Producing deepfake is easy. It is hard to detect. They operate with a description of reality rather than reality itself (e.g., a video). Any artifact a system can identify to support a Deepfake can also be removed in a subsequent Deepfake creation. This article discusses the art of Deepfake.
What Is Deepfake?
Deepfakes are a condition of artificial intelligence that allows you to create realistic-looking videos. They’re used in movies, YouTube videos, and more.
The goal of using this type of AI is to trick people into thinking that what they see is real—even though it’s not.
Experts at academic institutions created Deepfake technology starting in the 1990s and subsequently, novices in internet forums. The industry has lately embraced the techniques.
Why Should Deepfake Be a Concern?
Deepfake technology is an emerging and highly disruptive form of synthetic media. Deepfake can manipulate public opinion, create confusion and discord, spread fake news, distribute false information, and produce fake images and videos.
Deepfake is a new form of media that has the potential to be used in malicious ways. Unscrupulous individuals can use this technology to create fake videos of political leaders, celebrities, and even people committing crimes.
Today’s Deepfakes are not as good as Hollywood’s CGI, but they are getting better daily. The process involves using artificial intelligence (AI) to replace one person’s face with another person’s face using:
- a mixture of machine learning algorithms
- 3D modeling software like Maya or ZBrush
- video editing tools like Adobe Premiere Pro CC
- retouching programs such as Adobe Photoshop CC or After Effects CC.
Deepfakes have also attacked significant figures, including Nancy Pelosi, speaker of the House, and Facebook CEO Mark Zuckerberg. It has raised growing worries about the high risk of misinformation and deception; thus, directly affecting the cybersecurity landscape.
Deepfakes, for example, are used to deceive. Second, they use newly invented technology such as autoencoders and generative adversarial networks. Malicious hackers can use deep learning algorithms to precisely target a person’s resemblance features, such as face shape or body posture. It provides incredibly convincing impersonations, which attackers are reaping the benefits of.
Existing Tools to Detect Deepfakes
You can detect Deepfakes using machine learning and human-based techniques. You can also use a combination of both to identify Deepfakes. The most common ways to detect a fake video include:
Machine learning: This technique uses neural networks to classify whether an image is genuine. It’s based on the fact that images are composed of pixels with fixed values in brightness levels or colors. Using this information, you can train your computer to recognize how images look when they’re real and when they aren’t real (i.e., if there’s something wrong with them).
Human-based techniques: A second approach relies on humans identifying what makes an image seem fake by looking at it closely through their own eyes—and then reporting back with their findings after comparing them with known “real” pictures from either side of the debate (including those from different sources).
How Deepfakes Can Help Organizations
When applied ethically, Deepfake technology has a lot of promise to help enterprises. Here are some examples from the real world.
The Dal Museum in St. Petersburg, Florida, uses Deepfake technology. When tourists rang the bell on the kiosk, a life-sized lifelike replica of the surrealist artist (1904-1989) materialized in front of them and told them a life story.
Lyrebird, a Canadian AI firm, makes unique products utilizing Deepfake voice technology. The firm collaborates with the ALS Association on “Project Revoice” to assist those with ALS, also known as Lou Gehrig’s illness.
The program allows persons with ALS who have lost their capacity to converse to express in their own real and distinctive voice.
Disney has improved its visual effects by utilizing high-resolution Deepfake face-swapping innovation as Deepfake technology progresses.
Disney developed their system by gradually training it to recognize facial movements, incorporating a face-swapping capability, and refining it to stabilize and perfect the result.
Deepfakes have arisen on prominent social media platforms, most prominently on Zao. This Chinese Deepfake app enables users to replace their faces with those of actors from tv shows and movies such as Romeo, Juliet, and Game of Thrones.
Deepfake positive and negative possibilities
Deepfake can be used in both positive and negative aspects. However, it is better to be aware of the possibility that this technology can have negative consequences rather than positive ones.
- You must remember that Deepfakes are not limited to one purpose, and they are not limited to one field of use.
- You can make any content with it; even fake news or misinformation could be spread through Deepfake videos.
- In other words, you should always double-check everything before sharing something on social media because there might be an alternative version available that may be more accurate than the one you saw the first time around!
In conclusion, we can say that deepfake technology is a very powerful tool that can be used in both positive and negative aspects. However, it is better to be aware of the possibility that this technology can have negative consequences rather than positive ones.