Speaker 1: Thanks for tuney into tech Stuff. If you don't recognize
Speaker 1: my voice, my name is Osva Looshan, and I'm here
Speaker 1: because the inimitable Jonathan Strickland has passed the baton to
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Speaker 1: the old episodes will remain available in this feed. Welcome
Speaker 1: to tech Stuff. This is the story. Every Wednesday, we
Speaker 1: bring you an in depth interview with someone at the
Speaker 1: forefront of technology or someone who can unknock a world
Speaker 1: where tech is that it's most fascinating. This week it's
Speaker 1: Harney for Reid. He's a professor of electrical engineering and
Speaker 1: computer science at the University of California, Berkeley, with a
Speaker 1: CSI sounding specialization digital forensics. His focus is on image
Speaker 1: analysis and human perception, so he's the guy you call
Speaker 1: when you need to know whether or not you're confronting
Speaker 1: at deep fake, and many do. He's constantly talking to
Speaker 1: journalists to help them determine what's real and what's fake online.
Speaker 1: In his lab at UC Berkeley, he and his students
Speaker 1: study the various ways misinformation is created and spread and
Speaker 1: how it erodes trust. In our institutions.
Speaker 2: And one more thing.
Speaker 1: For Reid is the founder and chief science officer of
Speaker 1: get Real Labs, where he consults with businesses, news organizations,
Speaker 1: and law enforcement to authenticate digital content. You might be
Speaker 1: wondering how far Reed got into this field. If so,
Speaker 1: you're not alone.
Speaker 2: Somebody said to me the other day, Oh, you were
Speaker 2: so prescient. I'm like, no, we weren't. We were just
Speaker 2: screwing around.
Speaker 1: Farred first started pondering the implications of digital images back
Speaker 1: in nineteen ninety seven.
Speaker 2: This is really pre digital Almost film was still the
Speaker 2: dominant source of media that we took photographs on the
Speaker 2: Internet was nothing right. There was no social media, and
Speaker 2: everything was very nascent. You could see the trends, you
Speaker 2: knew things. Something was bubbling up with the Internet and
Speaker 2: with digital technolog Freed was a postdoc at the time.
Speaker 2: I was at the library getting a book, which now
Speaker 2: just seems quaint, and I was waiting in line, and
Speaker 2: there was a return card, and on the return cart
Speaker 2: was a big book called the Federal Rules of Evidence.
Speaker 2: I'm not a legal scholar, I'm not a lawyer, but
Speaker 2: I was bored and I flipped it open to a
Speaker 2: random page and it was titled introducing Photographs into Evidence
Speaker 2: in a Court of Law. And I liked taking photographs.
Speaker 2: I was working with digital images, but nothing to do
Speaker 2: with this topic, and I thought, I wonder what the
Speaker 2: rules are, and so I read it and there was
Speaker 2: almost a footnote that said, there's this digital format and
Speaker 2: we're going to treat digital the same way we treat analog.
Speaker 2: And I just remember thinking, I don't know anything, but
Speaker 2: that seems like a bad idea.
Speaker 1: This passage really stuck with him, and for years he
Speaker 1: couldn't stop thinking about the implications of a digital world,
Speaker 1: the fact that digital manipulation would change our perception of
Speaker 1: what's real because the photographic medium had fundamentally shifted. What
Speaker 1: surprised him was that few others were taking note.
Speaker 2: It's really unusual in an academic life where you start
Speaker 2: thinking about a problem and you go into the academic
Speaker 2: literature and there is nothing. It was just crickets, because
Speaker 2: there was no reason to be thinking about the problem.
Speaker 1: Two years later, as a professor of computer science at Dartmouth,
Speaker 1: he was playing around in photoshop creating a comic image
Speaker 1: of his friend when he had an epiphany.
Speaker 2: Mathematically, I just did something very interesting. I introduced pixels
Speaker 2: that have been synthesized by photoshop to make the image bigger, right,
Speaker 2: because they didn't exist, and I remember thinking, oh, I
Speaker 2: should be able to detect that.
Speaker 1: In that moment, he started writing code and actually developed
Speaker 1: programs to detect digital manipulation. The world woke up to
Speaker 1: the importance of this work, and he started getting asked
Speaker 1: to chime in on serious cases for the Associated Press,
Speaker 1: for law enforcement, for national security.
