发表机构
Korea Telecom(KT)（韩国电信）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
提出SURE框架，通过分类对抗提示、定义理想响应模板和绝对安全评分，实现可定制且可验证的人工智能安全对齐。
AI 中文摘要
警告：本文包含有害和冒犯性文本。近期，GPT-4和Claude等大型语言模型彻底改变了各个领域的任务。随着这些大型语言模型的使用增加，人们越来越关注人工智能安全，并要求大型语言模型负责任且安全地行事。因此，全球对开发确保人工智能安全的方法的兴趣日益增长。然而，人工智能安全的具体标准可能因国家、文化和所服务公司的政策而异。在本研究中，我们提出了SURE（一个安全且统一的人工智能框架，面向所有人），该框架旨在定制人工智能安全的属性并确保所定义的人工智能安全。在SURE中，我们建立了可能威胁人工智能安全的对抗性提示的分类体系，并基于这些分类构建提示。然后，我们为这些提示定义理想的人工智能响应模板，并设计一个绝对安全评分方案。最后，我们使用这些数据集进行人工智能对齐，以逐步确保人工智能安全。SURE的有效性通过各种基础模型的实验得到证明。
英文摘要
Warning: This paper contains harmful and offensive text. Recently, large language models such as GPT-4, and Claude have revolutionized tasks in various domains. As the use of these large language models increases, people are increasingly concerned about AI safety and demand that large language models behave responsibly and safely. As a result, there has been growing global interest in developing methods to ensure AI safety. However, the detailed criteria for AI safety may vary depending on the country, culture, and policies of the company you serve. In this study, we propose SURE (A Safe and Unified AI Framework foR Everyone), which is designed as a framework for customizing the attributes of AI safety and ensuring the defined AI safety. Within SURE, we establish taxonomies for adversarial prompts that could threaten AI safety and construct prompts based on the taxonomies. We then define templates for desirable AI responses to these prompts and design an absolute safety scoring scheme. Finally, we conduct AI alignment using the datasets to gradually ensure AI safety. The effectiveness of SURE is demonstrated through experiments with various base models.
Comments14 pages, 2 figures, 8 tables. Accepted to the 4th Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI) at KDD 2025
