The 404 Media Podcast (Premium Feed)

Forget about the bad guy creating the app. There's nothing you can do about that person. They're like the street level dealers. You gotta go after the kingpins. That's who you go after, and you bash them over the head until they get their act together.

Hello, and welcome to the four four Media Podcast, where we bring you unparalleled access to hidden worlds, both online and IRL. Four four Media is journalists founded and needs your support. To subscribe, go to 44media.co, as well as bonus content every single week. Subscribers also get access to additional episodes where we respond to their best comments. And to get early access to our interview series too.

Gain access to that content at 44media.co. Also, remember to subscribe to our YouTube channel where you can watch all episodes. I think we're pretty good at telling the difference between an AI generated image and a real photograph, but when I need help, I call Hani Farid, which we have on the podcast today. Farid is the co founder of Get Real, a company that specializes in detecting Deepfakes and is the developer of PhotoDNA. You may not have heard of PhotoDNA, but PhotoDNA is a very important piece of software that today is used by any serious internet platform that automatically detects some of the worst images that exist online, and we started talking to Hani pretty regularly in 2017 when Sam first reported on Deepfakes as that technology evolved and changed how we perceive reality, so have our conversations.

I wanted to talk to him today on the podcast so you could hear one of those conversations, and so that Honey and I can zoom out, reflect on the past few years, and speculate about where we might be headed next. Okay, Honey, thank you so much for coming on the podcast.

It's good to be with you.

Just to give some background to how we know each other, I think we started talking when we were still motherboard and Sam was doing some of the first reporting on Deepfakes. Not some of the first, the first reporting on the first. When we were trying to wrap our head around the problem and how tech platforms are going to deal with it, we immediately ended up looking at photo DNA, which is something you worked on. Yeah. And that seemed imminently relevant, and it has only become more so since then.

So I thought, can you start by explaining what photo DNA is and why is that something you worked on at the time? Yeah.

So we're going back now almost twenty years. 2008 was around the time I started working on it. And it's hard to remember twenty years ago, but the internet was still pretty nascent. Things were early. AI was nothing and mobile was just coming up and social was still sort of an annoying teenager.

Now it's a full blown raging lunatic adult. And even in the early days, even before 2008, as soon as the internet started, the National Center for Missing and Exploited Children, NCMEC as it's called, was already starting to see just a flood of child sexual abuse material now in the digital world versus the previous analog world. And they very early on started getting very concerned about the floodgates opening up around child sexual abuse and kids being abused and that content being recorded and that content being shared. And now it's a global problem without any real barriers to entry because there's no, you know, none of the usual barriers within analog physical world. And in 2008, I started working with Microsoft because they, I would say to their credit, were one of the few tech companies at the time that really thought, oh man, this is not cool.

Like, we gotta fix this problem. And just I don't wanna get too graphic, but people need to understand that when you talk about child sexual abuse, we are not talking about 16 and 17 year olds, which by the way, is still a problem, don't get me wrong. But average age today is under the age of 12, kids involved in child sexual abuse. And that goes down to two years old, one years old, and a few months old. You're talking about literally toddlers.

So I don't want hear any discussion about, you know, oh, they're almost 18. This is not what the issue is. This is horrific, horrific content. Ernie Allen, the previous president of Nick Mick used to call them crime scene photos. Stop calling them child stop first of don't call them kiddie porn.

Don't call them child porn. And these are crime scene photos. And that and if you've seen these, and I have, and they are horrific, and they will give you nightmares. This is a really ugly, ugly part of the Internet and the content, the kids are getting younger and the content is getting more violent and problems have only escalated over the last twenty years. And so I only say that so that people understand what we are talking about.

Okay, so back in 2008, you know, again, internet was nascent, we didn't have the type of computing power, we didn't have AI, and we were already seeing a spread of child sexual abuse. And I was asked by Microsoft and the then Technology Coalition, as they were called, to come down to DC and to talk to them about how they can mitigate the spread of this content. And at the time, they were thinking about the problem this way. Well, you know, the Internet was already big. So how do you scan every piece of content that's uploaded?

