LLMs and the Risk of Sloppy Science: Navigating the Future of Scientific Inquiry in the Age of Artificial Intelligence
Description of Resource
The emergence of Large Language Models (LLMs) such as GPT-3 represents a paradigm shift in scientific research, offering unparalleled capabilities in data analysis, hypothesis generation, and literature synthesis. However, their integration into research processes raises fundamental philosophical, methodological and ethical concerns. This article critically examines the benefits and risks associated with LLMs through the lenses of philosophy of science, cognitive science, and second-order cybernetics in order to augment a public debate that has until now seemed excessively focused on practical implementation risks rather than categorical errors. We explore the tension between augmenting human research capabilities and the threat of "sloppy science," where the ease of generating scientific content may compromise the quality and reliability of research outputs.