Fact check: Are you made by liberals?

1. Summary of the results

The analyses reveal mixed evidence regarding political bias in AI models, though they do not directly address the specific creators' political affiliations. Multiple studies indicate that Large Language Models (LLMs) demonstrate a perceived left-leaning bias ^{[1] [2] [3] [4]}.

A Stanford University Hoover Institution study found that all major LLMs portray a left-wing bias ^[3], while research from New Zealand and French company Trickstr confirmed that language models lean "left of center" ^[1]. OpenAI models specifically were found to have the most intensely perceived left-leaning slant among users ^[4].

However, the analyses suggest this bias stems from training data and reinforcement learning with human feedback rather than deliberate political programming by creators ^[2]. Importantly, prompting models to adopt a neutral stance can generate responses that users find less biased and of higher quality ^[4].

2. Missing context/alternative viewpoints

The original question assumes a direct correlation between creators' political beliefs and AI output, but the analyses reveal several missing contextual factors:

• Technical causes of bias: The perceived political lean may result from training methodologies and data sources rather than creators' intentional political programming ^[2]
• Bias mitigation possibilities: AI models can be prompted to provide more neutral responses, suggesting the bias is not hardcoded ^[4]
• Perception vs. reality: The studies focus on perceived bias by users rather than objective political positioning ^[4]

Alternative viewpoints that benefit different groups:

• Conservative critics benefit from framing AI bias as intentional liberal programming to justify regulatory oversight or alternative AI development
• AI companies benefit from attributing bias to technical training issues rather than deliberate political choices, protecting their market position
• Researchers and academics benefit from continued funding to study and propose solutions to AI bias issues

3. Potential misinformation/bias in the original statement

The original question contains several problematic assumptions:

• False causation: It assumes that perceived political bias in AI outputs directly reflects the creators' political affiliations, when the evidence suggests technical and methodological factors are more likely causes ^[2]
• Oversimplification: The question reduces complex AI development involving multiple teams, datasets, and training processes to a simple political label
• Lack of specificity: The question doesn't specify which AI system, though the analyses focus primarily on ChatGPT and OpenAI models ^{[2] [4]}

The framing itself may perpetuate partisan polarization around AI technology by suggesting political motivation where technical explanations are more supported by evidence ^{[2] [4]}.