How do you determine if there's a child in it? How do you determine if the child is underage? How do you determine if it's sexually explicit? And you just couldn't do it. You couldn't do it in 2008, you can barely do it today.

But what I learned is that at the same time, it wasn't just that people were always creating new content, they were. It's that they were also recycling old content over and over and over and over again. And now we're getting to photo DNA finally. And I said, I'm a typical academic, right? Somebody tells me a problem they wanna solve.

If I can't solve it, I don't give up. I change the problem. So I changed the conversation. I'm like, guys, you're trying to solve the wrong problem. Solve this problem.

Solve the problem that once you've seen a piece of content and you have identified as child sexual abuse, child is in it, underage, sexually explicit, let's stop the redistribution. Like, let's just solve that problem, which turned out to be really freaking hard. And then we'll go and tackle the next set of problems. And so that's what PhotoDNA does. So what PhotoDNA does is it reaches into a piece of digital content and it extracts a distinct digital signature.

Like the name suggests, the signature is stable as the content makes its way around the internet and gets modified. And it's distinct. Two images of different things don't share the same digital signature. And so the way it works is today, this technology has now been deployed more or less worldwide. If you upload an image to Facebook, it will extract its photo DNA, It will compare it against a list of known child sexual abuse material provided by the National Center for Missing and Exploited Children.

That list, by the way, is in the tens of millions. And if it's a match, well, then you flag it and it gets reported. And by the way, for all those people out there who are gonna start jumping up and down in my head being, oh, privacy this, privacy that, all of your content is being scanned. Don't be stupid, right? It's being scanned for copyright infringement.

It's being scanned for malware, ransomware, phishing scams, all kind every single piece of content that you voluntarily upload is being scanned. So sit down and shut up about it. Right? We've been doing this to protect the music industry and movie industry for years and nobody was jumping up and down on their heads. So it's very clean technology, it's very, very targeted.

We deployed it, we developed it between 2008, 2009, deployed on Microsoft in 2009. And over the ten years after that, it started getting deployed worldwide. And the reason why it's relevant finally to this question, Emmanuel, is that the spread distribution of non consensual intimate imagery that Sam so presciently wrote about, more or less the same problem, although with some caveats now. So somebody creates a non consensual intimate imagery, and by the way, don't call it revenge porn. The women in these images didn't do anything that requires revenge.

It's non consensual. We can stop the redistribution of that in the same way. Once somebody creates this piece of content and uploads it, it gets flagged, tagged, and we just add it to that list of things. The difficulty now in the world of AI is people can make new versions of that so unbelievably fast that this hashing, as it's called perceptual hashing, photo DNA, still an important tool, don't get me wrong, but if you can now create tens of thousands of these images every day, this is the mother of all the whack a moles. But that's what the technology is, and it's still being used today.

Yeah. We're definitely going to get into that problem of quantity that you just described. Yeah. I guess just to get like a tad more technical, because this is something that I always found fascinating and maybe is useful for the people listening. The way that this so called DNA or the signature hash is extracted is basically an image is made out of pixels, right?

PhotoDNA turns the values of those pixels into like a numerical value of some kind. That is what is kept on file. Yeah. And then you're able to look at every other image, see if it has the same numerical value or same signature, and that way nobody really even has to like look at the images, you're not keeping a record of the images, you're just like, you're comparing these signatures to each other and that's for reasons that we've talked about in the podcast before, it's like it's very difficult to even like investigate these issues because the laws around this material is so, so strict. Like I as a journalist, I'm not allowed to look at it.

Yes. So this is kind of a neat way to deal with the problem.

Yeah, no, you said it exactly right. You basically basically convert an image which is a bunch of pixels into a bunch of numeric values. And I'm not going to tell you exactly how it works because that's not the smartest thing in the world to do because that's how people reverse engineer it. And then just this relatively small number of numeric values are stored. They are quite removed from the original image, and then you just do comparisons.

