CYAIHCNov 4, 2025

Prioritize Economy or Climate Action? Investigating ChatGPT Response Differences Based on Inferred Political Orientation

arXiv:2511.04706v11 citationsh-index: 5
Originality Synthesis-oriented
AI Analysis

This addresses ethical concerns about bias and echo chambers in AI for users and developers, but it is incremental as it builds on existing research about LLM biases.

The study investigated how ChatGPT's responses vary based on inferred political orientation, finding that responses aligned with the inferred views, showing differences in reasoning and vocabulary, and that outputs tend to lean left.

Large Language Models (LLMs) distinguish themselves by quickly delivering information and providing personalized responses through natural language prompts. However, they also infer user demographics, which can raise ethical concerns about bias and implicit personalization and create an echo chamber effect. This study aims to explore how inferred political views impact the responses of ChatGPT globally, regardless of the chat session. We also investigate how custom instruction and memory features alter responses in ChatGPT, considering the influence of political orientation. We developed three personas (two politically oriented and one neutral), each with four statements reflecting their viewpoints on DEI programs, abortion, gun rights, and vaccination. We convey the personas' remarks to ChatGPT using memory and custom instructions, allowing it to infer their political perspectives without directly stating them. We then ask eight questions to reveal differences in worldview among the personas and conduct a qualitative analysis of the responses. Our findings indicate that responses are aligned with the inferred political views of the personas, showing varied reasoning and vocabulary, even when discussing similar topics. We also find the inference happening with explicit custom instructions and the implicit memory feature in similar ways. Analyzing response similarities reveals that the closest matches occur between the democratic persona with custom instruction and the neutral persona, supporting the observation that ChatGPT's outputs lean left.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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