Speaker 2: And then twenty fifteen, sixteen seventeen AI hit and the
Speaker 2: world exploded. But it exploded for a few reasons because one,
Speaker 2: at least with Photoshop, there was a barrier to entry.
Speaker 2: You had to actually know how to use photoshop. But
Speaker 2: then when AI came around, you just go to chat
Speaker 2: cheepetiting type, give me an image of X, right, and
Speaker 2: give me an image of Y, give me a video
Speaker 2: of this, give me an audio of this. And so
Speaker 2: suddenly there's no barrier to entry. But more importantly, social
Speaker 2: media dominates the landscape. We went from a few million
Speaker 2: users to a few billion users, and so now not
Speaker 2: only could people easily with no barrier to entry, create
Speaker 2: fake content, they could distribute it to the masses and
Speaker 2: it gets amplified because the algorithms amplify the most outrageous things.
Speaker 2: People want things that conform to the worldview. We are hyperpartisan,
Speaker 2: both here and abroad, and that was the perfect storm create, distribute, amplify,
Speaker 2: rinse and repeat. And so now through the AI revolution,
Speaker 2: it's bizarre what's happening.
Speaker 1: We'll dive into the world Careed does on deep fakes
Speaker 1: in a bit, but first I had to ask you
Speaker 1: about something seemingly completely unrelated, death bods. So you were
Speaker 1: quoted in this Atlantic article about death bods with the
Speaker 1: headline no one is ready for digital immortality, So nie it.
Speaker 1: It'll be good to define on terms like what do
Speaker 1: we mean by this idea of digital immortality?
Speaker 2: Yeah, I don't know that it's a well established term.
Speaker 2: But here's my definition. Is that your likeness, the way
Speaker 2: you think, the way you talk, the way you look,
Speaker 2: lives on an eternity in a digital form through a
Speaker 2: version of AI that embodies how I write, how I think,
Speaker 2: how I talk in order to interact with other people.
Speaker 2: It's interactive, that's the key, but it's dynamic.
Speaker 1: What got you interested in this topic and why did
Speaker 1: you agree to be a source in the story.
Speaker 2: So this is almost a philosophical and legal question, and
Speaker 2: I'm neither of those things. But I got to say
Speaker 2: I've been thinking a lot about it, technically, personally, philosophically.
Speaker 2: Here's why I've been thinking about it. So one is,
Speaker 2: I'm a professor. I've been a professor for twenty five years.
Speaker 2: I love teaching. I love my students. I hate them
Speaker 2: some days, but I usually love them. They're amazing and
Speaker 2: weird and wonderful in many ways. So is there a
Speaker 2: story here where I can keep teaching after I die?
Speaker 2: Like there's something sort of magical about that. I think
Speaker 2: about it for my parents. Both my parents are now
Speaker 2: in their late eighties. One of them will die first,
Speaker 2: almost certainly, And what does it mean for the one
Speaker 2: who They've been together for fifty years? So there's parts
Speaker 2: of it. I think this is wonderful, this idea that
Speaker 2: one of my parents can wake up and open up
Speaker 2: their iPad and have a conversation with the person that
Speaker 2: they spent fifty years of their lives with. On the
Speaker 2: other hand, if that happens early in life, is that
Speaker 2: healthy for somebody? If a thirty year old loses their spouse,
Speaker 2: is that good? That they never sort of physically move on.
Speaker 2: I also think about it from a technical perspective, what
Speaker 2: would that look like for somebody who's famous where there's
Speaker 2: a big digital footprint. I think we have all the
Speaker 2: pieces to do that. We have the large language models,
Speaker 2: we have voice, we have likeness, we have video, and
Speaker 2: you're already seeing people do this creating digital avatars of
Speaker 2: both people who are with us and not with us,
Speaker 2: so that you can interact with them. I can go
Speaker 2: scrape every single piece of writing that Martin Luther King
Speaker 2: Junior wrote. I can grab his speeches, I can grab
Speaker 2: his likeness, I can grab his voice, and I could
Speaker 2: create an avatar of him that I could interact with.
Speaker 1: Well, it reminds me of your work on deep fis
Speaker 1: in some sense, because, as you said, exactly, all the
Speaker 1: pieces are there technically and otherwise. Yeah, but society's clearly
Speaker 1: not ready.
