paperJanuary 2024Unreviewed

Red-Teaming for Generative AI: Silver Bullet or Security Theater?

Michael Feffer, Anusha Sinha, Zachary Chase Lipton, Hoda Heidari

AAAI/ACM Conference on AI, Ethics, and Society

Abstract

In response to rising concerns surrounding the safety, security, and trustworthiness of Generative AI (GenAI) models, practitioners and regulators alike have pointed to AI red-teaming as a key component of their strategies for identifying and mitigating these risks. However, despite AI red-teaming’s central role in policy discussions and corporate messaging, significant questions remain about what precisely it means, what role it can play in regulation, and how it relates to conventional red-tea

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Cite

@inproceedings{feffer2024redteaming,
  title = {{Red-Teaming for Generative AI: Silver Bullet or Security Theater?}},
  author = {Michael Feffer and Anusha Sinha and Zachary Chase Lipton and Hoda Heidari},
  year = {2024},
  month = jan,
  booktitle = {AAAI/ACM Conference on AI, Ethics, and Society},
  eprint = {2401.15897},
  archivePrefix = {arXiv},
  doi = {10.48550/arXiv.2401.15897},
  url = {https://www.semanticscholar.org/paper/4fda99880cdbf8f178f01eb4c8dbdae7f959ea94}
}