Towards a Learner-Centered Explainable AI: Lessons from the learning sciences

Human-Centered Explainable AI Workshop at ACM CHI Conference on Human Factors in Computing Systems 2022 In this short paper, we argue for a refocusing of XAI around human learning goals. Drawing upon approaches and theories from the learning sciences, we propose a framework for the learner-centered...

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Hauptverfasser: Kawakami, Anna, Guerdan, Luke, Cheng, Yang, Sun, Anita, Hu, Alison, Glazko, Kate, Arechiga, Nikos, Lee, Matthew, Carter, Scott, Zhu, Haiyi, Holstein, Kenneth
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Sprache:eng
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Zusammenfassung:Human-Centered Explainable AI Workshop at ACM CHI Conference on Human Factors in Computing Systems 2022 In this short paper, we argue for a refocusing of XAI around human learning goals. Drawing upon approaches and theories from the learning sciences, we propose a framework for the learner-centered design and evaluation of XAI systems. We illustrate our framework through an ongoing case study in the context of AI-augmented social work.
DOI:10.48550/arxiv.2212.05588