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Speaker 1: There are No Girls on the Internet. As a production

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Speaker 1: of iHeartRadio and Unbossed Creative, I'm Bridget Todd, and this

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Speaker 1: is there are no girls on the Internet. I am

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Speaker 1: sad to say that. I think that we are witnessing

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Speaker 1: the revival of menstrual shows using AI on social media

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Speaker 1: platforms like TikTok. When you actually look at what menstrual

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Speaker 1: shows were and the role they played and upholding the

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Speaker 1: status quo back in the day, and then look at

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Speaker 1: what's happening right now with these AI generated racist videos

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Speaker 1: depicting black women on TikTok. The similarities are shocking. Now.

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Speaker 1: This is something I could talk a lot about. As

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Speaker 1: I was writing my thoughts for the outline for today's conversation,

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Speaker 1: I said, oh, I'm at tad pages, I'm at twell pages.

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Speaker 1: And eventually we had to say, like, okay, enough pages

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Speaker 1: like this. You have to put a stop to this.

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Speaker 1: This is too much. So here with me to get

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Speaker 1: into all of it, is my producer.

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Speaker 2: Mike him Bridget, thanks for having me here. I know

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Speaker 2: this is a topic that you have studied, have a

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Speaker 2: lot to say about, and so I am very interested

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Speaker 2: to hear how what's going on on TikTok right now

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Speaker 2: reminds you of what was happening with minstrel joes one

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Speaker 2: hundred years ago? Is that the right sort of time

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Speaker 2: frame that we're.

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Speaker 1: Talking like nineteenth century, eighteenth and nineteenth century, So let's

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Speaker 1: start there. Let's start with what a minstrel show is

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Speaker 1: for folks who did not spend all of their college

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Speaker 1: years like pouring through this and obsessing over the minutia

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Speaker 1: of minstrel shows. The minstrel show was an incredibly popular

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Speaker 1: form of American theater and entertainment in the nineteenth century,

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Speaker 1: where mostly white performers would wear blackface to make themselves

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Speaker 1: look like black people and portray really racist stereotypes that

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Speaker 1: showed black people as like lazy, stupid buffoons. A common

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Speaker 1: trope in these skits would be black folks trying and

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Speaker 1: failing to become citizen, where they would fail in some

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Speaker 1: kind of a humorous way because they were too stupid

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Speaker 1: to figure it out or too lazy, like there would

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Speaker 1: be a test they were supposed to take and they

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Speaker 1: would oversleep and miss the date or something like that,

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Speaker 1: And it was very much meant to be a source

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Speaker 1: of humor at black people's expense. When these shows would

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Speaker 1: depict black women, we were depicted as what's known as

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Speaker 1: the Sapphire caricature, which sort of shows black women as

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Speaker 1: being rude, loud, malicious, aggressive, stubborn, and really overbearing. So

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Speaker 1: kind of what you might think of as the angry

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Speaker 1: black woman trope in the kind of media that we

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Speaker 1: still see today now. While there were some black people

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Speaker 1: who did perform in minstrel shows ironically putting black face

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Speaker 1: makeup on their already black faces to exaggerate their already

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Speaker 1: black features, which I always found to be interesting that

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Speaker 1: you would have these black performers drawing an outline on

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Speaker 1: their lips to make them look more black even though

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Speaker 1: they have black features. I always found that to be

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Speaker 1: kind of funny.

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Speaker 2: That is really interesting, and it reminds me of this

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Speaker 2: concept that you told me about. Is a different context,

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Speaker 2: they idea have similacrum where there's like a copy of

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Speaker 2: a copy, and then people will make a new copy

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Speaker 2: that has features that never existed in the original, but

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Speaker 2: those new features become like the idea of what the

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Speaker 2: thing is, and that it kind of reminds me of

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Speaker 2: that a little bit. The idea that black actors would

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Speaker 2: apply makeup to make themselves look the way they were

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Speaker 2: supposed to look for this very particular performance.

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Speaker 1: Oh, this is Boujayard's concept of simulacrum absolutely right, where

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Speaker 1: just having an actual black performer on stage is not

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Speaker 1: black enough, because you've been trained that what a black

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Speaker 1: person is is these like exaggerated facial features, an exaggerated

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Speaker 1: skin tone, and so to have an actual black person

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Speaker 1: on stage is not black enough. You need in order

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Speaker 1: to feel like you're really experiencing that experience, you need

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Speaker 1: it to be like this like hyper exaggerated way that

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Speaker 1: you've already experienced it. That's completely not what an actual

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Speaker 1: black person looks like. That I always saw that to

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Speaker 1: be so interesting. And so while there were a few

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Speaker 1: black performers who performed in minstrel shows in blackface makeup

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Speaker 1: with exaggerated features, the overwhelming and vast majority of performers

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Speaker 1: in minstrel shows were white actors wearing black face makeup

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Speaker 1: for the explicit purpose of portraying these racist stereotypes of

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Speaker 1: black people.

