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Speaker 1: Already, and this is the daily This is the Daily

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Speaker 1: os oh. Now it makes sense.

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Speaker 2: Good morning and welcome to the Daly Ohs.

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Speaker 3: I'm Zara and over the next little while, we're going

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Speaker 3: to be bringing you a bonus series featuring our favorite

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Speaker 3: deep dives from twenty twenty four. We've put together the

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Speaker 3: best deep dives to listen to on the beach, road,

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Speaker 3: tripping when you don't want to talk to the person

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Speaker 3: next to you, or just reflecting on the year that was.

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Speaker 3: Welcome to tda's summer series. Earlier this year, we did

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Speaker 3: a deep dive into the new digital player helping to

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Speaker 3: shape public discourse online. Now the TLDR is the bots

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Speaker 3: are targeting your social media algorithms and the content that

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Speaker 3: you get served online. In today's deep dive, Chloe explores

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Speaker 3: how these digital armies are being mobilized to influence public opinion.

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Speaker 3: It's a fascinating element of our online world. So without

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Speaker 3: further ado, let's get into the episode. Now, Chloe, you've

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Speaker 3: become something of a bot.

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Speaker 2: Expert in the last couple of weeks.

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Speaker 3: But for anyone that hasn't spent as much time in

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Speaker 3: the weeds of bot mania as you have, Yes, can

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Speaker 3: you just explain what exactly is a bot?

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Speaker 1: I have been in the weeds of the botmania. It's

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Speaker 1: quite a place to be, and it can sound really

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Speaker 1: techy when we talk about this stuff, but it's pretty

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Speaker 1: much every time you jump on social media and you

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Speaker 1: see somewhat of a spammy comment on a popular Instagram account.

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Speaker 1: Just look at the Daily Yours's account, you'll see plenty

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Speaker 1: of them.

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Speaker 2: Excellent plug, excellent plug.

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Speaker 1: You'll see them most often in the comment section within

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Speaker 1: seconds of making a post on Instagram.

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Speaker 3: Yeah, and I feel like, you know, even if you

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Speaker 3: just look at our Instagram, you're seeing things like how

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Speaker 3: coach Sarah changed my life. They changed the name of

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Speaker 3: Sarah to multiple different women.

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Speaker 2: But there you go.

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Speaker 3: There's some like semi nude women that have come up

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Speaker 3: in gifts in our comment section.

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Speaker 1: Click on my io you'll get rich fast.

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Speaker 3: So those sorts of comments you're saying, those are coming

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Speaker 3: from bot accounts, right.

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Speaker 1: Yeap, So that is a bot account. But when we

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Speaker 1: look at bots more broadly, bots are programmed to perform automated,

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Speaker 1: repetitive tasks over a network. Okay, so they're deliberately designed

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Speaker 1: to mimic human behavior. They look like humans, they sound

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Speaker 1: like real users. Only bots can generate content at a

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Speaker 1: speed and a scale that we humans simply couldn't. So

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Speaker 1: that's thousands upon thousands of comments a day. There are

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Speaker 1: some helpful bots like chat gpt is, a chatbot, Siri Alexa,

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Speaker 1: but others, as we know, are less helpful.

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Speaker 3: They are less helpful, but they are absolutely everywhere. Like

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Speaker 3: it takes, you know, one second of looking, as you said,

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Speaker 3: at a popular account and you just get flooded with

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Speaker 3: this stuff. How significant I mean, I'm just using anecdotal

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Speaker 3: evidence here, So how significant are the presence of these

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Speaker 3: bots in the online world.

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Speaker 1: Yeah, it's wild. And to give you a sense of

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Speaker 1: the scale of things, nearly half of all online traffic

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Speaker 1: in twenty twenty three came from fake users.

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Speaker 2: That is crazy.

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Speaker 1: So bots, yeah, now, that's according to a new report

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Speaker 1: by IT security firm Imperva, which also found that bad

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Speaker 1: bots programmed to defraud and scam users accounted for nearly

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Speaker 1: one third of all of that traffic.

