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.

生成式人工智能技术（GenAI）可能被用于积极和消极目的，这篇论文讨论了 GenAI 所带来的双重用途困境，并提出了针对此问题的短期和长期目标，旨在引发学术界对此重要主题的深入讨论。