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Speaker 2: And it wasn't just entertainment, right, Like people would laugh

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Speaker 2: in the audience, but you were telling me before the

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Speaker 2: show about the important functional role that these shows.

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Speaker 1: Had exactly so they were incredibly popular as entertainment, but

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Speaker 1: they sorted this this more important purpose of reaffirming and

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Speaker 1: re establishing the political and social ideologies of the time,

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Speaker 1: and they really occupy that this gray area that comes

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Speaker 1: up a lot when we're talking about this kind of

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Speaker 1: popular culture, this ambiguousness between humorous entertainment that's just like, oh,

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Speaker 1: nothing to think twice about, doesn't really matter, isn't really

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Speaker 1: that important, is not that deep, and the functional reinforcement

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Speaker 1: of white supremacy. And it really reminds me a lot

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Speaker 1: of how like all right, members use memes today like

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Speaker 1: everything is couched and all of this irony and all

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Speaker 1: of this plausible deniability and all of this kind of

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Speaker 1: wink wink, no, no, it's just a joke. But back then,

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Speaker 1: the KKK was exploiting that very same ambiguity to permeate control.

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Speaker 1: As the nineteenth century gave way to the twentieth, and

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Speaker 1: so this kind of form of popular entertainment that people

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Speaker 1: were just consuming mindlessly as like oh, it's just a joke, YadA, YadA, YadA,

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Speaker 1: became a way of just reaffirming the status quo of

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Speaker 1: black people. As you know, other different, less than and

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Speaker 1: not really worthy of full citizenship rights. Things like that.

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Speaker 1: And so I would argue if the popular depiction of

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Speaker 1: media involving black people shows us as lazy, stupid, angry, loud,

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Speaker 1: completely unable to conform to the dominant culture of like

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Speaker 1: hard working, mainstream white Americans, that is such an incredibly

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Speaker 1: powerful tool to uphold and reaffirm that, you know, black

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Speaker 1: folks should not be given full citizenship. Black folks should

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Speaker 1: not be given full rights. Black folks cannot be integrated

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Speaker 1: into white society, quote unquote. And it's almost time it

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Speaker 1: becomes this thing of like, oh well, it's it's not

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Speaker 1: that I hate black people, it's for their own good.

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Speaker 1: This attitude where it provides a kind of polite justification

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Speaker 1: for things like segregation, Like a black person would be

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Speaker 1: overwhelmed if they had had a job, because look how

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Speaker 1: stupid they are. From what I saw on this menstrual show,

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Speaker 1: you could almost provides a kind of cover of these

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Speaker 1: pretty grotesque political and social attitudes.

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Speaker 2: It's so interesting to hear that history, like very tempting

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Speaker 2: to think about the way the alright uses memes with

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Speaker 2: irony and humor to give them that plausible deniability. It

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Speaker 2: feels new, but you're saying it's not new at all.

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Speaker 2: You know, it's been going on for well over one

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Speaker 2: hundred years, maybe longer.

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Speaker 1: Oh that's the thing about white supremacy, Like it seems new,

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Speaker 1: but it is. It's always a page from a very

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Speaker 1: well worn playbook, just sort of reimagined for today. And

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Speaker 1: I think that's exactly what we're seeing with the proliferation

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Speaker 1: of AI being used to create what I would argue

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Speaker 1: are the twenty twenty five equivalent of menstrual shows today

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Speaker 1: for the digital age. So even though menstrual shows in

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Speaker 1: theater died out, I would argue that they are having

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Speaker 1: a comeback today in the digital realm. And just like

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Speaker 1: those menstrual shows of yesteryear were used to affirm political

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Speaker 1: and social ideologies under the guise of it just being

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Speaker 1: entertainment and it not being that deep, I think it

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Speaker 1: is no coincidence that we are seeing the rise of

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Speaker 1: digital blackface, where non black creators are using AI to

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Speaker 1: create viral skits depicting racist black stereotypes all over TikTok today.

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Speaker 2: How did you come upon this? Because I'm not on TikTok,

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Speaker 2: I haven't seen this tell me about these videos, bridget So.

