New study highlights that generative AI systems—especially large language models like ChatGPT—tend to produce standardized, mainstream content, which can subtly narrow users’ worldviews and suppress diverse and nuanced perspectives. This isn't just a technical issue; it has real social consequences, from eroding cultural diversity to undermining collective memory and weakening democratic discourse. Existing AI governance frameworks, focused on principles like transparency or data security, don’t go far enough to address this “narrowing world” effect. To fill that gap, the article introduces “multiplicity” as a new principle for AI regulation, urging developers to design AI systems that expose users to a broader range of narratives, support diverse alternatives and encourage critical engagement so that AI can enrich, rather than limit, the human experience.

A new study by researchers at the Icahn School of Medicine at Mount Sinai finds that widely used AI chatbots are highly vulnerable to repeating and elaborating on false medical information, revealing a critical need for stronger safeguards before these tools can be trusted in health care. The researchers also demonstrated that a simple built-in warning prompt can meaningfully reduce that risk, offering a practical path forward as the technology rapidly evolves. Their findings were detailed in the August 2 online issue of Communications Medicine [https://doi.org/10.1038/s43856-025-01021-3].