Beyond Algorethics: Addressing the Ethical and Anthropological Challenges of AI Recommender Systems
It addresses the problem of AI recommender systems undermining user autonomy and well-being for society, but it is incremental as it builds on existing ethical critiques without introducing new technical solutions.
This paper tackles the ethical and anthropological challenges of AI recommender systems, which shape digital environments by constructing user experiences and raising concerns over privacy and autonomy, and proposes a three-dimensional framework integrating policy, research, and education to reorient these systems toward enhancing human dignity.
This paper examines the ethical and anthropological challenges posed by AI-driven recommender systems (RSs), which increasingly shape digital environments and social interactions. By curating personalized content, RSs do not merely reflect user preferences but actively construct experiences across social media, entertainment platforms, and e-commerce. Their influence raises concerns over privacy, autonomy, and mental well-being, while existing approaches such as "algorethics" - the effort to embed ethical principles into algorithmic design - remain insufficient. RSs inherently reduce human complexity to quantifiable profiles, exploit user vulnerabilities, and prioritize engagement over well-being. The paper advances a three-dimensional framework for human-centered RSs, integrating policies and regulation, interdisciplinary research, and education. These strategies are mutually reinforcing: research provides evidence for policy, policy enables safeguards and standards, and education equips users to engage critically. By connecting ethical reflection with governance and digital literacy, the paper argues that RSs can be reoriented to enhance autonomy and dignity rather than undermine them.