works

CFP: A Reinforcement Learning Framework for Comprehensive Fairness-Performance Trade-Off in Machine Learning

Zhang, S., Bai, J., Guan, M., Zhang, Y., Sun, J., Huang, Y., Wang, J., Wan, C., Su, T., & Pu, G. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-72332-2_30 · Cited by 1 · see citing works

Investigating Fairness in Machine Learning-based Audio Sentiment Analysis using Spectrograms and Bag-of-visual-wordsPreprint

Luitel, S., Liu, Y., & Anwar, M. M. (2023) · Research Square · doi:10.21203/rs.3.rs-2566840/v1 · Cited by 1 · see citing works

Public Attitudes Toward Algorithmic Risk Assessments In Courts: A Deliberation ExperimentPreprint

Woemmel, A., Hüning, H., & Mechtenberg, L. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4773841 · Cited by 1 · see citing works

The Performance-Actionability Trade-Off in Retention Prediction at Middle School

Lavado, S., Mateus, M., & Zejnilović, L. (2022) · International Conference on Machine Learning and Applications · doi:10.1109/icmla55696.2022.00087

Mutatis Mutandis: Revisiting the Comparator in Discrimination Testing

Álvarez, J. M., & Ruggieri, S. (2026) · Computational Intelligence · doi:10.1111/coin.70238

Intersectional consequences for marginal fairness in prediction models for emergency admissionsPreprint

Lett, E., Shahbandegan, S., Barak‐Corren, Y., Fine, A., & Cava, W. L. (2024) · medRxiv · doi:10.1101/2024.11.05.24316769

Effective Guidance for Model Attention with Simple Yes-no Annotations

Lee, S., Payani, A., & Chau, D. H. (2024) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata62323.2024.10825776

Fair machine learning models for disease prediction: In-depth interviews with key health expertsPreprint

Nghiem, N., & Tiatia, R. (2025) · medRxiv · doi:10.1101/2025.02.04.25321632

Towards Multi-stakeholder Evaluation of ML Models: A Crowdsourcing Study on Metric Preferences in Job-Matching System

Yokota, T., & Nakao, Y. (2025) · Communications in computer and information science · doi:10.1007/978-3-031-82633-7_8

Coordination of network heterogeneity and individual preferences promotes collective fairness

Han, X., Ma, S., Wang, W.-X., Sánchez, Á., Stanley, E., Cao, S., & Zhang, B. (2025) · Patterns · doi:10.1016/j.patter.2025.101293

Fairness, Value Alignment, and Governance in LLMs: The Case of Insurance PricingPreprint

Lin, C., Xu, X., & Huang, C. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5574261

Fairness and Equity in AI for Societal Decision-Making

Abrar, S. M., & Martínez, V. F. (2025) · Encyclopedia of GIS · doi:10.1007/978-3-319-23519-6_1680-1

Algorithmic fairness in context: liberty, opportunity, and well-being as ethical anchors

Perdana, A., Li, P., & Wangge, G. (2026) · AI and Ethics · doi:10.1007/s43681-025-00963-7

Provable Fairness Repair for Deep Neural Networks

Ma, J.-N., Wang, J.-Y., Xuan, Q., & Wang, Z. (2025) · International Conference on Automated Software Engineering · doi:10.1109/ase63991.2025.00049

A systematic exploration of fairness requirements, modeling, and operationalization in engineering AI-based software systems

Caetano, S. P., & Lee, S.-W. (2026) · Journal of Systems and Software · doi:10.1016/j.jss.2026.113066

Bullying an AI? Misbehavior toward an AI moral patient in interactive marketing

Zhu, M., Liu, M. T., Lo, F., & Lee, V. (2026) · Journal of Research in Interactive Marketing · doi:10.1108/jrim-07-2025-0408

Review of Data-Driven Bias: Analysis of Concepts for Fairness Audits in the Regulation of High-Risk AI Systems

Grenzebach, J., & Radüntz, T. (2026) · Communications in computer and information science · doi:10.1007/978-3-032-25308-8_7

Fairness Impossibility in AI-ML Systems: An Integrative Ethics Approach

Honenberger, P. (2026) · Synthese Library/Synthese library · doi:10.1007/978-3-032-10073-3_14

Algorithmic UDAP

Gillis, T. B., Stacy, R., Brumer, S., & Black, E. (2026) · ACM Symposium on Computer Science and Law (CSLAW) · doi:10.1145/3788646.3789525

Effect of Resources on the Efficiency-Fairness Tradeoff for Allocation Problems

Singh, S., Kanich, C., & Kash, I. A. (2026) · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · doi:10.1145/3805689.3812245

Privilege Scores

Bothmann, L., Boustani, P. A., Álvarez, J. M., Casalicchio, G., Bischl, B., & Dandl, S. (2026) · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · doi:10.1145/3805689.3812340

The Anti-Ethical Architecture of AI: Why Optimisation Algorithms Undermine Human Ethos in Business

Koghut, M. (2026) · Business, management and economics · doi:10.5772/intechopen.1015844

Quantifying fairness-efficiency trade-offs in machine learning credit models: a Pareto frontier approach using lending club data

Li, T., & Lu, P. (2026) · Empirical Economics · doi:10.1007/s00181-026-02927-0

Bias in Algorithm‐Assisted Decision‐Making: A Theory‐Based Intervention

Li, A., & Fan, S. (2026) · Journal of Applied Social Psychology · doi:10.1111/jasp.70083

The Fairness Illusion? A Cross-Dataset Audit of Accuracy and Demographic Bias in Credit Scoring Based on Machine Learning

Ellis, C. (2026) · Journal of risk and financial management · doi:10.3390/jrfm19090674

From Bias to Fairness: Can Synthetic Data Bridge the Gap in Tabular Machine Learning?

Mota, M. B., & Recamonde‐Mendoza, M. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-39904-5_33

Responsible AI-driven decision-making for fair and efficient continuity of care among older adults

Ghazalbash, S., Zargoush, M., Verter, V., & Nair, A. (2026) · Omega · doi:10.1016/j.omega.2026.103685

Machine learning for public policy: Do we need to sacrifice accuracy to make models fair?Preprint

Rodolfa, K. T., Lamba, H., & Ghani, R. (2020) · arXiv (Cornell University) · Cited by 2 · see citing works

An Empirical Comparison of Bias Reduction Methods on Real-World Problems in High-Stakes Policy Settings

Lamba, H., Rodolfa, K. T., & Ghani, R. (2021) · ACM SIGKDD Explorations Newsletter · doi:10.1145/3468507.3468518 · Cited by 13 · see citing works

Discovering Trade-offs in Fairness and Accuracy: A Multi-Objective Approach

(21970667), A. C., (21970358), A., (21941732), A. N., & (21970670), P. L. (2024) · Open Research Exeter (University of Exeter)

Emergent Unfairness: Normative Assumptions and Contradictions in Algorithmic Fairness-Accuracy Trade-Off Research.Preprint

Cooper, A. F., & Abrams, E. (2021) · arXiv (Cornell University) · Cited by 1 · see citing works

Emergent Unfairness in Algorithmic Fairness-Accuracy Trade-Off Research

Cooper, A. F., Abrams, E., & NA, N. (2021) · Proceedings of the AAAI/ACM Conference on AI Ethics and Society · doi:10.1145/3461702.3462519 · Cited by 57 · see citing works