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Speaker 1: I think I've talked about it on the show, but

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Speaker 1: I took kind of a deep break from TikTok after

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Speaker 1: it was temporarily banned and then came back because I

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Speaker 1: just kind of hated that entire thing. I hated how

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Speaker 1: the platform put up that banner thanking Trump for like

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Speaker 1: bringing back TikTok and his leadership. It felt it had

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Speaker 1: big stunt energy to me, and I didn't like that. Also,

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Speaker 1: by the way, some I related you might have saw

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Speaker 1: in the news that Trump actually just recently pushed back

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Speaker 1: the deadline to enforce a TikTok ban again. Now, remember

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Speaker 1: back a few years ago, when TikTok was we were

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Speaker 1: being told the biggest threat to national security, so much

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Speaker 1: so that it had to be banned via emergency legislation

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Speaker 1: at the Supreme Court said was only justified because of

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Speaker 1: the supposed survey of the threat. It don't seem like

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Speaker 1: it's that big of a thread anymore. Something has changed,

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Speaker 1: because the deadline to enforce this band has been pushed

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Speaker 1: back twice and now a third time just last week,

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Speaker 1: which really gives you a into how urgent it was.

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Speaker 1: Apparently during Trump's recent talks with the President of China,

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Speaker 1: TikTok didn't even come up, so like, that's how urgent

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Speaker 1: of a threat it actually is.

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Speaker 2: It's truly amazing to me how rapidly that went from

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Speaker 2: the biggest issue facing the country to something that people

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Speaker 2: don't even talk about anymore.

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Speaker 1: Not to toot my own horn, not to get all

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Speaker 1: Kara Swisher on y'all, but when they first started saying that,

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Speaker 1: I said, this is a stunt, and here we are.

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Speaker 1: I feel like that is coming to fruition. But in

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Speaker 1: any event, that all left kind of a bad taste

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Speaker 1: in my mouth. That aligned with the rise of TikTok Shop,

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Speaker 1: which I've talked about on the show before. It just

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Speaker 1: basically was like, TikTok, the vibes are not vibing. It

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Speaker 1: is not for me. So imagine my surprise when I

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Speaker 1: check back in with TikTok a little bit later after

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Speaker 1: my deep break from the platform, and the first handful

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Speaker 1: of videos I see are these over the top AI

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Speaker 1: generated video skits depicting black women in these very racist,

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Speaker 1: stereotypical ways, and it really got me thinking about the

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Speaker 1: ways that I'm seeing black women and our identity show

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Speaker 1: up more and more in AI generated content and what

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Speaker 1: it says about our culture, both online and off. So

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Speaker 1: the first one of these videos I saw was actually

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Speaker 1: not even that bad. I don't actually think this specific

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Speaker 1: video was created to be like a digital minstrel show. However,

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Speaker 1: I do want to back up because I think that

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Speaker 1: you could argue that anybody who was using AI to

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Speaker 1: generate content they put on social media is inherently doing

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Speaker 1: something unethical. This was the argument that electrical engineer and

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Speaker 1: AI ethicist as Ariah Cole Shepherd made in our episode

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Speaker 1: that we'll link back to, back in twenty twenty two,

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Speaker 1: when all of these AI generated kind of futuristic looking

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Speaker 1: sell these were all over Facebook. People were like changing

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Speaker 1: their Facebook picture to be these AI generated images. She

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Speaker 1: basically argued that anybody who is using AI to make

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Speaker 1: art is inherently stealing from human artists, and there is

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Speaker 1: no ethical way to participate in that, an argument that frankly,

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Speaker 1: I am personally like sympathetic too. What's funny about that episode, though,

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Speaker 1: going back and listening to it, is that she made

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Speaker 1: this great point. This was back in twenty twenty two,

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Speaker 1: that people should be very wary about feeding their likeness

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Speaker 1: voluntarily into this random AI platform to generate like a

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Speaker 1: cute Facebook picture, because that platform, it's definitely using your

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Speaker 1: image to train their AI. This was back in twenty

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Speaker 1: twenty two when she was warning against this, and now

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Speaker 1: here we are in twenty twenty five and people are

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Speaker 1: saying things like, Wow, the AI is so good. It

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Speaker 1: can generate these hyper realistic depictions of black women that

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Speaker 1: I can't even tell her AI and it's like, yeah, huh,

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Speaker 1: you gave it your picture, of course it can. I

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Speaker 1: think it's one of the quirks of having done this

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Speaker 1: show for five years because you get to really cover

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Speaker 1: when people are warning about something and then five years

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Speaker 1: later cover the inevitable fallout. That's like, oh, the thing

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Speaker 1: these people were warning about is happening now.

