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现双重用途困境——新技术既有造福人类的可能性，也存在被滥用于作恶的风险。生成式人工智能（GenAI）技术（如大型语言模型和扩散模型）已展现出卓越能力（例如上下文学习、代码补全、文本到图像的生成与编辑）。然而，攻击者同样可以利用GenAI生成新型攻击手段，并提升现有攻击的速度与有效性。本文报告了在谷歌（由斯坦福大学与威斯康星大学麦迪逊分校共同组织）举办的关于GenAI双重用途困境研讨会的发现。本文并非旨在全面论述，而是试图综合研讨会中部分有趣发现。我们讨论了学界在该课题上的短期与长期目标。希望本文既能成为这一重要议题的讨论起点，也能为研究界提供值得攻关的有趣问题。