Generative AI And Copyright In Agricultural Extensions
- IJLLR Journal
- Apr 21
- 1 min read
Shivranjni, CHRIST (Deemed to be University), Delhi, NCR
ABSTRACT:
Generative AI models like GPT-4 and Llama 4, powered by large language models (LLMs), have advanced capabilities across diverse fields. Their application in agricultural extension and advisory services, emphasizing climate-smart practices to enhance food production and reduce greenhouse gas emissions. Despite their potential, generative AI raises significant legal challenges regarding training data and outputs. Many AI systems rely on copyrighted materials, raising concerns about intellectual property (IP) infringement.
In agricultural advisory services, LLMs can transform key areas like farm mechanization, crop monitoring, livestock management, and water management by optimizing operations, predicting outcomes, and enhancing resource use. For instance, they can analyze data to recommend planting schedules or improve crop yields. However, these advancements face hurdles, particularly in managing IP issues related to training data. Copyright laws often do not protect AI-generated outputs unless significant human input is involved. Training generative AI on copyrighted materials sparks debates on "fair use."
Legal uncertainties persist, with lawsuits against AI companies addressing copyright infringement. Until resolved, these issues create ambiguity for adopting LLMs in agriculture. This paper highlights these challenges and explores IP implications globally.
Keywords: Advisory services, Agricultural extension, Generative AI, Copyright infringement, Legal concerns
