A relevant problem is now represented by “misinformation”, based on the creation and dissemination of substantially false texts, images, and videos. This problem is further amplified by the new information technologies, which make these realizations increasingly being automated.

For example, artificial intelligence algorithms can generate a fairly convincing text to fool the average reader, potentially providing a way to mass-produce fake news, bogus reviews and phony social accounts.

In this regard, the American researchers carried out an interesting experiment: they asked some Harvard students to identify AI-generated text. The students were able to spot only half of all fakes on their own.

But, thankfully, AI can now be used to identify artificial text too.

Researchers from Harvard University and WIT on AI Lab at MIT in Boston have developed a new tool for spotting texts generated using AI. This algorithm, called by acronym GLTR (Giant Language Model Test Room), exploits the fact that artificial text generators are based on statistical patterns, as opposed to the actual meaning of words and sentences. In other words, this tool can tell if the words used in the analyzed text seem too predictable to have been written by a human hand, because our brain, with the same meaning, loves complexity and variety.

In summary, GLTR analyzes words that are statistically likely to appear after preceding word in the text, highlighting the most predictable words in green, less predictable in yellow and red and the least predictable and the most original in purple.

At this point, the researchers carried out the same experiment reported above with the same Harvard students, but with the help of  GLTR highlighting: the students were able to spot 72% of artificial texts.

As a result, AI-powered tools such as this may become valuable weapons in the fight to catch unethical purposes, often inherent in fake news, deep fakes and automatic chatbots.

(source MIT Technological Review – 2019)

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