Opening a conversation on responsible environmental data science in the age of large language models

The general public and scientific community alike are abuzz over the release of ChatGPT and GPT-4. Among many concerns being raised about the emergence and widespread use of tools based on large language models (LLMs) is the potential for them to propagate biases and inequities. We hope to open a conversation within the environmental data science community to encourage the circumspect and responsible use of LLMs. Here, we pose a series of questions aimed at fostering discussion and initiating a larger dialogue. To improve literacy on these tools, we provide background information on the LLMs that underpin tools like ChatGPT. We identify key areas in research and teaching in environmental data science where these tools may be applied, and discuss limitations to their use and points of concern. We also discuss ethical considerations surrounding the use of LLMs to ensure that as environmental data scientists, researchers, and instructors, we can make well-considered and informed choices about engagement with these tools. Our goal is to spark forward-looking discussion and research on how as a community we can responsibly integrate generative AI technologies into our work. Impact Statement With the recent release of ChatGPT and similar tools based on large language models, there is considerable enthusiasm and substantial concern over how these tools should be used. We pose a series of questions aimed at unpacking important considerations in the responsible use of large language models within environmental data science.