Abstract The rapid acceptance and use of large‑language models (LLMs)—including ChatGPT, Gemini, Claude, and related systems—has sparked a contentious debate over their suitability for children. Proponents argue that early exposure equips children with essential competencies for a future dominated by generative AI. They cite potential gains in cognition, personalized tutoring, and social interaction. Critics, however, warn that children’s access to LLMs may jeopardize children’s physical, cognitive, social, and mental health. They echo concerns that later emerged after two decades of unregulated social‑media use. Drawing parallels with the delayed regulatory response to social‑media platforms, this paper advocates a precautionary ban on children’s use of LLMs. First, we delineate the precautionary principle and its four requisite conditions—epistemic uncertainty, credible scientific indication of serious harm, irreversibility of damage, and proportionality of response. We then contrast the rigorous, evidence‑based admission processes governing other products such as medicine with the comparatively lax market entry of digital technologies, illustrating how the latter’s laissez‑faire stance facilitated widespread harm. Next, we show early empirical findings and high‑profile incidents (including deaths) suggesting that LLMs can contribute to emotional dependency, impair problem‑solving skills, and exacerbate mental‑health vulnerabilities among children. Although some studies report modest benefits, the current evidence base remains preliminary and inconclusive. Given the plausibility of severe, potentially irreversible harms and the absence of robust safeguards, a temporary, proportionate ban on LLM use by children emerges as the most prudent policy. This prohibition should persist until developers can demonstrably prove that the net benefits outweigh the risks, thereby shifting the burden of proof onto proponents of allowing children access to LLMs.
Robbins et al. (Mon,) studied this question.