Privy: Envisioning and Mitigating Privacy Risks for Consumer-facing AI Product Concepts
AI creates and exacerbates privacy risks, yet practitioners lack effective resources to identify and mitigate these risks. We present Privy, a tool that guides practitioners without privacy expertise through structured privacy impact assessments to: (i) identify relevant risks in novel AI product concepts, and (ii) propose appropriate mitigations. Privy was shaped by a formative study with 11 practitioners, which informed two versions — one LLM-powered, the other template-based. We evaluated these two versions of Privy through a between-subjects, controlled study with 24 separate practitioners, whose assessments were reviewed by 13 independent privacy experts. Results show that Privy helps practitioners produce privacy assessments that experts deemed high quality: practitioners identified relevant risks and proposed appropriate mitigation strategies. These effects were augmented in the LLM-powered version. Practitioners themselves rated Privy as being useful and usable, and their feedback illustrates how it helps overcome long-standing awareness, motivation, and ability barriers in privacy work.
Authors
- Sauvik Das (ORCID: https://orcid.org/0000-0002-9073-8054)
- Yu‐Ju Yang (ORCID: https://orcid.org/0009-0005-1989-0044)
- Thomas Şerban von Davier (ORCID: https://orcid.org/0000-0002-0678-3996)
- Hao-Ping Lee (ORCID: https://orcid.org/0000-0002-8063-1034)
- Kyzyl Monteiro (ORCID: https://orcid.org/0000-0002-2723-9500)
- Jodi Forlizzi (ORCID: https://orcid.org/0000-0002-7161-075X)
- Isadora Krsek (ORCID: https://orcid.org/0000-0001-9624-5077)
- Matthew Bilik
Institutions
- University of Illinois Urbana-Champaign (US)
- University of Washington (US)
- Carnegie Mellon University (US)
Publication Details
- Published
- 2026-04-13
- DOI
- https://doi.org/10.1145/3772318.3791279
- Primary Topic
- Ethics and Social Impacts of AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Science Foundation