How much can you trust artificial intelligence?

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The answer seems simple, but it's not. Generative models, as the technology behind ChatGPT is called, are trained to generate content that appears to have been written by a person, not to provide 100% correct answers.

Therefore, they are notorious for making errors with authority—that is, for issuing incorrect answers in a way that makes them appear, to an unsuspecting reader, genuine. And this error occurs most frequently precisely in questions that require more depth and knowledge, which are precisely those in which the user will have the most difficulty detecting an error.

According to Thoran Rodrigues, CEO of BigDataCorp and an artificial intelligence shop expert, it's impossible to use generative models beneficially without first understanding how they work and, most importantly, their limitations. "Using these technologies while blindly accepting all the answers returned is the prelude to a potential social disaster for humanity," comments the expert.

Generative models don't learn like humans. They can analyze billions of texts, articles, images, computer code, mathematical formulas, and other types of content and mimic their writing style, but the machine doesn't think.

It's not concerned with whether the content is correct, only with the strength of the association between the contents. If the correlation is strong, the tone is authoritative, regardless of whether the content is correct, and the way the response is written, in turn, conveys to the user the perception that there is a basis behind what was returned.

For the expert, it's important that these limitations and problems are made very clear by the companies building these models. "People's natural tendency is to anthropomorphize technology, that is, to treat artificial intelligence as another person. And we can't expect everyone in the world to understand how these algorithms work and the associated risks. It's important that developers make the limitations of their tools clear."