Publication detail

Disinformation Capabilities of Large Language Models

VYKOPAL, I. PIKULIAK, M. SRBA, I. MÓRO, R. MACKO, D. BIELIKOVÁ, M.

Original Title

Disinformation Capabilities of Large Language Models

Type

article in a collection out of WoS and Scopus

Language

English

Original Abstract

Automated disinformation generation is often listed as one of the risks of large language models (LLMs). The theoretical ability to flood the information space with disinformation content might have dramatic consequences for democratic societies around the world. This paper presents a comprehensive study of the disinformation capabilities of the current generation of LLMs to generate false news articles in English language. In our study, we evaluated the capabilities of 10 LLMs using 20 disinformation narratives. We evaluated several aspects of the LLMs: how well they are at generating news articles, how strongly they tend to agree or disagree with the disinformation narratives, how often they generate safety warnings, etc. We also evaluated the abilities of detection models to detect these articles as LLM-generated. We conclude that LLMs are able to generate convincing news articles that agree with dangerous disinformation narratives.

Keywords

large language models, disinformation generation, human evaluation, fake news detection

Authors

VYKOPAL, I.; PIKULIAK, M.; SRBA, I.; MÓRO, R.; MACKO, D.; BIELIKOVÁ, M.

Released

16. 8. 2024

Publisher

Association for Computational Linguistics

Location

Bangkok

ISBN

979-8-8917-6094-3

Book

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Pages from

14830

Pages to

14847

Pages count

18

URL

https://aclanthology.org/2024.acl-long.793

BibTex

@inproceedings{BUT193294,
  author="VYKOPAL, I. and PIKULIAK, M. and SRBA, I. and MÓRO, R. and MACKO, D. and BIELIKOVÁ, M.",
  title="Disinformation Capabilities of Large Language Models",
  booktitle="Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
  year="2024",
  pages="14830--14847",
  publisher="Association for Computational Linguistics",
  address="Bangkok",
  doi="10.18653/v1/2024.acl-long.793",
  isbn="979-8-8917-6094-3",
  url="https://aclanthology.org/2024.acl-long.793"
}

Responsibility: Ing. Marek Strakoš