In the context of growing privacy concerns with chatbots, the paper ‘User Privacy Harms and Risks in Conversational AI: A Proposed Framework’ by Ece Gumusel and colleagues introduces a privacy framework for text-based AI interactions. The study provides tools for developers to ensure responsible chatbot applications. Read the study here.

• Identified various privacy harms and risks in text-based AI chatbot interactions.
• Employs Solove’s taxonomy to create a framework analyzing these privacy concerns.
• A grounded theory approach was used for analysing privacy through various interaction stages.
• Offers a novel lens to manage privacy considerations in conversational AI.

This insightful work aids in enhancing user privacy in conversational AI, thereby influencing future design and policy development for chatbot implementations.