Speaker 1: Already and this is the Daily This is the Daily OS.
Speaker 1: Oh now it makes sense.
Speaker 2: Good morning and welcome to the Daily OS. It's Sunday,
Speaker 2: the second of March. I'm Billy, I'm Zara.
Speaker 1: We're back in your ears on a Sunday morning again. Again.
Speaker 2: We love surprising you with a new episode on Sundays.
Speaker 1: And Zara, I think today's topic.
Speaker 2: Is very relevant and interesting and super interesting. So we
Speaker 2: are nearly, at any moment now about to enter election
Speaker 2: season in Australia.
Speaker 3: The number of times that we have said that ONCAS
Speaker 3: we're nearly there, We're just there. However, many synonyms can
Speaker 3: say for we are close to an election.
Speaker 1: We are close to an election.
Speaker 2: So there is one that is due to be held
Speaker 2: on the seventeenth of May, or before if Prime Minister
Speaker 2: Anthony Alberanezi decides for us to go to an election earlier,
Speaker 2: and that could mean that we are about to enter
Speaker 2: a period of dis and misinformation in Australia. So today
Speaker 2: we are talking about a very specific type of false
Speaker 2: information and that.
Speaker 1: Is deep fakes.
Speaker 2: More specifically, we want to talk about how deep fakes
Speaker 2: can impact elections, and in this context we're talking about
Speaker 2: deep fakes that are deceptive and harmful. A quick note
Speaker 2: before we start. This podcast is produced with financial support
Speaker 2: from Microsoft. However, the content does remain entirely independent. And
Speaker 2: if you're wondering why Microsoft would be interested in sponsoring
Speaker 2: a podcast on deep fakes.
Speaker 4: In it, I was quite interested.
Speaker 2: Well you, yeah, because you might not know that they
Speaker 2: are very involved in this space and they have teams
Speaker 2: that track the threat of actors who are often the
Speaker 2: ones creating deep fakes.
Speaker 3: Very interesting, now, Billy, you have used the word deep
Speaker 3: fake a record number of times in the introduction of
Speaker 3: a podcast. For anyone who's not familiar with the term, though,
Speaker 3: what are you talking about when you say deep fake?
Speaker 2: So they are digital photos or videos of someone that
Speaker 2: looks very real, but they have actually been created using
Speaker 2: artificial intelligence and they are fake, although often they're not
Speaker 2: entirely fake. So it could be a video where ninety
Speaker 2: percent of that video is real, but then there's ten
Speaker 2: percent that is generated by AI and is fake. But
Speaker 2: it's that ten percent that is really deceptive.
Speaker 4: Well, I guess yeah.
Speaker 3: When you're looking at something and so much of it
Speaker 3: looks real, your sense of what's real and what's fake
Speaker 3: is so.
Speaker 2: Distortive exactly, and that is a key feature of deep fakes,
Speaker 2: that they are highly highly realistic. Now, one famous example
Speaker 2: that comes to my mind when we talk about deep
Speaker 2: fakes is I don't know if you've seen this there
Speaker 2: or if you remember this, but the image of Pope
Speaker 2: Francis in a Valenciago quilted jacket. It's kind of walking
Speaker 2: the streets in this massive white jacket, and it went
Speaker 2: completely viral at the time in March train twenty three,
Speaker 2: and a lot of people obviously didn't know it was
Speaker 2: a fake photo because it looked so real, and two
Speaker 2: years ago, there wasn't really the conversations happening at the
Speaker 2: time that there are now, when we are much more
Speaker 2: aware that there are so many fake images, and obviously
Speaker 2: we are talking about AI so much even we're talking
Speaker 2: about AI so much more today than we were a
Speaker 2: month ago, let alone two years ago, and so that
Speaker 2: is one of I would say that's one of the
Speaker 2: more innocuous examples of deep fakes where although it was fake,
Speaker 2: it didn't necessarily do any damage by people believing that
Speaker 2: it was real. But why we're talking about it today
Speaker 2: is because deep fakes can and they have been used
Speaker 2: in a much more deceptive way, and one of those
Speaker 2: ways is during elections.
Speaker 4: I see how you're bringing this altogether.
Speaker 1: We're circling that.
Speaker 2: So there have been examples around the world where politicians
Speaker 2: or political candidates or even just people who want a
Speaker 2: certain party to win, have used deep fakes to mislead
Speaker 2: voters and to benefit their campaign. Or it could not
Speaker 2: even be for that reason, it could just be to
Speaker 2: cause chaos or cause disruption.
