mlsanityData to 7 Oct 2026

A Case for Humans-in-the-Loop: Decisions in the Presence of Erroneous Algorithmic Scores

arXiv 2002.08035 ↗First posted 19 Feb 2020cs.CYcited by 74

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Abstract (arXiv)

The increased use of algorithmic predictions in sensitive domains has been accompanied by both enthusiasm and concern. To understand the opportunities and risks of these technologies, it is key to study how experts alter their decisions when using such tools. In this paper, we study the adoption of an algorithmic tool used to assist child maltreatment hotline screening decisions. We focus on the question: Are humans capable of identifying cases in which the machine is wrong, and of overriding those recommendations? We first show that humans do alter their behavior when the tool is deployed. Then, we show that humans are less likely to adhere to the machine's recommendation when the score displayed is an incorrect estimate of risk, even when overriding the recommendation requires supervisory approval. These results highlight the risks of full automation and the importance of designing decision pipelines that provide humans with autonomy.

Key facts. Cited by 74 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Feb 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 13; 2022: 18; 2023: 13; 2024: 11; 2025: 9; 2026: 10.

74 papers.

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  1. 2024Relying on the Unreliable: The Impact of Language Models' Reluctance to Express Uncertaintycited by 106
  2. 2021Towards a Science of Human-AI Decision Making: A Survey of Empirical Studiescited by 85
  3. 2023Understanding the Role of Human Intuition on Reliance in Human-AI Decision-Making with Explanationscited by 73
  4. 2021Towards Unbiased and Accurate Deferral to Multiple Expertscited by 71
  5. 2022Human-Algorithm Collaboration: Achieving Complementarity and Avoiding Unfairnesscited by 45
  6. 2022Improving Human-AI Partnerships in Child Welfare: Understanding Worker Practices, Challenges, and Desires for Algorithmic Decision Supportcited by 37
  7. 2022Towards Transparency in Dermatology Image Datasets with Skin Tone Annotations by Experts, Crowds, and an Algorithmcited by 35
  8. 2023Improving Human-AI Collaboration With Descriptions of AI Behaviorcited by 35
  9. 2021Role of Human-AI Interaction in Selective Predictioncited by 33
  10. 2022Exploring How Machine Learning Practitioners (Try To) Use Fairness Toolkitscited by 33
  11. 2022Advancing Human-AI Complementarity: The Impact of User Expertise and Algorithmic Tuning on Joint Decision Makingcited by 33
  12. 2022Who Goes First? Influences of Human-AI Workflow on Decision Making in Clinical Imagingcited by 32
38 more
  1. 2022A Taxonomy of Human and ML Strengths in Decision-Making to Investigate Human-ML Complementaritycited by 22
  2. 2025From Calibration to Collaboration: LLM Uncertainty Quantification Should Be More Human-Centeredcited by 21
  3. 2021Designing for human-AI complementarity in K-12 educationcited by 19
  4. 2022"There Is Not Enough Information": On the Effects of Explanations on Perceptions of Informational Fairness and Trustworthiness in Automated Decision-Makingcited by 19
  5. 2022Toward Supporting Perceptual Complementarity in Human-AI Collaboration via Reflection on Unobservablescited by 19
  6. 2021Leveraging Expert Consistency to Improve Algorithmic Decision Supportcited by 17
  7. 2022Imagining new futures beyond predictive systems in child welfare: A qualitative study with impacted stakeholderscited by 15
  8. 2021The Impact of Algorithmic Risk Assessments on Human Predictions and its Analysis via Crowdsourcing Studiescited by 13
  9. 2024Human Expertise in Algorithmic Predictioncited by 13
  10. 2021Planning to Fairly Allocate: Probabilistic Fairness in the Restless Bandit Settingcited by 12
  11. 2024Cost-Sensitive Learning to Defer to Multiple Experts with Workload Constraintscited by 12
  12. 2021Learning to be Fair: A Consequentialist Approach to Equitable Decision-Makingcited by 11
  13. 2021On the Fairness of Machine-Assisted Human Decisionscited by 10
  14. 2025AI Mismatches: Identifying Potential Algorithmic Harms Before AI Developmentcited by 10
  15. 2021Equity and Artificial Intelligence in Education: Will "AIEd" Amplify or Alleviate Inequities in Education?cited by 9
  16. 2024Decoding AI's Nudge: A Unified Framework to Predict Human Behavior in AI-assisted Decision Makingcited by 9
  17. 2023AI Reliance and Decision Quality: Fundamentals, Interdependence, and the Effects of Interventionscited by 8
  18. 2023Capturing Humans' Mental Models of AI: An Item Response Theory Approachcited by 8
  19. 2021Learning to Predict with Supporting Evidence: Applications to Clinical Risk Predictioncited by 7
  20. 2023Toward Operationalizing Pipeline-aware ML Fairness: A Research Agenda for Developing Practical Guidelines and Toolscited by 7
  21. 2024Calibration Attacks: A Comprehensive Study of Adversarial Attacks on Model Confidencecited by 7
  22. 2023Training Towards Critical Use: Learning to Situate AI Predictions Relative to Human Knowledgecited by 6
  23. 2026From Future of Work to Future of Workers: Addressing Asymptomatic AI Harms for Dignified Human-AI Interactioncited by 6
  24. 2023A Systematic Literature Review of Human-Centered, Ethical, and Responsible AIcited by 5
  25. 2022Trucks Don't Mean Trump: Diagnosing Human Error in Image Analysiscited by 4
  26. 2023When Are Two Lists Better than One?: Benefits and Harms in Joint Decision-makingcited by 4
  27. 2025Towards Uncertainty Aware Task Delegation and Human-AI Collaborative Decision-Makingcited by 4
  28. 2021Mindless Attractor: A False-Positive Resistant Intervention for Drawing Attention Using Auditory Perturbationcited by 3
  29. 2021"Part Man, Part Machine, All Cop": Automation in Policingcited by 3
  30. 2022On the Relationship Between Explanations, Fairness Perceptions, and Decisionscited by 3
  31. 2023FiFAR: A Fraud Detection Dataset for Learning to Defercited by 3
  32. 2024Integrating Expert Judgment and Algorithmic Decision Making: An Indistinguishability Frameworkcited by 3
  33. 2022Doubting AI Predictions: Influence-Driven Second Opinion Recommendationcited by 2
  34. 2023Designing Equitable Algorithmscited by 2
  35. 2023Decision-aid or Controller? Steering Human Decision Makers with Algorithmscited by 2
  36. 2024When Stereotypes GTG: The Impact of Predictive Text Suggestions on Gender Bias in Human-AI Co-Writingcited by 2
  37. 2025Selective Prediction Reduces the Negative Effects of Automation Bias Overall but Increases False Negativescited by 2
  38. 2025When the Domain Expert Has No Time and the LLM Developer Has No Clinical Expertise: Real-World Lessons from LLM Co-Design in a Safety-Net Hospitalcited by 2

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