Summary of Large Language Models Can Impersonate Politicians and Other Public Figures, by Steffen Herbold et al.
Large Language Models can impersonate politicians and other public figures
by Steffen Herbold, Alexander Trautsch, Zlata Kikteva, Annette Hautli-Janisz
First submitted to arxiv on: 9 Jul 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The study investigates the ability of Large Language Models (LLMs) to generate responses that impersonate political and societal representatives. The results show that LLMs can produce high-quality text, including persuasive political speech, that is perceived as authentic and relevant by a cross-section of British society. This raises concerns about the potential harm these models can cause on society if they are used to contribute meaningfully to public political debates without proper oversight. The study highlights the need for large-scale and systematic studies on this topic. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary A new study looks at how well computers can pretend to be politicians and experts, making it seem like real people wrote what they say. The research shows that these computer programs can make pretty good fake speeches that sound authentic and relevant. This is a problem because it means that if we use these computers to write things that look like they were written by important people, nobody will know the difference. This could be bad for society because it could spread misinformation and confuse people. |
