mlsanityData to 7 Oct 2026

Improving Human-AI Partnerships in Child Welfare: Understanding Worker Practices, Challenges, and Desires for Algorithmic Decision Support

arXiv 2204.02310 ↗First posted 5 Apr 2022cs.HC cs.AI cs.CYcited by 37

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Abstract (arXiv)

AI-based decision support tools (ADS) are increasingly used to augment human decision-making in high-stakes, social contexts. As public sector agencies begin to adopt ADS, it is critical that we understand workers' experiences with these systems in practice. In this paper, we present findings from a series of interviews and contextual inquiries at a child welfare agency, to understand how they currently make AI-assisted child maltreatment screening decisions. Overall, we observe how workers' reliance upon the ADS is guided by (1) their knowledge of rich, contextual information beyond what the AI model captures, (2) their beliefs about the ADS's capabilities and limitations relative to their own, (3) organizational pressures and incentives around the use of the ADS, and (4) awareness of misalignments between algorithmic predictions and their own decision-making objectives. Drawing upon these findings, we discuss design implications towards supporting more effective human-AI decision-making.

Key facts. Cited by 37 papers in the map (data through 7 Oct 2026). Builds on 22 of its 71 references that are in the map. First posted on arXiv 5 Apr 2022.

Builds on

22 of 71 references.

References · 22

  1. 2020Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performancecited by 396
  2. 2018Manipulating and Measuring Model Interpretabilitycited by 256
  3. 2019The What-If Tool: Interactive Probing of Machine Learning Modelscited by 207
  4. 2021To Trust or to Think: Cognitive Forcing Functions Can Reduce Overreliance on AI in AI-assisted Decision-makingcited by 118
  5. 2017Building machines that adapt and compute like brainscited by 99
  6. 2021Towards a Science of Human-AI Decision Making: A Survey of Empirical Studiescited by 85
  7. 2020A Case for Humans-in-the-Loop: Decisions in the Presence of Erroneous Algorithmic Scorescited by 74
  8. 2018Fairness and Accountability Design Needs for Algorithmic Support in High-Stakes Public Sector Decision-Makingcited by 66
  9. 2019Unremarkable AI: Fitting Intelligent Decision Support into Critical, Clinical Decision-Making Processescited by 53
  10. 2021Everyday algorithm auditing: Understanding the power of everyday users in surfacing harmful algorithmic behaviorscited by 47
  11. 2021The Flaws of Policies Requiring Human Oversight of Government Algorithmscited by 44
  12. 2021Teaching Humans When To Defer to a Classifier via Exemplarscited by 29
10 more
  1. 2021Soliciting Stakeholders' Fairness Notions in Child Maltreatment Predictive Systemscited by 27
  2. 2020A Human-Centered Review of the Algorithms used within the U.S. Child Welfare Systemcited by 23
  3. 2021A Framework of High-Stakes Algorithmic Decision-Making for the Public Sector Developed through a Case Study of Child-Welfarecited by 23
  4. 2021Algorithms and Decision-Making in the Public Sectorcited by 20
  5. 2018Investigating Human + Machine Complementarity for Recidivism Predictionscited by 19
  6. 2021Sibyl: Understanding and Addressing the Usability Challenges of Machine Learning In High-Stakes Decision Makingcited by 19
  7. 2021Designing for human-AI complementarity in K-12 educationcited by 19
  8. 2021Towards A Process Model for Co-Creating AI Experiencescited by 18
  9. 2021Leveraging Expert Consistency to Improve Algorithmic Decision Supportcited by 17
  10. 2020Keeping Community in the Loop: Understanding Wikipedia Stakeholder Values for Machine Learning-Based Systemscited by 16

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Citing papers per year: 2022: 4; 2023: 12; 2024: 10; 2025: 6; 2026: 5.

