Summary of Generative Ai Misuse: a Taxonomy Of Tactics and Insights From Real-world Data, by Nahema Marchal et al.
Generative AI Misuse: A Taxonomy of Tactics and Insights from Real-World Data
by Nahema Marchal, Rachel Xu, Rasmi Elasmar, Iason Gabriel, Beth Goldberg, William Isaac
First submitted to arxiv on: 19 Jun 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper presents a taxonomy of tactics used to misutilize generative, multimodal artificial intelligence (GenAI) models. The research is based on an analysis of approximately 200 reported incidents of misuse between January 2023 and March 2024, drawing from both academic literature and real-world observations. The study uncovers novel patterns in GenAI misuse, including potential motivations, strategies, and the ways attackers exploit system capabilities across various modalities such as image, text, audio, and video. The findings provide insights into how GenAI models are specifically exploited or abused in practice, shedding light on the tactics employed to cause harm. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper finds that Generative, Multimodal Artificial Intelligence (GenAI) can be misused in many ways. Researchers looked at 200 reports of misuse over a few months and found some patterns. They discovered what motivates people to misuse GenAI, how they do it, and what kinds of attacks happen across different types of media like images, text, audio, and videos. |