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Speaker 2: It makes me feel like I wish we'd done a

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Speaker 2: better job of warning, But I guess that's the NAT.

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Speaker 1: I mean, hey, we made that episode.

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Speaker 2: We made that episode. You know, we did what we could.

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Speaker 1: So there are all kinds of reasons to inherently not

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Speaker 1: love this specific use of AI, Like even if this

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Speaker 1: person is not trying to use AI to create, you know,

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Speaker 1: racist depictions of black women, which he says he is

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Speaker 1: explicitly not trying to do when it's pretty clear from

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Speaker 1: his work that that is the case. There are all

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Speaker 1: kinds of reasons to not necessarily love this dynamic, including

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Speaker 1: what we know about the astronomical amount of energy the

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Speaker 1: AI uses, Like it's hard for me not to feel

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Speaker 1: some type of way about wanting to use this much

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Speaker 1: energy to create a stupid skit on TikTok. But in

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Speaker 1: any event, the first one of these AI generated skits

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Speaker 1: with black women video that I saw really take off

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Speaker 1: on TikTok, de picks it up a black woman in

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Speaker 1: a mall when a white older woman comes up to

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Speaker 1: her to confront her about her hair. I love my

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Speaker 1: natural hair. That hair isn't real. Death is seeking you

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Speaker 1: at the Bingos table. I almost kind of get what

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Speaker 1: the creator of this video is going for in this

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Speaker 1: particular instance. It's almost kind of an AI depiction of

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Speaker 1: what the French call the of the wit of the staircase,

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Speaker 1: which is a phrase. I've always loved the idea that

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Speaker 1: a black woman would have the absolute perfect retort to

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Speaker 1: this rude white woman to put her in her place, right,

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Speaker 1: And I can actually see how this specific video that

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Speaker 1: really jump started all these other videos. Was actually an

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Speaker 1: attempt to affirm things that I think are positive depictions

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Speaker 1: of black womanhood, like us being quick with our words,

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Speaker 1: us being poised, the idea of being able to read

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Speaker 1: somebody and put them in their place with a clever

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Speaker 1: retort like Hello, if you ever watched Dynasty, which if

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Speaker 1: you're too young, ask your parents, because they were definitely

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Speaker 1: watching it. Diane Diane Carroll's character as this like classy, wealthy,

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Speaker 1: take no prisoners, Dominique Devereaux always knew what to say,

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Speaker 1: to use her words to put like wealthy white ladies

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Speaker 1: in their place while remaining poised and classy and wealthy, like.

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Speaker 1: I think this is a video that is meant to

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Speaker 1: evoke that aspect of black womanhood, and I think it

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Speaker 1: is meant to make us feel good positive, be like yay,

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Speaker 1: this AI black woman really knew what to say to

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Speaker 1: put this white woman in her place. It was created

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Speaker 1: by a black creator who said that he is interested

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Speaker 1: in seeing more representation of black identity in AI. I

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Speaker 1: watched a little bit of a talk that he did

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Speaker 1: at a conference about how to make money from AI,

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Speaker 1: a point I want to come back to in a moment.

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Speaker 1: But here's what he had to say.

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Speaker 3: I remember when they were creating photos in artificial intelligence,

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Speaker 3: and it acts the artificial intelligence to create them four

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Speaker 3: pictures of a beautiful woman. All four of those were

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Speaker 3: not African American women. Let's say like that, we're not.

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Speaker 3: So I felt like I needed to change that. So

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Speaker 3: I decided to work with a lot of AI organizations

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Speaker 3: and companies to help them.

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Speaker 4: Create milleniated people, to create heir textures to make sure

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Speaker 4: that they don't make our women look too aggressive to

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Speaker 4: put like all body positivity.

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Speaker 3: All women have different shapes. All women here is going

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Speaker 3: to be different. It's okay to have flaws. These are

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Speaker 3: the things that I fight for on a back end.