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  1. 2023Understanding the Role of Human Intuition on Reliance in Human-AI Decision-Making with Explanationscited by 73
  2. 2023Improving Human-AI Collaboration With Descriptions of AI Behaviorcited by 35
  3. 2022A Validity Perspective on Evaluating the Justified Use of Data-driven Decision-making Algorithmscited by 30
  4. 2023Understanding Frontline Workers' and Unhoused Individuals' Perspectives on AI Used in Homeless Servicescited by 29
  5. 2023Ground(less) Truth: A Causal Framework for Proxy Labels in Human-Algorithm Decision-Makingcited by 25
  6. 2022A Taxonomy of Human and ML Strengths in Decision-Making to Investigate Human-ML Complementaritycited by 22
  7. 2023Effective Human-AI Teams via Learned Natural Language Rules and Onboardingcited by 20
  8. 2022Toward Supporting Perceptual Complementarity in Human-AI Collaboration via Reflection on Unobservablescited by 19
  9. 2023Understanding the Effect of Counterfactual Explanations on Trust and Reliance on AI for Human-AI Collaborative Clinical Decision Makingcited by 18
  10. 2022Imagining new futures beyond predictive systems in child welfare: A qualitative study with impacted stakeholderscited by 15
  11. 2024Position: Towards Bidirectional Human-AI Alignmentcited by 15
  12. 2023Competent but Rigid: Identifying the Gap in Empowering AI to Participate Equally in Group Decision-Makingcited by 11
25 more
  1. 2023Counterfactual Prediction Under Outcome Measurement Errorcited by 10
  2. 2025AI Mismatches: Identifying Potential Algorithmic Harms Before AI Developmentcited by 10
  3. 2023Training Towards Critical Use: Learning to Situate AI Predictions Relative to Human Knowledgecited by 6
  4. 2024Studying Up Public Sector AI: How Networks of Power Relations Shape Agency Decisions Around AI Design and Usecited by 6
  5. 2025Tempo: Helping Data Scientists and Domain Experts Collaboratively Specify Predictive Modeling Taskscited by 6
  6. 2023Discretionary Trees: Understanding Street-Level Bureaucracy via Machine Learningcited by 5
  7. 2024Human Delegation Behavior in Human-AI Collaboration: The Effect of Contextual Informationcited by 5
  8. 2025Towards Uncertainty Aware Task Delegation and Human-AI Collaborative Decision-Makingcited by 4
  9. 2024(Beyond) Reasonable Doubt: Challenges that Public Defenders Face in Scrutinizing AI in Courtcited by 3
  10. 2024Beyond Recommendations: From Backward to Forward AI Support of Pilots' Decision-Making Processcited by 3
  11. 2024Explainable and Human-Grounded AI for Decision Support Systems: The Theory of Epistemic Quasi-Partnershipscited by 3
  12. 2024Thoughtful Adoption of NLP for Civic Participation: Understanding Differences Among Policymakerscited by 3
  13. 2024Legacy Procurement Practices Shape How U.S. Cities Govern AI: Understanding Government Employees' Practices, Challenges, and Needscited by 3
  14. 2025Street-Level AI: Are Large Language Models Ready for Real-World Judgments?cited by 3
  15. 2023Talk2Care: Facilitating Asynchronous Patient-Provider Communication with Large-Language-Modelcited by 1
  16. 2025Measurement as Bricolage: Examining How Data Scientists Construct Target Variables for Predictive Modeling Taskscited by 1
  17. 2023Recentering Validity Considerations through Early-Stage Deliberations Around AI and Policy Designcited by 0
  18. 2024Beyond Predictive Algorithms in Child Welfarecited by 0
  19. 2024Reimagining AI in Social Work: Practitioner Perspectives on Incorporating Technology in their Practicecited by 0
  20. 2025Who Leads? Comparing Human-Centric and Model-Centric Strategies for Defining ML Target Variablescited by 0
  21. 2026SHARP: Social Harm Analysis via Risk Profiles for Measuring Inequities in Large Language Modelscited by 0
  22. 2026Intelligent Reasoning Cues: A Framework and Case Study of the Roles of AI Information in Complex Decisionscited by 0
  23. 2026From Tool to Agent: How Worker Needs Reorganize Across the Agentic Roles of Workplace AIcited by 0
  24. 2026Agents for Experiments, Experiments for Agents: A Design Grammar for AI-Enabled Experimental Sciencecited by 0
  25. 2026RuleEdit: Failure-Guided Human-AI Model Editing with Prospective Impact Previewcited by 0