Ethical Implications of AI-Driven Personalization in Digital Media

Abstract

This paper examines the ethical issues resulting from AI-driven personalization of digital media: concerns with privacy, algorithmic bias, and impacts on information diversity. Our mixed-method approach draws on secondary data analysis and case studies of major digital platforms to uncover current, significant challenges within the practice of personalization. Our results include cases of pervasive data gathering, in most cases well beyond user awareness; algorithmic bias, which reinforces societal inequalities in most cases; and filter bubbles, which stand in the way of varied viewpoints. One underscores the need for more transparent data practices, robust bias mitigation strategies, and mechanisms ensuring information diversity. A basic ethical framework to scrutinize AI-driven personalization applications is proposed, and open directions for future research are highlighted. This work contributes to the discussion unfolding at the moment for the development of responsible AI in digital media. It underlines that the moves in technological progress need to be balanced with ethical considerations, which understand user rights and social well-being.