How to avoid artificial intelligence errors when using tools like ChatGPT

A well-crafted response from an artificial intelligence can give a false sense of security. But when it comes to AI, clarity and accuracy are not the same thing. ChatGPT and other similar tools can present false information in objective language, include non-existent references, or answer confidently to a question for which they do not have enough data.

This type of error is already known as hallucination and remains a challenge for language models. A study published by OpenAI in 2025 shows that traditional evaluation methods can encourage risky responses: if the model is rewarded primarily for being correct, it may try to answer even when the information is not known.

OpenAI warns that ChatGPT may respond overly confidently to ambiguous or complex questions.

Why does the answer seem so convincing?

The model does not demonstrate confidence in the same way as a person. It generates an answer based on learned patterns and can produce a sequence of words that seems coherent even when the factual content is wrong. This explains why an incorrect date, an invented statistic, or a non-existent quote can appear alongside perfectly natural sentences.

Without built-in search tools, an answer may not include events that occurred after the training period. Even when the AI has internet access, it is still necessary to verify the sources used.

First step: find the original source

A quick check starts with the most important part of the answer. If there is a number, a date, a statement, or a specific claim, look for the source before reproducing it. The existence of a quote does not guarantee that it is correct. OpenAI recommends checking quotes, data, technical information, and external references directly. Anthropic follows similar guidance and warns that even references that seem convincing may not be based on facts.

The simplest way to check is to open the source and confirm whether it actually says that. It is also worth noting the publication date, who produced the material, and whether the excerpt was taken out of context.

How to verify in a few minutes

For a factual claim, the process can be simple: identify the main information, find a reliable source, and compare the two contents. If the answer states that a company launched a product, for example, look for the official announcement.

For data on economics, health, or legislation, give preference to public bodies, recognized institutions, and original documents. When the information involves research, look for the study instead of relying solely on the summary produced by the AI.

Another strategy is to ask the tool itself to present the sources used and, when there is web research, to check the links. This can speed up the work, but it does not replace verification, as the AI can also misinterpret a source.

What to do when there is no certainty?

The best answer is not always the most complete one. If the information is important and the source cannot be confirmed, treat the content as unverified. This attitude is especially relevant in the workplace, where a text, report, presentation, or decision can lead the error to other people if no one checks the original information.

For OpenAI, indicating uncertainty or asking for clarification is preferable to presenting something that may be wrong with confidence. Using AI with agility also requires knowing when to stop for a few minutes and verify the facts. The tool can save time in research and material production, but fact validation remains an essential human step.