It’s the evening of May 10th, 2019. Ctrl Shift Face, a popular channel, uploads the following video to YouTube:
The discourse surrounding this video, and the many others like it, raises a general sentiment that what is being seen is creepy, disturbing, and outright dangerous – the process of ‘deep faking’ in which a face is taken, then mapped onto another. But, most criticism stops there – even if every YouTube commenter solely voiced these sentiments, they’d make up less than 0.2% of the overall view count; the vast majority are simply spectators.
So what makes this passive consumption dangerous? More than you might think. Let’s break down some of the key reasons.
It’s Open Source, and Anyone Can Access It
Now, that code’s useless by itself. It comes neatly packaged, but not alongside the personal expertise you need to make it work – just like any other open source product.
The similarities to other successful open source products don’t end there, however. Take a closer look at the edit logs, or open issues. People are working together around the clock, continuously eradicating bugs, adding guides, and publishing manuals. Followers and contributors are growing in number, while the code itself gets consistently more effective. To a tech developer like me, it’s a beautiful thing; a testament to how dedicated coders can combine their expertise and allow for trending technology to evolve.
The tenacity and creativity of developers can be awe-inspiring, but it’s also a presentation of opportunity for those who wish to abuse open source projects.
Informed Consumers are the Minority
The majority of popular deep fake videos are obviously branded as such, using well-known celebrities and scenarios as the basis for their content. Their purpose is entertainment, which reduces inherent defense and mistrust into seeing deep fake as a comedic tool, or internet joke. Videos where celebrities gain the faces of other celebrities are pretty harmless, and they’re the most common.
It’s easy for this format to become harmful. Replace the people and scenarios with ones you don’t know, and if done properly, it’s hard to detect what is real; most cases where deep fakes are used are openly trying to entertain, and not deceive, via using obvious likenesses for entertainment value. Arnold Schwarzenegger’s face on Bill Hader’s body is Arnold Schwarzenegger’s face on Bill Hader’s body, but John Doe’s face on Joe Public’s body is simply a new, artificial person.
This penetration of our senses only strengthens as you’re exposed to it.
Mass Media is Diluting Dangers
The easiest way to doom a trend in modern America, is for it to be noticed by Jimmy Kimmel. Take a look at this clip from earlier this week:
The exposition of deep fake technology via channels like this accentuates my previous point. Here, we see the technology used in a completely ersatz way, adding to the joke. It may seem like this is evidence for a harmless, comedic potential of deep faking, but it merely creates a common perception that this is the norm.
And guess what? It is. The most prevalent use for deep fake technology will always be entertainment, whether it’s remastering old films efficiently, improvising a skit on a talk show, or adapting whatever emerges from internet culture next. This primary body has ample room for more sinister usage, hidden beneath normality. If someone is exposed to entertaining deep fakes daily, they’re more vulnerable to that annual, targeted smear campaign or fake news video.
It’s Becoming Easier to Utilize
So far, I’ve talked about deep fakes as a general idea or open source technology. This freedom of potential is lost when it’s packaged as a specific product, and completely subject to the team behind it (and their dodgy terms & conditions that was hastily agreed to).
This ease of access also improves companies’ ability to perfect the technology. For every face tuned, their machine learning algorithms get marginally smarter. The question is, who does this help, and who has access to this growing pool of information?
So What’s Exciting About All of This?
Fear and excitement are two degrees of the same reaction. When dwelling upon the concepts and realities of deep faking, your heart rate or cortisol levels may not surge, but there’s still an inherent dark side to any positive. I’ve lived in Silicon Valley for a long time, and have seen it work both ways – trends that seemed scary at first, like machine learning, drones and driverless cars, all garnered benefits as they developed.
The misguided notion that advanced, technical concepts are beyond the understanding of the common user has been around since the inception of the internet. Deep fakes are the perfect vehicle for this new zeitgeist, as they adhere and warp people’s very personas, in a very dynamic way. We can’t change the level of impact deep fakes will have on technology, or society as a whole. We can, however, shape this impact for the better through educating people.
Other Notes for Consideration:
Which included contests through DARPA
Just generally, apps like face2face coupled with voice emulators make it possible for anyone to impersonate anyone with real-time video.
“Just because you saw it doesn’t mean it was real.”
The basis for an entirely new generation of conspiracy theories.