Speaker 2: I don't think we're ready. But look a lot of things,
Speaker 2: if you look at the last two, three, four or
Speaker 2: five decades from technology we weren't ready for and we
Speaker 2: became ready for it.
Speaker 1: Right.
Speaker 2: Look, you can go back to in vitual fertilization. When
Speaker 2: it first started, people were freaked out by that completely
Speaker 2: normal now, right, And by the way, this could also
Speaker 2: be generational. I can imagine some of my students here
Speaker 2: at UC Berkeley think sure, who cares, right, And I'm
Speaker 2: an older guy and I'm like, ah, that seems a
Speaker 2: little weird. So this may just go away generationally, which
Speaker 2: is usually how this happens.
Speaker 1: By the way, do you think we'll see a fundamental
Speaker 1: shift in our society in this case in terms of
Speaker 1: how we think about death.
Speaker 2: I think this idea of a digital immortality is really profound.
Speaker 2: And look, I don't know where this AI revolution is
Speaker 2: going right now. I don't think anybody really does. But
Speaker 2: something is happening. There is something here that is quite dramatic.
Speaker 2: I think it's going to reshape society. I think it's
Speaker 2: going to reshape education. I think it's going to reshape
Speaker 2: the workforce. I think it's going to reshape a lot
Speaker 2: of things. And I do think your likeness or your
Speaker 2: being or your essence or whatever you want to call
Speaker 2: that can live on and you can interact with people.
Speaker 2: You can continue to have a podcast after you die,
Speaker 2: you can keep interviewing people.
Speaker 1: When we come back. How deep fakes impact everyone even
Speaker 1: if you don't know it. There's an interesting point of
Speaker 1: intersection between so death bots and your more core field
Speaker 1: of study, and that's this Indian politician who a parliamentary candidate,
Speaker 1: who created a video of his deceased father endorsing him
Speaker 1: as his rightful heir.
Speaker 2: Yeah.
Speaker 1: I mean this is kind of a world's collide moment
Speaker 1: between misinformation, deep fakes, and digital immortality.
Speaker 2: Yeah. Yeah, So for people who didn't see it, India
Speaker 2: had an election this year, big one and you know,
Speaker 2: billion plus people voting. It was chaotic, and a politician
Speaker 2: did exactly this. His father was a well known politician,
Speaker 2: and he created a digital recreation with his voice and
Speaker 2: his likeness and he was talking and endorsing his son.
Speaker 2: So I have a couple of thoughts on that right now,
Speaker 2: in this particular moment, as we're still grappling, I think
Speaker 2: there should be two rules, which are consent and disclosure.
Speaker 2: And it's really simple, like, if you're going to use
Speaker 2: somebody's likeness, you should have consent, and if you're going
Speaker 2: to distribute it, you should have disclosure. Now, consent is
Speaker 2: difficult when somebody is dead. But if I want to
Speaker 2: get an endorsement from somebody, who's living. I have to
Speaker 2: get their consent yep. And if I distribute that, it
Speaker 2: has to be very clearly labeled and disclosed as this
Speaker 2: is AI generated. I'll give you a really nice example
Speaker 2: of this where it was sort of cool. I was
Speaker 2: during the Olympics. One of the newscasters, well known and
Speaker 2: I'm just blinking out his name right now, was creating
Speaker 2: AI generated personalized summaries. So my wife was watching the
Speaker 2: Olympics and she would get these personalized summaries from the broadcaster.
Speaker 2: So the content was personalized to her based on what
Speaker 2: she was watching. And then the voice being generated was his,
Speaker 2: and the script was being AI generated. Everything was with
Speaker 2: his permission, and it was disclosed to her that it
Speaker 2: was AI generated and summarized. And I think that was
Speaker 2: really well done in terms of the things that were
Speaker 2: made clear of what you were getting and how it
Speaker 2: was being delivered to you.
Speaker 1: That's sort of a high watermark for how this stuff works.
Speaker 1: When it works well. Yeah, Do you think as a
Speaker 1: society we're more likely to move toward that high water
Speaker 1: mark through collective demand or through regulation or through some
Speaker 1: decision from the tech overlords like what gets us there?
