Gamut - A Design Probe to Understand How Data Scientists Understand Machine Learning Models

CHI, pp. 5792019.

Cited by: 45|Bibtex|Views72|DOI:https://doi.org/10.1145/3290605.3300809
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Other Links: dblp.uni-trier.de|dl.acm.org|academic.microsoft.com

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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