And importantly, for those people who have heard of hashing, they've probably heard of MD5 hashing or SHA-one hashing or what's called hard hashing, this is what's called perceptual hashing. The thing with hard hashing is it's great if you are looking for exactly the same file, pixel for pixel, bit for bit. But the way images work is they're constantly being modified ever so slightly, but not perceptually. So if I take an image, for example, and modify one pixel, you and I would look at it and say those are exactly the same image. But hard hashing MD5 SHA-one would say completely different images.

Whereas the perceptual hashing would say, nope, those are the same image. And so that was the trick here. That was the insight back in 2008 is how do you make this hashing resilient to the types of modifications we expect? And it's not perfect. There are modifications that you can do that will destroy the hash.

It's okay, we'll see another version of it, we'll hash that one, and that will get added to the library. But here's the thing you also have to understand. And this used to make me crazy. People would say, all right, this is all fine and good, but you know, you're not going to solve the problem. And I always wanted to slap these people upside the head.

I'm like, since when do I have to build a technology that solves 100% of the problem before we deploy it? Like what fantasy land are you living in? So this doesn't have to solve all the problems, but it took a huge bite out of the problem from when we were completely blind to now NickMic is receiving literally tens of millions of reports based on photo DNA, which means tens of millions of these images are not getting redistributed, number one. Number two is people don't share one or two images, they share hundreds, thousands, tens of thousands. And if they share one image that I've seen before, I get it all.

So that's the thing you got to understand is once you have the account, and you have probable cause now, right? You have shared an image that I know is child abuse, you can go after everything in that account. That's number two. And here's number three, this is the important one that people forget. This was never when we designed this a law enforcement issue.

This was never designed to help law enforcement put really bad people in prison. I mean, I don't mind if that's what happens, but that's not what it was designed for. This is what it was designed for. Go talk to kids who are victims of this, and I've talked to many of them over the decades. And what they will tell you is single worst day of their life is when they were sexually abused.

Second, third, fourth, fifth, sixth, seventh, eighth, ninth, tenth, and the hundreds other worst days are every time they are notified when their image is being circulated online. Imagine the worst day of your life, the most humiliating, awful, painful day of your life, somebody has photographed it, and day after day, month after month, year after year, people are sharing that content. This was meant to stop re victimization of these young kids. And that's really important to keep in mind here, is that when we do that, we are helping in our own small way, that re victimization to those kids.

So this way of dealing with the problem is how we found you and started talking to you. Today, you are mostly well, I don't know, you could tell me, but you co founded this company Get Real and you deal with a lot of synthetic images, AI generated images, fake images, digital images, however you want to call them. Can you talk about the shift from photo DNA dealing with these kind of images to, like, purely digital images or manipulated images doesn't seem super obvious to me. So, like, how did how did you you go

from one thing to the next? Yeah, in fact, what's interesting about this is PhotoDNA was actually the anomaly. So the way I got to PhotoDNA is I was working on this question of digital authentication in the pre AI and honestly pre digital age. I started my academic career in '99, 1999. I like to tell my students I started in the 1900s, which to them you may as well be 1929, they don't know what the difference is.

And I was thinking about how you authenticate digital images. New York Times wrote a story about it. Tim Cranton from Microsoft stole that article and like, maybe this guy can help with the child abuse stuff. And so the photo DNA was interestingly enough, was the divergence. And then when that project sort of took off and it was years and years of work, then I just simply returned back.

And then what happened was that that digital authentication was still a fairly niche field, relatively self contained. We were working with media outlets, Associated Presses and the Reuters and the Algeance France, and people like you, you know, for like a few viral images that would go around every once every few months. Working with law enforcement, national security on legal cases where evidence was being introduced in the court of law. And then of course, five years ago, this whole space exploded with generative AI and Deepfakes. And suddenly we went from, okay, somebody wants to create a fake, they need a little bit of skill and they need some time and they need some effort, then maybe they can make a good fake, but they're not making 10,000 of them every day, which is the world we live in now.

