ChatGPT and Environmental Research

ChatGPT, the latest text-based artificial intelligence (AI) tool, has quickly gained popularity and is poised to revolutionize various aspects of our lives, including education and research.With its advanced natural language processing (NLP) capabilities, ChatGPT can understand and interpret human language like never before, allowing users to ask questions and receive answers in a conversational and intuitive manner.In this Viewpoint, we aim to draw from our NLP research background and share our experience and thoughts about ChatGPT by providing 10 real-world examples from different areas of environmental research.Our objective is to demonstrate how this emerging tool can be leveraged for research purposes while also highlighting potential pitfalls and challenges.By sharing these experiences, we hope to encourage the responsible and effective use of ChatGPT in research and beyond.The generative pretrained transformer (GPT) is a cuttingedge natural language generation (NLG) model, and its latest iteration, GPT-3.5 (GPT-4 1 was released on March 14, 2023), was on a massive corpus of textual data, such as books, articles, and Web sites, with billions of model parameters (GPT-3 for the details). 2ChatGPT is a fine-tuned application based on the GPT-3.5 engine at its initial release that uses supervised finetuning modeling (learning based on labeled prompt data), reward model construction (ranking the model responses), and proximal policy optimization (a class of reinforcement learning to optimize the reward policy).Two techniques used in ChatGPT are in-context learning and prompt engineering.Incontext learning enables the agent to learn and adapt in real time, making it more versatile and capable of handling a wider range of situations.While ChatGPT can respond to a question with no additional hints (zero-shot prompts), its response quality improves by providing additional examples before asking questions (few-shot prompts).Prompt engineering involves designing model inputs, such as questions and statements, to obtain better outputs (i.e., responses).The popularity of ChatGPT stems from its rapid, informative, and seemingly "intelligent" responses to any questions.However, it is important to question whether the model truly understands the content it produces, because