Experts-in-the-Loop: Establishing an Effective Workflow in Crafting Privacy Q&A
This addresses the problem of improving transparency and accessibility of privacy policies for users through conversational AI, though it appears incremental as a workflow proposal.
The paper tackles the challenge of making privacy policies accessible through conversational AI by proposing a dynamic workflow for transforming them into Q&A pairs, which facilitates interdisciplinary collaboration and incorporates large language models while addressing associated challenges.
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.