Evaluating Interpretability CS 282 BR Topics in

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Evaluating Interpretability CS 282 BR Topics in Machine Learning: Interpretability and Explainability Ike Lage 02012023 Overview Evaluating interpretability in the interpretable ML community: Interpretability depends on human experience

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01
Evaluating Interpretability CS 282 BR Topics in Machine Learning: Interpretability and Explainability

Ike Lage
02/01/2023<br>
02
Overview Evaluating interpretability in the interpretable ML community:
Interpretability depends on human experience of the model
Disagreement about the best way to measure it
These papers:
Evaluating factors related to interpretability through user studies<br>
03
Other Relevant Fields Human-Computer Interaction (HCI):
Theories for how people interact with technology
Psychology:
Theories for how people process information
Both have thought carefully about experimental design<br>