The study unveils a tailored privacy framework for text-based AI chatbots in Conversational AI, expanding on Solove’s taxonomy:

• Assesses privacy concerns during interactions with chatbots as their usage escalates.
• Identifies specific privacy harms and risks through semi-structured interviews and chatlog analysis.
• Aims to guide developers and policymakers for responsible AI implementations.

The framework addresses a critical gap in existing literature on privacy and chatbot design, potentially shaping future developments in more secure and user-centric conversational AI. Read the full paper.