AI-Driven Content Filtering on Instagram and Its Impact on Youth Lifestyle and Interaction

The proliferation of artificial intelligence (AI) in social media platforms has transformed how content is curated and consumed, particularly among younger demographics. This study investigates the impact of AI-driven content filtering on Instagram and how it influences lifestyle preferences and patterns of social interaction among youth aged 16–20 in Palembang, Indonesia. Instagram’s recommendation algorithms, powered by machine learning, tailor content based on users’ behavioral data, which can lead to the formation of filter bubbles environments where individuals are predominantly exposed to homogenous information. Adopting a qualitative approach, the study utilized literature review, content analysis, and in-depth interviews with active youth Instagram users to explore behavioral shifts linked to algorithmically personalized content. Findings indicate that persistent exposure to curated media significantly shapes youth lifestyle aspirations, particularly in domains such as beauty standards, fashion trends, and social validation practices. Moreover, the filter bubble effect fosters the creation of socially insulated groups, reducing exposure to diverse perspectives and limiting critical engagement. Drawing on Information Integration Theory, the study provides a conceptual framework for understanding how algorithmic filtering mechanisms influence user cognition and social behavior. The results underscore the dual role of AI in both enhancing user experience and reinforcing content echo chambers. The study concludes that improving digital literacy and algorithmic awareness is essential to mitigating potential social fragmentation and promoting balanced content consumption. These insights contribute to the broader discourse on AI ethics, user agency, and the societal implications of personalized media environments.