mlsanityData to 7 Oct 2026

A Sociotechnical View of Algorithmic Fairness

arXiv 2110.09253 ↗First posted 27 Sep 2021cs.CY cs.LG stat.MLcited by 24

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Abstract (arXiv)

Algorithmic fairness has been framed as a newly emerging technology that mitigates systemic discrimination in automated decision-making, providing opportunities to improve fairness in information systems (IS). However, based on a state-of-the-art literature review, we argue that fairness is an inherently social concept and that technologies for algorithmic fairness should therefore be approached through a sociotechnical lens. We advance the discourse on algorithmic fairness as a sociotechnical phenomenon. Our research objective is to embed AF in the sociotechnical view of IS. Specifically, we elaborate on why outcomes of a system that uses algorithmic means to assure fairness depends on mutual influences between technical and social structures. This perspective can generate new insights that integrate knowledge from both technical fields and social studies. Further, it spurs new directions for IS debates. We contribute as follows: First, we problematize fundamental assumptions in the current discourse on algorithmic fairness based on a systematic analysis of 310 articles. Second, we respond to these assumptions by theorizing algorithmic fairness as a sociotechnical construct. Third, we propose directions for IS researchers to enhance their impacts by pursuing a unique understanding of sociotechnical algorithmic fairness. We call for and undertake a holistic approach to AF. A sociotechnical perspective on algorithmic fairness can yield holistic solutions to systemic biases and discrimination.

Key facts. Cited by 24 papers in the map (data through 7 Oct 2026). Builds on 145 of its 427 references that are in the map. First posted on arXiv 27 Sep 2021.

Builds on

145 of 427 references.

References · 145

  1. 2016Equality of Opportunity in Supervised Learningcited by 2,000
  2. 2019Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AIcited by 1,543
  3. 2017Counterfactual Fairnesscited by 802
  4. 2016Fair prediction with disparate impact: A study of bias in recidivism prediction instrumentscited by 671
  5. 2018A Reductions Approach to Fair Classificationcited by 585
  6. 2016Inherent Trade-Offs in the Fair Determination of Risk Scorescited by 582
  7. 2017On Fairness and Calibrationcited by 406
  8. 2017Algorithmic decision making and the cost of fairnesscited by 402
  9. 2017Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairnesscited by 381
  10. 2018Fairness Without Demographics in Repeated Loss Minimizationcited by 363
  11. 2018Learning Adversarially Fair and Transferable Representationscited by 353
  12. 2019Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Settingcited by 346
38 more
  1. 2018Improving fairness in machine learning systems: What do industry practitioners need?cited by 262
  2. 2020Fairness without Demographics through Adversarially Reweighted Learningcited by 251
  3. 2017Predict Responsibly: Improving Fairness and Accuracy by Learning to Defercited by 228
  4. 2018Empirical Risk Minimization under Fairness Constraintscited by 226
  5. 2018A comparative study of fairness-enhancing interventions in machine learningcited by 208
  6. 2019The What-If Tool: Interactive Probing of Machine Learning Modelscited by 207
  7. 2019Flexibly Fair Representation Learning by Disentanglementcited by 196
  8. 2018Fairness of Exposure in Rankingscited by 189
  9. 2018Delayed Impact of Fair Machine Learningcited by 183
  10. 2018Fair Clustering Through Fairletscited by 176
  11. 2019Fair Regression: Quantitative Definitions and Reduction-based Algorithmscited by 168
  12. 2019Towards Fairer Datasets: Filtering and Balancing the Distribution of the People Subtree in the ImageNet Hierarchycited by 156
  13. 2017Fairness in Machine Learning: Lessons from Political Philosophycited by 148
  14. 2019Mitigate Bias in Face Recognition using Skewness-Aware Reinforcement Learningcited by 145
  15. 2019On the Fairness of Disentangled Representationscited by 144
  16. 2019Inherent Tradeoffs in Learning Fair Representationscited by 144
  17. 2020Algorithmic Fairnesscited by 143
  18. 2018The Frontiers of Fairness in Machine Learningcited by 139
  19. 2019Fairness-Aware Ranking in Search & Recommendation Systems with Application to LinkedIn Talent Searchcited by 137
  20. 2019The Ethics of AI Ethics -- An Evaluation of Guidelinescited by 129
  21. 2019Fairness in Recommendation Ranking through Pairwise Comparisonscited by 127
  22. 2019Compositional Fairness Constraints for Graph Embeddingscited by 126
  23. 2019On the Apparent Conflict Between Individual and Group Fairnesscited by 126
  24. 2019Towards a Critical Race Methodology in Algorithmic Fairnesscited by 124
  25. 2019Fairness in Deep Learning: A Computational Perspectivecited by 123
  26. 2019Lessons from Archives: Strategies for Collecting Sociocultural Data in Machine Learningcited by 116
  27. 2019Fair Generative Modeling via Weak Supervisioncited by 114
  28. 201850 Years of Test (Un)fairness: Lessons for Machine Learningcited by 101
  29. 2020Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligencecited by 100
  30. 2020Fair Regression with Wasserstein Barycenterscited by 99
  31. 2019Fair Algorithms for Clusteringcited by 98
  32. 2018A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual & Group Unfairness via Inequality Indicescited by 97
  33. 2018Fairness Under Unawareness: Assessing Disparity When Protected Class Is Unobservedcited by 94
  34. 2016Fairness in Reinforcement Learningcited by 93
  35. 2017Beyond Parity: Fairness Objectives for Collaborative Filteringcited by 93
  36. 2019Problem Formulation and Fairnesscited by 85
  37. 2019Fairness risk measurescited by 85
  38. 2018An Empirical Study of Rich Subgroup Fairness for Machine Learningcited by 81

