{"total":19,"rows":[{"id":"2112.11471","title":"Towards a Science of Human-AI Decision Making: A Survey of Empirical Studies","created":"2021-12-21","cited_by_count":86,"area":null},{"id":"2207.09584","title":"Sample Efficient Learning of Predictors that Complement Humans","created":"2022-07-19","cited_by_count":46,"area":null},{"id":"2202.08821","title":"Human-Algorithm Collaboration: Achieving Complementarity and Avoiding Unfairness","created":"2022-02-17","cited_by_count":45,"area":null},{"id":"2204.02310","title":"Improving Human-AI Partnerships in Child Welfare: Understanding Worker Practices, Challenges, and Desires for Algorithmic Decision Support","created":"2022-04-05","cited_by_count":39,"area":null},{"id":"2310.14774","title":"Principled Approaches for Learning to Defer with Multiple Experts","created":"2023-10-23","cited_by_count":38,"area":null},{"id":"2208.07960","title":"Advancing Human-AI Complementarity: The Impact of User Expertise and Algorithmic Tuning on Joint Decision Making","created":"2022-08-16","cited_by_count":33,"area":null},{"id":"2302.06503","title":"Ground(less) Truth: A Causal Framework for Proxy Labels in Human-Algorithm Decision-Making","created":"2023-02-13","cited_by_count":25,"area":null},{"id":"2204.10806","title":"A Taxonomy of Human and ML Strengths in Decision-Making to Investigate Human-ML Complementarity","created":"2022-04-22","cited_by_count":23,"area":null},{"id":"2202.04092","title":"Machine Explanations and Human Understanding","created":"2022-02-08","cited_by_count":20,"area":null},{"id":"2207.13834","title":"Toward Supporting Perceptual Complementarity in Human-AI Collaboration via Reflection on Unobservables","created":"2022-07-28","cited_by_count":19,"area":null},{"id":"2109.01443","title":"The Impact of Algorithmic Risk Assessments on Human Predictions and its Analysis via Crowdsourcing Studies","created":"2021-09-03","cited_by_count":13,"area":null},{"id":"2103.09990","title":"Human-AI Symbiosis: A Survey of Current Approaches","created":"2021-03-18","cited_by_count":8,"area":null},{"id":"2402.06287","title":"AI, Meet Human: Learning Paradigms for Hybrid Decision Making Systems","created":"2024-02-09","cited_by_count":7,"area":null},{"id":"2405.12458","title":"Studying Up Public Sector AI: How Networks of Power Relations Shape Agency Decisions Around AI Design and Use","created":"2024-05-21","cited_by_count":6,"area":null},{"id":"2104.06982","title":"To Trust or Not to Trust a Regressor: Estimating and Explaining Trustworthiness of Regression Predictions","created":"2021-04-14","cited_by_count":5,"area":null},{"id":"2407.12710","title":"A Unifying Post-Processing Framework for Multi-Objective Learn-to-Defer Problems","created":"2024-07-17","cited_by_count":5,"area":null},{"id":"2601.09871","title":"Epistemology gives a Future to Complementarity in Human-AI Interactions","created":"2026-01-14","cited_by_count":5,"area":null},{"id":"2202.09447","title":"A Mental-Model Centric Landscape of Human-AI Symbiosis","created":"2022-02-18","cited_by_count":4,"area":null},{"id":"2303.09657","title":"ESCAPE: Countering Systematic Errors from Machine's Blind Spots via Interactive Visual Analysis","created":"2023-03-16","cited_by_count":2,"area":null}],"next_cursor":null}