WTF is a Deep Fake?
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Ready or not, deep fakes are here to stay. Deep fakes are going to change the way we trust information around us and even each other. The question is - are we prepared for the threat they cause while being able to harness their potential for good?

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Johnny Harris is an Emmy-winning independent journalist and contributor to the New York Times. Based in Washington, DC, Harris reports on interesting trends and stories domestically and around the globe, publishing to his audience of over 3.5 million on Youtube.  Harris produced and hosted the twice Emmy-nominated series Borders for Vox Media. His visual style blends motion graphics with cinematic videography to create content that explains complex issues in relatable ways.

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Like you can see the color on the face isn't quite right and hair is obviously like a wig.

But this video was like from a few years ago.

Which 1 of these is fake and which 1 of these is real?

Maybe you're some wizard and you could tell, but I couldn't.

Deeptown Cruise was a tipping point for deepfakes.

last few years, we've crossed a threshold into a world where moving images are manipulated in ways that make them indistinguishable from reality.

It is the world of high quality deepfakes.

The catastrophic potential to public trust and to markets that could come from deepfake attacks.

This is happening quicker than any of us could have imagined.

So I want to get you up to speed on what's happening with deepfakes, how they're revolutionizing entertainment, And creating new challenges and fears for the people who make our laws and the people who enforce those laws.

Make it look like anyone is saying anything at any point in time.

Ultimately, I want to show you how much of a threat deepfakes actually pose.

And answer the biggest question of all, what is even real?

I promise I'm not like gonna do like some little bait and switch.

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Let's dive back into the wild, weird world of deepfakes.

We've been faking the moving image for at least 100 years.

Thomas Edison wanted to spice up his news reporting from the front lines of the Spanish-American War back in like the end of the 1800s.

So to do this, he shot some fake battle scenes in New Jersey and then cut them together with shots from Cuba, making this look like it was happening in Cuba and it wasn't.

And for the next hundred years, motion picture manipulation remained as crude and simplistic as Edison's sneaky editing.

But then suddenly, in 2014, with the invention of a new type of AI, everything started to change.

The incredibly realistic so-called deep fake.

Is there a way to know when this is fake and to tell when it's fake?

We now have the ability to make people look like other people.

Like, I could be Johnny, or I could be Nick the studio manager.

Look, I'm Nick the studio manager right now.

And what's crazy is even if you go back and watch what I just showed you frame by frame, you likely won't be able to tell.

We can do all of this because of this clever computing process.

It's called Generative Adversarial Networks, or GANs.

This is where 2 AIs work in tandem to get the best fake image possible.

So you have these 2 AIs, 1 of them is a forger,

The forger creates an image based on what you ask it to make

and then it shows that image to the other AI, the detective.

The detective goes over the image and points out all of the reasons it's fake.

It knows what to look for because it's been trained on hundreds, sometimes thousands of images of exactly what the finished products are supposed to look like.

me try again, and it goes away and it makes another image Fixing the pixels

The detective AI once again points out all of the weaknesses in the fake image.

And the forger goes back and makes a new 1.

And so the longer you give 1 of these AI models to train on, it basically goes through this creation and improvement cycle over and over until you get the best deep fake possible.

There are many ways to train a deep fake, but this is the most common.

And it's actually how we got the deep fake that we're running on this clip right now.

My face is slowly morphing into something else and it's basically pixel perfect.

We had to run a training model on this face for 2 weeks.

An important point here is that we used to have to train these models on huge amounts of data.

You need a lot of footage from someone's face to train these models.

Which is why it's mostly worked on like actors who have a lot of high quality face data available.

Or how you get Jim Carrey imposed onto Jack Nicholson's face in The Shining.

Or Willem Dafoe in Silence of the Lambs instead of Anthony Hopkins.

These last 2 clips were done by a super talented deepfake artist named Control Shift Face and he's actually the 1 who's doing the deepfakes for this video too.

He's the artist behind that video that went super viral a few years ago of Bill Hader doing an Arnold Schwarzenegger impression and turning into Arnold Schwarzenegger.

Get out of this, the bomb in there, get out!

And he's now working at a deepfake production company called Deep Voodoo, where he worked on that Kendrick Lamar video.

For me personally, it's exciting because I can do these goofy, funny movie remixes that I

And yes, when I was talking to him in our interview, he was using a live deepfake mask and changing between different characters.