Speaker 2: More broadly, yeah. I mean, there's nothing in the last
Speaker 2: twenty years or twenty five years that gives me confident
Speaker 2: that our tech overlords are going to do the right thing.
Speaker 2: They're going to do the thing that maximizes their profits.
Speaker 2: And we know this. Let's stop pretending otherwise that Silicon
Speaker 2: Value is anything other than it is. It's a modern
Speaker 2: day Wall Street in some ways, by the way, even
Speaker 2: more powerful, right, because they control information, not just money,
Speaker 2: and that arguably is much more powerful. I don't think
Speaker 2: this comes from consumers, because we're not customers, we're the product.
Speaker 2: We as users, I should say, have almost no power
Speaker 2: at all. And so the media we tried, right, we
Speaker 2: tried criticizing and embarrassing, and we tried dragging them in
Speaker 2: front of Congress. Nothing effects change. So what does good regulation?
Speaker 2: We got to put guardrails on this and look, there's
Speaker 2: nothing there is nothing in our physical world that it
Speaker 2: is not subject to regulation to make products safe and reasonable.
Speaker 2: But somehow we've abandoned that for the last twenty five
Speaker 2: years because it's the Internet. So I do think it's
Speaker 2: going to have to come I don't think it's going
Speaker 2: to come from the US. It is coming from the UK.
Speaker 2: It is coming from the EU, it is coming from Australia,
Speaker 2: and I think those are going to be the leaders
Speaker 2: in this space. And you saw this with GDPR with
Speaker 2: the privacy rules in many ways that I don't think
Speaker 2: it solved the privacy problem around the world, but it
Speaker 2: moved the needle on the problem. And the EU and
Speaker 2: the UK have moved very aggressively on AI safety, on
Speaker 2: digital safety, and on misuse of monopolies, and I think
Speaker 2: it's going to have to come at that level.
Speaker 1: I want to talk about some of the more personal
Speaker 1: ways in which we can experience deep fakes. I think
Speaker 1: a lot of people think maybe it only touches politicians
Speaker 1: or celebrities. But there was an NPR story about a
Speaker 1: case you worked someone that involved a Baltimore teacher. Can
Speaker 1: you talk about what happened there?
Speaker 2: This case is I'm fascinated by, and I still don't
Speaker 2: think we've gotten to the end of it. Tell you,
Speaker 2: first of all, your listeners, what the case is. Baltimore
Speaker 2: Public School audio of the principle saying things that were
Speaker 2: racist was leaked, and it was leaked to some news outlet,
Speaker 2: and it was bad and it was if you listen
Speaker 2: to it it's pretty bad, and the principal said, this
Speaker 2: isn't me, this is AI generated, And we analyze the audio.
Speaker 2: Several labs analyze the audio. There is alteration to the audio.
Speaker 2: That is, we can hear and see that it's been
Speaker 2: spliced together five or six segments, but when we analyze
Speaker 2: the individual segments, it is not one hundred percent clear
Speaker 2: to us that it is AI generated. It could be
Speaker 2: that he said these things, but they were sort of
Speaker 2: stitched together in a way that put them out of context,
Speaker 2: which would be deceptive. It could be that it's AI
Speaker 2: generated and our tools simply didn't detect it. It could
Speaker 2: be that this is a case of the liar's dividend,
Speaker 2: where the principle really did say this, but he's claiming
Speaker 2: he didn't say it.
Speaker 1: Honey, can you explain exactly what the liar's dividend is?
Speaker 2: The liar's divining go something like this. It says, when
Speaker 2: you live in a world or anything can be manipulated.
Speaker 2: Any image can be fake, any audio can be fake,
Speaker 2: any video can be fake. Nothing has to be real.
Speaker 2: I get to use the fact that fake things exist
Speaker 2: as an excuse for what I've done. But this case
Speaker 2: is a really good example of how dangerous this technology
Speaker 2: is for two reasons. One is, with twenty to thirty
Speaker 2: seconds of your voice, I don't need hours. I can
Speaker 2: clone your voice. I can upload it to an AI
Speaker 2: tool that I use and that I can type and
Speaker 2: have you say anything I want. That means anybody with
Speaker 2: twenty seconds of their voice available has a vulnerability. So
Speaker 2: this is not for movie stars and podcasters. This is everybody.
