AWS Adds Explainability to SageMaker

Amazon Web Services is adding an automated machine learning tool to its SageMaker machine learning model builder that improves model accuracy via explainable AI. The new SageMaker feature dubbed Autopilot generates a model explainability report via SageMaker Clarify, the Amazon tool used to detect algorithmic bias while increasing the transparency of machine learning models. The reports would help model developers understand how individual attributes of training data contribute to a predicted result. The combination is promoted as helping to identify and limit algorithmic bias and explain predictions, allowing users to make informed decisions based on how models arrived at conclusions, AWS said this week. The reports also include "feature importance values" that allow developers to understand as a percentage the correlation between a training data attribute and how it contributed to a predicted result.