And so about four years ago, as you mentioned, we started Get Real to help deal with this. And what Get Real does is it works with media outlets, it works with law enforcement, with national security, and more and more with enterprise. It's working with Fortune 500 companies so that they know when they're interviewing somebody on a on a call like this that it's not a North Korean imposter IT worker. They know that when they're talking to their CEO and they tell them to transfer $25,000,000, that really is their CEO. They know when a video of their CEO is leaked with them kicking puppies down the road, it's real it's fake, not real.

And so how they are contending with all of this. And we're also starting to work with the large social media platforms that are really struggling under the weight of this. For the first time, was I mean, they've always had a problem, but this seems to be the first time where they're like, Oh man, this is really bad. And I think it's because the volume and the sophistication of the fates is nothing we've seen before. So in my day job, I'm still working on the child abuse stuff.

I still I still talk to the folks over at the National Centre for Missing and Exploited Children, the Canadian Centre for Child Protection, law enforcement, courts still dealing with these issues, but more and more is dealing with this question of how do we know what we are seeing is real or not? And that went from a monthly to a weekly to a daily to an hourly question.

And also from a theoretical one to a real one, right? Like when we were starting to report about Deepfakes, obviously, the problem always has been and remains non consensual images of women mostly. That's the majority of the abuse that happens, but people were speculating, oh, well, what if somebody makes a fake video of our CEO saying something to manipulate stock or transfer money? And to be clear, that is happening, right? It's like we're in it now.

It is a thing that is happening. 100%. And two things. One is I would say yesterday, just yesterday, I was talking to the president of a very, very large bank, And this is what's happening to him. People are have gotten his identity, and they are creating fake videos, and it's bad for him.

It's bad for him personally, it's bad for his bank, it's bad for the reputation, because they're perpetrating scams on people's identity. And suddenly, by the way, people are paying attention because it's not some random woman in the world who's being harmed, which was problematic, don't get me wrong. But suddenly, these CEOs are like, oh, this can happen to me. I now care about this problem. And when it starts happening to the senators and the members of congress and the presidents and the cabinet, they will start caring about it too because that's the way the world works.

This just came to mind. I can say this now because the website has been shut down, but Mr. Deepfakes, which was a very prominent nexus of creating non consensual content, one of the things that people shared there were the data sets that you would need to create the identity of someone. And again, 99% of it was female celebrities. But one day I was just looking through like the hundreds of data sets that they had dedicated to different people, and I noticed that like at the very end, after all the female celebrities, it was like CEO of Chase, CEO of this company, CEO and I was like, oh, it's like this is about to happen for real.

Yeah. Yeah. Yeah. Yeah. There's entire, on the dark web and more more and more so on the surface web too, like fraud for hire.

Like, you want a a deepfake of CEO of pick your favorite bank, no problem. Right? Half of Bitcoin and I'm gonna create it for you. I don't think this is the way the world should work, but it is the way the world works, and now people are noticing. And now people wanna do something about Welcome is what I say.

Yeah. So if I'm the CEO of a Fortune 500 company, and I think that this is a threat, which it is Yeah. Then hiring Get Real and hiring all these cybersecurity firms and whatever service I need in order to mitigate that risk is small price to pay to protect myself as best I can against this threat. Again, as we've said, most people are individuals that people are just creating non potential nude images of. Not to put the onus to fix the problem on these individuals, but it's like, for those individuals, like, what do you think they can do?

Or like, what do you think they should do? I hate this question

because I don't have a good answer for you. But let me start by saying this, is you're right. The multi billion dollar fortune 500 company, they'll protect themselves, Right? They'll they'll write a six, seven digit check and they'll protect themselves and, you know, they'll be fine. Right?

They'll mitigate the threat and they'll deal with it. What does the average person do? What does the woman who has a single image of herself online or somebody just took a photo of her walking down the street? And what does she do? And the brutal answer is there's not a lot she can do.

