AI is turning research into a scientific monoculture (www.nature.com)

The increasing focus on generative AI in research is creating a "scientific monoculture," where diverse methodologies and topics are overshadowed by a uniformity driven by institutional incentives and funding priorities. As more researchers align their projects with AI perspectives, the originality and pluralism of inquiry are at risk. This trend not only homogenizes scientific discourse but also reinforces a feedback loop where AI-centric research dominates discussions, leading to the marginalization of valuable questions that fall outside this narrative. This phenomenon has significant implications for the AI/ML community, as it risks eroding intellectual diversity which is essential for adaptability in research. The reliance on shared analytical tools and methodologies may limit the exploration of complex phenomena, making science less resilient to future challenges. To combat this monocropping, experts suggest implementing structural safeguards like diversified funding, promoting methodological rotation, and adopting editorial practices that embrace diverse paradigms. By doing so, the academic community can ensure that the study of AI enriches rather than constrains scientific inquiry, preserving the adaptive capacity required to navigate evolving technological landscapes.