Recommendation System as a Social Determinant of Health

• Published in: Digital society : ethics, socio-legal and governance of digital technology socio-legal and governance of digital technology, 2024-08, Vol.3 (2), Article 28
• Main Author: Goswami, Arijit
• Format: Article
• Language: English
• Subjects: Computer Science; Computers and Society; Intellectual Property; IT Law; Media Law; Original Paper; Philosophy of Technology; R & D/Technology Policy
• ISSN: 2731-4650; 2731-4669
• DOI: 10.1007/s44206-024-00118-x

Recommendation systems operate as underlying algorithms in social media platforms, e-commerce websites, online news websites, community forums, and media publication platforms, among other digital spaces. These artificial intelligence (AI) systems collect data about an individual’s browsing behavior, demographics, and engagement with diverse content to offer personalized suggestions about information that the user would be interested in. The personalization of recommendations and the resulting engagement of the user with the offered information create preference feedback loops that narrow down the diversity of content that the user is exposed to. It eventually leads to an oversupply of information on a particular theme and promotes certain stereotypes and ideologies in the user’s mind, leading to polarization and deception of the users. Extremist viewpoints and the promotion of certain standards can potentially impact the mental health of the users. The conceptual paper investigates the potential of recommendation systems in affecting the mental well-being of users it suggests information to. By drawing on the mechanism of echo chamber formation by recommendation systems and the impact of echo chambers on mental and physical health, the paper attempts to interconnect the field of content recommendation algorithms and health. It also envisages an approach to mitigate the effects of echo chambers on the health of individuals.