First of all, the perpetrators of a lot of these crimes don't even live within our borders. Right? They're outside The US jurisdiction, right? The state laws that have been passed, they're fine. But unless the victim and the perpetrator are in the same state and you can convince the police and or FBI to go after this person, you got very little going for you.

And here's what I think is the sad reality. When your colleague Sam Cole started writing about this, it was the Taylor Swifts and the Scarlett Johansons who are vulnerable. You needed a lot of content to create these deepfakes. You needed thousands of images. But what has happened in the intervening years is I need a single image of you.

I can take a single image of you. And I have your face, I need ten seconds of your voice, I have your voice. You post the most innocent photo on Instagram, I can take that and I can nudify it. And then I can send it back to you and start trying to extort you or just humiliate you. And the reality is that this is the same trend that we've seen, is that women and vulnerable groups are silenced because when they speak up, they get death threats.

When they speak their opinion, they get death threats. And now when they post a photo of themselves, they get extorted. And the reality is that there's not a lot they can do. There's the Take It Down Act, right, which is going into effect soon here in The US that forces the platform to take it down. But here's the problem.

You said it yourself. The onus is on the victims. They have to go hunting for this stuff. I mean, this is a full time job, right? Meanwhile, tech companies are becoming richer.

Mark Zuckerberg is getting richer. Elon Musk is getting richer. Elon Musk isn't just hosting this stuff. His platform is producing it for God's sakes. You guys written about this.

So there's not a lot they can do. I do wanna say one thing positive. There's a great organization out there that I work with. I'm on the board called the Cyber Civil Rights Initiative. And it is an amazing organization that has at least can point you to resources that can help.

So if you have questions, if you've been a victim, CCRI, the Cyber Civil Rights Initiative, is your first stop. There are some other NGOs out there that are popping up that are trying to help to take this content down. But there is no easy answer here. And we can't arrest our way out of this problem. This is going to have to be you have to come down hard like a ton of bricks on the Mark Zuckerbergs and the Elon Musk.

You have to start finding them hundreds of billions of dollars, not millions, billions. You have to send a message to them. You keep screwing around like this, and we're gonna sue you back to the dark ages. Right? There's gonna be nothing left.

And watch how fast they get smart and they solve this problem. Until you make it hurt, they will not fix this problem. And when you do, they will. I know this for certain.

It's not a solution, but something that I have been thinking about lately is we've written a lot of pretty upsetting stories about some of these Notify ads rippling through specific schools or like small towns. And those stories are difficult because you see how the school or the police are not prepared to deal with the problem, but I guess there's some positivity in there because what you also see is parents coming together and being like, this is unacceptable and we have to do something. And I think that as a result, counter intuitively of the technology being normalized, where it's like, people know what is happening, they agree that it's bad, and they know how to talk about it, and at least ask for somebody to do something, as opposed to where we were in 2017, where it's just like this thing fell out of the sky and if this happened, you don't even want to talk about it because you don't want to draw attention to it.

I think that's right. So let's talk about what's happening. I mean, I'm sure everybody's seen the stories. You guys have written about it and I agree they are. They're hard stories.

I have a hard time getting through them. I live them on a regular basis. I've worked these cases. So what's happening is these young kids, 12, 13, 14 and younger, are being advertised on social media, by the way, for nudify apps. So here's your first sin, right?

Well, I guess it's the second sin. The first sin is the people creating the technology. The second sin is that the metas of the world are profiting from people advertising this, targeting 12, 13, 14 year old boys who are then going to Instagram taking photos of their school mates, young girls, and pushing them through Nudify and then sharing them either privately or publicly. And I gotta say everybody's a victim here. The girls 100%, At the very top of the list, right?

They are being victimized. I think the boys are victims, a different type of victim. I don't you can't look at a 12 year old boy whose frontal cortex is still a decade and a half away from being fully developed and say, should go to jail for this. I think they're a different type of victim. I think they've done something wrong and there should be consequences, but there's no winners and losers here.

