Artificial Intelligence and mass media: negative aspects of content personalization algorithms

Abstract

The development of artificial intelligence (AI) technologies and machine learning algorithms is increasingly influencing various aspects of social life, gradually finding its place not only in social media but also in journalism (Newman). They are actively being integrated into various fields of mass media, enabling the automation of several processes within media companies, thereby optimizing the work of journalists, editors, and media managers. This topic represents a pertinent issue in the modern information society (Túñez López et al.). AI and its machine learning capabilities have become integral parts of the processes of content creation, analysis, and distribution, bringing new opportunities along with significant challenges. For instance, personalization algorithms allow for the adaptation of information to the individual interests and preferences of each user, increasing their engagement and satisfaction with the content. Thus, social networks and many other internet platforms are personalized for each user based on their demographic profiles and personal data. This article provides an overview of current scientific data on the potential risks associated with the use of content personalization algorithms in mass media. The results and conclusions of the article will help to better understand the nature of these risks and the associated challenges for the field of mass communication.