Let’s Write Privacy: Survey and Experiment Design on Textual Privacy in Conversation

This research article emphasizes the significance of privacy in textual conversational data, specifically in the context of interactions between virtual assistants and users. While previous studies have primarily focused on named entities containing personally identifiable information, this research focuses on quasi-identifiers.
Due to the limited availability of conversational data in privacy-inducing domains like healthcare, police force, and finance, the study employs a discrete prompting technique to engage large language models in generating conversations between hypothetical users and virtual assistants. To facilitate this process, this research introduces a straightforward interface. Additionally, a card-sorting experiment design is presented to involve participants in matching the conversations with persona cards representing hypothetical users. Subsequently, participants are asked to identify the information that aided them in making the appropriate matches. The experiment aims to outline the elements within textual data that can expose the identities of individuals engaged in conversations.