Everybody's a loser here. Every parent on both sides are losers. The school is a loser. The community is a loser. And meanwhile, the Apples and the Googles, these apps are being hosted on the goddamn Apple Store.

Come on, what are we doing here? They're being advertised to these kids. And they are gut wrenching. And I agree with you that I've worked a case on this recently in small community and it just tore the community apart. I mean, was brutal to watch.

Forget about, you know, what happened to the young girls and what happened to the young, like it just tore through this community. And if there's any sort of bright spot on this, I think you're right that people are shutting a band together and saying this is unacceptable. Like what are we doing here? And I think it's gonna get worse before it gets better. But I do take some comfort in that people, unlike seven, eight years ago when we first started talking about it, like, well, it's the internet, what are you going to do about it?

Which has sort of been what we've been doing for a good twenty years. Like, no, no, no, we're going to do something about this. And now we got to figure out. But here's what I would say is, you got to go upstream. You got to go after Apple and Google.

They're hosting these apps. You gotta go after the cloud flares, the infrastructure that is enabling these apps to exist. Visa, Mastercard, if they're being used to pay. Like, there's a whole ecosystem that powers these apps. They don't live in isolation.

Go after the ecosystem, man. Like, forget about the bad guy creating the app. There's nothing you can do about that person. They're gonna pop up. They're like the street level dealers.

You gotta go after the kingpins. Right? That's who you go after, and you bash them over the head until they get their act together.

Shifting to not just non consensual news, but AI generated images generally. Now that they're so common and they're all over social media, are you getting a sense that the public's ability to differentiate between real and fake is getting better? Is it getting worse? Is it changing? Like, do you think culturally, in terms of like media literacy, we're adapting to it

at all? I don't know about the trajectory, but let me tell you what I do know. So in my lab, our bread and butter is developing mathematical and computational techniques to detect manipulated media. That's sort of what we do. But along the way, what we also do is we run perceptual studies.

We run studies where we bring people either physically into the lab or we recruit them online. We have them look at images, listen to audio, watch videos. We tell them what the task is. Half will be real, half will be fake. We give them training, we explain what they're going to do, and then we set them off.

Basically, they're slightly better than chance, flipping a coin. They're really bad at it. And this is where we've set you up for success. You're in a lab environment. We've told you what to do, right?

But the content is not emotional. It's not trying to manipulate you. It's not trying to outrage you. It's not political. It's as benign as can be.

And they're basically a chance. So do I think people are good at this? No. Do I think they're gonna get good at it? No.

Because it's not what social media social media is not setting you up for success. Social media is setting you up to doom scroll for as long as you can. So Mark Zuckerberg and Elon Musk can sell you more ads so they can become the next level of trillionaire. That's what it's designed for. And it's not designed for thoughtfulness or for insight or for care or anything else.

That's it. That's the whole business model.

So you're obviously good at it. I think I am pretty good at it. The other day, I wrote about this recently, but I was looking at Twitter and it was a picture of a celebrity and it wasn't any it wasn't full nudity and it wasn't anything like very lewd, but I was like, this seems a little weird, and then I figured out that it was like a slightly manipulated image, right? It was like a red carpet image of a celebrity, but it's like, this is not actually it, but it's like, they made the dress a little shorter, they made the cleavage a little bit more revealing, but it's like very, very subtle. And I was like, oh, that almost got me.

And then I thought, well, well, I don't know if I've been had before. And I'm wondering like, how do you think about that problem? Like, you don't know what you don't know.

Yeah. Somebody asked me the other day, has anybody ever created a deepfake that you couldn't detect? And I thought, well, by definition, I cannot answer that question. So here's the difficulty. I do this for a living and I do it every single day.

And I am struggling purely visual. Like, give me my math and my computation and our software and give us some time and let me talk to my team, which includes a former investigative reporter and a threat intel and seven PhDs. We'll figure it out. We will. But it takes a little bit of time and it's a small army of us doing this and we all do this for a living.

