Abstract
Contextual information is a prerequisite for timely offering of personalized decision support and recommendation. Yet, research on context-aware recommender systems (CARS) does not appear to be thriving, and finding public datasets containing context factors is a challenging task. We can make various assumptions about why this drop in research interest happened - be it ethical considerations or the popularity of opaque deep learning models that merely consider context in an implicit way. This is an unwelcome development. We argue that continued effort must be put on the creation of suitable datasets. Furthermore, we see significant opportunities in the development of next-generation CARS in the space of interactive AI assistants powered by Large Language Models.