Conference & Journal Paper
How Generative AI Empowers Attackers and Defenders Across the Trust & Safety Landscape
Patrick Gage Kelley, Steven Rousso-Schindler, Renee Shelby, Kurt Thomas, Allison Woodruff
Proceedings of the ACM CHI Conference on Human Factors in Computing Systems (CHI '26), Barcelona, Spain, 1316:1–1316:21, 2026
April 2026
Abstract
Generative AI (GenAI) is a powerful technology poised to reshape Trust & Safety. While misuse by attackers is a growing concern, its defensive capacity remains underexplored. This paper examines these effects through a qualitative study with 43 Trust & Safety experts across five domains: child safety, election integrity, hate and harassment, scams, and violent extremism. Our findings characterize a landscape in which GenAI empowers both attackers and defenders. GenAI dramatically increases the scale and speed of attacks, lowering the barrier to entry for creating harmful content, including sophisticated propaganda and deepfakes. Conversely, defenders envision leveraging GenAI to detect and mitigate harmful content at scale, conduct investigations, deploy persuasive counternarratives, improve moderator wellbeing, and offer user support. This work provides a strategic framework for understanding GenAI's impact on Trust & Safety and charts a path for its responsible use in creating safer online environments.
- generative ai
- frontier ai
- trust & safety
- child safety
- election integrity
- hate
- harassment
- scams
- violent extremism
Cite this paper
@inproceedings{kelley2026how,
title = {How Generative AI Empowers Attackers and Defenders Across the Trust & Safety Landscape},
author = {Kelley, Patrick Gage and Rousso-Schindler, Steven and Shelby, Renee and Thomas, Kurt and Woodruff, Allison},
year = {2026},
doi = {10.1145/3772318.3791363},
url = {https://doi.org/10.1145/3772318.3791363},
booktitle = {Proceedings of the ACM CHI Conference on Human Factors in Computing Systems (CHI '26), Barcelona, Spain, 1316:1–1316:21, 2026},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
}