Privacy policies play a vital role in safeguarding user privacy as legal
jurisdictions worldwide emphasize the need for transparent data processing.
While the suitability of privacy policies to enhance transparency has been
critically discussed, employing conversational AI systems presents unique
challenges in informing users effectively. In this position paper, we propose a
dynamic workflow for transforming privacy policies into privacy
question-and-answer (Q&A) pairs to make privacy policies easily accessible
through conversational AI. Thereby, we facilitate interdisciplinary
collaboration among legal experts and conversation designers, while also
considering the utilization of large language models' generative capabilities
and addressing associated challenges. Our proposed workflow underscores
continuous improvement and monitoring throughout the construction of privacy
Q&As, advocating for comprehensive review and refinement through an
experts-in-the-loop approach.

通过将隐私政策转化为隐私问答对，我们提出了一种动态工作流程，以便通过对话人工智能系统轻松获取隐私政策，促进法律专家和对话设计师之间的跨学科合作，并考虑到大型语言模型生成能力的利用及相关挑战，同时强调隐私问答构建过程中的持续改进和监控，并倡导通过专家参与的全面审查和改进。