Recognizing the Algorithmic Literacy of Users in XAI - An Example-Based Approach

Recommender systems are widely used in today's society, but many of them do not meet users' needs and therefore fail to reach their full potential. Without careful consideration, such systems can interfere with the natural decision-making process, resulting in the disregard for recommendations provided. Therefore, it is vital to take into account multiple factors, including expertise, time and risk associated with decisions, as well as the system's context to identify suitable affordances. Furthermore, it is important to consider the algorithmic and digital literacy of the users. This analysis could reveal innovative design opportunities, like combining a recommender system with a digital agent. As a result, it may meet interpersonal needs and facilitate a more natural interaction with the system. Implementing this combination in a digital marketplace could be a promising way to empower users towards an independent life.