Local Rule-Based Explanations of Black Box Decision Systems

Understand

The recent years have witnessed the rise of accurate but obscure decision systems which hide the logic of their internal decision processes to the users.

• The lack of explanations for the decisions of black box systems is a key ethical issue, and a limitation to the adoption of machine learning components in socially sensitive and safety-critical contexts.
• %Therefore, we need explanations that reveals the reasons why a predictor takes a certain decision.
• In this paper we focus on the problem of black box outcome explanation, i.e., explaining the reasons of the decision taken on a specific instance.