Recommender Systems in the News
This course explores the impact of AI-based recommendations on our media consumption. As one of the most prevalent artificial intelligence applications, Recommender Systems (RS) play a pivotal role in curating personalized content experiences for users amidst the vast expanse of online content.
Among them, News Recommender Systems (NRS) are becoming ubiquitous in the digital media landscape. Particularly in the realm of political news, the adoption of NRS can significantly impact journalistic distribution, affecting journalistic work practices and news consumption. Thus, NRS impact both the supply and demand of political news.
Throughout the course, students will examine the fundamental principles of recommender systems, including their role in alleviating information overload and enhancing user engagement. By understanding the mechanics of RS, participants gain insights into the societal implications and ethical considerations of AI-driven recommendation systems, particularly within the context of news distribution.
Designed as an introductory course, this class is aimed at learners from diverse backgrounds, requiring no prior knowledge of programming or AI concepts. The course will equip students to navigate the evolving landscape of news consumption and engage in informed discussions about technology's intersection with media and society by providing a foundational understanding of AI-based recommendations.
- Trainer/in: Kirill Andreev
- Trainer/in: Silvia Westerwick
- Trainer/in: Maria Vanesa Yepes Serna