The AI Memory Gap: Users Misremember What They Created With AI or Without

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.

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Published
2026-04-13
DOI
https://doi.org/10.1145/3772318.3791494
Citations
1
Primary Topic
Explainable Artificial Intelligence (XAI)
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article
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article

The AI Memory Gap: Users Misremember What They Created With AI or Without

Robin Welsch, Sven Goller, Daniel Buschek, Tim Zindulka et al.
1 citations
Explainable Artificial Intelligence (XAI)
article

The AI Memory Gap: Users Misremember What They Created With AI or Without

Robin Welsch, Sven Goller, Daniel Buschek, Tim Zindulka, Danielle Priscila Bueno Fernandes
article en
1 citations

Abstract

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.

University of Bayreuth (DE), Aalto University (FI)
Openalex Percentile: Top 99%
Explainable Artificial Intelligence (XAI)
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The AI Memory Gap: Users Misremember What They Created With AI or Without — Robin Welsch, Sven Goller, et al. · (2026) | TGRS Research Map | TGRS