Do you believe your eyes: Deepfake explained

Artificial intelligence (AI) is a technique for teaching a computer, a robot, or a product to think intelligently like a human. Artificial intelligence (AI) studies how the human brain functions while attempting to solve issues. The study's eventual product is intelligent software systems. AI seeks to enhance computer abilities that are connected to human understanding, such as problem-solving, learning, and reasoning. And one of the popular technologies that uses AI in recent years is Deep Fake technology.

Deepfake technology has recently been in the news. Deepfakes are the most recent advancement in computer imagery, produced when artificial intelligence (AI) is trained to swap out one person's likeness for another in a recorded video.

In this article, we will explain what deepfake is, how it works, why people use deepfake, types of deepfake, benefits and drawbacks of deepfake, and whether deepfake is a crime or not. Lastly, we will discuss the future of deepfake technology.

What is Deepfake and How it Works?

Deepfake technology is used to fabricate information by replacing or synthesizing faces, audio, and emotions. Deepfake is used to digitally mimic an action that a person took but did not actually carry out. Deepfake uses artificial intelligence(AI) to create fictional content at the next level . The person who is being impersonated could be a well-known figure who is the focus of the misinformation campaign, such as a politician, celebrity, or business owner. However, Deep Fakes can also be used to disseminate untrue information about any individual.

What is Deepfake Used for?

Deepfake's principal objective is to persuade viewers and listeners to believe something that did not actually occur. Because of this, it is typically employed in movies to create a creative impact when the entertainers are not there. Another well-known instance is when deepfake was used in Star Wars films to depict characters as they were as children or to replace characters who had passed away. In fact, there have been instances when online businesses have made advantage of this technology to give customers the option to virtually try on clothing and accessories.

Deepfake is used in a lot of areas such as spreading misinformation and inspiring misunderstanding, fear, or disgust, creating false narratives of people, creating revenge porn, generating a specific public image for the subject, and censuring or mocking the subject.

How Did Deepfakes Start and Who Created Them?

It can be argued that the first 'conventional' deep fake technology was created and developed by the academic community in the late 1990s, around the time the internet was initially becoming widely used. Around that same period, amateurs in online groups modified and expanded upon this invention.

Although "deep fakes" have no single creator, one of their most vital parts, generative adversarial networks (GANs), were developed in 2014 by Ian Goodfellow, a Ph.D. graduate who would subsequently begin working at Apple.

How does Deepfake Work?

Deepfakes is based on deep learning, which is the study of artificial neural networks. This is clear from the name (ANNs). Deepfake algorithms use these to take in data, learn from it, and make new data in the form of facial expressions or a whole face overlaid on yours.

Most deepfake software is made with either autoencoders or generative adversarial networks (GANs) (GANs).

Autoencoders learn to copy the large amounts of data they are given, mostly photos of faces and expressions, so that they can make the data sets that people ask for. They are usually not exact copies, though.

GANs, on the other hand, have a smarter system that includes a generator and a discriminator. The first one uses the information it has learned to make deepfakes that must then fool the second one.

The discriminator checks how well the generator's images work by comparing them to real images. Deepfakes that perfectly imitate human behavior are, of course, the best ones.

So, how is this tech used to make deepfakes? The algorithms that run apps like Reface and DeepFaceLab are always learning from the data that goes through them. This lets them change facial features and expressions or put one face on top of another.

The software is basically a video editor that lets you change the way faces look. Some apps are more complicated than others, but you can do just about anything with them, from making someone look younger or older to putting yourself in movies.

But there are still flaws in the technology. Deepfakes may be harder to make than fake live videos, but it can be just as easy to figure out that they are fake.

What is a Deepfake App?

Deepfake Apps are fake software that you can use online and that works in the cloud. All you have to do to use our app is upload videos and click a button. You can make deep fake videos using deepfake programs in a matter of seconds, and the finished products appear remarkably real. Deepfake films can be quite troublesome if used to mislead someone, especially in politics, even though the applications are meant to be amusing.

