As I was presenting a webinar last month based around the complexities and common issues of risk modeling, a question came up surrounding the validation of models utilizing artificial intelligence and machine learning algorithms. In particular, the question regarded what sort of practical approaches we can take, and how those of us outside of the AI experts can understand a technical topic like this one. Or, at the very least, how we can (as non-experts) comprehend the gist of what’s required, and leave the more in-the-weeds aspects to those machine masters.