Interactional foundations for critical AI literacies

• The ubiquity and ease of use of large language models makes it easy to overlook the interactional and interpretive processes at play. To understand the attraction of this technology we need to trace its sociotechnical roots. From divination and horoscopes and from ELIZA to present-day large language models, I document how people have been thinking with things, outsourcing judgement, and making sense of interactively presented non-sense. Following the lead of Lucy Suchman to “slow down discourses of the ‘smart’ machines”, I consider the interactional foundations of our engagement with technologies of language. I make the case that the fluid output, fine-tuned overconfidence, and interactive design of these computational artefacts conspire to exploit our interpretive processes and interactional infrastructure, rendering them irresistible to lay people and researchers alike. This means that a deep understanding of processes of human interaction and sense-making will be a foundational resource for the growing arsenal of methods in critical AI literacy.

AI Expands Scientists’ Impact but Contracts Science’s Focus

• Development in Artificial Intelligence (AI) has accelerated scientific discovery. Alongside recent AI-oriented Nobel prizes, these trends establish the role of AI tools in science. This advancement raises questions about the potential influences of AI tools on scientists and science as a whole, and highlights a potential conflict between individual and collective benefits. To evaluate, we used a pretrained language model to identify AI-augmented research, with an F1-score of 0.875 in validation against expert-labeled data. Using a dataset of 41.3 million research papers across natural science and covering distinct eras of AI, here we show an accelerated adoption of AI tools among scientists and consistent professional advantages associated with AI usage, but a collective narrowing of scientific focus. Scientists who engage in AI-augmented research publish 3.02 times more papers, receive 4.84 times more citations, and become research project leaders 1.37 years earlier than those who do not. By contrast, AI adoption shrinks the collective volume of scientific topics studied by 4.63% and decreases scientist’s engagement with one another by 22.00%. Thereby, AI adoption in science presents a seeming paradox — an expansion of individual scientists’ impact but a contraction in collective science’s reach — as AI-augmented work moves collectively toward areas richest in data. With reduced follow-on engagement, AI tools appear to automate established fields rather than explore new ones, highlighting a tension between personal advancement and collective scientific progress.

Scientists invented a fake disease. AI told people it was real

• The format of the fake-disease experiment — and the way the results pretended to be from an official source, namely an academic paper, might have been a key factor in its success. In a separate study of 20 LLMs, Omar found that LLMs are more prone to hallucinate and elaborate on misinformation when the text they’re processing looks professionally medical — formatted like a hospital discharge note or clinical paper — than when it comes from social-media posts (M. Omar et al. Lancet Digit. Health 8, 100949; 2026). “When the text looks professional and written as a doctor writes, there’s an increase in the hallucination rates,” says Omar.
• The experiment’s reach has now spread into the published medical literature. The bixonimania research has been cited by a handful of researchers, including a study that appeared in Cureus, a journal published by Springer Nature, the publisher of Nature, by researchers at the Maharishi Markandeshwar Institute of Medical Sciences and Research in Mullana, India (S. Banchhor et al. Cureus 16, e74625 (2024); retraction 18, r223 (2026)). (Nature’s news team is editorially independent of its publisher.) That study cites one of the fake preprints and says: “Bixonimania is an emerging form of POM [periorbital melanosis] linked to blue light exposure; further research on the mechanism is underway.”

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