While news media has for long been subject to algorithmic filtering by social media companies, recent developments in data science and artificial intelligence offer new possibilities for traditional news media organizations to develop and implement recommender systems on their platforms. Recommender systems can enhance users’ experiences by adding relevance, depth, and offering unexpected content, but as news become personalized, discussion of the values embedded in filtering systems also emerge.
This workshop involves members of the AI, Media & Democracy Lab (AIMD), Center for Tracking and Society (CTS), and associates to the Platform Intelligence in News project (PIN). AIMD lab focuses on the democratic implications of AI technology in media and involves prominent researchers from diverse disciplines (law, philosophy, communication, and computer science) that have contributed substantially to the research on news recommender systems. Center for Tracking and Society is the home for interdisciplinary research on digital tracking, data practices and automated decision-making across contexts of the welfare state. CTS is partner to the PIN project, an R&D project about the integration of NPL and recommender systems in a large Danish media organization.
The aim of this workshop is to exchange ideas about experiences with news recommendations, including the integration of values in recommender systems, methods and learnings from studying user experiences, and the potential futures of AI in the newsroom. The workshop is structured by three sessions comprising brief presentations (approx. 10 min) followed by a group discussion.