Generative AI challenges academic integrity not only by enabling students to delegate substantial portions of their academic work, but also by blurring the ethical boundaries by which students distinguish acceptable assistance from misconduct. Drawing on semi-structured interviews (n=20), AI chat logs, and course documents (syllabi, submitted assignments), we investigated how students themselves make moral sense of AI use in academic writing. Our analysis results in a range of novel findings: First, there are at least five distinct sites of AI-use conceptualization, ranging from faculty's intended AI policy, to students' actual AI use. Second, students use over 20 distinct rationalizations to justify AI use, such as that copying AI-generated text is victimless; that any AI text reflecting their own beliefs or their own style is their own writing; or that they are learning more by using AI -- even extensively -- than otherwise. We present a taxonomy of these rationalizations, and show how some of them are employed to justify conscious violations of course policies. Third, student rationalizations occur in both an ad hoc and post hoc manner, and they are not necessarily self-consistent. These and other findings suggest that modern AI presents a steep, ethical, slippery slope which students conceptually slide down, landing far outside the pedagogical goals and expectations of instructors. We discuss implications for educational design and AI policy.

翻译：生成式AI不仅通过让学生将大量学术工作外包来挑战学术诚信，还模糊了学生区分可接受帮助与不当行为的伦理界限。基于半结构化访谈（n=20）、AI聊天记录及课程文档（教学大纲、提交作业），我们研究了学生如何在道德上理解学术写作中的AI使用。分析得出了一系列新发现：第一，AI使用概念化存在至少五个不同层面，从教师预期的AI政策到学生实际的AI使用。第二，学生使用超过20种不同的合理化理由来为AI使用辩护，例如：复制AI生成的文本无受害者；任何反映自身信念或风格的AI文本即为其原创；以及通过使用AI（甚至大规模使用）比不使用学到更多。我们提出了这些合理化的分类体系，并展示其中部分如何被用于为故意违反课程政策辩护。第三，学生的合理化过程既包括临时性也包括事后性，且未必自我一致。这些及其他发现表明，现代AI呈现出一条陡峭的伦理滑溜斜坡，学生在概念上沿此下滑，最终远低于教师的教学目标与期望。我们讨论了对教育设计及AI政策的启示。