Every major technical invention resurfaces the dual-use dilemma -- the new technology has the potential to be used for good as well as for harm. Generative AI (GenAI) techniques, such as large language models (LLMs) and diffusion models, have shown remarkable capabilities (e.g., in-context learning, code-completion, and text-to-image generation and editing). However, GenAI can be used just as well by attackers to generate new attacks and increase the velocity and efficacy of existing attacks. This paper reports the findings of a workshop held at Google (co-organized by Stanford University and the University of Wisconsin-Madison) on the dual-use dilemma posed by GenAI. This paper is not meant to be comprehensive, but is rather an attempt to synthesize some of the interesting findings from the workshop. We discuss short-term and long-term goals for the community on this topic. We hope this paper provides both a launching point for a discussion on this important topic as well as interesting problems that the research community can work to address.

翻译：每一项重大技术发明都会重新引发双重用途困境——新技术既有可能被用于善举，也有可能被用于作恶。生成式人工智能（GenAI）技术，如大型语言模型（LLMs）和扩散模型，已展现出显著能力（例如，上下文学习、代码补全以及文本到图像的生成与编辑）。然而，攻击者同样可以利用GenAI来生成新型攻击，并提高现有攻击的速度和有效性。本文报告了由斯坦福大学和威斯康星大学麦迪逊分校共同组织、在Google举办的一场研讨会关于GenAI双重用途困境的发现。本文并非旨在全面覆盖，而是试图综合研讨会中一些有趣的发现。我们讨论了社区在此主题上的短期和长期目标。希望本文既能成为这一重要议题讨论的起点，又能为研究社区提供可着手解决的有趣问题。