Speaker 2: Number one. Number two is anybody who's caught saying or
Speaker 2: doing something that they don't want to take ownership of
Speaker 2: can say it's fake. Yep, the dog ate my homework,
Speaker 2: all right, this is easy. And so both of those
Speaker 2: are problematic because where's our shared sense of reality. It
Speaker 2: used to be when you had images and video, despite
Speaker 2: the fact that there was photoshop, despite the fact that
Speaker 2: Hollywood could could manipulate videos, we had a pretty reasonable
Speaker 2: confidence in what we read and saw and heard. And
Speaker 2: you can't say that anymore. This is why I spent
Speaker 2: so much time talking to journalists and fact checkers and
Speaker 2: lawyers and law enforcement. So on this particular case, it
Speaker 2: really showed how this has trickled all the way down
Speaker 2: to high school teachers.
Speaker 1: Zooming out from the individuals to the collective. One of
Speaker 1: the interesting things that happens is whenever there's like a
Speaker 1: world event that everyone's paying attention to, you get this
Speaker 1: fire hose of fake images. I remember in the early
Speaker 1: days of the conflict in Gaza, there was this aerial
Speaker 1: image with what was supposed to be Palestinian tents making
Speaker 1: the word help us or you know. Right out to
Speaker 1: the La fires began, there were these images of the
Speaker 1: Hollywood Sign on fire. I don't know how many people
Speaker 1: believe these images were actually true or in some ways,
Speaker 1: what the harm is if they did. But what's going
Speaker 1: on here?
Speaker 2: So let's start with the La fires. First of all,
Speaker 2: many images coming out of those fires were fake. What's
Speaker 2: the harm, Well, this one's easy. If people believe there's
Speaker 2: fire in this neighborhood, that is very bad. Fire departments
Speaker 2: are going to get distracted. First responders are going to
Speaker 2: get distracted. People are scared that their neighborhood is on fire.
Speaker 2: They're going to get distracted. So I do think there
Speaker 2: is real harm I think in the Gosspt images. Also,
Speaker 2: this is a complicated conflict, and we are all trying
Speaker 2: to get our heads around this thing and figure it out,
Speaker 2: and meanwhile people are fanning the flames, trying to push
Speaker 2: a particular narrative on either side, and I don't think
Speaker 2: that's healthy. Look, we can have serious discussions about how
Speaker 2: to combat climate change, we can have serious discussions about
Speaker 2: how to resolve the Israeli Palestinian conflict. We can have
Speaker 2: serious discussions about a lot of things, but we've got
Speaker 2: to start with a set of facts. And when you
Speaker 2: pollute the higher information ecosystem, we are at a loss.
Speaker 2: You could say, okay, well somebody believe the fake image
Speaker 2: of the tense. Okay, who cares? But here's why you care,
Speaker 2: Because then when the real images come out showing human
Speaker 2: rights violations, showing people being killed, people being bombed, how
Speaker 2: do I believe it? When you pollute the information ecosystem,
Speaker 2: everything is in doubt. And suddenly you have people who
Speaker 2: are denying that anybody's died, You have people denying that
Speaker 2: the fires exist, you have people denying that people are
Speaker 2: dying from COVID. Because this is how untrusting we have become,
Speaker 2: and that I have a real problem with, because look,
Speaker 2: no matter what side of the political or ideological aisle
Speaker 2: you are on, can we at least agree that if
Speaker 2: we don't have a shared factual system, a shared sense
Speaker 2: of reality, we do not have a society or democracy.
Speaker 2: We can't be arguing about whether one plus one is two.
Speaker 2: And I would argue that this problem started well before
Speaker 2: deep fakes. Social media is the one that is amplifying
Speaker 2: and encouraging this type of behavior because it engages users,
Speaker 2: drives ad drives attention, drives profits. The problem is not
Speaker 2: just the creation side, it's the distribution side, and that,
Speaker 2: I would argue, is the bigger problem here than the
Speaker 2: deep fake.
