Epidemiology Biostatistics and Public Health · Published 2026-06-15 · DOI 10.54103/2282-0930/31293
Alessandro Marcon, Valentina Panetta, Giuseppe Maglietta, Lorenza Scotti, Vittorio Simeon, Giovanni Veronesi
The rapid diffusion of large language models (LLMs) is reshaping many aspects of biomedical research, prompting reflection on the evolving role of biostatisticians in a changing landscape. This commentary addresses this transformation from two complementary perspectives. First, we examine how LLMs can assist biostatisticians in professional practice, highlighting their potential to enhance efficiency, support complex analytical reasoning, and facilitate communication and training. Second, we discuss the limitations and risks associated with LLM use, including challenges to reproducibility, susceptibility to bias, data protection and regulatory constraints, and limited accountability. Finally, we outline a vision for the role of scientific societies in actively guiding this transition. By promoting methodological competence, ethical awareness, and professional identity, they can help ensure that generative AI becomes an instrument of responsible innovation rather than a source of methodological bias and epistemic uncertainty.
Abstract from DOAJ. Public domain (CC0 1.0).
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Marcon, A., Panetta, V., Maglietta, G., et al. (2026). Will generative AI replace biostatisticians? Opportunities, challenges, and professional responsibility in the era of large language models.. Epidemiology Biostatistics and Public Health. https://doi.org/10.54103/2282-0930/31293