Most of the time, they hurt the victim's mind, make it harder for them to get a job, and hurt their relationships. Bad people have also used this method to threaten and scare journalists, politicians, and other public figures who are not as well known. Cybercriminals also use deepfake technology to commit fraud online.

On the internet, there are a lot of deepfake apps. Think about how the videos will affect the actors who were fictitious before you use them.

What Kind of Deepfakes Exist?

There are currently five types of deepfake:

• Textual Deepfakes
• Video Deepfakes
• Audio Deepfakes
• Social media Deepfakes
• Real-time or live deepfakes

Let's dive into the details.

1. Textual Deepfakes

Early on in the development of machine learning and natural language processing (NLP), it was believed that a machine could not perform a creative task like writing or drawing. Imagine the year 2021, when the best AI-generated writing can now create sentences with human-looking brevity and clarity, all thanks to the robust language models and libraries that academics and data science experts have been steadily building over the years.

2. Video Deepfakes

The main tool used by deepfake criminals is the production of fake images and videos. It is the most common type of deepfake given that we live in a world where social media is pervasive and where videos and photos better explain incidents and stories than text does.

AI that can now produce videos is more powerful and potentially dangerous than AI that can only understand natural language.

3. Audio Deepfake

Neural networks and artificial intelligence are not limited to processing text, images, and videos. They can also clone human voices. A data repository holding an audiotape of a person whose voice must be reproduced is all that is required. Deepfake algorithms will be able to mimic the prosody of a single person's voice by learning from this data gathering.

4. Social media Deepfakes

Using deepfake technology in conjunction with the creation of stories or blogs, one can construct a difficult-to-detect fake Internet profile. For instance, a deepfake with the alias Maisy Kinsley on social media platforms such as LinkedIn and Twitter was convincingly a (nonexistent) Bloomberg reporter. Her profile picture appeared to have been created by a computer program. The fact that Maisy Kinsley's public profile frequently attempted to connect with Tesla stock short-sellers suggests that the profile was likely created for financial gain.

5. Real-time or live deepfakes

Deepfake technology is astoundingly sophisticated, enabling businesses to produce advertising clones, governments to resemble political opponents, and hackers to replicate user voices to bypass voice-based verification.

Using an innovative deepfake tool, YouTubers are already altering their appearances in real-time. Some artificial intelligence softwares are capable of transforming your appearance via videoconferencing and streaming networks. Streamers have already begun using the capability on sites such as Twitch, and broadcasters and creators of any other media output can utilize this software.

Figure 1. Types of Deepfake

How can you tell a Deepfake?

Deepfake videos that are poorly constructed may be simple to discern, but it can be difficult to spot ones that are of higher quality. However, there are several techniques you may use to identify deep fakes both manually and with the aid of AI.

Bad lip-synching, flickering around transposed faces' edges, badly rendered jewelry and teeth, misplaced or misshapen facial features, unnatural eye movement, facial expressions, body movement or body shape, awkward facial-feature positioning, awkward-looking posture or physique, inconsistent noise or audio, an absence of feeling can help to identify the deep fakes.

What are the Advantages and Disadvantages of Deep Fake?

The primary advantages of deepfake are as follows:

• You may bring a deceased actor or actress back. If we don't consider ethics, it is both possible and very simple! Also, it is probably less expensive than alternative choices.

• More realistic scenes in movies can be shot with the help of deepfake.

• Personal avatars can be made using deepfake technology. These can subsequently be utilized in training programs for a variety of professions or in apps that let users try on clothing or new hairstyles at home.

• Generic technology could make it easier for people and businesses to enter the financial sector by enabling the quick and inexpensive creation of everything from movies to advertisements and games.

The main disadvantages of deepfake are as follows:

• Audio deepfakes have previously been employed to deceive individuals by using cloned voices to make them believe they are speaking with someone they can trust. To persuade a worker at a company to send money to the scammer's account, con artists can deep-fake the voice of a tech CEO.

• It is possible to steal or rebuild the identities of common people using publicly accessible media. Cybercriminals may steal from their fictitious victims or otherwise abuse their identities.

• Modifying deepfake models can cause the identities of several persons who have never lived to suddenly appear in large numbers. The use of these identities in various fraud schemes is possible. There have already been reports of similar occurrences in the wild.

