ML Explainability with Amazon SageMaker Debugger Amazon Web Services

ML is no longer just an aspirational technology exclusive to academic and research institutions; it has evolved into a mainstream technology that has the potential to benefit organizations of all sizes. However, a lack of transparency in the ML process and the black box nature of resulting models is a hindrance for improved ML adoption in industries such as financial services and healthcare. For a team developing ML models, the responsibility to explain model predictions increases as the impact of predictions on business outcomes increase. For example, consumers are likely to accept a movie recommendation from an ML model without needing an explanation. The consumer may or may not agree with the recommendation, but the need to justify the prediction is relatively low on the model developers.