The uncritical adoption of AI in science is alarming — we urgently need guard rails
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Computerized automation can hamper the acquisition of skills and expertise. Credit: Westend61/Getty
The scientific community is adopting artificial-intelligence tools, especially large language models (LLMs), at an astonishing speed. LLM-assisted paper writing has drastically increased over the past three years1 and researchers have sought to incorporate semi-autonomous agents into their workflows. However, the rapid and uncritical adoption of AI in science comes with significant risks2. Several problems are already apparent: papers that use AI tools focus on a narrower set of established research questions3, and in some cases have been evaluated to have less scientific merit4, than do studies that do not rely on AI.
Why an overreliance on AI-driven modelling is bad for science