Speaker 1: Coming up. Harney for Reid on what it takes to
Speaker 1: identify a deep fake stay with us. When we first spoke,
Speaker 1: it was just five years ago in twenty nineteen. The
Speaker 1: big question at the time was is there going to
Speaker 1: be a causal piece of fake media that measurably sways
Speaker 1: the outcome of an election? And some people say the
Speaker 1: answer to that is no. I mean the New yorkd
Speaker 1: apiece in twenty twenty three saying basically, you know that
Speaker 1: the deep fakes haven't had that characterismic effect that some
Speaker 1: people thought they would. The Atlantic run a story recently
Speaker 1: under the headline AI's fingerprints were all over the election,
Speaker 1: but deep fakes and information weren't the main issue, and
Speaker 1: the kind of the point about both pieces was that
Speaker 1: what deep fakes are really being used for is to
Speaker 1: create memes and satire rather than to directly trick people.
Speaker 1: And the second point was quote to growing numbers of people,
Speaker 1: everything is fake now except what they know or other feel.
Speaker 2: Yeah.
Speaker 1: So has this been less explosively destructive than people thought
Speaker 1: it would be? Or are the New York and the
Speaker 1: Atlantic slightly missing the point in your view?
Speaker 2: I agree and disagree with them. I agree that there
Speaker 2: was no single atomic bomb that got dropped, and that
Speaker 2: you can draw a line from me to be saying
Speaker 2: this change in election, But nobody thought that was going
Speaker 2: to be the case. So I think that's a little
Speaker 2: bit of a straw man argument.
Speaker 1: Right.
Speaker 2: Okay, here's the other reason I disagree. Go talk to
Speaker 2: the people in Slovakia, because what they will tell you
Speaker 2: is that forty hours before election, there were two candidates,
Speaker 2: a Pronato and a pro Putin candidate, and the pro
Speaker 2: NATO candidate was up four points. A deep fake of
Speaker 2: the Pro NATO candidate was released saying We're going to
Speaker 2: rig the election, and two days later the pro Plutin
Speaker 2: candidate won by four points. There was an eight point
Speaker 2: swing in the polls in forty eight hours. Now were
Speaker 2: the polls wrong? Possibly? Did it have anything to do
Speaker 2: with the deep fake? Don't know, but this could have
Speaker 2: been the first example, just a couple of years ago,
Speaker 2: of where a deep fake was a tipping point. So
Speaker 2: I'm not sure i'd buy that story. I think this
Speaker 2: is more about death by a thousand cuts than by
Speaker 2: dropping an atomic bomb. I think that when you keep
Speaker 2: polluting the information ecosystem, everybody loses trust because you don't
Speaker 2: trust NPR, you don't trust in your times, you don't
Speaker 2: trust an end Who do you trust? Well, you trust
Speaker 2: the guy who's yelling at you telling you what to believe, right,
Speaker 2: because you've sort of given up. Yeah, And I would
Speaker 2: say that, you know it's fundamentally Is that a deep
Speaker 2: fake problem? No, I think that's a social media problem.
Speaker 2: I think that's traditional media problem. I think that's a
Speaker 2: polarization problem. I think it's the nature of politics today,
Speaker 2: both here and abroad, because we have politicians who are
Speaker 2: just outright lying to us now. So I do think
Speaker 2: that can you point specifically to deep fakes? No, but
Speaker 2: I do think it was an accelerant. I do think
Speaker 2: it contributed to our general distrust and then our inability
Speaker 2: to hear things that go against our worldview, and I
Speaker 2: do think that that affected change. I do think you
Speaker 2: can't look at the landscape of what Facebook and Twitter
Speaker 2: and YouTube and TikTok, how they control the information ecosystem
Speaker 2: for the vast majority of Americans, how they have promoted
Speaker 2: false information, both traditionally false and deep fake falls. You
Speaker 2: can't look at that and say that has had no
Speaker 2: impact on the way we think. I think that's probably wrong.
Speaker 1: So you mentioned you've been at this for some time
Speaker 1: since opening that legal textbook all those years ago. Could
Speaker 1: you have imagined how much trust in society has raided?