Here's what I would say is I don't think that our visual system is reliable enough. And here's the other thing too, and this came out of a recent study that we did. This was actually a collaboration with my wife, who's a computational neuroscientist, Emily Cooper, and two students, Catherine Davide and Sarah Barrington. So we showed people videos and we controlled how long they would see the video, So one second, two seconds, three seconds, etcetera. And what we found is as the videos got longer and longer and longer, people got better at finding the face.

And that sort of makes sense because the longer the video was, you'd eventually see something that was sort of wrong or inconsistent. And so they went from chance at one second to about 75%. Still not great, by the way, 75%. But what also happened is for the real videos, they stayed near chance no matter how long the video was. And the reason for that is that the absence of evidence is not evidence.

And so you have to think about this from both sides of the aisle. When you see something fake and you see something wrong, okay, great. Although it's going to become more and more rare as the tech gets better. But when you don't see anything wrong, what do you say? Do you say it's real?

No, not really. That doesn't really So there's this weird asymmetry. The other thing too, and you just pointed to this, it's right now a lot of the conversation is real fake. AI real. But what's happening is we're getting into this middle ground where it's like, yeah, like this part is real, but then this stuff was, you know, removed or added or shortened or lengthened.

Then it gets even harder because now you're looking for these local manipulations. And that gets harder and harder and harder, of course.

That's what I'm finding now. I think this is the era that we're entering to, which is very scary, but also, I mean, fascinating. I'm sure we'll talk about it in the coming years is the tools are very new, and they're moving very fast. The technology has gone very fast, but it's like the use so far has been pretty clumsy. Right?

It's like you look at these nudes, you look at these, I don't know, videos from Russia about Zelensky or something. It's like they're so heavy Yeah. It's like, now we're at a point where the people using the tools are starting to get more subtle with it, and that is where a lot of the most confounding media is going to come from. Not necessarily from the technology getting all that better, but wielding it in a more subtle way.

I agree. I think two things are happening at the same time. One is the technology is getting better, but you're 100% right, But it's that the adversary is learning how to use these tools. And even the Russian state sponsored actors, I mean, you go back, you know, ten years, it was pretty clumsy, the disinformation campaign. Still worked, but clumsy, but it's getting more and more sophisticated.

They're evolving. Cyber criminals evolve. And that's going to make everybody's job much, much harder as the years go on, no doubt.

You make clear in all the kind of company copy for Get Real, that you're developing these automated tools for detecting images, but also really emphasize the fact that there's always a human involved in the process and that you need a human for this process. And from what you're saying, it seems like that's not going to change. Like we're not going to get into some autopilot solution here. Like you always need a human to to look at it and, I don't know, take contextual clues and so on.

I'd add a friendly amendment to that. Context matters here. So for example, we have technology that will sit in a stream, Zoom calls, Team calls, Webex calls, determine if the person you're talking to is real or not. Fully 100% automatic, no human in the loop. And the reason is that it's a fairly well contained problem.

For the most part, the videos look exactly like what they look like now, right? One person and sitting in front of the camera, they are talking, they have a microphone, they have a camera, they're arm's length away from the camera. And we are really, really good at that. So full blown, what we call in the stream detection, 100% automatic. File based.

So, the New York Times sends me a video of a Tomahawk missile hitting the Iranian school, which is what happened a few months ago. Yeah, you're going to want to put eyeballs on that, right? Part of that is because the technology is not perfect. Part of that is you sometimes need bespoke analyses. And so when the stakes are really high, courts of law, high stakes cases like this, human in the loop.

There's other cases where we have we have a one of the big social media companies, we analyze two, three million images a day, fully automatic. And that's because it's one of many signals that they use. So it sort of depends, right? But I will tell you when we get calls from the big media outlets and the wires, and usually when we do, something serious has happened, human in the loop, right? The tech is great.

