ABSTRACT Artificial intelligence (AI) is often viewed with skepticism in the natural sciences, where traditional values of observation, data, and replication dominate. This article challenges that skepticism by arguing that AI—particularly large language models and machine learning tools used in generative AI—should be seen not as shortcuts or threats but as powerful partners in addressing today’s most complex ecological challenges. Issues like climate change and biodiversity loss demand synthesis and integration across vast and multidimensional data sets, which are capabilities where AI excels. While AI’s risks—like misuse or overreliance—are often experienced at the personal scale, its greatest benefits unfold at societal and global scales. Scientific societies also stand to gain by incorporating AI into conference planning, publishing, and policy guidance. Importantly, the next generation of scientists must be equipped with the skills and mindset to work alongside these tools. Rather than replacing scientists, AI offers a new way to think, scale, and act, helping science do what it does best: explore, adapt, and solve big problems.
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Stephen R. Midway
James A. Nelson
Fisheries
Louisiana State University
University of Georgia
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Midway et al. (Tue,) studied this question.
www.synapsesocial.com/papers/68e6d7971ffa7aa7d63d1706 — DOI: https://doi.org/10.1093/fshmag/vuaf094