Ethical frameworks for the use of natural language processing (NLP) are urgently needed to shape how large language models (LLMs) and similar tools are used for healthcare applications. Healthcare faces existing challenges including the balance of power in clinician-patient relationships, systemic health disparities, historical injustices, and economic constraints. Drawing directly from the voices of those most affected, and focusing on a case study of a specific healthcare setting, we propose a set of guiding principles for the use of NLP in maternal healthcare. We led an interactive session centered on an LLM-based chatbot demonstration during a full-day workshop with 39 participants, and additionally surveyed 30 healthcare workers and 30 birthing people about their values, needs, and perceptions of NLP tools in the context of maternal health. We conducted quantitative and qualitative analyses of the survey results and interactive discussions to consolidate our findings into a set of guiding principles. We propose nine principles for ethical use of NLP for maternal healthcare, grouped into three themes: (i) recognizing contextual significance (ii) holistic measurements, and (iii) who/what is valued. For each principle, we describe its underlying rationale and provide practical advice. This set of principles can provide a methodological pattern for other researchers and serve as a resource to practitioners working on maternal health and other healthcare fields to emphasize the importance of technical nuance, historical context, and inclusive design when developing NLP technologies for clinical use.

翻译：针对自然语言处理（NLP）在医疗保健中的应用，亟需构建伦理框架以规范大语言模型（LLMs）及相关工具的使用方式。医疗领域面临诸多既有挑战，包括医患关系中的权力平衡、系统性健康差异、历史不公正以及经济限制因素。我们基于最受影响群体的真实声音，并以特定医疗场景的案例研究为核心，提出一套在母胎保健中应用NLP的指导原则。在为期一天的工作坊中，我们面向39名参与者开展以LLM聊天机器人演示为中心的互动环节，同时对30名医疗工作者和30名分娩者进行问卷调查，了解他们对母胎健康领域NLP工具的价值取向、需求与认知。通过对调查结果及互动讨论进行定量与定性分析，我们将研究结果整合形成系列指导原则。我们提出九项母胎保健领域NLP伦理使用原则，分为三大主题：（i）承认情境重要性、（ii）整体性评估，以及（iii）价值主体认定。针对每项原则，我们阐述其理论基础并提供实践建议。该原则体系可为其他研究者提供方法论范式，并为从事母胎健康及其他医疗领域的实践者提供资源，强调在开发临床NLP技术时须重视技术细节、历史背景与包容性设计。