Reconfiguration of Media Communication in the Age of AI and Inequality
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Abstract
Artificial Intelligence (AI) is transforming the production, distribution, and consumption of information within digital media ecosystems. While AI offers unprecedented opportunities for innovation, efficiency, and personalization, it also risks deepening existing socioeconomic and digital inequalities. This study explores the complex relationship between AI, media access, and inequality in the digital era. This exploratory research employed a descriptive approach by analyzing secondary sources, including academic literature, media reports, policy documents, and online resources related to AI and digital media. Data were synthesized to identify patterns of structural injustices and regulatory challenges in both the Global North and Global South. The findings indicate that AI-driven tools such as automated journalism, algorithms, deepfake technologies, and generative models are reshaping traditional media workflows. While these innovations enhance efficiency and personalization, they also introduce concerns related to bias, misinformation, opacity in corporate practices, and the erosion of editorial authority. The analysis further reveals that structural inequalities and regulatory gaps mediate the benefits of AI, often privileging technologically advanced actors while marginalizing underserved groups. The study concludes that although AI has the potential to revolutionize media practices, its integration into digital ecosystems risks widening digital divides and reinforcing power asymmetries. Without inclusive policies, ethical leadership, and equitable access frameworks, AI may consolidate control in the hands of a few, thereby undermining media pluralism and social equity.
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