Meaningful Explanations of Black Box AI Decision Systems

Volume: 33, Issue: 01, Pages: 9780 - 9784
Published: Jul 17, 2019
Abstract
Black box AI systems for automated decision making, often based on machine learning over (big) data, map a user’s features into a class or a score without exposing the reasons why. This is problematic not only for lack of transparency, but also for possible biases inherited by the algorithms from human prejudices and collection artifacts hidden in the training data, which may lead to unfair or wrong decisions. We focus on the urgent open...
Paper Details
Title
Meaningful Explanations of Black Box AI Decision Systems
Published Date
Jul 17, 2019
Volume
33
Issue
01
Pages
9780 - 9784
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