Natural language processing (NLP) tools have the potential to boost civic participation and enhance democratic processes because they can significantly increase governments' capacity to gather and analyze citizen opinions. However, their adoption in government remains limited, and harnessing their benefits while preventing unintended consequences remains a challenge. While prior work has focused on improving NLP performance, this work examines how different internal government stakeholders influence NLP tools' thoughtful adoption. We interviewed seven politicians (politically appointed officials as heads of government institutions) and thirteen public servants (career government employees who design and administrate policy interventions), inquiring how they choose whether and how to use NLP tools to support civic participation processes. The interviews suggest that policymakers across both groups focused on their needs for career advancement and the need to showcase the legitimacy and fairness of their work when considering NLP tool adoption and use. Because these needs vary between politicians and public servants, their preferred NLP features and tool designs also differ. Interestingly, despite their differing needs and opinions, neither group clearly identifies who should advocate for NLP adoption to enhance civic participation or address the unintended consequences of a poorly considered adoption. This lack of clarity in responsibility might have caused the governments' low adoption of NLP tools. We discuss how these findings reveal new insights for future HCI research. They inform the design of NLP tools for increasing civic participation efficiency and capacity, the design of other tools and methods that ensure thoughtful adoption of AI tools in government, and the design of NLP tools for collaborative use among users with different incentives and needs.

翻译：自然语言处理（NLP）工具具有提升公民参与和加强民主进程的潜力，因为它们能显著增强政府收集与分析公民意见的能力。然而，这些工具在政府中的采纳仍较为有限，如何在发挥其益处的同时防范意外后果，依然是一项挑战。以往研究多聚焦于提升NLP性能，而本研究则探讨政府内部不同利益相关方如何影响NLP工具的审慎采纳。我们访谈了七位政治官员（作为政府机构负责人的政治任命官员）和十三位公务员（负责设计与实施政策干预的职业政府雇员），探究他们如何决定是否及如何使用NLP工具来支持公民参与过程。访谈表明，两组政策制定者在考虑NLP工具的采纳与使用时，均关注其职业发展需求以及展示工作合法性与公平性的需要。由于政治官员与公务员的需求存在差异，他们偏好的NLP功能与工具设计亦有所不同。有趣的是，尽管需求与观点不同，两组人员均未明确应由谁倡导NLP的采纳以增强公民参与，或由谁负责应对考虑不周的采纳行为可能引发的意外后果。这种责任归属的模糊性可能是导致政府NLP工具采纳率偏低的原因。我们讨论了这些发现如何为未来人机交互研究提供新视角，包括：为提升公民参与效率与能力而设计NLP工具；设计确保政府审慎采纳人工智能工具的其他工具与方法；以及为具有不同动机与需求的用户设计可协同使用的NLP工具。