Can You Detect Deepfakes with the Help of Artificial Intelligence?

Deepfakes are synthetic videos that have come a long way. It is a technology to replace the person in an image or video with somebody else who takes after. Deepfakes have garnered widespread attention for their uses in Hollywood, pornographic videos, political speeches, fake news, and financial fraud.

Now you have got to know that deepfakes are created to spread misinformation. It is a threat to the online world. It can tarnish the reputation of people. It is becoming crucial to detect deepfake videos as much as possible so that this type of cybercrime can be prevented from happening.

The concept of deepfake is straightforward. It is like replacing the face of person A with person B. Before it is presented to you, hundreds of pictures are collected for both people. Then, you will encode all these images with the help of deep learning CNN network. Once you have done it, you will need a decoder to reconstruct those images.

Since deepfake videos can harm anyone, the technology must be developed to detect them. Artificial intelligence is a tool used to create deepfakes. Similarly, you will need artificial intelligence to kill deepfake videos. However, the essential question is whether it can be verified with the technology.

How can you identify deepfakes?

There is no denying that the technology is at an infant stage, but it is still possible to spot an amateur deepfake. Here are some factors you should consider while examining deepfakes.

  • Skewed angles

Many deepfake tools put one image on top of the other. When it happens, it looks like a human image but more of like an uncanny valley. If you feel that the face is unable to show visible expressions or it has skewed angles, you should look over it carefully. You can quickly identify it is a deepfake.

  • Body shape

Most of the tools focus on facial expressions. They try it to make it as unique as possible. The entire concentration on facial expressions is because viewers generally look at the face. If you want to detect deepfake videos, you should look at the body too. Compare the face with the body. Try to examine if it aligns with the rest of the body. For instance, in some of the videos, you can easily detect the shoulders and the body do not match with each other.

  • Sound

Most of the deepfake tools focus on creating an appealing and convincing visual, bust some of the videos also require the use of voice changing tools. It generally happens in the case of deepfake podcasts. Such tools may replicate the vocal identity, but it may sound robotic despite spending long hours. If you feel robotic intonation or lack of rhythm, pixilated voice, and odd pronunciation, you should immediately understand it is nothing but a deepfake.

What solutions are available to detect deepfakes?

Though you can identify deepfakes by carefully evaluating the facial expressions, the tone and the body shape, as far as it is about the role of technology to curb the production of deepfakes, experts are still not sure about their potential.

Of course, you cannot wholly rely on technology to restrict the making of deepfakes. Organisations need to set ethical policies. Human intervention should be encouraged where the machine is making a decision, especially about deepfakes. Organisations should take the responsibility of providing trustworthy content, and at the same time, they must be cautious to examine if any such video is streaming on the internet.

The government should also make stringent laws against deepfake makers. They must be prohibited as it can destroy the image of any famous person publicly. Higher authorities are finding ways to detect such videos.

As far as it is about the role of technology to detect deepfakes, it will be quite hard for AI tools to differentiate between original and fake videos. Companies need to create a high-end AI tool to detect such videos. It may cost a small fortune. Some start-up companies may have to fund it with the help of loans like loans for unemployed, personal loans, business loans etc.

Apart from ways as mentioned earlier to detect such deepfakes, another solution is confirming the trusted source.

Content verification is not that effective

The studies have proved that tagging fake news is not the solution to stop people from being influenced by such kind of content. Hardly 2 to 3% of people can perceive the fact with fake tags.

This ideology does not work because people believe a story that confirms their worldview. You cannot consider this a perfect solution.

Well, you can easily understand that the technology is still in progress to curb the making of such videos. It will be hard to make any statement about the duration for the development of such technology. Until a reliable AI tool is developed, you can detect deepfakes by bearing in mind the factors mentioned above.

Description: Artificial intelligence is still in progress to detect deepfakes. As of now, you can identify them by examining facial expressions, body shape and the tone and intonation.

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