Detecting undisclosed LLM-generated content in parliamentary texts
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Abstract (arXiv)
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.
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References · 22
- 2021All That's 'Human' Is Not Gold: Evaluating Human Evaluation of Generated Textcited by 287
- 2023"Kelly is a Warm Person, Joseph is a Role Model": Gender Biases in LLM-Generated Reference Letterscited by 199
- 2023M4: Multi-generator, Multi-domain, and Multi-lingual Black-Box Machine-Generated Text Detectioncited by 121
- 2025Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Taskcited by 106
- 2024Systematic Biases in LLM Simulations of Debatescited by 99
- 2023Ghostbuster: Detecting Text Ghostwritten by Large Language Modelscited by 91
- 2024The Political Preferences of LLMscited by 84
- 2024Hidden Persuaders: LLMs' Political Leaning and Their Influence on Voterscited by 71
- 2023Contrasting Linguistic Patterns in Human and LLM-Generated News Textcited by 62
- 2024Do LLMs write like humans? Variation in grammatical and rhetorical stylescited by 62
- 2024DetectRL: Benchmarking LLM-Generated Text Detection in Real-World Scenarioscited by 38
- 2024Assessing Political Bias in Large Language Modelscited by 32
10 more
- 2025Adversarial Paraphrasing: A Universal Attack for Humanizing AI-Generated Textcited by 17
- 2024Vox Populi, Vox AI? Using Language Models to Estimate German Public Opinioncited by 13
- 2024Learning to Rewrite: Generalized LLM-Generated Text Detectioncited by 13
- 2025Comparing LLM-generated and human-authored news text using formal syntactic theorycited by 11
- 2023Beyond Black Box AI-Generated Plagiarism Detection: From Sentence to Document Levelcited by 10
- 2024Investigating Markers and Drivers of Gender Bias in Machine Translationscited by 4
- 2024Using Machine Learning to Distinguish Human-written from Machine-generated Creative Fictioncited by 4
- 2026The AI Cognitive Trojan Horse: How Large Language Models May Bypass Human Epistemic Vigilancecited by 2
- 2025ParliaBench: An Evaluation and Benchmarking Framework for LLM-Generated Parliamentary Speechcited by 1
- 2026Interpretable Text Classification Applied to the Detection of LLM-generated Creative Writingcited by 1
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