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Computers have steadily improved their ability to simulate reality. In place of the genuine settings and props that were formerly popular, the modern film depends significantly on computer-generated sets, scenery, and characters, and most of the time these sequences are nearly indistinguishable from reality.

Deepfake technology has gained a lot of press recently. It is the most recent generation of computer imaging, are formed when artificial intelligence (AI) is designed to substitute one person’s likeness in recorded video with another.

The term “Deepfake” is evidently a mix of two common words: “deep” and “fake.” The term “deep” alludes to the AI technique utilized in this case, which is known as deep learning.

It is used to produce fake material in synthetic media, such as replacing or synthesizing faces, voices, and altering emotions. It is used to digitally replicate an activity that a human did not perform.

How Does DeepFake Works?

Deepfake software may be created in a variety of methods using machine learning techniques. Alternatively, they are algorithms that can produce content based on data input.

When software is given the responsibility of creating a new face or replacing a portion of a person’s face, it must first be taught. The software is fed a large amount of data, which it then utilizes to learn how to generate new data on its own.

They are mostly based on autoencoders, although they can also be based on generative adversarial networks (GAN).

Let’s look at these tactics more closely to understand how they operate.

Autoencoder:

The autoencoder is a deep learning AI software charged with analyzing video clips to determine how a person appears from various perspectives and environments and then mapping that person onto the human in the target video using common traits.

GANS Generative Adversarial Networks:

GANs are used to find and fix problems in the deepfake across several rounds, making it harder for deepfake detectors to decode them.

GANs are also a common way for making deepfakes, depending on the analysis of massive quantities of data to “learn” how to produce new instances that are excruciatingly accurate in comparison to the actual thing.

DeepFake Technology Affecting The World:

On the internet, the number of deepfake materials is continually expanding. Agreeing to Deeptrace, there were 7,964 deepfake videos accessible at the starting of 2019; nine months afterward, there were 14,678. It has likely kept on growing since that point.

Deepfakes that fall into the wrong hands may cause chaos and uncertainty. A video of two guys on a motorcycle kidnapping a toddler in India was published on WhatsApp in 2018. Following the distribution of the video, there was widespread fear among the populace, which resulted in the deaths of numerous people.

A Sword With Two Faces: DeepFake Misused

Leaders, celebrities, and influencers have power in our culture. With their cooperation, misinformation may also affect the attitude of the public and stimulate action. And similar events have previously occurred. Deepfake porn films starring celebrities have emerged on the internet on several occasions.

Fake porn movies were the start of deepfake’s proliferation. Deepfake porn has harmed a number of female celebrities. Among them were Daisy Ridley, Jennifer Lawrence, Emma Watson, and Gal Gadot.

Women close to world leaders, like Michelle Obama, Ivanka Trump, and Kate Middleton, were also affected by the situation. DeepNude, a desktop program appeared. It was capable of removing women’s garments. It was eventually taken down, but versions of the program may still be seen floating around in cyberspace.

POLITICS:

Politicians are the next group to be impacted by deepfake. President Obama was caught on tape disparaging President Trump.

Nancy Pelosi’s words were manipulated in another video to give the impression that she was inebriated. President Trump ridiculed Belgium for joining the Paris Climate Agreement in a separate video.

ART:

Making iconic portraits talk is a prominent use of deepfake in art. This was done using Da Vinci’s Mona Lisa by Russian scholars. To entice tourists, the Dali Museum in Florida reproduced their namesake using old film footage.

Social Media:

While some social media platforms, such as Facebook and Twitter, have updated their policies to combat deepfake and restrict synthetic material, others have embraced it. Face-swapping camera functions have been available on Snapchat since 2016. TikTok has added the ability for users to swap faces in videos.

-Because deepfake has only been around for a few years, legislation governing its use has not yet kept up with the technology. It is completely unregulated in many nations. China is one of the nations that has enacted legislation prohibiting the use of deepfake.

Social media is already bearing the threat of identity theft and deepfake is now fueling it. Thousands of people suffer from identity theft each year and it is a severe danger. Hackers used to steal the identity and make accounts on social media by available pictures of individuals. With deepfake it’s almost impossible to distinguish real accounts from fake. 

How Can You Spot A DeepFake:

As deepfakes become more common, society as a whole will need to adjust to recognizing them, much like internet users have become accustomed to seeing other sorts of fake news.

In many cases, such as in cybersecurity, more deepfake technology is required to identify and prevent it from spreading, which may lead to a vicious circle and potentially cause more harm.

Artificial intelligence is used to detect deepfakes, which uses algorithms identical to those used to construct the deepfakes themselves. They are able to identify indications that aren’t visible in genuine images or movies.

However, systems have evolved to imitate eye blinking over time. Among the warning signs are:

  • Individual facts or figures that are blurrier than the background; 
  • Jerky movements;
  • Speech and lip movement are not synchronized well; 
  • Variations in skin tone or unnatural skin color;
  • Issues with lighting;
  • There are more pixels in the frame.

To Sum Up!

Deepfake is a relatively new and exciting technology. Humanity is still coming to know it, and it hasn’t discovered its full potential in our society. It’s like a two-sided coin, a technology with both advantages and disadvantages. It has the ability to either hurt or benefit our world. We’ll need some time to figure out how to make the most of it in various businesses. As with previous advancements in the past, there will be various ways to regulate it throughout time.