From information to influence: how Generative AI is reshaping public opinion, misinformation, and social polarization in the digital age

Abstract

Generative Artificial Intelligence (AI) has revolutionized digital communication, changing the way information is generated, shared, and accessed. However, despite its advantages, it also comes with risks such as AI-generated misinformation, algorithmically tailored opinion-forming, and growing polarization. This proposed study aims to investigate the interplay between generative AI, public opinion formation, misinformation and social polarization from an interpretivist philosophical perspective by adopting a qualitative research approach and thematic analysis, as well as qualitative document analysis of journal articles, AI governance reports, policy documents and selected digital media case studies to identify patterns, meanings and emerging themes. The analysis identifies four related themes: the transformation of information production with generative AI, the amplification and spread of misinformation created with AI, increased influence of algorithmic systems on public opinion and political discourse, and further ideological polarization with new governance and ethical issues. The study findings suggest that while generative AI can improve information access, communication and civic engagement, its misuse can lead to the fragmentation of information integrity, destroy public confidence in information, impair democratic discourse, and exacerbate social polarization. It offers innovative insights for policymakers, tech companies, media platforms, teachers, and researchers to help ensure a morally accountable digital information sphere and develop coordinated policy measures to address misinformation and foster a healthier digital information environment.