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May 6, 2024
Artificial Advocates: Biasing Democratic Feedback using AI
Sam Patterson, Jeremy Dolan, Simon Wisdom, Maten
Summary
The "Artificial Advocates" project by our team targeted the vulnerability of U.S. federal agencies' public comment systems to AI-driven manipulation, aiming to highlight how AI can be used to undermine democratic processes. We demonstrated two attack methods: one generating a high volume of realistic, indistinguishable comments, and another producing high-quality forgeries mimicking influential organizations. These experiments showcased the challenges in detecting AI-generated content, with participant feedback showing significant uncertainty in distinguishing between authentic and synthetic comments.
Cite this work:
@misc {
title={
Artificial Advocates: Biasing Democratic Feedback using AI
},
author={
Sam Patterson, Jeremy Dolan, Simon Wisdom, Maten
},
date={
5/6/24
},
organization={Apart Research},
note={Research submission to the research sprint hosted by Apart.},
howpublished={https://apartresearch.com}
}