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For several years now, deepfakes have been agitated like a scarecrow on the Internet. If you are not familiar with this concept, know that it is a video or sound that has been modified using artificial intelligence. The idea is to make people believe in its authenticity even though it is fictitious. This makes it possible to deploy disinformation on a large scale with an impact that can be devastating.
An Unforeseen Danger
However, researchers from University College Cork have found a new, unexpected effect of this content. Indeed, while the general public is increasingly aware of the risk, Internet users are becoming more and more skeptical of real content. Which can pose a huge problem, because if citizens no longer believe in anything, democratic life becomes difficult, if not impossible.
In detail, scientists have gone into detail sifting through 1,200 tweets on the Russian invasion of Ukraine, some of which warned of the risks of viewing deepfake content on social networks.
Cited by FastCompany, John Twomey, psychology researcher, and one of the authors of this precise study:
Deepfakes are a double-edged sword, in many ways. They will also increase our distrust of real media. In other words, when deepfakes have become the norm, it's easier for people to point the finger at legitimate, real information and say that it's also fake. ;#8217;phony content.
While many elections must be held around the world in 2024, including those in the States -United which will be crucial, their discovery turns out to be explosive. The authors particularly suggest that platforms pay particular attention to content that comments on deepfakes.
As for Internet users, they are invited to ask for proof from people who claim that a video is inauthentic. You should also be patient and not be categorical about a publication. It is often necessary to wait before a video is examined and we can comment on its authenticity.
On the social media side, awareness has begun to arise. In 2021, Facebook communicated on a new detection system developed by its teams. The latter, based on reverse engineering, is capable of obtaining information on deepfakes generated using models that were not yet known. If you are interested in this topic, you can get more information in our article here.
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