The final, formatted version of the article will be published soon.
PERSPECTIVE article
Front. Artif. Intell.
Sec. AI in Food, Agriculture and Water
Volume 7 - 2024 |
doi: 10.3389/frai.2024.1326153
Large language models can help boost food production, but be mindful of their risks
Provisionally accepted- 1 Oxford Internet Institute, Social Sciences Division, University of Oxford, Oxford, United Kingdom
- 2 University of Oxford, Oxford, England, United Kingdom
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.
Keywords: Large langauge models, Generative AI, Agriculture, food systems, food production, artificial intelligence
Received: 13 Nov 2023; Accepted: 09 Sep 2024.
Copyright: © 2024 De Clercq and Mahdi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Djavan De Clercq, Oxford Internet Institute, Social Sciences Division, University of Oxford, Oxford, United Kingdom
Adam Mahdi, Oxford Internet Institute, Social Sciences Division, University of Oxford, Oxford, United Kingdom
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