The role of large language models in interdisciplinary research: Opportunities, challenges and ways forward

Abstract

Abstract Large language models (LLMs) are gaining importance in research as they offer many benefits. One often overlooked benefit is their potential to facilitate and support interdisciplinary research, which is key to addressing current global challenges, such as the twin crises of biodiversity loss and climate change. LLMs can help reduce the costs associated with knowledge transfer and bridge gaps between different fields of study. They can also be especially useful in helping ecologists understand and adopt powerful techniques common in other fields. However, using LLMs in research, especially for complex tasks, carries important risks, including the possibility of generating inaccurate information, which can lead to false conclusions. We recommend that researchers adhere to best practices when using LLMs for research by providing appropriate prompts and dividing complex tasks into smaller, more manageable tasks that facilitate learning and testing. Moreover, journals should implement policies to ensure that information and code generated using LLMs are properly validated. Academic programs should incorporate formal training in LLMs, equipping students and researchers with the necessary skills to use these tools more effectively and responsibly, including for interdisciplinary research.

Keywords

• ChatGPT
• ecological research
• Gemini
• generative artificial intelligence
• large language models
• machine learning