AI-Driven Content Curation and Its Impact on Media Diversity in Social Networks

Abstract

The rapid advancement of generative artificial intelligence (AI) has made AI-driven content curation a dominant force in shaping public discourse on social media. Platforms, including Facebook, YouTube, and TikTok employ recommendation algorithms to personalise content and increase user engagement. However, these systems also intensify concerns over media pluralism, algorithmic bias, and misinformation. By prioritising user preferences, they reinforce filter bubbles and restrict exposure to diverse viewpoints. As a result, democratic dialogue weakens, and public opinion formation becomes distorted. This study examines how AI-assisted content curation affects media diversity in European social networks, focusing on platform accountability and regulatory challenges. Special attention is given to recent policy interventions, including DSA (2022), Germany’s Action Plan (2024), and the EU AI Act (2025) initiatives on AI-generated political content. However, they also expose significant gaps in enforcement and oversight. To evaluate regulatory impact, this study analyses platform policies, legal frameworks, and AI content selection mechanisms. Despite transparency being a main objective, findings reveal current regulations unable to reduce algorithmic bias or achieve balanced content representation. In response, the study advocates for improved explainable AI (XAI) models, demands stronger regulatory oversight, and supports increased user control over content selection. By addressing these shortcomings, this research contributes to the wider debate on AI ethics, media governance, and digital policy in Europe.

Ähnliche Arbeiten