Speaker 1: And where did you see it kind of happening all
Speaker 1: the way? So the answer is no, I didn't see
Speaker 1: this coming. And in the early days the liar's diving,
Speaker 1: it didn't exist. When there was when there was film
Speaker 1: in audio of you saying and doing something, nobody said
Speaker 1: it was fake. And by the way, here's how you
Speaker 1: know I'm right. Go back to twenty sixteen. Then the
Speaker 1: first candidate Trump got caught on the Access Hollywood tape
Speaker 1: saying what that he grabs women in places that I
Speaker 1: won't mention on this podcast. And when he got called
Speaker 1: on it, he didn't say it was fake. He apologized
Speaker 1: three months later, when he was now in office, he
Speaker 1: said it was fake. That was the moment when I
Speaker 1: realized this was a real thing. So it was actually
Speaker 1: fairly recently, because up until then the tech wasn't good enough,
Speaker 1: and frankly, nobody had thought about it. But once Trump
Speaker 1: normalized that you don't like information, call it fake news,
Speaker 1: suddenly this became the mantra. AI was still pretty nascent,
Speaker 1: but now it's actually a plausible deniability. Now it's actually
Speaker 1: not an unreasonable thing. And if you go back and
Speaker 1: look at that Access Hollywood tape, you never see him talking.
Speaker 2: It's just audio. And so if that was released today, yeah,
Speaker 2: you we'd have to think pretty carefully whether it was
Speaker 2: real or not.
Speaker 1: Your vacation in some ways to talk about this and
Speaker 1: bring attention to it in the media. But your business
Speaker 1: is also to bring some technological solutions to the detection problem.
Speaker 2: Is that right? Yeah? Yeah, So I will tell you
Speaker 2: I say this only half jokingly. I started the company
Speaker 2: just because I couldn't keep up with the demand. I
Speaker 2: just needed people to help me do this.
Speaker 1: Because the best way to start a company, I think.
Speaker 2: Yeah, I'm like guys, I used to get one call
Speaker 2: a week, and there was one a day, and now
Speaker 2: it's time to day and pretty soon it's gonna be
Speaker 2: one Hundreday I can't. I honestly can't keep up. But
Speaker 2: more less snarky, if you will, Like you know, we
Speaker 2: really need to get a handle on this problem. And
Speaker 2: I think there's a couple of places we want to
Speaker 2: help organizations get a handle on it. So clearly, media outlets,
Speaker 2: clearly you have to help the big news wires and
Speaker 2: the major news agencies when they are dealing with breaking
Speaker 2: news of La fires and Gaza and Inaugurate and whatever.
Speaker 2: They've got to know what the hell's going on. We
Speaker 2: have to help them. We clearly have to help law
Speaker 2: enforcement at national security agencies reason about a very complicated world,
Speaker 2: from evidence in a court of law to things with
Speaker 2: geopolitical implications. We have to help organizations. We are seeing
Speaker 2: massive frauds being perpetrayed on Fortune five hundred companies. We
Speaker 2: are seeing imposter hiring. We are seeing people attack companies
Speaker 2: with fake audio and video of CEOs, to damage their
Speaker 2: stock price. We want to help individuals right deal with
Speaker 2: the stuff when they are getting information, how do they trust?
Speaker 2: And so we are developing a suite of tools that
Speaker 2: would authenticate content, images, audio, and video to help people
Speaker 2: make decisions. And it's not a value judgment. We're not
Speaker 2: saying this is good or bad or ineter. In fact,
Speaker 2: now we're even saying if it's true or false. We
Speaker 2: are simply saying is this an authentic photo, image or
Speaker 2: video or is it not. It's a pretty simple question
Speaker 2: with a very very complicated and difficult answer. And by
Speaker 2: the way, if that's not an if, it's a when,
Speaker 2: it's a when that happens that you have to start
Speaker 2: thinking about this because it will happen, right, because anybody
Speaker 2: can create these fakes. Now there's somebody doesn't like their
Speaker 2: seat on an airline, they're going to go off and
Speaker 2: attack your company by creating a fake image or a
Speaker 2: video or an audio and they're going to try to
Speaker 2: hurt you. And it's frankly not that hard to do.
Speaker 1: And the protote elements of what you're working on, what
Speaker 1: is the technology that enables it.
Speaker 2: Yeah, I'm going to tell you a little bit about it,
Speaker 2: but not all of it, because you know, in the
Speaker 2: cybersecurity world you have to be a little careful. But
Speaker 2: underneath it is I've been doing this for twenty five years.
