Is GPT-4 Less Politically Biased than GPT-3.5? A Renewed Investigation of ChatGPT's Political Biases
Erik Weber, J\'er\^ome Rutinowski, Niklas Jost, Markus Pauly

TL;DR
This study compares the political biases and personality traits of GPT-3.5 and GPT-4, revealing that GPT-4 has slightly reduced biases and better emulates political viewpoints, with responses influenced by test sequencing.
Contribution
It provides a detailed comparative analysis of GPT-3.5 and GPT-4's political biases and personality traits using standardized tests, highlighting improvements in bias reduction and viewpoint emulation in GPT-4.
Findings
GPT-4 shows slightly less political bias than GPT-3.5.
GPT-4 accurately emulates assigned political viewpoints.
Test sequencing influences model responses and observed biases.
Abstract
This work investigates the political biases and personality traits of ChatGPT, specifically comparing GPT-3.5 to GPT-4. In addition, the ability of the models to emulate political viewpoints (e.g., liberal or conservative positions) is analyzed. The Political Compass Test and the Big Five Personality Test were employed 100 times for each scenario, providing statistically significant results and an insight into the results correlations. The responses were analyzed by computing averages, standard deviations, and performing significance tests to investigate differences between GPT-3.5 and GPT-4. Correlations were found for traits that have been shown to be interdependent in human studies. Both models showed a progressive and libertarian political bias, with GPT-4's biases being slightly, but negligibly, less pronounced. Specifically, on the Political Compass, GPT-3.5 scored -6.59 on the…
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Taxonomy
TopicsArtificial Intelligence in Healthcare and Education · Machine Learning in Healthcare
MethodsRefunds@Expedia|||How do I get a full refund from Expedia? · 15 Ways to Contact How can i speak to someone at Delta Airlines · Label Smoothing · Absolute Position Encodings · Linear Layer · Position-Wise Feed-Forward Layer · Cosine Annealing · Transformer · Byte Pair Encoding · Layer Normalization