I love your face, it's up my sleeve here.

Deepfaking has already started to shape the entertainment industry.

Filmmakers are using deepfake technology to translate films into other languages.

There's a six-part TV show in the UK about a bunch of rowdy neighbors.

All of these characters are all deepfaked celebrities.

2 years ago, If someone told me something like this would exist, I don't think I would believe him.

And what will be next in like another 235 years?

It's getting to the point where deepfakes are nearly impossible to decipher as computer generated, which is super exciting, but also kind of scary.

The FBI tells NBC News they're following the rapidly developing technology closely.

I believe that this is the next wave of attacks against America.

And this is where we talk about the doom and gloom part.

And for that, yes, I have a lot of paper.

Lawmakers and law enforcement are getting worried about this technology.

Here's a letter From Congress to the Director of National Intelligence, raising the alarm that hyper-realistic digital forgeries, popularly referred to as deepfakes, use sophisticated machine learning techniques to produce convincing depictions of individuals doing or saying things that they never did.

I kind of love when Congress talks about technology.

By blurring the line between fact and fiction, deepfake technology could undermine public trust in recorded images and video as objective depictions of reality.

Oh, and by the way, this letter was back in 2018, basically the stone age for AI image generation.

More recently, I saw a Democratic Senator giving his opening remarks to his colleagues in Congress via a deep faked voice that sounded perfectly like him.

We have seen what happens when technology outpaces regulation.

Europol, which is the European International Police Agency, says that experts estimate that as much as 90% of online content may be synthetically generated by 2026.

Meaning AI will be making most of the stuff that we watch on the internet.

Their big fear in all of this is that deepfakes will quote lead to a situation where citizens no longer have a shared reality causing what they call an information apocalypse.

Here is a 43 page report from the US Department of Homeland Security And look at this title page.

Especially this moment where it goes from a classic sans-serif to a serif.

DHS says that deepfakes and the misuse of synthetic content pose a clear, present, and evolving threat to the public across national security, law enforcement, financial, and societal domains.

The Pentagon is using its big research wing, the 1 that helped invent, I don't know, the GPS, the COVID vaccine, and the literal internet, that 1, to look into deepfakes and how to combat them.

Like, they're taking this very seriously.

But my big problem with all of these reports is they're couched in such vague language.

What can deepfakes actually be used for outside of making really cool Kendrick Lamar music videos and TikTok Tom Cruises.

Well, for get a taste, look no further than Ukraine.

The Russian president says a military operation is now underway in Eastern Ukraine.

Column of Russian armor crossing into Ukrainian territory from the north.

At first, I said that I would return to Donbass.

This is not Ukrainian President Volodymyr Zelensky.

This is a deepfaked video that appeared on a Russian language Ukrainian news site just 4 weeks after Russia invaded Ukraine.

Russian troops were trying to take over Kiev, which would have meant a massive victory for Putin.

Information on the ground was scant and foggy.

And this video pops up of Vladimir Selensky urging his troops to surrender to Russian forces.

Now listen, this is kind of a crappy version of a deepfake.

I mean, misshapen head, weird accent and voice, wasn't super pulled off.

Because what this video did do is it made people question every other video coming out of Ukraine.

And this is what Congress meant when they were freaking out in 2018 about the idea of deepfakes blurring the line between fact and fiction, undermining trust in recorded images and videos as objective depictions of reality.

And this is actually, so far in my reporting on this, the biggest takeaway.

I don't know if we realize what a big shift this is.

As deepfake technology gets better, yes, it allows people to create compelling fake evidence, and that is worrisome, but it also allows people to dismiss real evidence, real footage as oh that's just a deep fake we can do that now we can't trust anything.

It's not just what they could create it's the doubt that is cast on authentic video and audio.

Okay let's get to another concrete threat here to get us away from all the vague language of government agencies talking about how scary this all is.

Deepfakes are becoming a nightmare for evidence in court.

In 2020, there was a child custody case where the mother presented as evidence audio recording of the child's father saying violent things over the phone.

It was submitted as legit evidence as proof to be like, this dad is unfit to have the kid.

But after some digital forensics, it became clear that the mother had used an online tutorial and some cheap software to doctor the audiophile to add in fake violent words.

Most judges and juries are not ready for this.

Most wouldn't think to question evidence like this that sounds like a smoking gun and yet was totally fake.

