The Impact of Recommender Algorithms in Cyberspace on Social Behavior and Human Rights

In cyberspace, recommender algorithms play an important role in guiding users towards content that is tailored to their interests and needs. These algorithms personalize content and improve the user experience by analyzing users' behavioral data in cyberspace. However, these processes also bring with them numerous social and ethical challenges and consequences, including the creation of algorithmic biases, echo chambers, and a reduction in the diversity of content presented to users, which can lead to the polarization of views and a threat to democracy. This article analyzes the challenges of recommender algorithms, including algorithmic biases and their social consequences, using a descriptive-analytical method and library and Internet resources. The aim of this paper is to examine in detail the ethical considerations and regulatory approaches to counter the negative consequences of these algorithms and to propose co-regulatory solutions to improve fairness and transparency in recommender algorithms. Finally, the results of this research show that creating fair and non-discriminatory algorithms requires a combination of technological and regulatory approaches that are consistent with the principles of human rights and freedom of expression.