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Citing papers per year: 2022: 2; 2023: 6; 2024: 8; 2025: 4; 2026: 4.

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  1. 2023Generative AIcited by 119
  2. 2024Safeguarding Large Language Models: A Surveycited by 73
  3. 2024Building Guardrails for Large Language Modelscited by 61
  4. 2022Algorithmic Fairness in Business Analytics: Directions for Research and Practicecited by 18
  5. 2023Causal Fairness under Unobserved Confounding: A Neural Sensitivity Frameworkcited by 10
  6. 2025DeepTRACE: Auditing Deep Research AI Systems for Tracking Reliability Across Citations and Evidencecited by 10
  7. 2023ACROCPoLis: A Descriptive Framework for Making Sense of Fairnesscited by 8
  8. 2025A Tale of Two Identities: An Ethical Audit of Human and AI-Crafted Personascited by 8
  9. 2022Uncertainty-aware predictive modeling for fair data-driven decisionscited by 6
  10. 2023Compatibility of Fairness Metrics with EU Non-Discrimination Laws: Demographic Parity & Conditional Demographic Disparitycited by 5
  11. 2024A Survey of AI Reliancecited by 4
  12. 2023Fair Enough? A map of the current limitations of the requirements to have fair algorithmscited by 2
12 more
  1. 2024Analysing and Organising Human Communications for AI Fairness-Related Decisions: Use Cases from the Public Sectorcited by 2
  2. 2025Talking About the Assumption in the Roomcited by 2
  3. 2024(Unfair) Norms in Fairness Research: A Meta-Analysiscited by 1
  4. 2023An AI-Guided Data Centric Strategy to Detect and Mitigate Biases in Healthcare Datasetscited by 0
  5. 2024Learning with Digital Agents: An Analysis based on the Activity Theorycited by 0
  6. 2024Perceptions of Discriminatory Decisions of Artificial Intelligence: Unpacking the Role of Individual Characteristicscited by 0
  7. 2024Technology as uncharted territory: Contextual integrity and the notion of AI as new ethical groundcited by 0
  8. 2025A Flexible Fairness Framework with Surrogate Loss Reweighting for Addressing Sociodemographic Disparitiescited by 0
  9. 2026Unheard in the Digital Age: Rethinking AI Bias and Speech Diversitycited by 0
  10. 2026Unravelling the (In)compatibility of Statistical-Parity and Equalized-Oddscited by 0
  11. 2026Sima AIunty: Caste Audit in LLM-Driven Matchmakingcited by 0
  12. 2026Whose Alignment? Comparing LLM Process Alignment Across Diverse Organizational Decision Contextscited by 0