When Advice Becomes Infrastructure: Ethical Governance of Conversational AI in Psychoactive Substance Information Ecosystems

Public debates about psychoactive substances have traditionally been organized around the pharmacology of compounds and the institutional control of supply. In digitally mediated societies, however, the pathways through which people encounter psychoactives are increasingly informational: search engines, recommender systems, social platforms, and—distinctively—conversational AI. These systems do not merely deliver neutral facts. They rank, frame, personalize, and conversationally validate claims in ways that can shape perceived norms, acceptable risk thresholds, and willingness to seek help. This opinion advances the concept of AI-mediated exposure to capture how algorithmic curation and interactive dialogue become upstream determinants of psychoactive-related harms and benefits across the continuum from everyday medicines to non-medical use. From a social-scientific ethics perspective, the central question is not whether AI is “good” or “bad,” but what obligations apply when AI performs interpretive authority in contexts characterized by vulnerability, stigma, and unequal access to trusted expertise. The paper argues for an ethics-centered governance framework grounded in four commitments: epistemic responsibility (how claims are generated, warranted, and communicated), relational responsibility (how users are treated in moments of uncertainty, distress, and stigma), distributive justice (who benefits and who bears risk under unequal conditions), and accountability (how behavior is evaluated, contested, and corrected over time). The aim is to treat conversational AI as a public-facing institution whose design choices must be ethically legible and publicly contestable, oriented toward harm reduction without intensifying surveillance, moralization, or inequity.