Many machine learning methods are more or less black boxes for the end user. Even those who develop the machine learning methods can struggle with explaining how methods actually work, or which variables that are most decisive for a specific prediction. The latter is a GDPR requirement for automated individual decision-making. We will give an overview of current methods for opening black boxes. Some of them are useful, while others need more research to be more useful than harmful.
The lecture will be held by Dr. Anders Løland, Norwegian Computing Center.