Large language models like ChatGPT are purveyors of plausibility. The chatbots, many based on so-called generative AI, are trained to respond to user questions by scraping the internet for relevant information and assembling coherent answers, churning out convincing student essays, authoritative legal documents and believable news stories. But, because publicly available data contains misinformation and disinformation, some machine-generated texts might not be accurate or true. That has triggered a scramble to develop tools to identify whether text has been drafted by human or machine. Science is also struggling to adjust to this new era, with live discussions over whether chatbots should be allowed to write scientific papers or even generate new hypotheses.