As large language models (LLMs) become embedded in interactive text generation, disclosure of AI as a source depends on people remembering which ideas or texts came from themselves and which were created with AI. We investigate how accurately people remember the source of content when using AI. In a pre-registered experiment, 184 participants generated and elaborated on ideas both unaided and with an LLM-based chatbot. One week later, they were asked to identify the source (noAI vs withAI) of these ideas and texts. Our findings reveal a significant gap in memory: After AI use, the odds of correct attribution dropped, with the steepest decline in mixed human-AI workflows, where either the idea or elaboration was created with AI. We validated our results using a computational model of source memory. Discussing broader implications, we highlight the importance of considering source confusion in the design and use of interactive text generation technologies.

翻译：随着大型语言模型（LLMs）被嵌入交互式文本生成系统，AI来源的披露取决于人们能否准确记忆哪些想法或文本源于自身、哪些由AI生成。本研究探讨了人们在使用AI时对内容来源的记忆准确性。在一项预先注册的实验中，184名参与者在无辅助和基于LLM的聊天机器人辅助两种条件下生成并扩展想法。一周后，他们被要求识别这些想法与文本的来源（无AI辅助 vs AI辅助）。研究结果揭示了显著的记忆鸿沟：使用AI后，正确归因的概率显著下降，其中混合人机协作流程（想法生成或扩展任一环节涉及AI）的准确率下降最为明显。我们通过来源记忆计算模型验证了该结果。在讨论更广泛影响时，我们强调在交互式文本生成技术的设计和使用中必须考虑来源混淆问题。