Detecting undisclosed LLM-generated content in parliamentary texts
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Computer Science > Computation and Language
Title:Detecting undisclosed LLM-generated content in parliamentary texts
Abstract:In this paper, we evaluate the extent of undisclosed LLM-generated content in texts from the parliaments of the United Kingdom and Sweden. In many areas, such as in journalism or in academic writing, there are often requirements to clearly disclose whether AI tools, such as LLMs, have been used. In the case of parliamentary texts, the guidelines on disclosure of AI use are more vague. However, in order to maintain transparency and retain public trust, it is generally recommended that parliamentarians should state whether or not they have used AI when writing texts, such as parliamentary motions. Here, we train an interpretable (glass-box) text classifier using pre-LLM parliamentary texts and LLM-generated versions of such texts. We then apply the classifier to a test set containing recent parliamentary texts, finding a steady increase in undisclosed LLM use, in both parliaments, from 2022 onwards.
| Subjects: | Computation and Language (cs.CL) |
| Cite as: | arXiv:2606.14209 [cs.CL] |
| (or arXiv:2606.14209v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2606.14209
arXiv-issued DOI via DataCite (pending registration)
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