Artificial intelligence

Abstract: This article provides a critical analysis of the ethical issues surrounding content personalization in the digital media landscape and identifies the boundaries between useful recommendations and manipulative practices. In the context of rapid advances in artificial intelligence and algorithmic content curation, this research is particularly relevant, as recommendation systems now shape the information environment for billions of users worldwide. The author examines the theoretical foundations of personalization as a technological phenomenon and analyzes the mechanisms of recommendation systems based on collaborative filtering, behavioral pattern analysis, and machine learning. Special attention is given to the dual nature of personalization: on one hand, it enhances user experience, saves time, and delivers relevant content; on the other, it creates risks of consciousness manipulation, the formation of information bubbles, and limitations on individual cognitive autonomy. The article thoroughly investigates ethical dilemmas related to the use of personal data, algorithmic transparency, and platform accountability for recommended content. The phenomenon of information bubbles is examined as a consequence of excessive personalization, leading to societal polarization, echo chambers, and restricted access to diverse viewpoints. The psychological mechanisms through which recommendation systems influence decision-making, belief formation, and user behavioral patterns are analyzed. The author identifies criteria for distinguishing beneficial personalization from manipulative practices, including: algorithmic transparency, user control capabilities, adherence to informed consent principles, protection of cognitive autonomy, and platform social responsibility. Particular attention is devoted to vulnerable user groups, especially children and adolescents, who are particularly susceptible to algorithmic influence. The article proposes a conceptual model of ethical personalization based on balancing recommendation effectiveness with respect for user autonomy. International approaches to personalization regulation are examined, including the European Digital Services Act and other legislative initiatives aimed at ensuring transparency and accountability of algorithmic systems. The practical significance of this research lies in formulating recommendations for recommendation system developers, regulators, and users regarding the implementation of ethical personalization. The author emphasizes the necessity of developing media literacy and critical thinking as tools for countering manipulative practices in the digital environment. The research conclusions underscore the need for an interdisciplinary approach to addressing the ethical issues of personalization, combining technological, legal, psychological, and social dimensions. The study identifies the need to develop ethical standards and industry self-regulation mechanisms that will ensure a balance between innovation and the protection of user rights in the digital society.

Keywords: ethics of personalization, recommendation systems, artificial intelligence, information bubbles, manipulation, algorithmic transparency, media ethics, collaborative filtering

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