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Speaker 1: So obviously that sounds nice, and I am aligned with

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Speaker 1: his overall point about more inclusion needed in any and

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Speaker 1: all tech spaces. I'm broadly aligned with what he's saying,

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Speaker 1: but personally, I am still uncertain, Like when I think

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Speaker 1: about the kind of representation that I want in AI,

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Speaker 1: more representation in terms of who is making decisions about

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Speaker 1: how AI is made, how it is impacting people, especially

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Speaker 1: marginalized people. I don't necessarily need or even want this

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Speaker 1: to be translated into us being the ones who are

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Speaker 1: depicted and thus being sort of consumed in AI content,

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Speaker 1: because I feel that that really mirrors the exact same

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Speaker 1: way that we're treated in media now, which I don't

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Speaker 1: think is equal. We are historically the thing that is

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Speaker 1: being consumed by others, while also historically not being in

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Speaker 1: charge of the production or getting an equal share of

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Speaker 1: the revenue of that thing. So just like in sports, film, music,

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Speaker 1: et cetera, and I am not super interested in recreating

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Speaker 1: that same dynamic using AI. So I want to be

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Speaker 1: clear that I am talking about a black person who

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Speaker 1: makes content depicting other black people using AI. Obviously, that

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Speaker 1: does not necessarily mean that this one creator is immune

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Speaker 1: to harmful depictions of black women. Let's not forget podcasts

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Speaker 1: like Fit and Fresh are run by black men and

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Speaker 1: they push some of the most harmful lies about black

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Speaker 1: women that I've ever heard. But to be clear, I

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Speaker 1: do not think this specific AI creator is trying to

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Speaker 1: use AI to depict Black women in a negative or

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Speaker 1: stereotypical light to make fun of us. And again, to

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Speaker 1: be clear, it's pretty clear from his work that that

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Speaker 1: is not what he's trying to do. He's trying to

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Speaker 1: do the opposite. But because that AI video got almost

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Speaker 1: ten million views and his platform on TikTok, the AI

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Speaker 1: clap back King is growing because of that virality. Of course,

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Speaker 1: this sparked several copycats who are now taking this kind

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Speaker 1: of content to the extreme in ways that are like

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Speaker 1: super obviously explicitly racist.

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Speaker 5: Let's take a quick break at our back.

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Speaker 1: So we're talking about these viral racist ais featuring black

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Speaker 1: women that are all over TikTok, and how the first

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Speaker 1: iteration of one of these viral videos I actually don't

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Speaker 1: think was meant to be racist, but that other creators

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Speaker 1: really bullied by the success of that initial viral video,

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Speaker 1: really took that format and ran with it, went extream

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Speaker 1: with it, and we're absolutely trying to be racist. Now,

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Speaker 1: this is a tried and true thing that we have

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Speaker 1: seen about the way that AI content takes off online. Like, Mike,

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Speaker 1: do you remember seeing shrimp Jesus on Facebook?

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Speaker 2: Yeah? I do. That felt like a good use of AI.

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Speaker 1: Better than this, for sure. So Shrimp Jesus was this

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Speaker 1: AI slap that was all over Facebook for a while,

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Speaker 1: and you know, with AI, people pump out all kinds

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Speaker 1: of weird stuff something hits, and then they just pump

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Speaker 1: out more and more and more exaggerated versions of that

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Speaker 1: first iteration of the thing that hit because they found

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Speaker 1: sectatus and they just want to like see if they

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Speaker 1: can duplicate that over and over and over again. So

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Speaker 1: at first it's just an AI image of Jesus Christ

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Speaker 1: writing a giant shrimp. But at the end, it's like

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Speaker 1: Jesus and he's entirely made out of shrimp, and he

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Speaker 1: has like lobster legs and crawdad arms and like little

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Speaker 1: shumpy crustacean disciples and stuff all around him. Like it's

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Speaker 1: just like a more and more exaggerated version of that

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Speaker 1: first thing that initially hit with a little bit of

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Speaker 1: virality on social media.

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Speaker 2: And I feel that's like what AI is really good at,

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Speaker 2: just taking something and making it more and more extreme

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Speaker 2: and absurd. And it was pretty funny, but it also

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Speaker 2: felt kind of like harmless, you know, like Jesus and

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Speaker 2: shrimp were not actually being harmed in that series of videos.

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Speaker 1: Well that's the thing. Like it's one thing when it's

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Speaker 1: something that's nonsensical or silly, like a picture of Jesus

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Speaker 1: made out of shrimp. It is another when we are

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Speaker 1: talking about potentially harmful depictions of historically marginalized people that

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Speaker 1: affirm existing political or social ideologies or stereotypes. So even

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Speaker 1: though the original originator of these kinds of videos is black,

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Speaker 1: I know for a fact that a lot of the

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Speaker 1: people who are making them now, who are kind of

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Speaker 1: doing that sort of extreme version, are not black. And

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Speaker 1: I would call that digital blackface, where non black people

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Speaker 1: are using online tools like AI to depict black identity

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Speaker 1: in these highly racist, highly exaggerated, highly stereotypical ways that

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Speaker 1: can be really harmful and also are used to reaffirm

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Speaker 1: existing political or social ideologies or worldviews. Like I am

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Speaker 1: super comfortable saying these videos are using this format to

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Speaker 1: intentionally depict black women and black people in ways that

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Speaker 1: are racist. It is not an accident. So let's watch

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Speaker 1: a few more to get a sense of what I'm

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Speaker 1: talking about. So this video is a take on the

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Speaker 1: first iteration of the video that I talked about earlier.

