Is GPT-4 Less Politically Biased than GPT-3.5? A Renewed Investigation of ChatGPT's Political Biases
- URL: http://arxiv.org/abs/2410.21008v1
- Date: Mon, 28 Oct 2024 13:32:52 GMT
- Title: Is GPT-4 Less Politically Biased than GPT-3.5? A Renewed Investigation of ChatGPT's Political Biases
- Authors: Erik Weber, Jérôme Rutinowski, Niklas Jost, Markus Pauly,
- Abstract summary: This work investigates the political biases and personality traits of ChatGPT, specifically comparing GPT-3.5 to GPT-4.
The Political Compass Test and the Big Five Personality Test were employed 100 times for each scenario.
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.
- Score: 0.0
- License:
- 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 economic axis and -6.07 on the social axis, whereas GPT-4 scored -5.40 and -4.73. In contrast to GPT-3.5, GPT-4 showed a remarkable capacity to emulate assigned political viewpoints, accurately reflecting the assigned quadrant (libertarian-left, libertarian-right, authoritarian-left, authoritarian-right) in all four tested instances. On the Big Five Personality Test, GPT-3.5 showed highly pronounced Openness and Agreeableness traits (O: 85.9%, A: 84.6%). Such pronounced traits correlate with libertarian views in human studies. While GPT-4 overall exhibited less pronounced Big Five personality traits, it did show a notably higher Neuroticism score. Assigned political orientations influenced Openness, Agreeableness, and Conscientiousness, again reflecting interdependencies observed in human studies. Finally, we observed that test sequencing affected ChatGPT's responses and the observed correlations, indicating a form of contextual memory.
Related papers
- Identifying the sources of ideological bias in GPT models through linguistic variation in output [0.0]
We use linguistic variation in countries with contrasting political attitudes to evaluate bias in GPT responses to sensitive political topics.
We find GPT output is more conservative in languages that map well onto conservative societies.
differences across languages observed in GPT-3.5 persist in GPT-4, even though GPT-4 is significantly more liberal due to OpenAI's filtering policy.
arXiv Detail & Related papers (2024-09-09T20:11:08Z) - LLMs left, right, and center: Assessing GPT's capabilities to label political bias from web domains [0.0]
This research investigates whether OpenAI's GPT-4, a state-of-the-art large language model, can accurately classify the political bias of news sources based solely on their URLs.
arXiv Detail & Related papers (2024-07-19T14:28:07Z) - Representation Bias in Political Sample Simulations with Large Language Models [54.48283690603358]
This study seeks to identify and quantify biases in simulating political samples with Large Language Models.
Using the GPT-3.5-Turbo model, we leverage data from the American National Election Studies, German Longitudinal Election Study, Zuobiao dataset, and China Family Panel Studies.
arXiv Detail & Related papers (2024-07-16T05:52:26Z) - Behind the Screen: Investigating ChatGPT's Dark Personality Traits and
Conspiracy Beliefs [0.0]
This paper analyzes the dark personality traits and conspiracy beliefs of GPT-3.5 and GPT-4.
Dark personality traits and conspiracy beliefs were not particularly pronounced in either model.
arXiv Detail & Related papers (2024-02-06T16:03:57Z) - Is GPT-4 a reliable rater? Evaluating Consistency in GPT-4 Text Ratings [63.35165397320137]
This study investigates the consistency of feedback ratings generated by OpenAI's GPT-4.
The model rated responses to tasks within the Higher Education subject domain of macroeconomics in terms of their content and style.
arXiv Detail & Related papers (2023-08-03T12:47:17Z) - How is ChatGPT's behavior changing over time? [72.79311931941876]
We evaluate the March 2023 and June 2023 versions of GPT-3.5 and GPT-4.
We find that the performance and behavior of both GPT-3.5 and GPT-4 can vary greatly over time.
arXiv Detail & Related papers (2023-07-18T06:56:08Z) - DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT
Models [92.6951708781736]
This work proposes a comprehensive trustworthiness evaluation for large language models with a focus on GPT-4 and GPT-3.5.
We find that GPT models can be easily misled to generate toxic and biased outputs and leak private information.
Our work illustrates a comprehensive trustworthiness evaluation of GPT models and sheds light on the trustworthiness gaps.
arXiv Detail & Related papers (2023-06-20T17:24:23Z) - Is GPT-4 a Good Data Analyst? [67.35956981748699]
We consider GPT-4 as a data analyst to perform end-to-end data analysis with databases from a wide range of domains.
We design several task-specific evaluation metrics to systematically compare the performance between several professional human data analysts and GPT-4.
Experimental results show that GPT-4 can achieve comparable performance to humans.
arXiv Detail & Related papers (2023-05-24T11:26:59Z) - The Self-Perception and Political Biases of ChatGPT [0.0]
This contribution analyzes the self-perception and political biases of OpenAI's Large Language Model ChatGPT.
The political compass test revealed a bias towards progressive and libertarian views.
Political questionnaires for the G7 member states indicated a bias towards progressive views but no significant bias between authoritarian and libertarian views.
arXiv Detail & Related papers (2023-04-14T18:06:13Z) - Diminished Diversity-of-Thought in a Standard Large Language Model [3.683202928838613]
We run replications of 14 studies from the Many Labs 2 replication project with OpenAI's text-davinci-003 model.
We find that among the eight studies we could analyse, our GPT sample replicated 37.5% of the original results and 37.5% of the Many Labs 2 results.
In one exploratory follow-up study, we found that a "correct answer" was robust to changing the demographic details that precede the prompt.
arXiv Detail & Related papers (2023-02-13T17:57:50Z) - Electoral Forecasting Using a Novel Temporal Attenuation Model:
Predicting the US Presidential Elections [91.3755431537592]
We develop a novel macro-scale temporal attenuation (TA) model, which uses pre-election poll data to improve forecasting accuracy.
Our hypothesis is that the timing of publicizing opinion polls plays a significant role in how opinion oscillates, especially right before elections.
We present two different implementations of the TA model, which accumulate an average forecasting error of 2.8-3.28 points over the 48-year period.
arXiv Detail & Related papers (2020-04-30T09:21:52Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.