Human-Centered Privacy Research in the Age of Large Language Models

TL;DR

The paper argues that privacy concerns surrounding large language models require a human-centered research agenda that complements existing model-focused work. It proposes a Special Interest Group to unite researchers across usable security, HCI, NLP, and related fields to study user disclosure behaviors, mental models, and ownership of data, and to design privacy-friendly interfaces and usable privacy tools. Four focus areas are outlined: understanding user privacy challenges, designing privacy-aware interfaces, building user-facing privacy management tools, and addressing societal challenges beyond individual users, with dedicated subsections for challenges and solutions. The work emphasizes balancing privacy with utility and safety, the need for data sovereignty and transparent data practices, and the importance of policy collaboration to establish standards that promote privacy-respecting LLM-based systems.

Abstract

The emergence of large language models (LLMs), and their increased use in user-facing systems, has led to substantial privacy concerns. To date, research on these privacy concerns has been model-centered: exploring how LLMs lead to privacy risks like memorization, or can be used to infer personal characteristics about people from their content. We argue that there is a need for more research focusing on the human aspect of these privacy issues: e.g., research on how design paradigms for LLMs affect users' disclosure behaviors, users' mental models and preferences for privacy controls, and the design of tools, systems, and artifacts that empower end-users to reclaim ownership over their personal data. To build usable, efficient, and privacy-friendly systems powered by these models with imperfect privacy properties, our goal is to initiate discussions to outline an agenda for conducting human-centered research on privacy issues in LLM-powered systems. This Special Interest Group (SIG) aims to bring together researchers with backgrounds in usable security and privacy, human-AI collaboration, NLP, or any other related domains to share their perspectives and experiences on this problem, to help our community establish a collective understanding of the challenges, research opportunities, research methods, and strategies to collaborate with researchers outside of HCI.