Artificial intelligence opens new frontiers in deep time biodiversity research

Source: https://bsse.ethz.ch/news-and-events/d-bsse-news/2025/08/artificial-intelligence-opens-new-frontiers-in-deep-time-biodiversity-research.html Parent: https://bsse.ethz.ch/news-and-events/d-bsse-news.html?AUTHOR=Q2Fyb2xpbiBBcm5kdCBGb3BwYQ&path=L2NvbnRlbnQvc3BlY2lhbGludGVyZXN0L2Jzc2UvZGVwYXJ0bWVudC9lbi9uZXdzLWFuZC1ldmVudHMvamNyOmNvbnRlbnQvcGFyL25ld3NmZWVkXzQzMTg

A new Perspectives paper in Nature Reviews Biodiversity explores how artificial intelligence (AI) is reshaping palaeontology and biodiversity research, offering transformative tools to analyse complex fossil data and evolutionary patterns across deep time. The authors from ETH Zurich and the University of Zurich highlight how AI is already being used to automate fossil data processing, extract morphological traits, and model evolutionary dynamics – paving the way for a new era of discovery.

Beyond technical advances, the paper emphasises the ethical imperative of equitable access to AI technologies. As AI becomes increasingly central to scientific progress, disparities in computing infrastructure and expertise risk widening the gap between well-resourced institutions and the broader research community. The authors call for inclusive strategies to ensure that AI’s benefits are shared widely, enabling global participation in palaeontological innovation.

“AI is transforming how we tackle complex tasks like understanding biodiversity through deep time. To ensure real progress, access to AI tools and knowledge must be inclusive and shared across the global scientific community.”

Daniele Silvestro, senior scientist in the Computational Evolution group at D-BSSE and co-author of this publication

While AI holds immense promise, the paper also cautions that its full potential in biodiversity research is yet to be realised. Challenges such as data quality, model limitations, and the complexity of biological and geological processes remain. Addressing these issues will be key to unlocking AI’s capabilities and ensuring it serves as a tool for inclusive scientific advancement.

Find original article published in Nature Reviews Biodiversity:

Silvestro, D. and Pimiento, C. (2025) Eexternal page merging uses of artificial intelligence in deep time biodiversity research. Nat. Rev. Biodivers. https://doi.org/10.1038/s44358-025-00075-4

\ Learn about research in the Computational Evolution group led by Tanja Stadler.