ProtoTree: Addressing the black-box nature of deep learning models

One of the biggest obstacles in the adoption of Artificial Intelligence is that it cannot explain what a prediction is based on. These machine-learning systems are so-called black boxes when the reasoning for a decision is not self-evident to a user. Meike Nauta, Ph.D. candidate at the Data Science group within the EEMCS faculty of the University of Twente, created a model to address the black-box nature of deep learning models. Algorithms can already make accurate predictions, such as medical diagnoses, but they cannot explain how they arrived at such a prediction. In recent years, a lot of attention has been paid to the explainable AI field.