Detail publikace

Disinformation Capabilities of Large Language Models

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

Originální název

Disinformation Capabilities of Large Language Models

Typ

článek ve sborníku mimo WoS a Scopus

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

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

Autoři

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

Vydáno

16. 8. 2024

Nakladatel

Association for Computational Linguistics

Místo

Bangkok

ISBN

979-8-8917-6094-3

Kniha

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

Strany od

14830

Strany do

14847

Strany počet

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"
}

Odpovědnost: Ing. Marek Strakoš