EAA Web Session: ML Explainability in Actuarial Data Science: A Primer

Explainability is the cornerstone of practicability of ML and AI techniques – without thorough insights into the inner workings of the more advanced decision making and prediction methods, usage become hampered by the worst kind of information asymmetry: Unpredictable model outputs not fit for productive use. Ultimately, AI and ML methods will be well-suited for use in actuarial contexts, but to this end, more and better tools to understand these tools need to be procured and utilized.

Registration deadline: 8 March 2022