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

12/11/2022
by   Anna Kawakami, et al.
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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.

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