AI-mediated risks and real-life challenges in mushroom foraging

The rise of AI-based mushroom identification applications impacts foraging despite significant risks from relying solely on AI-generated advice. Popular AI-based mushroom identification tools were tested using 100+ photos of nearly 60 species, taken in real-world conditions. Even the best-performing tool failed in almost 15% of cases, with others performing worse. None of tested applications consistently provided a single, correct answer, demonstrating they cannot be trusted for definitive life-or-death identification decisions.

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Publication Details

Journal
npj Science of Food
Published
2026-02-24
DOI
https://doi.org/10.1038/s41538-026-00752-4
Primary Topic
Silymarin and Mushroom Poisoning
Type
article
Field-Weighted Citation Impact
0.00

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article

AI-mediated risks and real-life challenges in mushroom foraging

Fransina Christina King, Nik Kuznetsov, Yu Xia, Sergei Kuznetsov et al.
npj Science of Food
Silymarin and Mushroom Poisoning
article

AI-mediated risks and real-life challenges in mushroom foraging

Fransina Christina King, Nik Kuznetsov, Yu Xia, Sergei Kuznetsov, Milos Ljubisavljevic
article en

Abstract

The rise of AI-based mushroom identification applications impacts foraging despite significant risks from relying solely on AI-generated advice. Popular AI-based mushroom identification tools were tested using 100+ photos of nearly 60 species, taken in real-world conditions. Even the best-performing tool failed in almost 15% of cases, with others performing worse. None of tested applications consistently provided a single, correct answer, demonstrating they cannot be trusted for definitive life-or-death identification decisions.

npj Science of Food
United Arab Emirates University (AE), Karolinska Institutet (SE), KTH Royal Institute of Technology (SE)
Advanced Technology Research Council, Chinese Academy of Sciences, Kunming Institute of Botany, Chinese Academy of Sciences
Openalex Percentile: Top 45%
Silymarin and Mushroom Poisoning
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