This year’s challenge focuses on online news recommendation, addressing both the technical and normative challenges inherent in the design of effective and responsible recommender systems for news publishing. The challenge will delve into the unique aspects of news recommendation. These include modeling user preferences based on implicit behavior, accounting for the influence of the news agenda on user interests, and managing the rapid decay of news items. Furthermore, our challenge also embraces the normative complexities. These involve investigating the effects of recommender systems on the news flow, and whether they resonate with editorial values. By providing participants with a comprehensive dataset and a robust news recommendation evaluation framework, our goal is to tackle these multifaceted challenges head-on. As part of the challenge, Ekstra Bladet will be releasing an anonymized dataset with approximately 2 million random users who engaged with EkstraBladet.dk over a six-week period.