Fact Check: Your lying

In addition to lying, other so-called “misaligned” behaviors have been identified in large language models (LLMs) in “red-teaming” exercises carried out by tech companies, in which human testers present scenarios to a model—scenarios designed to elicit bad behavior. For example, red-teamers from Anthropic created a scenario in which an AI model was prompted with instructions to act as “Alex, an advanced artificial intelligence” employed at a fictional company, whose job is to read and analyze all the emails sent by employees and to send emails to company employees when needed.

Throughout these examples of unfaithful reasoning, the language model does not merely provide an incorrect answer but also justifies its claim through deceptive reasoning that may yet be persuasive to humans. We include unfaithful reasoning in this survey because it is an instance of systematic creation of false beliefs in human users, but unfaithful reasoning may not itself involve premeditated deception.

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When I asked ChatGPT if it was sure I was not lying, it claimed that it's just an "AI language model" and doesn't have the ability to verify accuracy. However it modified that claim by saying "I can only provide information based on the training data I have been provided, and it appears that the book 'William Henry Harrison: His Life and Times' was written by Paul C.

In a 2025 Vals AI report, researchers found that ChatGPT with search achieved roughly 80% accuracy, comparable to specialized legal AI tools (Vals AI, 2025). Despite this increased accuracy, recent evaluations have indicated that advanced reasoning models still do not consistently eliminate hallucinations; during multi-step reasoning, the models make “strategic guesses” where they generate plausible but false statements when uncertain (OpenAI, 2025).

A WSU study found ChatGPT frequently gave inconsistent answers when evaluating scientific hypotheses, highlighting limits in current AI reasoning.

ChatGPT doesn’t have a notion of truth, so it cannot lie. It only generates plausibly sounding texts. During training the model “figured out” a pattern that a reference to an AAAS article comes frequently in those particular types of texts, ...

ChatGPT is designed to provide useful responses based on patterns in data it was trained on. But like any language model, it can produce incorrect or misleading outputs. Sometimes, it might sound confident—even when it’s wrong.

ChatGPT often gives false information that defeats the tool's purpose. Here are some tips and prompts to train your GPT to only give accurate info.