Gamut - A Design Probe to Understand How Data Scientists Understand Machine Learning Models
CHI, pp. 5792019.
EI
Abstract:
Without good models and the right tools to interpret them, data scientists risk making decisions based on hidden biases, spurious correlations, and false generalizations. This has led to a rallying cry for model interpretability. Yet the concept of interpretability remains nebulous, such that researchers and tool designers lack actionable...More
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