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Speaker 1: Look at me, slam my, curly wave blonde. Wig ahh.

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Speaker 2: That's not your natural color.

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Speaker 6: The only color you should be worried about is which

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Speaker 6: color palette they've gonna use on you.

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Speaker 1: At the more coke. So it's the same setup. A

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Speaker 1: black woman walked an AI generated black woman being like, Ooh,

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Speaker 1: I love this hair. Some pretty egregious aave going on

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Speaker 1: in this in this video, but that a white woman

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Speaker 1: comes up to her, SOA's like, that's not your natural

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Speaker 1: hair color. It ends in a threat of violence, and

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Speaker 1: the black woman actually lunges at the white lady who

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Speaker 1: is talking shit about her hair. And so again you

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Speaker 1: can see how in the first iteration of that video,

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Speaker 1: the woman is just able to like check the white

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Speaker 1: lady who's talking shit about her hair, was like a

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Speaker 1: cunning phrase, and go on about her day. In this one,

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Speaker 1: but not only is the woman more exaggerated, her response

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Speaker 1: is like a threat of violence and a violent attack.

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Speaker 1: It's we've we've we've really ratcheted up the ratchet, so

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Speaker 1: to speak.

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Speaker 2: Yeah, And the thing that got ratcheted down was the

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Speaker 2: quality of the joke, because that first joke death is

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Speaker 2: waiting for you at the bingo table, that is so

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Speaker 2: much better than the second one about what color palette.

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Speaker 2: The more that that's weak.

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Speaker 1: That's the thing is that that initial video is I

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Speaker 1: think it's like I get what they're going for. It's

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Speaker 1: like clever. This is hardly even a joke, And it

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Speaker 1: actually gets even worse because another iteration of these sort

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Speaker 1: of AI generated racist videos on TikTok is this very

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Speaker 1: popular account where it's female Bigfoot and basically it depicts

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Speaker 1: a gorilla like Bigfoot as a black woman. So here's

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Speaker 1: one of the videos that got two million views on TikTok.

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Speaker 1: What's up, bitch? Is this Bigfoot? One hand the baddest

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Speaker 1: bitch in the woods? Part time cryptic, full time problem.

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Speaker 1: Don't follow me if you scare a flease. So talk

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Speaker 1: about exaggerated. It is a bigfoot with like blonde extensions,

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Speaker 1: wearing like a pink bikini and speaking like you just heard,

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Speaker 1: and there's I mean, there's not even really the joke

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Speaker 1: is just like black women are animals, like black women

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Speaker 1: are ghetto and black women are animals like that, Like

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Speaker 1: that's the joke in quotation marks.

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Speaker 2: Yeah, it's not much of a joke.

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Speaker 1: I mean, that's the thing about racist content like this

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Speaker 1: is that they're barely even jokes. So when people are like, oh,

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Speaker 1: it's just a joke, what is the joke? You know

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Speaker 1: what I'm saying, Like, they're barely even jokes. There's an

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Speaker 1: entire bucket of this kind of content that is AI generated,

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Speaker 1: which people are calling slave talk, which essentially is meant

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Speaker 1: to show enslaved people on plantations, but it reimagined if

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Speaker 1: they had social media and we're doing vlogs. Here's one example.

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Speaker 7: Some of y'all think it's hard doing what I do.

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Speaker 7: Some of y'all all so lazy, So that could be

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Speaker 7: why MASSA got us working an extra hard today. But

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Speaker 7: that's fine with me as long as I'm getting dinner tonight.

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Speaker 1: So that's obviously meant to show this idea that like

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Speaker 1: slavery wasn't that bad and that enslaved people were actually

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Speaker 1: happy to be enslaved, which is a very common trope

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Speaker 1: that we saw in minstrel shows that was used to

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Speaker 1: really try to convince people who might otherwise be abolitionists

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Speaker 1: that slavery was actually good for black people. It gave

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Speaker 1: them food, it gave them stability, it gave them housing.

