Real-Time Hyper-Personalized Generative AI Should Be Regulated to Prevent the Rise of "Digital Heroin"

Raad Khraishi, Cristovão Iglesias Jr, Devesh Batra, Peter Gostev, Giulio Pelosio, Ramin Okhrati, Greig A Cowan

Keywords: generative ai, real-time personalization, behavioral addiction, digital media, public health, policy interventions, machine learning ethics

Abstract: This position paper argues that real-time generative AI has the potential to become the next wave of addictive digital media, creating a new class of digital content akin to ``digital heroin'' with severe implications for mental health and youth development. By shortening the content-generation feedback loop to mere seconds, these advanced models will soon be able to hyper-personalize outputs on the fly. When paired with misaligned incentives (e.g., maximizing user engagement), this will fuel unprecedented compulsive consumption patterns with far-reaching consequences for mental health, cognitive development, and social stability. Drawing on interdisciplinary research, from clinical observations of social media addiction to neuroscientific studies of dopamine-driven feedback, we illustrate how real-time tailored content generation may erode user autonomy, foment emotional distress, and disproportionately endanger vulnerable groups, such as adolescents. Due to the rapid advancement of generative AI and its potential to induce severe addiction-like effects, we call for strong government oversight akin to existing controls on addictive substances, particularly for minors. We further urge the machine learning community to act proactively by establishing robust design guidelines, collaborating with public health experts, and supporting targeted policy measures to ensure responsible and ethical deployment, rather than paving the way for another wave of unregulated digital dependence.

Lay Summary: This position paper argues that real‑time generative AI could become a new form of highly addictive digital media, “digital heroin”, with serious effects on mental health and youth development. Because these systems can create and tailor content in seconds, and because many platforms are driven by engagement‑maximizing incentives, they may push unprecedented, compulsive use that harms mental health, cognitive development, and social stability. Drawing on research from clinical studies of social media addiction and neuroscience on dopamine‑driven feedback, we argue that rapid, personalized content can reduce user autonomy, increase emotional distress, and especially endanger adolescents and other vulnerable groups. Given the fast pace of AI progress and the risk of addiction‑like effects, we call for strong government oversight similar to controls on addictive substances, particularly for minors. We also urge the machine‑learning community to adopt robust design guidelines, collaborate with public‑health experts, and support targeted policies to ensure responsible deployment and to avoid another wave of unregulated digital dependence.

Submission Number: 379