This sort of technology is getting so accessible and easy to use.

In fact, this VO that you're listening to right now is actually fake.

I made it using a cheap and easy software widely available to anyone." Now imagine that you're on a jury, and you're presiding over a criminal case.

And even though there may not be any manipulated evidence in front of you, there's now a nagging voice in the back of your mind that's like, Remember that time that Johnny tricked me in that YouTube video?

Who's to say all of this visual evidence that I'm seeing in court isn't also fake?

Surveillance footage, body cam footage, heck, even audio taken in a bus from a presidential candidate.

And now it can all be called into question.

And then of course, deepfakes are being used for good old fashioned cybercrime.

Man, cybercrime, it just sounds so quaint.

Elon Musk was recently faked to help shill a new crypto scam.

Bex.net, a site that will help ordinary people to gain financial independence.

And yeah, this one's obviously fake and poorly done.

And some scams are already way more persuasive.

Like this group of fraudsters who were able to clone the voice of a major bank director and then use it to steal 35 million dollars in cold hard cash.

Just by deep faking this guy's voice and like using it to make a phone call to transfer a bunch of money.

Okay, but in reality, the risk of eroding trust in the public or weakening our legal system or giving cybercriminals a new weapon.

All of these are actually the rarest uses of deepfakes.

The main victims of this new technology, at least at the moment, are women.

These sexually suggestive ads are popping up online.

By 1 estimate, 96% of deepfake production is used to produce porn.

Almost all of which are using women who have not consented to this.

Just 2 years ago Telegram got in trouble because it was found that they had private groups on their service that were using deepfake technology to remove the clothes of more than 100, 000 women.

It used to just be the faces of celebrities because they're the ones who have all this high quality data out in the world that you can train a model on.

The tech has developed such that an ordinary person with a few images on social media could suddenly have their faces deep faked onto the body of a porn star.

Martin has found dozens of doctored images and videos of herself.

She has no idea who's responsible for them.

Let's first remember that when a new technology comes along, it typically evolves rapidly, way faster than the lawmakers who need to understand it to regulate it do.

So we're in the kind of Wild West phase where the lawmakers are kind of just trying to get their head around this stuff.

China is actually the first country to have regulated what they call deep synthesis technologies by requiring all deep fake content to be clearly marked as having been modified.

Luckily, a surveillance state is a lot easier to regulate this kind of stuff.

Boy do I love going through European Commission PowerPoint slides.

Like China, the EU is trying to make it so that you have to label deep fakes.

But of course in a Western democracy you have to put this line, unless necessary for the exercise of a fundamental right or freedom or for reasons of public interest.

Oh man, those pesky rights always getting in the way of being able to regulate stuff.

The UK is also trying to figure this out.

They are targeting the porn situation, the 1 that is the mass majority of the uses of deepfakes.

Doing deepfake porn without consent comes with a penalty of prison, though it's super hard to enforce this stuff.

That's what's so tricky, but they're trying.

Will the government take urgent action and repair this mess?

And then there's tech companies, like here on YouTube.

They say that they will pull down any video that quote, includes deceptive uses of manipulated media, i.e.

Deep fakes, which may pose serious risk of harm.

Who decides what serious risk of harm is?

But 1 promising solution here would be to fight software with software.

If we could train software to detect the quirks of deepfakes like the unnatural blinking or some of the other weird subtle things that the human eye can't pick up on, we would have a strong way of verifying what is real footage and what is distorted.

So deepfakes are here and they're seemingly here to stay.

We are entering a new chapter of how humans consume and relate to information.

It's a chapter as significant in my mind as some of the other big chapters, like when we learned to capture light and record it.

Photographs could be used in court as proof.

They could be used in science to capture and understand the world around us.

In journalism, it allowed us to show, not just tell.

And when we made those images move, we could capture more truth, more proof, more evidence.

And then we could connect and spread those images far and wide.

Truth and evidence coursed through the world's internet.

This evolution of the moving image and its uses in the connected world is taking an unexpected turn away from being the bedrock of evidence and towards the foggy territory of deception and confusion.

We're going to have to navigate this chapter carefully.

We're going to have to push even harder to know where our images came from, who made them, and for what purpose.

And We're going to have to resist the urge to believe everything we see, no matter how real it looks.

See all Johnny Harris transcripts on Youtube

Deep Fakes are About to Change Everything