The positive sides of DEEPFAKE

The positive sides of DEEPFAKE
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In deze les zitten 30 slides, met interactieve quizzen, tekstslides en 7 videos.

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The positive sides of DEEPFAKE

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First some vocabulary:

https://quizlet.com/_bpgfge?x=1qqt&i=1fkbbg

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Yes, positive deepfake examples exist
Artificial intelligence technology, to many, is scary. It’s packed full of ethical questions and uncertain future applications. Perhaps one of the more alarming functionalities enabled by AI advancement is the creation of deepfakes.  

Deepfakes undermine our trust in the information we see. Plus, they present plenty of opportunities for mischief and malicious use. It’s hard to see how we could hope to show such functionality in a positive light — or how anyone could ever come to trust it.
  

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Name opportunities for mischief
and malicious use

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But, as with any tool, there are beneficial uses for deepfakes too. Here, we explore some oft-forgotten positive deepfake examples. How can deepfake technology be a force for good?

But first:                                          What is a deepfake?
  

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But, as with any tool, there are beneficial uses for deepfakes too. Here, we explore some oft-forgotten positive deepfake examples. How can deepfake technology be a force for good?

But first:                                          What is a deepfake?
  

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 What is a deepfake?
The term deepfake is a portmanteau of ‘deep learning’ and ‘fake’. Deepfakes are convincing content depicting artificially constructed events.

That content could be a video, photo, or audio recording. Whatever the medium, its content has undergone a verisimilar change via artificial rendering. (Think changes to a face, a voice, or any element of a person’s movements, speech, or actions.)



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 What is a deepfake?
This most often affects celebrities and predominant public figures. Their likeness is used, but the content isn’t real. They aren’t truly saying those words, or physically enacting those movements.

To be a true deepfake, the creation of this artificial content must involve the use of AI and machine learning functionality. Specifically, deep learning.


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This, understandably, has raised a sea of concerns. Aggravating this alarm is the fact that plenty of stories about deepfakes discuss deepfake pornography, fake news and fraud. But where there’s bad, there’s good.
Positive deepfake examples also exist.

So, let’s look at some of the beneficial applications of the technology.


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Educational deepfake examples
Deepfake technology holds positive potential for education. It could revolutionise our history lessons with interactivity. It could preserve stories and help capture attention. How? With deepfake examples of historical figures.
For instance, in 2018 the Illinois Holocaust Museum and Education Centre created hologrammatic interviews. So, visitors could talk to and interact with Holocaust survivors. They could ask questions and hear their stories. As deepfake technology advances, this kind of virtual history could become achievable on a much wider scale.

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Reactions

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Another example comes from CereProc, a company that ‘resurrected’ JFK in voice. This deepfake made it possible to hear the late president deliver the speech he would have delivered, if not for his assassination.

In this way, deepfake technology could help us preserve not just the facts in history books, but the impact historical events had on real people.



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Reactions

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Reaching worldwide audiences
Positive deepfake examples also show how the technology can make language barriers (and bad dubbing) a thing of the past.

Take, for instance, the David Beckham malaria announcement. By using AI technology, David Beckham was shown to speak nine different languages in order to share a message for the Malaria Must Die campaign.




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Deepfake characters
There are a lot of positive deepfake examples for use in the entertainment industry. Deepfakes can keep film characters consistent.

For example, consider the times that an actor has passed away. Deepfake technology can fill the role of CGI, recreating the likeness of unavailable past actors. So, the character doesn’t have to pass away with their actor. For example, the recreation of the late Peter Cushing in Star Wars: Rogue One (2017), who passed away in 1994.





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Deepfake characters
Or, consider times when a character needs to be older or younger than their actor. For example, the late Carrie Fisher’s character, Princess Leia. Even though the actress herself was not available, her young likeness was recreated. This also demonstrates another positive use of deepfake technology: ageing and de-ageing.





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Positive deepfake examples in the art world
Moving away from film, it’s also possible to find positive deepfake examples for the art world.
AI technology could help us create virtual museums. This would allow access to the world’s masterpieces for people that otherwise might not be able to experience them in person. We could share convincing, deepfake artwork across the world.
Deepfake technology could even allow us to resurrect dead artists. For instance, Salvador Dali at the Salvador Dali Museum in Florida.





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Positive deepfake examples in the art world
Perhaps a more novel use of deepfakes could be to bring art to life. Samsung’s AI research laboratory has allowed the Mona Lisa to move her head, eyes and mouth. So, if you thought she was watching you before…







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More positive deepfake examples 

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DUTCH POLICE USE DEEPFAKES TO SOLVE A CRIME
The Dutch police have utilized a deepfakes video to appeal for information on the 2003 murder of a young boy. According to authorities in Rotterdam, it is a “world-first” inquiry using artificially altered video.







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The technology behind so-called deepfake videos is helping boost the impact of a new generation of adverts for missing people.







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Earning trust: proceed with caution
When it comes to deepfakes, there’s plenty of potential for the technology, good and bad. Naturally, the desire is to see more positive deepfake examples, rather than fraud and negativity.
But this can’t happen until the concerns are answered, the correct cautions are taken, and we find a way to trust the tech.
This means that we need to see when something is real and when it’s AI-generated. We need rules that keep the technology helpful, and practices that prevent it from causing harm.









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