Infusing domain knowledge in AI-based "black box" models for better explainability with application in bankruptcy prediction

27 May 2019Sheikh Rabiul IslamWilliam EberleSid BundySheikh Khaled Ghafoor

Although "black box" models such as Artificial Neural Networks, Support Vector Machines, and Ensemble Approaches continue to show superior performance in many disciplines, their adoption in the sensitive disciplines (e.g., finance, healthcare) is questionable due to the lack of interpretability and explainability of the model. In fact, future adoption of "black box" models is difficult because of the recent rule of "right of explanation" by the European Union where a user can ask for an explanation behind an algorithmic decision, and the newly proposed bill by the US government, the "Algorithmic Accountability Act", which would require companies to assess their machine learning systems for bias and discrimination and take corrective measures... (read more)

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