Showing 1–20 of 47 results
/ Date/ Name
Dec 13, 2018Improving fairness in machine learning systems: What do industry practitioners need?Jul 28, 2022Toward Supporting Perceptual Complementarity in Human-AI Collaboration via Reflection on UnobservablesJan 9, 2020The TA Framework: Designing Real-time Teaching Augmentation for K-12 ClassroomsMay 6, 2021Everyday algorithm auditing: Understanding the power of everyday users in surfacing harmful algorithmic behaviorsApr 2, 2021Designing for human-AI complementarity in K-12 educationSep 26, 2024Policy Maps: Tools for Guiding the Unbounded Space of LLM BehaviorsApr 27, 2021Equity and Artificial Intelligence in Education: Will "AIEd" Amplify or Alleviate Inequities in Education?Jul 3, 2025Measurement as Bricolage: Examining How Data Scientists Construct Target Variables for Predictive Modeling TasksApr 5, 2022Improving Human-AI Partnerships in Child Welfare: Understanding Worker Practices, Challenges, and Desires for Algorithmic Decision SupportFeb 13, 2023Ground(less) Truth: A Causal Framework for Proxy Labels in Human-Algorithm Decision-MakingSep 24, 2024PolicyCraft: Supporting Collaborative and Participatory Policy Design through Case-Grounded DeliberationFeb 22, 2023Counterfactual Prediction Under Outcome Measurement ErrorMar 17, 2023Understanding Frontline Workers' and Unhoused Individuals' Perspectives on AI Used in Homeless ServicesJun 15, 2025Exploring the Potential of Metacognitive Support Agents for Human-AI Co-CreationOct 8, 2025Prototyping Multimodal GenAI Real-Time Agents with Counterfactual Replays and Hybrid Wizard-of-OzFeb 23, 2026ComplLLM: Fine-tuning LLMs to Discover Complementary Signals for Decision-makingSep 24, 2025PolicyPad: Collaborative Prototyping of LLM PoliciesNov 4, 2021Characterizing Human Explanation Strategies to Inform the Design of Explainable AI for Building Damage AssessmentApr 22, 2022A Taxonomy of Human and ML Strengths in Decision-Making to Investigate Human-ML ComplementarityMar 31, 2023Towards "Anytime, Anywhere" Community Learning and Engagement around the Design of Public Sector AI