Interpretability, Explainability, and Machine Learning – What Data Scientists Need to Know - KDnuggets

I use one of those credit monitoring services that regularly emails me about my credit score: "Congratulations, your score has gone up!" "Uh oh, your score has gone down!" I shrug and delete the emails. Credit scores are just one example of the many automated decisions made about us as individuals on the basis of complex models. I don't know exactly what causes those little changes in my score. Some machine learning models are "black boxes," a term often used to describe models whose inner workings -- the ways different variables ended up related to one another by an algorithm -- may be impossible for even their designers to completely interpret and explain.