Summary of Vox Populi, Vox Ai? Using Language Models to Estimate German Public Opinion, by Leah Von Der Heyde et al.
Vox Populi, Vox AI? Using Language Models to Estimate German Public Opinion
by Leah von der Heyde, Anna-Carolina Haensch, Alexander Wenz
First submitted to arxiv on: 11 Jul 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computers and Society (cs.CY); Applications (stat.AP)
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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 recent development of large language models (LLMs) has led to discussions about whether they could complement or replace traditional surveys, given their training data may reflect attitudes and behaviors prevalent in the population. This study investigates the extent to which LLMs can estimate public opinion in Germany by generating synthetic samples and asking them to predict vote choice. The findings suggest that while LLMs capture tendencies of certain voter subgroups, they miss multifaceted factors swaying individual choices. The study contributes to research on leveraging LLMs for studying public opinion and highlights disparities in opinion representation. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Large language models (LLMs) have sparked discussions about using them instead of traditional surveys. This study looks at how well LLMs can predict vote choice in Germany. Researchers made synthetic samples that matched real people’s characteristics and asked the LLM GPT-3.5 to make predictions. They found that GPT-3.5 was not very accurate, with a bias towards certain parties. The study shows that while LLMs get some things right, they don’t capture all the complex factors that influence people’s choices. |
Keywords
» Artificial intelligence » Gpt
