AI IN SOCIAL NETWORKS: PSYCHOLOGICAL CONSEQUENCES OF ALGORITHMIC MANIPULATION

Abstract

The integration of Artificial Intelligence (AI) within social networks has revolutionized user engagement and content consumption, but its underlying algorithms also raise concerns regarding psychological consequences. These algorithms, designed to personalize content and optimize user experience, often manipulate attention through curated feeds that reinforce biases, create echo chambers, and influence emotions. This paper explores the psychological effects of algorithmic manipulation in social networks, focusing on its impact on self-esteem, anxiety, and decision-making processes. By analyzing the feedback loops created by AI-driven recommendations, the study highlights how social media platforms can shape individual behavior, perceptions of reality, and social interactions. Furthermore, the research examines the role of algorithmic transparency, the responsibility of platform developers, and potential strategies for mitigating the negative psychological impacts of algorithmic manipulation. Ultimately, the paper calls for a more ethical approach to AI in social networks to ensure that user well-being is prioritized without compromising the technological advantages these platforms offer.