Preprint: “Generative AI Misuse: A Taxonomy of Tactics and Insights from Real-World Data”
The preprint shared below was recently shared on arXiv.
Title
Generative AI Misuse: A Taxonomy of Tactics and Insights from Real-World Data
Authors
Nahema Marchal
Google DeepMind
Rachel Xu
Jigsaw
Rasmi Elasmar
Google.org
Iason Gabriel
Google DeepMind
Beth Goldberg
Jigsaw
William Isaac
Google DeepMind
Source
via arXiv
DOI: 10.48550/arXiv.2406.13843
Abstract
Generative, multimodal artificial intelligence (GenAI) offers transformative potential across industries, but its misuse poses significant risks. Prior research has shed light on the potential of advanced AI systems to be exploited for malicious purposes. However, we still lack a concrete understanding of how GenAI models are specifically exploited or abused in practice, including the tactics employed to inflict harm. In this paper, we present a taxonomy of GenAI misuse tactics, informed by existing academic literature and a qualitative analysis of approximately 200 observed incidents of misuse reported between January 2023 and March 2024. Through this analysis, we illuminate key and novel patterns in misuse during this time period, including potential motivations, strategies, and how attackers leverage and abuse system capabilities across modalities (e.g. image, text, audio, video) in the wild.
Direct to Full Text Article (June 21, 2022 Version)
29 pages; PDF.
Filed under: Data Files, Journal Articles, News
About Gary Price
Gary Price (gprice@gmail.com) is a librarian, writer, consultant, and frequent conference speaker based in the Washington D.C. metro area. He earned his MLIS degree from Wayne State University in Detroit. Price has won several awards including the SLA Innovations in Technology Award and Alumnus of the Year from the Wayne St. University Library and Information Science Program. From 2006-2009 he was Director of Online Information Services at Ask.com.