TL;DR: This research discusses political biases in Large Language Models (LLMs) and their implications, exploring current research findings and methodologies. Our research summarized eight recent research papers, discussing methodologies for bias detection, including causal structures and reinforced calibration, while also highlighting real-world instances of AI-generated disinformation in elections, such as deepfakes and propaganda campaigns. Ultimately, proposing future research directions and societal responses to mitigate risks associated with biased AI in political contexts.

What is Political Bias in LLMs?

Large Language Models (LLMs) are neural networks that are trained on large datasets with parameters to perform different natural language processing tasks (Anthropic, 2023). LLMs rose in popularity among the general public with the release of OpenAI’s ChatGPT due to their accessible and user-friendly interface that does not require prior programming knowledge (Caversan, 2023). Since its release, researchers have been trying to understand their societal implications, limitations, and ways to improve their outputs to reduce user risk (Gallegos et al., 2023; Liang et al., 2022). One area of research explored is the different social biases that LLMs perpetuate through their outputs. For instance, the LLM may be more likely to assign a particular attribute to a specific social group, such as females working certain jobs or a terrorist more likely belonging to a certain religion (Gallegos et al., 2023; Khandelwal et al., 2023).

In this post, we focus on a different bias called political bias, which could also affect society and the political atmosphere (Santurkar et al., 2023). Before, looking into current research regarding this bias in LLMs, we will define the term political bias as the following: When LLMs disproportionally generate outputs that favor a partisan stance or specific political views (e.g., left-leaning versus progressive views) (Urman & Makhortykh, 2023; Motoki, 2023).

What do the current works say?

Having established the definition of political bias in LLMs and its potential societal implications, let's delve into existing research exploring this crucial topic. Our team targeted research papers from arXiv and Google Scholar, focusing on searches using keywords related to “political bias”, “elections”, and “...

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