Decision-Making in Everyday Life Based on Artificial Intelligence: The Case of Recommendation Systems

Abstract

This article examines the role of artificial intelligence in everyday decision-making, with a particular focus on recommendation systems. Its purpose is to explore how AI-based technologies collect and analyze user data to generate personalized suggestions that influence individual choices in areas such as entertainment, online shopping, and social media.

The study highlights the growing impact of recommendation systems by referring to real-world examples such as Netflix and Amazon, where a significant portion of user activity is guided by algorithmic recommendations. Statistical insights are used to demonstrate how these systems shape user behavior, improve efficiency, and enhance user experience.

At the same time, the article addresses key challenges associated with AI-driven decision-making, including privacy concerns, algorithmic bias, and users’ increasing dependence on automated systems. By analyzing both the advantages and potential risks, the article provides a balanced overview of the growing role of artificial intelligence in modern life and its impact on human autonomy in decision-making processes.