Unless you’ve been desperately trying to ignore it to maintain your sanity, you’ve probably noticed that we’re living in what some call the ‘post-truth’ era. Fake News could probably be called the catchphrase of the late 2010s.
Deepfakes are a huge part of that, and for many pose a very real threat.
It’s a fascinating subject from both a technological and cultural point of view, so maybe you’ve been wanting to learn more about it.
Let’s dive in.
A Brief Timeline of Deepfakes
- 1997: The Video Rewrite program modifies video footage to map one person’s face onto another. The program was developed as part of academic study into computer vision.
- 2017: Deepfake enters the public consciousness with the ‘Synthesizing Obama’ program, which modifies footage of Obama to show him mouthing words on an audio track. The project went viral online to show the dangers of technology in influencing our opinions of world leaders.
- Late 2017: Communities for amateur Deepfake videos start popping up on Reddit, including r/SFWdeepfakes. The original, r/deepfakes, is quickly criticized for putting popular actresses’ faces onto pornographic material.
- 2018: In response to amateur popularity (and infamy), commercial development gives us apps like FakeApp, and social media platforms start to experiment with introducing Deepfake features.
- 2018-2019: Backlash from the public forces social media platforms to review how they treat fakery on their platforms. Facebook completely bans Deepfakes which are created with the intention to mislead.
- 2019: Japanese AI company DataGrid creates a full-body Deepfake, with the intended use for fashion purposes.
How does Deepfake Tech Work?
Deepfake tech is reliant on autoencoders. Alan Zucconi explains it in his 2018 Deepfake series. You can also find a very simple description from NBC News:
Generally, consumer-level Deepfake tech produces videos which are fairly easy to debunk without being an expert. Most of the videos produced sit in the uncanny valley, and so we are very well aware that what we’re seeing isn’t real.
However, as is the nature of technology, it’s only going to get more sophisticated.
What Is Everyone Panicking About?
While the technology is pretty impressive, and can have many great uses from entertainment to helping the police generate future images of missing persons, many have concerns.
Whilst many of the most viral Deepfake videos are made for comedic purposes (most seeming to feature Nicholas Cage) some have already picked up traction by targeting political figures.
The perpetrators don’t seem to favor one side or the other, as politicians across the political spectrum have been targeted. The face of Argentine President Mauricio Macri was replaced with Adolf Hitler’s, Angela Merkel with Donald Trump, and a video of Nancy Pelosi was edited to make her appear to stammer. Some videos are clearly fake and created with the intention of mockery. Others appear more credible, and have been shared by major news networks.
It doesn’t take much imagination to realize the damage that could be caused by video evidence of political leaders saying damaging things would be harmful to any political landscape.
With a wealth of content hitting our screens, and most of it existing in an echo chamber, it’s possible that many would see multiple versions of a damaging Deepfake, and none of the content debunking it.
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When Reddit picked up the habit of mapping female celebrity faces onto pornography…was anyone surprised? However, once user-friendly apps started being shared in the community, the spread of these NSFW videos skyrocketed, leaving many actresses feeling very understandably uncomfortable.
In June 2019, an app called DeepNude was released which used neural networks to digitally remove women’s clothing. As the tech became more and more commercially available, there were fears that women could be targeted by ex-partners or scorned lovers.
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Are There Any Positives?
If the technology is so evil, why hasn’t it been universally banned? For starters, it’s very difficult to police the use of tech once it has been adopted and developed by so many. Secondly, only a portion of the content created has been made with malicious intent.
It has been particularly useful to the entertainment industry. Most notably the newest Star Wars trilogy was able to recreate the faces of Luke and Leia as their younger selves, despite Mark Hamill being older and Carrie Fisher sadly having passed away in 2016.
It is also an incredibly useful tool in film dubbing, as shown in a video created by Malaria Must Die which shows soccer star David Beckham speaking nine different languages. Film dubbing has always been…clunky to say the least. But in the Malaria Must Die video, David’s lips match the words he’s ‘speaking.’
So Where Do We Go From Here?
Demonizing new technology seems to be the public’s natural reaction. But if we want to look at things in a positive light, we must remember that as technology gets smarter, so do we.
Deepfake videos are, in principle, no different from Photoshopped images. The only difference is that we have lived with Photoshop for years and feel comfortable.
For Product Managers, new technology is always exciting, and should be seen as an opportunity for innovation. Does the same go for Deepfake tech? Perhaps only time will tell.
What do you think about the future of this technology? Let us know on Twitter! @ProductSchool