The Invisible Gaze: Algorithmic Sexual Optimization of Minors on TikTok, Instagram, and YouTube
Year: 2025
Type: article
Abstract: This paper investigates the unconscious structure of algorithmic sexual exploitation embedded in major social platforms such as TikTok, Instagram, and YouTube. By analyzing AI recommendation systems that learn from nonverbal signals—such as gaze duration, replays, and scroll behavior—we reveal how these systems drive young users, particularly underage girls, toward sexually optimized visual patterns. Rather than blaming users or condemning content, this work dissects the threefold relationship between platform designers, unaware viewers, and self-optimizing content creators, and exposes how engagement-driven feedback loops silently reinforce exploitative behavior. Framed from the perspective of a detached observer, this essay argues that platforms have transformed from spaces of meaning and education into desire optimization engines—while ethical responsibility remains unclaimed by all parties involved. This is not a moralistic critique, but a structural exposure of how gaze, algorithm, and profit have silently converged into one of the most dangerous feedback loops of the digital age.
Author: 上田, 高之
Language: English
Subfield: Safety Research
Field: Social Sciences
Domain: Social Sciences
SDG: Gender equality
Open Access status: green
OpenAlex ID: W7081635799
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