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[D] Machine Learning : Explaining Uncertainty Bias in Machine Learning

I am interesting in this topic, where one can attempt to extract meaningful interpretation on Uncertainty Bias in Machine Learning. Does anyone knows any related papers in this topic?

I already read several papers such as

Ribeiro, Marco Tulio, Sameer Singh, and Carlos Guestrin. “Why should i trust you?: Explaining the predictions of any classifier.” Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining. ACM, 2016.

Lipton, Zachary C. “The mythos of model interpretability.” arXiv preprint arXiv:1606.03490 (2016).

These papers try to interpret why certain models produce its prediction, while I am interesting to explain “Why this model uncertain of this data points”.

Thank you very much for your help.

submitted by /u/rmfajri
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.