What do marketers need to be aware of about video fakes?

If you've heard the term "deepfake," you might immediately be thinking of illegally opaque, fraudulent and even disturbing videos that have bobbled across the web over the past few years. But as deepfake videos - - and the AI technology behind these videos continue to get sophisticated, it's essential that marketers and creators across every industry learn how they work and explore how they can be applied to get and keep ahead of the changing environment.

For those who aren't familiar Deepfakes are fake media that has been altered digitally to substitute the appearance of a person convincingly, resulting in the capability to make videos which look and feel authentic however don't. This is why it's normal that they might get a bad rap as they spread misinformation and exploit peoples' likenesses.

As with any other technology, it's all in how you utilize it. Forward-thinking marketers and creators are already using deepfake technology and ethically responsibly and ethically -ethically and responsibly -to create new art forms and tell fresh stories and improve their own video campaigns.

In this piece this article, we'll discuss some examples of the use of fake technology for good, as well as ideas on how to experiment on your own with this technology.

What's a fake deepfake?

A deepfake can be described as a video or audio file of someone whose facial or body is digitally altered. Deepfakes use AI to produce a sense of likeness by using patterns to determine the expressions, tone, and movements.

Other terms for a deepfake may refer to synthetic or artificial media, as well as AI-generated content.

 A short history of deepfakes

The development of Generative Adversarial Networks (GAN) began the trend of real-looking fakes in 2014. GANs consist of two AI agents which forge images and detect forgery, allowing the AI to develop over time.

The creation of Deepfakes is also possible using a deep learning computer network known as a varial auto-encoder (VAE). VAEs are trained to encode images into low-dimensional representations of the subject, and later decode those representations back into moving images.

The term "deepfake" was coined in 2017. In the year, the media almost collectively sounded the alarm over deepfakes and viral videos, with the first fake videos of Barack Obama and Donald Trump being shared on social media.

However, deepfakes have other uses which are becoming increasingly relevant for everyday marketers - not just hackers or internet trolls trying to spread misinformation.

What are the effects of deepfakes?

Machine learning AI is a crucial part of developing a deepfake. Deepfakes depend on this tech to identify patterns in the visuals and data.

To create a fake deepfake video, the developer has to feed these machine learning algorithms with hours of footage, which then trains the deep neural network to recognize patterns, tone facial expressions, tone other things. The next stage is to integrate those learnings with graphics.

It doesn't take much to create a deepfake, only existing audio or video of the person you're trying to recreate. And although it may seem difficult at first creating a fake requires no complicated tools - only basic graphic design knowledge and video editing skills.

Examples of artful video deepfakes

Marketers are still in early phases of implementing deepfakes as well as other AI technology for video and digital marketing. The following deepfake examples don't precisely fit into the marketer's toolbox at this point However, they do demonstrate the potential of these AI technologies right now.

 1. Chris Shimojima's "Dolche - Big Man"

This stunning Staff Picked music video from filmmaker Chris Shimojima takes deepfake technology and flips it over its head by incorporating the faces of 14 performers (and 40 contributors) in a single tale. The result is a stunning and unexpected blend of technology and human expression.

 2. David Beckham's numerous different

Malaria Must Die used AI to manipulate soccer star David Beckham to speak in nine languages. They used deepfake technology to make an impact and markedly increase their impact.

 3. Salvador Dali's museum greeting

It took nearly 1,000 hours of machine learning to allow the Dali Museum to create their version of deep fake Salvador Dali precisely the way they want it. The new technology gives visitors to museums a new perspective and allows them to gain knowledge about art from the artist himself!

Three everyday applications for deepfake video tech

While some applications of deepfakes are beyond an common marketer's grasp, there are many creative and interesting ways to use deepfake tech in your own work.

• Repair sloppy lines in post: If you have only a little editing knowledge, you know the trials and tribulations of cutting together polished audio from a more conversational interview. No matter if your client misspoke or simply didn't answer with the full length of a phrase, using the technology of deepfake to fill in gaps is a great option to keep your post-production workflow moving along with no need to reshoot. (Just be sure to get consent from the person you're interviewing and of course!)
   
  
• personalize customer video in a mass the scale of: Marketers can implement an easy way to personalize their video greetings or promotional videos that feature prospects' names or their company names. You only need their names, and some audio from your on-camera talent for the deepfake technology to incorporate it into any video.
   
  
• Translate your video Deepfake technology opens a new world of easy translation. Instead of relying on subtitles, AI can insert translated, spoken audio that is either derived from an audio file or the initial actor's voice.

New technology, opportunities for new technologies

It's impossible to know for certain how the next generation of AI is going to bring however one thing is certain: deepfakes aren't going anywhere. Similar to other AI-powered technologies (chatGPT perhaps? ) Anyone who is eager to try deepfakes with eyes wide open to the potential for pitfalls will be well-suited to succeed in the evolving video landscape.