Speaker 3: Okay, So we're talking about it because we're in the
Speaker 3: lead up to an election and we've seen not just
Speaker 3: here but across the world examples of deep fakes being
Speaker 3: used during an election cycle. Can you talk me through
Speaker 3: some of the examples that we've seen of this and
Speaker 3: how it's been used.
Speaker 4: Yeah.
Speaker 2: I thought we would start in Australia because you might
Speaker 2: not be aware that there have actually been examples in
Speaker 2: Australian elections or by Australian parties of using deep fakes.
Speaker 2: So Queensland, Hm'm sure you've heard of it, familiar. They
Speaker 2: had an election last year and the Liberal National Party
Speaker 2: posted a video of the then Premier, Steven Miles dancing
Speaker 2: with text beneath it that said pov my rent is
Speaker 2: up sixty dollars a week, my power bill is up
Speaker 2: twenty percent. But the premier made a sandwich on TikTok,
Speaker 2: So basically they were saying that the premiere at the
Speaker 2: time was dancing and was happy despite the fact that
Speaker 2: the rent in the state had gone up on average
Speaker 2: for the average renter. Now, that video was actually labeled
Speaker 2: as AI generated, although I would say that the label
Speaker 2: was pretty easy to miss if you weren't necessarily looking
Speaker 2: out for it, and so it was just this completely
Speaker 2: fake video of Steven Male dancing.
Speaker 3: I remember seeing that at the time and coming up
Speaker 3: on you for you page it did, and I remember
Speaker 3: thinking that it was the first time I recall seeing
Speaker 3: something like that here in Australia.
Speaker 2: Yeah, and it generated a lot of media coverage. But
Speaker 2: then a lot of that coverage then pointed out that
Speaker 2: this is not unique to one side of politics. And
Speaker 2: actually around that time, well actually before that video was posted,
Speaker 2: the Australian Labor Party had also posted a video on
Speaker 2: their TikTok that had used AI to create a fake
Speaker 2: video of Federal Opposition leader Peter dune and dancing with
Speaker 2: the words dance if you want to build nuclear power
Speaker 2: plants in everyone's backyard. Zara, I'm going to send you
Speaker 2: the video for you to look.
Speaker 1: Right now.
Speaker 2: I realized this is an audio platform and so the
Speaker 2: audience can't see it. But Zara, I want to get
Speaker 2: your reaction.
Speaker 3: My god, oh my god.
Speaker 2: I'm going to say, it's probably not the most realistic.
Speaker 4: It looks nothing like Peter Dudden.
Speaker 2: Okay, but you can see that it's trying to kind
Speaker 2: of imitate him vaguely. Sure, Look, this is one of
Speaker 2: the examples where it is pretty clear to most people.
Speaker 1: That it was a fake video.
Speaker 3: However, it must be said that like you and I
Speaker 3: look at Peter Dudden day and day out where we
Speaker 3: work in news, we're very familiar with what he looks like.
Speaker 3: I imagine for someone that's perhaps not paying the same amount
Speaker 3: of attention, maybe they wouldn't be able to tell.
Speaker 2: You yes exactly. And also, I think the Stephen Miles one,
Speaker 2: if you look at that one, it was a lot
Speaker 2: more realistic. Yeah, but again, these are videos of the politicians,
Speaker 2: and so it is one of the more benign examples
Speaker 2: of how deep fakes can be used in elections.
Speaker 3: Okay, So if you're saying that those are benign examples,
Speaker 3: or perhaps more benign examples. What are some of the
Speaker 3: more troublesome deceptive examples that we've got out there.
Speaker 2: Yeah, so if we look overseas, there are quite a
Speaker 2: few more troublesome examples. So one example that the audience
Speaker 2: might be familiar with or might have seen in their
Speaker 2: feeds is that during the US election last year, in
Speaker 2: the lead up to that election, Elon Musk shared a
Speaker 2: video that looked like an ad campaign for Kamala Harris,
Speaker 2: who was the Democratic candidate for the US presidency last year.
Speaker 2: Here's a bit of that clip.
Speaker 5: I Kamal Harris and your Democrat candidate for presidents because
Speaker 5: Joe Biden finally exposed to sinilitive to be thanks, John,
Speaker 5: I was selected because I am the ultimate diversity hire.
Speaker 5: I'm both a woman and a president of color. So
Speaker 5: if you've criticized anything I say, you're both sexist and racist.
Speaker 3: That one's crazy because that sounds exactly like her.
Speaker 1: Yeah, it would be look video.
