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University of Cambridge, UK

Sam is a research scientist at the University of Cambridge whose work examines how AI is transforming, and threatening, the way evidence informs conservation and policy decisions. His research focuses on two main areas: the use of large language models for evidence synthesis; and AI, ecology, and conservation and how they intersect. Currently, he is working on the development of AI technologies to streamline the collation of evidence from academic and grey literature to better inform conservation action (https://doi.org/10.33774/coe-2025-rmsqf). His work also addresses the impact AI may have on evidence synthesis more broadly, in terms of poisoning the literature base with fake AI generated papers (https://doi.org/10.1038/d41586-025-02069-w) and changing how evidence is gathered and used by decision-makers.

Sam recently led and published the research paper ‘The potential for AI to revolutionize conservation: a horizon scan’ (https://doi.org/10.1016/j.tree.2024.11.013), leading an international group of conservation scientists and AI experts to examine the revolutionary potential of AI to serve conservation, and identify potential pitfalls. He also works with researchers and conservationists to navigate the ethical dimensions of introducing AI into conservation practice. This research informs broader questions of responsible AI deployment in evidence-based policymaking.