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Speaker 4: Wow.

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Speaker 3: I mean, I knew they were everywhere, but that's really

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Speaker 3: there everywhere.

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Speaker 1: They're everywhere.

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Speaker 3: And so when we're thinking about bots, you know, I

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Speaker 3: think that anyone that has spent time on the internet

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Speaker 3: knows not to click on you know, come earn money

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Speaker 3: with me with your crypto dollars, you know in our

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Speaker 3: comment section. But what are some of the other ways

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Speaker 3: the bots show up or the other ways that they

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Speaker 3: can I guess influence behaviors or conversations.

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Speaker 1: Well, that's a whole different podcast about how people are

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Speaker 1: scammed and frauded into clicking on things that they shouldn't.

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Speaker 1: But what I was really interested in was the way

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Speaker 1: bots can be used to make an opinion seem like

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Speaker 1: a fact, or to make it feel and zeem as

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Speaker 1: though it has either widespread support or widespace opposition for something.

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Speaker 1: What does that do for real users online? Because if

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Speaker 1: you can gear thousands upon thousands of accounts to push

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Speaker 1: a certain narrative, that can be really dangerous if we

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Speaker 1: think about elections or democracy or just public discourse at large.

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Speaker 3: It's a really interesting topic, but it does still seem

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Speaker 3: quite up there, and I would love to bring it

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Speaker 3: down to down here. Is there an example that you

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Speaker 3: can just provide, I guess to give some orientation as

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Speaker 3: to what you're actually talking about here.

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Speaker 1: So let's just say you're scrolling on X and you

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Speaker 1: read a bunch of different tweets, retweets shares comments of

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Speaker 1: those tweets saying apples are really really bad for you

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Speaker 1: and instead you should be buying oranges. This is really basic,

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Speaker 1: but just still wrapping heads around it. You're probably going

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Speaker 1: to start feeling a little bit suss about apples, even

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Speaker 1: though you might really like them. You just sort of

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Speaker 1: have a bit of questions about that. You might even

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Speaker 1: consider buying more oranges. And bots can create these spaces

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Speaker 1: that feel like communities are sharing ideas that it's just

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Speaker 1: normal people talking about how we all don't really like apples,

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Speaker 1: but there is an agenda at play. Now when you

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Speaker 1: consider the influence that, as I said, this could have

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Speaker 1: on politics or elections.

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Speaker 2: Not just apples and oranges, Not just.

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Speaker 1: Apples and oranges, it can be really scary.

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Speaker 2: What are the experts say about bots?

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Speaker 3: Because you know, they are a fairly new phenomenon, but

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Speaker 3: there must be a body of research out there.

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Speaker 1: I reached out to a bot doc.

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Speaker 2: Of course, a bot doc has a dock of bot.

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Speaker 1: She does have a real name. Her name is doctor

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Speaker 1: Sophia Mellinson Richard done from Canada's McMaster University. Now She

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Speaker 1: did a PhD on Bota gander when bot armies generate

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Speaker 1: mass content to saturate social media feeds and then manipulate audiences.

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Speaker 1: So doctor Richardoni told me about something called hashtag flooding,

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Speaker 1: which is essentially a tweet containing nothing but popularized keywords

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Speaker 1: and catchphrases in the form of hashtag.

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Speaker 2: After hashtag up to hashtag so annoying, so annoying.

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Speaker 1: Now, this tactic, as well as the rapid resharing of

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Speaker 1: human posts so twenty five thousand in ten minutes, can create,

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Speaker 1: like we were saying before, this illusion of widespread support

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Speaker 1: or widespread opposition for specific viewpoints. She says that this

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Speaker 1: happens as though the idea embedded in the tweed came

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Speaker 1: from grassroots popularization. So when we're talking about mimicking human behavior,

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Speaker 1: it's this feeling of oh, everyone thinks.

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Speaker 3: This, and you want to be a part of the everyone.

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Speaker 3: Like that's the human condition, right exactly.

