PIA-Bench: Towards Automated Privacy Impact Assessment with Large Language Models

Abstract

Privacy impact assessment (PIA) is a critical instrument for institutions to proactively identify privacy risks and develop mitigation strategies before system deployment. While mandated across regulatory and institutional contexts, executing PIA requires extensive privacy and technical expertise, posing a particular challenge for teams without access to such resources. Prior work shows the potential of leveraging large language models (LLMs) to assist practitioners' privacy decisions, but littl

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@misc{zheng2026piabench,
  title = {{PIA-Bench: Towards Automated Privacy Impact Assessment with Large Language Models}},
  author = {Jiamin Zheng and Hao-Ping Lee and Luo Mai and Jingjie Li},
  year = {2026},
  month = sep,
  eprint = {2609.12571},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.12571}
}