Large language models can help boost food production, but be mindful of their risks.

IF 3 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Frontiers in Artificial Intelligence Pub Date : 2024-10-25 eCollection Date: 2024-01-01 DOI:10.3389/frai.2024.1326153
Djavan De Clercq, Elias Nehring, Harry Mayne, Adam Mahdi
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引用次数: 0

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.

大型语言模型有助于提高粮食产量,但要注意其风险。
媒体对 ChatGPT 式大型语言模型(LLM)的报道主要集中在其引人注目的成就上,包括解决高级数学问题和在医学考试中达到专家级水平。但是,LLMs 在农业这个与人类生活息息相关的行业中的逐步应用却很少受到公众的关注。在这篇短文中,我们将探讨在粮食生产系统中更广泛地采用语言模型的风险和机遇。虽然语言模型有可能提高农业效率、推动创新并为更好的政策提供信息,但农业误导信息、收集大量农民数据以及威胁农业就业等挑战也是令人关注的重要问题。LLM 的快速发展凸显了农业政策制定者的必要性,他们需要认真思考各种框架和指导方针,以确保在粮食生产中负责任地使用 LLM,以免这些技术变得如此根深蒂固,以至于政策干预变得具有挑战性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.10
自引率
2.50%
发文量
272
审稿时长
13 weeks
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