Mechanistic Correspondence Between Attention-Manipulating Algorithms and Psychoactive Substances: Evidence and Regulatory Implications

This work examines mechanistic correspondence between algorithmic attentionmanipulation systems and classical psychoactive narcotics. Through comparativeanalysis of neurobiological mechanisms, behavioral patterns, and societal consequences,we document that recommendation algorithms activate identical neuralreward circuitry while producing comparable patterns of tolerance, withdrawal, andcompulsive use. Documentary evidence establishes corporate awareness of psychologicaleffects through internal research conducted prior to continued system operation.Historical analysis of narcotic regulation reveals structural parallels in industrybehavior, regulatory delay, and harm accumulation patterns. We assess whetherregulatory frameworks applied to psychoactive substances could be adapted for algorithmicsystems within existing legal constraints. Analysis concludes that mechanisticcorrespondence, documented corporate knowledge, and historical precedentwarrant consideration of adapted regulatory approaches, contingent on resolutionof constitutional and technological implementation challenges.