![]() Generative AI will also make some ways of detecting fraudulent papers-such as requesting full data sets-of little use. This is welcome, but unscrupulous authors will simply not own up. Nature requires authors to detail the use of AI tools in the preparation of a manuscript, and has banned the listing of an AI as a co-author. Scientific journals are not taking the threat from generative AI lightly. They could produce infinite amounts of seemingly genuine data, each graph tailored to each new fraudulent paper, non-stop. ![]() Imagine how much further a modern-day fraudster could get, armed with generative AI. In the end, he got sloppy, using the same data for more than one paper. Unfortunately for Schön, he couldn’t resist the temptation to produce ever-more apparent discoveries at an ever-faster rate. While some groups had expressed frustration at how difficult it was to reproduce his results, others suspected he was leaving crucial details out to cover his tracks from competitors on the way to a Nobel prize. ![]() Over several years, Schön had been fooling his collaborators, their bosses and the scientific community at large into believing that he had achieved a series of breakthroughs-published in Science or Nature every few weeks-that would revolutionise electronics. This observation lifted the lid on one of the most notorious frauds in the history of physics. In 2002, Julia Hsu and Lynn Loo, then working at Bell Labs in the United States, noticed two identical plots in separate papers co-authored by Jan Hendrik Schön, one of that legendary lab’s most prolific scientists. This is relevant to science, too, once you realise that there are fraudsters in the midst of the scientific community. So it is not the quality of the output but the scale at which it can be produced that is of concern. If AI can do a scriptwriter’s job a thousand times faster at a thousandth of the cost, a human needs to be a million times better to justify their fee. In the creative industries, generative AI tools such as ChatGPT and Midjourney threaten disruption not because they can produce writing or images that are better than a human might come up with, but because they can produce them at scale. Generative AI, the argument runs, might have some niche applications in scientific work, or aid menial tasks such as retouching the draft of a paper, but it does not go to the core of the scientific process. Scientists might think that their jobs are safe: after all, our task is to extract information from the natural world, not to create it. In the creative professions, the strain is beginning to show-witness, for example, this year’s strikes by Hollywood actors and writers. The ability of generative artificial intelligence to produce text and images indistinguishable from the work of humans has both gripped the public imagination and caused alarm. Stop judging researchers by their publications or risk a tsunami of fakes, warns Jorge Quintanilla
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