Speaker 2: We have developed a suite of different technologies that look
Speaker 2: at content from many different perspectives. We think about the
Speaker 2: entire content creation process. So let's take an image for
Speaker 2: an example. What happens with an image. You start out
Speaker 2: here in the physical three dimensional world. Light moves and
Speaker 2: hits the front of a lens. It passes through an
Speaker 2: optical train, It hits an electronic sensor where it gets
Speaker 2: converted from light photons analog to digital. It goes to
Speaker 2: a series of post processing steps. It gets compressed into
Speaker 2: a file, It gets uploaded to social media, it gets
Speaker 2: downloaded onto my desk, and then my job begins. And
Speaker 2: what we do is we insert ourselves into every part
Speaker 2: of that process, the physical world, the optics, the electronic sensor,
Speaker 2: the post processing, the packaging, and we build mathematical models
Speaker 2: that we can say this is physically plausible, this is
Speaker 2: physically implausible, this is consistent with a natural image, this
Speaker 2: is consistent with an AI generated image. And we have
Speaker 2: this suite of tools and then collectively, those come together
Speaker 2: to tell a story about our belief that that piece
Speaker 2: of content is authentic or not.
Speaker 1: What degree of conviction do you have on any given
Speaker 1: piece of content that you can verify with on it
Speaker 1: is real?
Speaker 2: First of all, great question, and I don't think it's
Speaker 2: going to surprise you that the answer is complicated. I mean,
Speaker 2: I'd like to be able to tell you ninety nine
Speaker 2: point seven percent. And by the way, anybody who tells
Speaker 2: you ninety nine point seven doesn't know what they're talking about.
Speaker 2: And here's why it depends. So for example, if you
Speaker 2: give me a high resolution twelve megapixel image, to its
Speaker 2: high quality, we can say a lot. If you give
Speaker 2: me an image that's three hundred by three hundred pixel
Speaker 2: and has gone through five levels of compression and resizing
Speaker 2: and uploaded and downloaded, it's really really hard. So it
Speaker 2: depends on the content. So there's a number of factors
Speaker 2: that play in, but the obvious ones are this. If
Speaker 2: you have a high quality, high resolution piece of content,
Speaker 2: we're pretty good at this, and that level of confidence
Speaker 2: and ability goes down as the quality the content degreates.
Speaker 2: It's like a physical DNA sample. You find a pile
Speaker 2: of blood. Your DNA sample is good, You find a
Speaker 2: tiny little half a drop of blood not so good. Look,
Speaker 2: anybody who knows anything about the space knows there are
Speaker 2: days where you say I don't know. I would much
Speaker 2: much rather say I don't know than get it wrong.
Speaker 1: So we told you about a regulation solution, you're working
Speaker 1: on a product solution. What about the average person who
Speaker 1: is listening to this podcast. What is the way to
Speaker 1: protect in this changing environment?
Speaker 2: This is easy. I really like this question because the
Speaker 2: answer they answer to everything is hard. This one's easy.
Speaker 2: Get off of social media. Stop getting your news from
Speaker 2: social media. That's it. You're not going to become an
Speaker 2: armchair analyst. You're not going to become a digital forensic expert.
Speaker 2: You're not going to become a misinformation expert. You can't
Speaker 2: do that, you can't do it at scale. But here's
Speaker 2: what you can do. Stop getting your goddamn news from
Speaker 2: social media. Annie, thank you, great talking to you guy.
Speaker 2: I can't believe it's been five years. Okay, let's do
Speaker 2: this again in five years and see and see where
Speaker 2: we are, and maybe it'll be my avatar that'll be
Speaker 2: talking with you.
Speaker 1: Then that's it for this week in Tech the text
Speaker 1: off i'mos Vloshin. This episode was produced by Eliza Dennis,
Speaker 1: Victoria Dominguez, and Lizzie Jacobs. It was executive produced by Me,
Speaker 1: Karen Price, and Kate Osborne for Kaleidis Kote and Katrina
Speaker 1: Novelle for iHeart Podcasts. Jack Insley mixed this episode and
Speaker 1: Kyle Murdoch Rodolphine Song join us on Friday for a
Speaker 1: special crossover episode with the podcasts part Time Genius. We'll
Speaker 1: be talking to Brian Merchant, author of Blood in the Machine,
Speaker 1: about being a ludd eyed. Please rate, review, and reach
Speaker 1: out to us at tech Stuff podcast at gmail dot com.
Speaker 1: We're excited to hear from you.