433
00:24:20,760 --> 00:24:23,240
Speaker 1: You know, they didn't really mind it. They were always

434
00:24:23,280 --> 00:24:26,320
Speaker 1: like smiling and dancing and happy, and so it is

435
00:24:26,400 --> 00:24:29,359
Speaker 1: very funny to me how AI is being used to

436
00:24:29,400 --> 00:24:33,720
Speaker 1: say the literal exact same thing folks were saying to

437
00:24:34,040 --> 00:24:37,120
Speaker 1: affirm that slavery wasn't that bad two hundred years ago.

438
00:24:37,600 --> 00:24:40,239
Speaker 2: And again, there was no joke there at all, Like

439
00:24:40,280 --> 00:24:44,280
Speaker 2: it wasn't even trying to be funny. It was just

440
00:24:44,640 --> 00:24:47,800
Speaker 2: deserving that purpose exactly.

441
00:24:48,359 --> 00:24:51,120
Speaker 1: And so when people say, oh, it's not that deep,

442
00:24:51,119 --> 00:24:53,879
Speaker 1: it's just a joke again, like I would love to,

443
00:24:53,880 --> 00:24:57,119
Speaker 1: I'm like missing the joke. I'm not see I'm not

444
00:24:57,280 --> 00:24:58,960
Speaker 1: seeing the joke now.

445
00:24:59,000 --> 00:24:59,760
Speaker 2: There was no joke.

446
00:25:00,160 --> 00:25:03,520
Speaker 1: Some of these slave talk videos also depict enslaved people

447
00:25:03,920 --> 00:25:08,639
Speaker 1: doing like very explicitly racist stereotypical stuff like eating watermelon

448
00:25:08,720 --> 00:25:12,520
Speaker 1: and drinking grape kool aid, like over the top racist imagery.

449
00:25:12,760 --> 00:25:16,199
Speaker 1: There's also AI videos of black women eating lots and

450
00:25:16,240 --> 00:25:18,840
Speaker 1: lots of fried chicken as part of like muck bangs,

451
00:25:18,920 --> 00:25:21,119
Speaker 1: those videos where you eat a lot of food, and

452
00:25:21,240 --> 00:25:27,840
Speaker 1: even AI generated criminals vlogging violent crime sprees. So as

453
00:25:27,880 --> 00:25:30,600
Speaker 1: bad as those are, I will say that not all

454
00:25:30,680 --> 00:25:34,720
Speaker 1: of these AI generated videos on TikTok are over the

455
00:25:34,760 --> 00:25:38,639
Speaker 1: top explicitly racist skits. Some are just really stupid, like

456
00:25:38,760 --> 00:25:44,040
Speaker 1: AI versions of Tyler Perry morality plays. I saw one

457
00:25:44,240 --> 00:25:48,000
Speaker 1: where it was a black mom telling her black daughter

458
00:25:48,040 --> 00:25:50,119
Speaker 1: to wash the dishes and the black daughter was like, no,

459
00:25:50,160 --> 00:25:53,120
Speaker 1: I don't want to wash the dishes, and it ends

460
00:25:53,160 --> 00:25:58,040
Speaker 1: with her mom being like her her mom's funeral essentially,

461
00:25:58,320 --> 00:26:03,200
Speaker 1: So it's a lot of like very simple morality place stories,

462
00:26:03,840 --> 00:26:06,159
Speaker 1: if I'm being honest, Like, I hate to say this,

463
00:26:06,359 --> 00:26:10,159
Speaker 1: but I'm sorry, it's just true. It's the kind of

464
00:26:10,280 --> 00:26:14,840
Speaker 1: content that I know absolutely fucking hits with some people

465
00:26:14,880 --> 00:26:17,520
Speaker 1: in my family. Like when I look at some of

466
00:26:17,560 --> 00:26:21,119
Speaker 1: my auntie's Facebook feeds, it's covered with this kind of

467
00:26:21,760 --> 00:26:26,120
Speaker 1: AI generated morality play skits, and they love it. They

468
00:26:26,160 --> 00:26:28,920
Speaker 1: don't care that it's AI, they don't care that it's

469
00:26:28,920 --> 00:26:33,080
Speaker 1: not real. They just like to see their world views

470
00:26:33,280 --> 00:26:37,120
Speaker 1: reaffirmed in these skits. And again I'm not talking about

471
00:26:38,000 --> 00:26:42,520
Speaker 1: explicitly racist skits. Just if the worldview could be kids

