Article

Learning Representations by Humans, for Humans

2019-06-01

Abstract excerpt

<p>We propose a new, complementary approach to interpretability, in which machines are not considered as experts whose role it is to suggest what should be done and why, but rather as advisers. The objective of these models is to communicate to a human decision-maker not what to decide but how to decide. In this way, we propose that machine learning pipelines will be more readily adopted, since they allow a decisi...

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Literature Corpus work: c6b45858-8f57-5d80-995d-033f8207fa47
DOI: 10.31234/osf.io/4nvts

Open publication

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