AI Large Language Models (LLMs) like ChatGPT are set to reshape some aspects of policymaking processes. Policy practitioners are already using ChatGPT for help with a variety of tasks: from drafting statements, submissions, and presentations, to conducting background research. We are cautiously hopeful that LLMs could be used to promote a marginally more balanced footing among decision makers in policy negotiations by assisting with certain tedious work, particularly benefiting developing countries who face capacity constraints that put them at a disadvantage in negotiations. However, the risks are particularly concerning for environmental and marine policy uses, due to the urgency of crises like climate change, high uncertainty, and trans-boundary impact. To explore the realistic potentials, limitations, and equity risks for LLMs in marine policymaking, we present a case study of an AI chatbot for the recently adopted Biodiversity Beyond National Jurisdiction Agreement (BBNJ), and critique its answers to key policy questions. Our case study demonstrates the dangers of LLMs in marine policymaking via their potential bias towards generating text that favors the perspectives of mainly Western economic centers of power, while neglecting developing countries' viewpoints. We describe several ways these biases can enter the system, including: (1) biases in the underlying foundational language models; (2) biases arising from the chatbot's connection to UN negotiation documents, and (3) biases arising from the application design. We urge caution in the use of generative AI in ocean policy processes and call for more research on its equity and fairness implications. Our work also underscores the need for developing countries' policymakers to develop the technical capacity to engage with AI on their own terms.

翻译：人工智能大型语言模型（如ChatGPT）将重塑政策制定过程的某些方面。政策实践者已开始使用ChatGPT协助完成从起草声明、提交材料和演示文稿到开展背景研究等多种任务。我们谨慎地认为，LLMs通过协助处理某些繁琐工作（特别是帮助面临能力限制而在谈判中处于劣势的发展中国家），有望在政策谈判中为决策者创造更为均衡的立足点。然而，在环境和海洋政策应用中，由于气候变化等危机的紧迫性、高度不确定性及跨境影响，相关风险尤为值得关注。为探究LLMs在海洋政策制定中的实际潜力、局限性与公平性风险，我们以近期通过的《国家管辖范围以外区域生物多样性协定》（BBNJ）为案例，构建人工智能聊天机器人并对其关键政策问题的回答进行评析。案例研究表明，LLMs在海洋政策制定中存在潜在危害——其生成文本可能偏袒以西方经济体为中心的视角，而忽视发展中国家观点。我们阐述了这些偏见进入系统的多种途径，包括：（1）基础语言模型固有的偏见；（2）聊天机器人与联合国谈判文件关联产生的偏见；（3）应用设计引发的偏见。我们呼吁在海洋政策过程中谨慎使用生成式人工智能，并建议加强对其公平性影响的研究。本研究成果同时凸显了发展中国家决策者发展自主参与人工智能技术应用能力的重要性。