Speaker 2: Yeah, if you were watching it, it would be really
Speaker 2: hard to tell that that is a fake video. And
Speaker 2: you probably couldn't immediately tell unless you were in tune
Speaker 2: with every single thing Kamla Harris has ever said, you
Speaker 2: would have to do some digging to figure out if
Speaker 2: that was real or fake, especially when it's shared by
Speaker 2: a very influential person. Now, that video received nearly one
Speaker 2: hundred and forty million views according to x's Metrics, and
Speaker 2: it was liked by nearly one million accounts. Wow, so
Speaker 2: that gives you an idea of how viral this kind
Speaker 2: of content can go.
Speaker 4: I'm just looking at the tweet responses. What's that called
Speaker 4: yesh x response?
Speaker 3: And ex responds someone who was retweeted one hundred and
Speaker 3: ninety three times and like ten thousand times said.
Speaker 4: Is this AI or reel?
Speaker 3: Yeah?
Speaker 4: So clear genuinely no idea.
Speaker 2: Yeah, it clearly wasn't that clear to me any many people.
Speaker 2: As I'm sure you've guessed. The reason we're talking about
Speaker 2: it is because it was completely fake. Kamala Harris never
Speaker 2: said those words, so that voice was completely AI generated,
Speaker 2: but it sounded and looked extremely realistic. Now, it's hard
Speaker 2: to measure what impact a video like that had on
Speaker 2: the minds of voters in the US. It could have
Speaker 2: had no impact at all, or it could be quite significant, Again,
Speaker 2: especially when shared by a very influential person such as
Speaker 2: Musk So that's one example, but there are also examples
Speaker 2: of foreign countries using deep fakes to interfere with elections.
Speaker 4: Can you unpack that more for me?
Speaker 2: Yeah, it's quite a big concept to get your head around.
Speaker 3: So foreign actors interfering with domestic elections in a different country.
Speaker 2: Exactly, And it's not really something that many of us
Speaker 2: would ever think about, but it's probably something that you've
Speaker 2: heard murmurs about, this idea that there are countries who
Speaker 2: try to interfere with other countries' elections with the aim
Speaker 2: of electing a government they believe will be more closely
Speaker 2: aligned with their own policies and agendas, or like I
Speaker 2: said before, it could not be because of that, it
Speaker 2: could be again just to create chaos and disruption to society.
Speaker 4: What are some examples of that?
Speaker 2: So if we stick with looking at the US election
Speaker 2: last year, Microsoft actually did a report into how rushing
Speaker 2: groups created deep fakes to try to influence the US election. Now,
Speaker 2: before I go on, I do just want to quickly
Speaker 2: mention that, as we discussed earlier, this podcast is sponsored
Speaker 2: by Microsoft, but when not required to talk about them
Speaker 2: in this section, they just have done a lot of
Speaker 2: research in this area that I thought was very relevant
Speaker 2: to talk about. Okay, good clear disclaimer, just want to
Speaker 2: be completely transparent there. So in a report last year,
Speaker 2: Microsoft found that two groups that were aligned with the
Speaker 2: Russian government, the Kremlin, had created and disseminated videos that
Speaker 2: were quote designed to discredit Harris again talking about Kamala
Speaker 2: Harris and stoke controversy around her campaign. So, for example,
Speaker 2: they found this one video that showed Harris supporters attacking
Speaker 2: an attendee at a Trump rally, and that video was
Speaker 2: completely false, but it was still seen by millions and
Speaker 2: millions of people, and there was no labeling or anything
Speaker 2: that indicated.
Speaker 1: This video was fake.
Speaker 2: So to someone who was just on their feedscrolling through,
Speaker 2: there wasn't any clear signs that this was a fake video.
Speaker 2: And so basically what they found is that these groups
Speaker 2: intentionally created these videos and planted them in front of
Speaker 2: US audiences to sway their opinion in this case against Harris.
Speaker 3: Yeah, it's really interesting and again needs to be said,
Speaker 3: this isn't happening on one side of politics. We've seen
Speaker 3: examples across the aisle when it comes to this Billy
Speaker 3: one thing that I think about when you're talking about
Speaker 3: this is the onus that exists on on the individual,
Speaker 3: because ultimately we're saying you can be served up fake
Speaker 3: content that is mimicking reality but is not real, and
Speaker 3: sometimes deceptively, sometimes in a more benign nature, and we
Speaker 3: are expecting audiences to be able to critically, I guess,
Speaker 3: analyze what they're seeing and understand how can people tell
Speaker 3: if videos that they're watching or photos they're seeing a
Speaker 3: real or AI generator. You know, for example, we've seen
Speaker 3: the President of the United States share something recently there
Speaker 3: was completely AI generated and completely fake.
