A Cautionary Tale About "Neutrally" Informative AI Tools Ahead of the 2025 Federal Elections in Germany

Ina Dormuth, Sven Franke, Marlies Hafer, Tim Katzke, Alexander Marx +4 more
2/21/2025
cs.LGcs.AI

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Abstract

In this study, we examine the reliability of AI-based Voting Advice Applications (VAAs) and large language models (LLMs) in providing objective political information. Our analysis is based upon a comparison with party responses to 38 statements of the Wahl-O-Mat, a well-established German online tool that helps inform voters by comparing their views with political party positions. For the LLMs, we identify significant biases. They exhibit a strong alignment (over 75% on average) with left-wing parties and a substantially lower alignment with center-right (smaller 50%) and right-wing parties (around 30%). Furthermore, for the VAAs, intended to objectively inform voters, we found substantial deviations from the parties' stated positions in Wahl-O-Mat: While one VAA deviated in 25% of cases, another VAA showed deviations in more than 50% of cases. For the latter, we even observed that simple prompt injections led to severe hallucinations, including false claims such as non-existent connections between political parties and right-wing extremist ties.

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@article{dormuth2025cautionary,
  title  = {A Cautionary Tale About "Neutrally" Informative AI Tools Ahead of the 2025 Federal Elections in Germany},
  author = {Ina Dormuth and Sven Franke and Marlies Hafer and Tim Katzke and Alexander Marx and Emmanuel Müller and Daniel Neider and Markus Pauly and Jérôme Rutinowski},
  year   = {2025},
  eprint = {2502.15568},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2502.15568v2}
}

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