• It's simple for someone with evil motives to slant the news. Conflict, anarchy, and even hunger may result from this.

Is Deepfake a Crime?

Since deep fakes are readily available and cost nothing, many people produce deep fake content featuring themselves or famous people, including politicians, actors and actresses, musicians, and artists. Deep Fakes of Obama, Trump, Zuckerberg, and Dal are a few well-known examples. Moreover, they are pretty convincing. In other words, it is challenging to tell whether one is genuine. As a result, it is thrilling to see your favorite actors in unrelated films or to hear your favorite musician calling out to you in a video.

Deep fake is considered a crime depending on the country and how it was used.

According to suggestions made by the Law Commission of England and Wales, spreading "deepfake" pornography without permission or secretly filming or photographing people in their underwear might result in prison terms of up to three years.

After making a number of arrests, largely of minors, South Korean police officers declared the creation of deep fakes to be a felony on May 2, 2021. The creation or dissemination of profound fake content is a serious felony, according to a police official.

The Organization for Social Media Safety has sponsored AB 1280 in the California State Assembly. It will stop people from making deepfakes that steal identities for pornographic videos by making it a crime to make and distribute deepfakes for these purposes.

Why is Deepfake Dangerous?

Deepfakes have the potential to seriously harm the global community. These deep fake videos do not have the approval of celebrities or adult film producers. In addition to possibly violating copyright laws, this might seriously traumatize the implicated celebrity on an emotional and mental level.

Regular individuals also experience it, not only famous people. The unsettling reality is that it is possible to achieve employing bots, which can publish a large number of naked pictures of various persons.

Deep Faking can occasionally be used to purposefully end someone's life. It is accomplished by deep faking an image of a person, usually a woman. After that, the victim is threatened with sending the bogus documents to their family, friends, or employer.

The trust that people have in content creators (news outlets, publications, etc.) as well as the subjects of deep fakes could be severely harmed by deep fakes, and new internet scams could be developed as a result.

Future of Deepfakes

Clearly, there is a great deal of worry about the potential immoral uses of deepfake. Scammers have even utilized AI-generated voice recordings to steal money by making phone calls and enticing customers to transfer money. It has previously been used to create false pornography of unconsenting victims.

Since deep fakes first appeared in late 2017, a number of apps and pieces of software, like DeepFace lab, FakeApp, and Face Swap, have become widely accessible, and the rate of invention has only picked up.

Companies are increasingly trying to make money off deep fakes by licensing the technology to social media and gaming companies. However, there is a considerable likelihood of deepfake abuse. There is worry that the technology, in the wrong hands, might create false information and false, deceptive videos, endangering national security.

Although Deepfakes can be used in both beneficial and harmful ways, their use should be directed in the proper directions as explained below:

• Video and radio advertisements, podcasts, dialogue and video customization

• Integration into AR/VR applications: Deepfakes and immersive technologies like AR and VR work together to enhance other's effects in a variety of applications, including gaming, remote corporate meetings, learning sessions, and fashion and retail.

• Synthetic media: For increased personalization, managing scheduling, enhancing the entertainment experience, enabling cost savings, and more, synthetic celebrities, films, audios, and other content can be produced.

History of the Deepfake

In 1997, Christoph Bregler, Michele Covell, and Malcolm Slaney created a program called Video Rewrite. This program changed existing video footage of a person speaking to show that person mouthing the words from a different audio track. This was the first system that could do this kind of facial reanimation completely automatically. It did this by using techniques for machine learning to find links between the sounds a person makes in a video and the shape of their face. The program was originally made for use in dubbing movies. It lets the movie sequence be changed so that the actors' lip movements are in sync with a new soundtrack.

As computer vision and artificial intelligence continued to progress, breakthroughs in human image synthesis enabled the general public to superimpose existing pictures and movies onto source photos or films using a machine-learning approach called generative adversarial network. The availability of this technology has led to its use in pornographic and political propaganda movies. In 2017, the term deepfake was invented, a combination of "deep learning" and "fake".