So we call it tech assisted services, right? We can't do it without the tech and the tech can't do it without us. And I don't see that changing anytime soon. But on the other sort of aspects, the tech is getting good enough now that it can work at scale, but it's different, right? When you're looking for fraud on large social media platform, you've got 20 signals, right?

One of which is, is this a Deepfake or not? Okay, that can be driven fully automatically. But there are other cases where you have to be more thoughtful and circumspect, and that's where experts come in and help with that analysis.

I guess final thing, just to get fully into speculation here, a reaction that people have to our reporting a lot of the time, which I don't blame people, but it's very pessimistic. They're like, well, if this is where we're at now, we're like fast approaching a world where you can't trust anything you see, you kind of abandon social media altogether, you don't trust any digital image, You just go into like full system failure. Yeah. And you you go analog in some fashion, unless you kind of will are willing to live in this world where, like, reality is is completely manipulated. What do you think it looks like?

What do you think the internet looks like in five years?

Yeah. First of all, I love that turn of a phrase, full system failure. There are days where it feels like that's where we are already. You know, whenever somebody asks me about the future, what I do is I think five years back. And I think, would I have predicted where we are now?

And the answer is no. I mean, I knew it was coming. I just didn't know it was gonna come this fast. I didn't think full blown audio video able to take somebody's identity from a single image in ten seconds. I thought that would come, but I'm shocked at how fast it came, right?

And I do this for a living. So five years from now, I don't know. I think one of a few things is gonna happen. As you said, full system failure, people just give up. And that's very bad, by the way.

Although if everybody just got off of social media, I think the world would be a significantly better place. And so if you wanna make the world a better place, delete your social media. You will be happier too. And I swear to God, your IQ will jump like 30 points. I think that, you know, one of the great things about being an academic in addition to my work over at Get Real is I get to see young kids and you're seeing a backlash.

And you're seeing these young kids being like, we don't want be on social media. Facebook is like, there's no way they're on Facebook. They think it's a joke. Right? And you know, so I saw a kid the other day, this made me so happy.

He had a Polaroid camera. Oh my God. And he's doing this, he's shaking his hand, you know, shaking his hand with the with with the film and developing it. I think there's gonna be a backlash. I I do think that people are exhausted by Silicon Valley and tech.

Social media is awful. The whole AI wave is not making it better, particularly the way it's being handled by most companies. And I think there's going be a backlash. And I think there's going to be a backlash to an analog world. One on one interactions, checking out.

I saw a study the other day, more than half of teenagers think the world would be a better place without the internet. Imagine that, half. That's incredible. I don't think they're wrong, by the way. I mean, lots of conveniences, lots of great things have happened, but lots of really bad things.

And I'm not sure, honestly, on any given day. So I think there's going to be a bit backlash. And the reason is, is that the new generation doesn't do what the old generation does. They don't care. They don't care what millennials and the Gen Z did.

They're going to do their own thing. And I think they're moving away from what they see as super, super toxic and unhealthy. So will there be a course correction? Yeah. How long will it take?

What will the collateral damage be? How will governments respond? How will the companies respond? How will societies respond? I don't know.

But I see glimmers of good news. Australia just recently banned social media for anybody under the age of 16. I think the cutoff should be 30, but fine, I'll live with 16. Some of the European countries are going to do the same thing. I think you're going to start to see significant movements to try to recover and take back our lives from the Silicon Valley trillionaires.

And I think there is going to be some real blowback, and it's long overdue and well deserved. That's the optimistic. The less optimistic is complete system failure, right? Everybody checks out. There's no reality anymore.

Breakdowns of societies and democracies because we can't agree on basic facts. I mean, I don't think that's out of the question, honestly. And because I think some people are making a good living with that scenario in mind. But I want to be optimistic. On the other hand, I've moved from Silicon Valley to 100 acres in Vermont, you know, just in case.

So

I'm gonna go ahead and take that as an optimistic note to end on despite the the nightmare scenario presented as well. Honey, thank you so much for coming on the pod. It's been a pleasure.

Always great to talk to you. Thanks for having me.

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