ArticleFrontiers in artificial intelligence2024
Large language models can help boost food production, but be mindful of their risks.
Article in Frontiers in artificial intelligence, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- An agroecological perspective on systems-level transformations to keep current food systems from degrading the global commons.Nature food · 2026Review
- Integration of LLMs and VLMs in plant stress phenotyping: From trait recognition to decision support.Plant phenomics (Washington, D.C.) · 2026Review
- AI for One Welfare: the role of animal welfare scientists in developing valid and ethical AI-based welfare assessment tools.Frontiers in veterinary science · 2025Article
- Advancements in Agricultural Ground Robots for Specialty Crops: An Overview of Innovations, Challenges, and Prospects.Plants (Basel, Switzerland) · 2024Review
Corrections and comments
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Authors and funding
4 authors.
Funding
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Abstract
Coverage of ChatGPT-style large language models (LLMs) in the media has focused on their eye-catching achievements, including solving advanced mathematical problems and reaching expert proficiency in medical examinations. But the gradual adoption of LLMs in agriculture, an industry which touches every human life, has received much less public scrutiny. In this short perspective, we examine risks and opportunities related to more widespread adoption of language models in food production systems. While LLMs can potentially enhance agricultural efficiency, drive innovation, and inform better policies, challenges like agricultural misinformation, collection of vast amounts of farmer data, and threats to agricultural jobs are important concerns. The rapid evolution of the LLM landscape underscores the need for agricultural policymakers to think carefully about frameworks and guidelines that ensure the responsible use of LLMs in food production before these technologies become so ingrained that policy intervention becomes challenging.
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Registered trials
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