mlsanityData to 7 Oct 2026

Fairness in Learning-Based Sequential Decision Algorithms: A Survey

arXiv 2001.04861 ↗First posted 14 Jan 2020cs.AIcited by 35

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Abstract (arXiv)

Algorithmic fairness in decision-making has been studied extensively in static settings where one-shot decisions are made on tasks such as classification. However, in practice most decision-making processes are of a sequential nature, where decisions made in the past may have an impact on future data. This is particularly the case when decisions affect the individuals or users generating the data used for future decisions. In this survey, we review existing literature on the fairness of data-driven sequential decision-making. We will focus on two types of sequential decisions: (1) past decisions have no impact on the underlying user population and thus no impact on future data; (2) past decisions have an impact on the underlying user population and therefore the future data, which can then impact future decisions. In each case the impact of various fairness interventions on the underlying population is examined.

Key facts. Cited by 35 papers in the map (data through 7 Oct 2026). First posted on arXiv 14 Jan 2020.

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Citing papers per year: 2021: 6; 2022: 6; 2023: 6; 2024: 8; 2025: 5; 2026: 4.

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  1. 2023Harms from Increasingly Agentic Algorithmic Systemscited by 134
  2. 2022Bias Mitigation for Machine Learning Classifiers: A Comprehensive Surveycited by 125
  3. 2022Fairness in Recommendation: Foundations, Methods and Applicationscited by 27
  4. 2022Achieving Long-Term Fairness in Sequential Decision Makingcited by 18
  5. 2022What-is and How-to for Fairness in Machine Learning: A Survey, Reflection, and Perspectivecited by 18
  6. 2023Runtime Monitoring of Dynamic Fairness Propertiescited by 17
  7. 2021Fair Sequential Selection Using Supervised Learning Modelscited by 16
  8. 2022Survey on Fair Reinforcement Learning: Theory and Practicecited by 14
  9. 2023A Classification of Feedback Loops and Their Relation to Biases in Automated Decision-Making Systemscited by 12
  10. 2023Towards Environmentally Equitable AI via Geographical Load Balancingcited by 10
  11. 2021Fairness with Continuous Optimal Transportcited by 9
  12. 2022Group Meritocratic Fairness in Linear Contextual Banditscited by 9
23 more
  1. 2024Fairness in Reinforcement Learning: A Surveycited by 9
  2. 2021Fairness in Missing Data Imputationcited by 8
  3. 2024Learning under Imitative Strategic Behavior with Unforeseeable Outcomescited by 8
  4. 2024Algorithmic Decision-Making under Agents with Persistent Improvementcited by 7
  5. 2021Long-Term Resource Allocation Fairness in Average Markov Decision Process (AMDP) Environmentcited by 6
  6. 2021Precarity: Modeling the Long Term Effects of Compounded Decisions on Individual Instabilitycited by 5
  7. 2021Multi-armed Bandit Requiring Monotone Arm Sequencescited by 5
  8. 2023Fairness and Sequential Decision Making: Limits, Lessons, and Opportunitiescited by 5
  9. 2024Long-Term Fairness Inquiries and Pursuits in Machine Learning: A Survey of Notions, Methods, and Challengescited by 4
  10. 2023Procedural Fairness Through Decoupling Objectionable Data Generating Componentscited by 3
  11. 2024Fair Best Arm Identification with Fixed Confidencecited by 3
  12. 2024Long-term Fairness For Real-time Decision Making: A Constrained Online Optimization Approachcited by 2
  13. 2025Counting Hours, Counting Losses: The Toll of Unpredictable Work Schedules on Financial Securitycited by 2
  14. 2026Fairness under uncertainty in sequential decisionscited by 2
  15. 2026Learning Fair Pareto-Optimal Policies in Multi-Objective Reinforcement Learningcited by 2
  16. 2024Understanding Decision Subjects' Engagement with and Perceived Fairness of AI Models When Opportunities of Qualification Improvement Existcited by 1
  17. 2025Demographic-Agnostic Fairness without Harmcited by 1
  18. 2026Benchmarking Bias Mitigation Toward Fairness Without Harm from Vision to LVLMscited by 1
  19. 2024Towards Environmentally Equitable AIcited by 0
  20. 2025Detecting underdetermination in parameterized quantum circuitscited by 0
  21. 2025Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinantscited by 0
  22. 2025Consumer Autonomy or Illusion? Rethinking Consumer Agency in the Age of Algorithmscited by 0
  23. 2026Inference-Time Policy Alignment for Fair Reinforcement Learningcited by 0