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Speaker 1: It's the concept of herd mentality, which is the idea

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Speaker 1: that individuals naturally want to conform to the dominant view

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Speaker 1: of the community.

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Speaker 3: Yeah, I mean, it's so fascinating, and the reason that

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Speaker 3: you came to I don't want to say, become obsessed

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Speaker 3: with this topic, but I mean had started your fascination

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Speaker 3: was around one example that we've seen in the last

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Speaker 3: couple of years.

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Speaker 2: Talk me through the Johnny Depp Amber Herd story.

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Speaker 1: I don't know if many people remember what the internet

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Speaker 1: looked like in twenty twenty two during the Johnny Depp

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Speaker 1: amber her defamation trial, but I recently listened to a

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Speaker 1: six part podcast that brought me right back there. So

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Speaker 1: for people who need a refresher on the story. Essentially,

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Speaker 1: Johnny Depp filed a lawsuit against his ex wife Amber

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Speaker 1: heard over an opinion article Herd wrote for The Washington Post.

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Speaker 1: She alleged she had experienced domestic abuse. Her didn't name Debt,

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Speaker 1: but he launched defamation proceedings against her, arguing he was

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Speaker 1: identifiable from the article and depth denies claims that he

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Speaker 1: physically abused her. Now, a jury in Fairfax County, Virginia

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Speaker 1: ultimately sided with Depp, and Herd was sued for defaming him.

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Speaker 1: But I think you might remember that the court proceedings

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Speaker 1: were streamed online.

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Speaker 3: Yeah, so I was going to say, can you, in

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Speaker 3: the minds of our listeners connect what we've just been

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Speaker 3: talking about which is you know all of this stuff

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Speaker 3: about bots and this case, what's the connection here?

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Speaker 1: So as the case played out in the courtroom, the

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Speaker 1: internet mounted its own unofficial trial of Amber Heard. This

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Speaker 1: is the premise of the podcast I was talking about earlier,

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Speaker 1: Who Trolled Amber? It's by UK media organization Tortoise. The

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Speaker 1: podcast found that a large part of the online hate

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Speaker 1: campaign against her was actually manufactured and executed by bot accounts.

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Speaker 1: Now I spoke to Xavia Greenwood, he produced the Who

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Speaker 1: Trolled Amber podcast.

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Speaker 4: Some of the main themes were that Amber Heerd deserves prison,

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Speaker 4: Amber Heard as a gold digger, Amber Heard as a fraud,

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Speaker 4: Amber Heard as a liar. To give you a sense

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Speaker 4: of the scale of things, there was a hashtag justice

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Speaker 4: for Johnny Depp that was viewed fifteen point seven billion

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Speaker 4: times hashtag just as Amber Heerd viewed a fraction of that,

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Speaker 4: and my friends were suddenly saying things that didn't really

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Speaker 4: sound like them. They were saying, well, you know what

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Speaker 4: if this time she was the abuser. And these were

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Speaker 4: people who typically in the Me too movement would be

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Speaker 4: a bit more cynical or maybe a bit more reserved

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Speaker 4: in making a judgment like that. So yeah, from the beginning,

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Speaker 4: we sort of saw that this was quite suspicious.

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Speaker 3: What else did this investigation uncover?

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Speaker 1: The team Tortoise brought together a database of over one

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Speaker 1: million anti amber Heard tweets, and they brought it together

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Speaker 1: and they found that more than half of them were inauthentic.

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Speaker 1: So what that means is either they were posted from

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Speaker 1: spam accounts with three followers and they were built in

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Speaker 1: the last two months, or they were amplified in an

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Speaker 1: inauthentic way so reshared and reshared thousands upon thousands of times.

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Speaker 3: Okay, I think the thing that I wonder when I

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Speaker 3: hear about this story is like, who is behind this

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Speaker 3: trolling campaign? It's very clear who benefits from it, but

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Speaker 3: who's behind it.

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Speaker 1: We don't know. According to the investigation, the team could

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Speaker 1: hypothesize multiple different scenarios and their likely were multiple different

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Speaker 1: agendas at play.

