Data storytelling meets interpretable machine learning: Decoding AI decisions for non-experts without revealing sensitive data and model details
This study proposes a formal definition of data storytelling in IML, introduces the DIST Pyramid to align data storytelling with IML, and presents the I-P-O Model to describe their interactions, and develops an architecture to explain AI decisions through distinct "What-if" and "Why-not" event-generation processes.
Le-Men Chao, Zi-Xuan Yang, An-Ran Fang et al.
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