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AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models., , , , , , , , , and 10 other author(s). J. Mach. Learn. Res., (2020)Explainable Active Learning (XAL): Toward AI Explanations as Interfaces for Machine Teachers., , , , and . Proc. ACM Hum. Comput. Interact., 4 (CSCW3): 1-28 (2020)Understanding the Role of Human Intuition on Reliance in Human-AI Decision-Making with Explanations., , , and . CoRR, (2023)How Much Automation Does a Data Scientist Want?, , , , , , , and . CoRR, (2021)Conversational Agents for Health and Wellbeing., , , , , , , , , and . CHI Extended Abstracts, page 1-8. ACM, (2020)Human-AI Collaboration via Conditional Delegation: A Case Study of Content Moderation., , , , , and . CHI, page 54:1-54:18. ACM, (2022)Introduction to AI Fairness., , , and . CHI Extended Abstracts, page 1-4. ACM, (2020)AI Explainability 360 Toolkit., , , , , , , , , and 10 other author(s). COMAD/CODS, page 376-379. ACM, (2021)All Work and No Play?, , , , , , , , , and . CHI, page 3. ACM, (2018)AI Transparency in the Age of LLMs: A Human-Centered Research Roadmap., and . CoRR, (2023)