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Speaker 2: Yeah, it's crazy, So this could.

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Speaker 1: Be genuine Johnny Depp fans who can acquire bots for

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Speaker 1: pretty cheap online and push support for their favorite actor

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Speaker 1: in other scenarios. Xavier floats what he calls a more

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Speaker 1: abstract theory.

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Speaker 4: I think it's sort of fairly widely known now that

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Speaker 4: authoritarian regimes who want to sow discouse or want to

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Speaker 4: cause confusion in the West that they seek out wedge issues.

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Speaker 4: So they seek out issues which divide Britain's, divide Americans,

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Speaker 4: divide Australians. They try to sort of drive a deeper wedge.

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Speaker 1: But something that really stuck with me from my conversation

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Speaker 1: with Xavier was a point he made about the future

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Speaker 1: of political discourse on social media.

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Speaker 4: If you can attack a celebrity who has enormous an

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Speaker 4: enormous amount of resources, as Amberhard did, was to stop

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Speaker 4: someone doing the same thing when it comes to attacking

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Speaker 4: a politician or when it comes to trying to sway

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Speaker 4: an election.

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Speaker 3: I mean, we're talking there about elections, and we of

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Speaker 3: course know that there is one coming up just around

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Speaker 3: the corner in the US. Are we expecting to see

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Speaker 3: this sort of interference from bots in the US election

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Speaker 3: this year?

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Speaker 1: We already have. Last month, the Biden administration charged Russian

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Speaker 1: media executives over an alleged targeted online campaign to influence

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Speaker 1: voters in the US and push hidden Russian government messaging.

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Speaker 1: Now it comes after US officials seized thirty two Internet

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Speaker 1: domain names that were covertly targeting specific demographics on social

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Speaker 1: media and promoting AI generated false narratives and pushing that

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Speaker 1: to those groups.

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Speaker 3: Okay, so there are ready allegations that we've seen this

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Speaker 3: at play when it comes to the US election. Ye,

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Speaker 3: I mean, I think that a natural endpoint here is

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Speaker 3: that if we're talking about the fact that even the

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Speaker 3: most powerful institutions, people, whatever, in the world can be

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Speaker 3: susceptible to this kind of bodagander, as we'll call it,

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Speaker 3: what is like an average dough like you or I

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Speaker 3: meant to do when it comes to protecting yourself against something.

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Speaker 1: Like this, Well, that was what came back in so

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Speaker 1: many of the conversations I was having. For the average

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Speaker 1: dough like you and me, A lot of it comes

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Speaker 1: down to awareness, staying vigilant, staying curious, question what you're

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Speaker 1: getting served, who's pushing it. And that's generally for anything

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Speaker 1: that you've seen online, but particularly when you're thinking something

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Speaker 1: looks a bit spammy, it likely might be it's important

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Speaker 1: to be critical about the content you're seeing before you

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Speaker 1: form an opinion, especially ahead of an election. Now, as

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Speaker 1: for what comes next, Xavier Greenwood says, we're largely in

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Speaker 1: uncharted waters.

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Speaker 4: What we saw with Amber heard trial, we may well

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Speaker 4: continue to see in an even more intense way in

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Speaker 4: the future. To some extent, the genie is out at

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Speaker 4: the box.

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Speaker 3: Thanks for listening to today's episode of tda's summer series.

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Speaker 3: We'll be back again tomorrow with another of our favorite

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Speaker 3: deep dives, but until then, have a wonderfully warm day.

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Speaker 4: My name is Lily Maddon and I'm a proud Arunda

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Speaker 4: Bungelung Caalcuttin woman from Gadighl Country. The Daily oz acknowledges

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Speaker 4: that this podcast is recorded on the lands of the

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Speaker 4: Gadighl people and pays respect to all Aboriginal and Torres

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Speaker 4: Strait Island and nations. We pay our respects to the

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Speaker 4: first peoples of these countries, both past and present.