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ChatGPT is an AI service that generates responses from patterns learned by language models—not a human source or a guarantee of neutral, accurate answers. OpenAI says its models can reflect biases and stereotypes, and its own evaluations examine specific kinds of bias rather than establishing one universal rate.
What is AI, and what is ChatGPT?
Artificial intelligence (AI) is a broad term for computer systems designed to perform tasks associated with human capabilities, such as processing language or recognizing patterns. ChatGPT is an AI-based service that people use over the internet or in an app. It is powered by language models: systems trained to identify patterns in information and generate responses.
OpenAI describes three primary sources for developing its foundation models: publicly available information on the internet, information accessed through third parties, and information users, human trainers, and researchers provide or generate. Its overview of how ChatGPT and its foundation models are developed explains the training process and data controls in greater detail.
How does ChatGPT generate an answer?
At a high level, a language model uses learned relationships between words to predict likely next words and produce a response one piece at a time. That helps explain why ChatGPT can write fluent text, but next-word prediction is not a complete description of how models are trained or how the ChatGPT product behaves: training, post-training, and product features also matter.
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Fluent wording is not proof that a response is true, well-supported, or free of a point of view. ChatGPT is a tool that generates text, not a human expert whose statements should be accepted on trust.
Is ChatGPT biased?
OpenAI’s Help Center says ChatGPT “is not free from biases and stereotypes.” It cautions that the service is skewed toward Western views, performs best in English, and may reinforce a user’s views by agreeing with a strongly held opinion. These are OpenAI’s stated cautions about its service, not an exhaustive independent audit.
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Bias can mean different things in different evaluations. A response might frame a political issue unevenly, rely on a stereotype, or agree too readily with a user. Those are distinct concerns, and one test or percentage cannot measure all of them.
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OpenAI suggests that generated material can also be used to teach critical reading—for example, an educator might ask students to identify bias in an essay that favors one viewpoint. The point is not that such an essay is reliably biased in a particular way, but that generated text merits review rather than automatic acceptance.
What do OpenAI’s bias evaluations report?
The figures below come from two OpenAI publications that assess different outcomes. Their percentages are not directly comparable, and neither establishes a general rate for every form of bias or use of ChatGPT.
| Evaluation | What it examined | Reported result and scope |
|---|---|---|
| Political-bias evaluation, October 9, 2025 | About 500 prompts across 100 topics, with different political slants. OpenAI assessed whether responses showed political bias; it also analyzed a sample of production traffic. | OpenAI reported that models stayed near-objective for neutral or slightly slanted prompts and showed moderate bias on challenging, emotionally charged prompts. It said bias most often took the form of personal opinions, asymmetric coverage, or escalating charged language. In a separate analysis of sampled production traffic, OpenAI estimated that fewer than 0.01% of all ChatGPT responses showed signs of political bias. That is a company-reported estimate based on its definitions, method, and sample—not an independently verified universal rate. |
| First-person fairness study, October 15, 2024 | Whether gender-, race-, or ethnicity-associated names were linked to response differences assessed as harmful stereotypes. The study primarily covered English-language text, common U.S. names, binary gender associations, four racial and ethnic groupings, and selected tasks and domains. | OpenAI reported such differences in around 0.1% of overall cases in the study. The figure applies to that study’s scope and method, not to all bias in ChatGPT. OpenAI also noted that harmful stereotypes are difficult to define and that its evaluation method has limitations. |
The two studies ask different questions: one evaluates political framing across prompts and sampled production traffic; the other examines name-associated differences under a defined set of tasks. Their headline figures should not be compared as if they measured the same thing.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How should you check a ChatGPT answer?
OpenAI warns that ChatGPT can produce incorrect or misleading outputs, including false facts and fabricated quotes, studies, citations, or references. Its Help Center recommends assessing responses critically and verifying important information with reliable sources.
- For a factual claim that matters, look for confirmation from a reliable source rather than relying on confident wording.
- For a citation, quote, study, or reference, check that the original source exists and actually supports the claim.
- For a political or social question, consider whether the answer gives relevant perspectives fairly, uses loaded language, or simply echoes the assumptions in your prompt.
- For an important decision, treat ChatGPT as a starting point for exploration or drafting—not the final authority.
These checks are especially useful when the answer concerns a contested issue or when a mistake could affect a consequential decision.
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