  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.
