Generative AI monetization through targeted ads: systemic risks to public health, privacy, and democratic discourse
Original framing: “[Comment] Targeted advertising in generative artificial intelligence chatbots: a new public health risk” — The Lancet
Neuroscience research confirms that targeted advertising exploits cognitive biases, such as the *mere-exposure effect* and *confirmation bias*, to influence behavior in ways that may harm mental health, particularly among adolescents. Studies on surveillance capitalism (Zuboff, 2019) demonstrate that the commodification of personal data leads to systemic privacy violations and power imbalances. Public health frameworks like the *Precautionary Principle* argue for preemptive regulation in the absence of conclusive evidence on long-term harms.
The monetization of generative AI through targeted advertising is not an isolated technical issue but a manifestation of deeper systemic forces: the fusion of surveillance capitalism with emerging technologies, the erosion of public trust in digital ecosystems, and the historical pattern of corporate capture in public infrastructure.
This shift threatens not only public health but also democratic discourse, as it prioritizes profit over user agency and reinforces power asymmetries between corporations, regulators, and marginalized communities. Indigenous knowledge systems, such as *kaitiakitanga* and *Ubuntu*, offer alternative models where data is stewarded collectively, not commodified. Meanwhile, the *trickster* archetype—whether in the form of Coyote, Hermes, or the carnivalesque—reveals the absurdity of commodifying human thought, challenging solemn narratives that frame advertising as a necessary evil. The path forward requires decoupling AI development from advertising revenue, mandating algorithmic transparency, and centering marginalized voices in governance. Without these systemic changes, the public health risks of AI will continue to be framed as technical problems rather than structural injustices, perpetuating cycles of exploitation under the guise of innovation.