The art of deception is as old as time itself and covers everything from counterintelligence
to Halloween masks. But one incredibly convincing method of subterfuge that's rapidly becoming
more common is the deep fake. The idea behind a deep fake is that it creates images that strongly
resemble a certain subject, usually a person, that isn't actually them. But I'm not talking about
some kind of cheap obvious Photoshop job that involves cut pasting your head onto a wait-lifter
friend's vacation photos. Instead, deep fakes can be nearly indistinguishable from the real thing
to the average human eye thanks to the use of artificial intelligence and machine learning.
So here's how it works. Programs that generate deep fakes use not one but two different AIs
working together. The first AI will scan many images of the subject to be faked and then create
new, faked images. The second AI will then examine these fakes and compare them to real images,
and if the differences are too stark, the second AI will mark the image as an obvious fake and
tell the first AI. So the first AI takes this information and continually adjusts the fake
images until the second AI's error rate hits a certain target. That is to say, until the second
AI can't tell a fake from the real thing anymore. This system is called a generative adversarial
network and although the idea behind it is fairly simple, advances in processing power have made
it a very powerful tool for producing convincing looking fakes. And because it's a fairly general
purpose technology, it has lots of cool applications. For example, an AI network like this can analyze
lots of people with a similar look to create a fake model for advertising purposes. It's much
cheaper than hiring a real model and paying them for a photo shoot, much of course to the chagrin of
attractive yet unemployed people everywhere. Deep fakes could also help with age progression photos
used by the police to help find missing people or even to upscale old school video games more
realistically so they look nice on modern displays. But if you've seen stories about deep fakes in the
news, you probably know that there's a much darker side to the technology. Unsurprisingly,
the majority of the deep fake videos on the internet right now are pornographic in nature,
with the idea often being to swap in a celebrity's face without their consent,
resulting in several well-known actresses falling victim to the practice. And because
deep fake technology has gotten good enough to create fake videos that make it appear as though
people have been caught on camera saying things they haven't, seriously it can accurately match
up lip movements to convincingly fake speech, there's a huge concern that it could be used
to spread fake videos of politicians saying insightful or inflammatory things in order to
push a certain agenda. Of course, this doesn't mean that everyone out there will be fooled,
but with how realistic deep fakes can be and how polarized the political climate is in many parts
of the world, political deep fakes could easily convince enough people. Recently, a video surfaced
of Nancy Pelosi giving a speech while slurring her words apparently drunk. The video wasn't even
a deep fake, it was merely slowed down, but it still racked up millions of views before finally
being exposed as fake. And with accusations of political manipulation becoming more common these
days, the rise of deep fake technology has led some observers to believe that it will have a
tangible effect on political discourse and even election results. Although it remains to be seen
if these fears actually come to pass, there are a number of cheaply accessible deep fake tools
that allow people to create deep fakes without a ton of technical skills. So if you want to tinker
with them yourself, I'd say just go ahead, but stay away from the politics and stick to swapping
Linus Faces into your friends wedding video. So thanks for watching guys, like, dislike,
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fakely manipulated to say that. I really think you should subscribe.