Speaker 4: Yeah.
Speaker 2: I speak to my friends about this all the time
Speaker 2: because we're always, you know, sending each other videos and whatnot,
Speaker 2: and we're always talking about how do we tell if
Speaker 2: this is real or not? And what's hard is that
Speaker 2: by definition, deep fakes are incredibly realistic. The whole point
Speaker 2: is for you to think.
Speaker 1: That they are real.
Speaker 2: I think the main thing to look for is who
Speaker 2: is sharing this video and what is the primary source
Speaker 2: or does a primary source even exist? So if it's
Speaker 2: from an verified, completely random account, then that's more likely
Speaker 2: to be a fake video than one shared by a
Speaker 2: reputable news outlet, or even better, a primary source, so Zara,
Speaker 2: as you know, at TDA, we are all about the
Speaker 2: primary source, So that means looking at where each and
Speaker 2: every piece of information originates from. So just for some
Speaker 2: context for the listeners, our guiding rule at TDA is
Speaker 2: that every fact we share needs to have a primary source.
Speaker 2: We need to know exactly where it came from and
Speaker 2: go to that place to get that information ourselves.
Speaker 1: So if we look at the video of.
Speaker 2: Kamala Harris shared by Elon Musk, that kind of is
Speaker 2: more murky because obviously Elon Musk's page is verified, so
Speaker 2: I understand why a lot of people would have thought
Speaker 2: it was real. But again, if we are looking for
Speaker 2: the primary source in that case, you would find it
Speaker 2: on either Harris's own verified page, all the Democratic parties
Speaker 2: verified socials. And if you can't find that video on either,
Speaker 2: and there's a good chance it's not real. But I
Speaker 2: think you can also consider whether that content perfectly fits
Speaker 2: a particular narrative being pushed by someone that it potentially
Speaker 2: could be too good to be true. And I also
Speaker 2: just want to say that this isn't about making you
Speaker 2: think that everything is fake. That is not what we're saying.
Speaker 2: I think we're just talking about developing a healthy level
Speaker 2: of skepticism, not too much that you completely distrust everything
Speaker 2: you see, but enough to stop and consider where this
Speaker 2: content is from. Could it be fake or manipulated? And
Speaker 2: if you're basing your opinion on this video that you're seeing,
Speaker 2: should you be checking whether there is a primary source?
Speaker 3: Now, Billy, I just want to end back. I guess
Speaker 3: where we started with a discussion about it here in Australia.
Speaker 3: Are there laws that regulate this sort of behavior here?
Speaker 2: Yeah, our audience has asked us a lot about this,
Speaker 2: and essentially the answer is that there is nothing that
Speaker 2: prohibits the use of AI in election campaigns. Also remembering
Speaker 2: that this is quite new technology. There is, however, regulation
Speaker 2: about campaign communication, so you know, information coming from the
Speaker 2: Labor Party directly or the Liberal Party or whatever party
Speaker 2: or political candidate, that communication is regulated. But as we
Speaker 2: saw in many of the examples above, the deep fakes
Speaker 2: that are misleading voters aren't usually coming from political parties directly.
Speaker 2: They're coming from other third party actors who perhaps have
Speaker 2: a certain agenda to push. It is a criminal offense
Speaker 2: in the Electoral Act to mislead or deceive an elector.
Speaker 1: When it comes to casting a vote. But again, this.
Speaker 2: Becomes harder to apply to videos posted on random accounts
Speaker 2: where the exact source of that video or image is
Speaker 2: not known.
Speaker 3: Look a really complex area, and especially as it interacts
Speaker 3: with election season. Definitely one that we have to keep
Speaker 3: an eye on and one that will continue to keep
Speaker 3: speaking about.
Speaker 4: So thank you for taking us through that.
Speaker 1: Billy, Thank you.
Speaker 3: We'll be back again tomorrow morning with a deep dive
Speaker 3: as usual, but until then, enjoy your weekend.
Speaker 1: My name is Lily Maddon and I'm a proud Arunda
Speaker 1: Bungelung Kalkadin woman from Gadighl Country.
Speaker 2: The Daily oz acknowledges that this podcast is recorded on
Speaker 2: the lands of the Gadighl people and pays respect to
Speaker 2: all Aboriginal and torrest Rate island and nations. We pay
Speaker 2: our respects to the first peoples of these countries, both
Speaker 2: past and present.