Muticia discusses the importance of transparency in forecasting models, emphasizing a preference for approaches that allow for reverse engineering of decisions. She highlights the challenges posed by deep neural networks, which often obscure the reasoning behind their outputs, leading to a lack of clarity in model predictions.
