Portland 2019 Analytics Symposium Video: Mark Madsen
The Black Box: Interpretability, Reproducibility, and Responsibility
Mark Madsen – Global Head of Architecture, Teradata
Historically, a model produced a result that was interpreted by a person who made a decision. In recent years, as the amount of data and number of decisions have grown, agency has been taken from humans and given to machines, which make decisions in a black box. Black boxes raise issues around explainability (or interpretability)—being able to explain how a decision was made—and reproducibility —being able to use the same data and model to make an identical decision.