Understanding U.S. Users' Security and Privacy Transparency Needs for Consumer-Facing Generative AI
Users increasingly rely on consumer-facing generative AI (GenAI) for tasks ranging from everyday needs to sensitive use cases. Yet, it remains unclear whether and how existing security and privacy (S&P) communications in GenAI tools shape users' adoption decisions and experiences. Understanding how users seek, interpret, and evaluate S&P information is critical for designing usable transparency that users can trust and act on. We conducted semi-structured interviews and design sessions with 21 U.S. GenAI users. Our findings suggest that available S&P information rarely drove initial adoption in practice, as participants often perceived it as incomplete, ineffective, or not credible. Inste...
| Authors | Jiaxun Cao, Yu Dong, Chunxi Zhan et al. |
|---|---|
| Primary category | cs.HC |
| Published | 19 April 2026 |
| Last updated at source | 19 June 2026 |
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