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Interpretable Directed Diversity: Leveraging Model Explanations for Iterative Crowd Ideation
We propose Interpretable Directed Diversity to automatically predict ideation quality and diversity scores, and provide AI explanations - Attribution, Contrastive Attribution, and Counterfactual Suggestions - to feedback on why ideations were scored (low), and how to get higher scores.
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