472
00:26:42,560 --> 00:26:45,040
Speaker 1: don't have any respect today, you know, if that's a

473
00:26:45,080 --> 00:26:48,880
Speaker 1: worldview you hold, if you're watching an AI generated garbage skit,

474
00:26:48,960 --> 00:26:51,919
Speaker 1: that reaffirms that you're gonna like it. And one of

475
00:26:51,960 --> 00:26:55,080
Speaker 1: the reasons why I am not super surprised by how

476
00:26:55,200 --> 00:26:58,480
Speaker 1: popular this kind of content has gotten is because of

477
00:26:58,520 --> 00:27:03,120
Speaker 1: the absolute choke that skit culture on social media had

478
00:27:03,280 --> 00:27:05,880
Speaker 1: even before the rise of the AI skit that we're

479
00:27:05,880 --> 00:27:08,399
Speaker 1: seeing now. It is something I've been screaming about for

480
00:27:08,440 --> 00:27:11,600
Speaker 1: a really long time, how people were making money off

481
00:27:11,600 --> 00:27:14,760
Speaker 1: of creating skits on TikTok and Facebook that depicted things

482
00:27:14,760 --> 00:27:18,400
Speaker 1: that never happened. And I'm not talking about obviously fictionalized

483
00:27:18,440 --> 00:27:21,320
Speaker 1: skits like you might see on Saturday Night Live or Portlandia.

484
00:27:21,440 --> 00:27:24,359
Speaker 1: I mean skits that you see on social media that

485
00:27:24,400 --> 00:27:28,080
Speaker 1: are intentionally blurring the line between fiction and reality to

486
00:27:28,240 --> 00:27:31,320
Speaker 1: try to get viewers to think they are watching footage

487
00:27:31,400 --> 00:27:33,560
Speaker 1: that somebody captured on their cell phone of something that

488
00:27:33,600 --> 00:27:36,479
Speaker 1: really happened, even though they're not, even though these are

489
00:27:36,520 --> 00:27:38,960
Speaker 1: actors and a skit that's been set up. You've probably

490
00:27:39,000 --> 00:27:41,720
Speaker 1: seen a million of these on social media and maybe

491
00:27:41,760 --> 00:27:45,040
Speaker 1: not thought too much about it. Have you seen these? Yeah?

492
00:27:45,119 --> 00:27:47,679
Speaker 2: I have definitely seen these where it'll be like some

493
00:27:47,800 --> 00:27:52,919
Speaker 2: kind of faith confrontation where somebody gets their come upance

494
00:27:53,040 --> 00:27:56,439
Speaker 2: or has a really good retort or something. Yeah, I

495
00:27:56,440 --> 00:27:58,480
Speaker 2: don't know how common they are. If my phone just

496
00:27:58,520 --> 00:28:00,879
Speaker 2: thinks that that's content, I like, I always feel a

497
00:28:00,920 --> 00:28:04,240
Speaker 2: little like guilty and dirty when I like that sort

498
00:28:04,280 --> 00:28:06,840
Speaker 2: of like somebody gotta come up and kind of skit

499
00:28:07,040 --> 00:28:10,320
Speaker 2: Like I guess sort of similar to those morality plays

500
00:28:10,320 --> 00:28:14,000
Speaker 2: that you were talking about, but yeah, they happen a lot.

501
00:28:14,480 --> 00:28:17,879
Speaker 1: Well, so again I don't really care that much. You know,

502
00:28:18,440 --> 00:28:21,800
Speaker 1: people love morality plays. I'm obsessed with Judge Judy because

503
00:28:21,800 --> 00:28:25,520
Speaker 1: I love I find the formula of someone getting you know,

504
00:28:25,720 --> 00:28:29,439
Speaker 1: getting come upance to be satisfying to watch over and

505
00:28:29,480 --> 00:28:31,760
Speaker 1: over and over again. You know, I don't love the

506
00:28:31,840 --> 00:28:34,080
Speaker 1: idea of people not being able to tell a real

507
00:28:34,119 --> 00:28:37,800
Speaker 1: situation from a fake situation and getting legitimately worked up

508
00:28:37,840 --> 00:28:41,160
Speaker 1: over a fictional scenario or whatever. But I think there

509
00:28:41,200 --> 00:28:43,360
Speaker 1: is a line where these skits go from really stupid

510
00:28:43,520 --> 00:28:46,840
Speaker 1: entertainment that isn't hurting anybody to legit harmful, and that

511
00:28:46,920 --> 00:28:49,400
Speaker 1: line is when they are used to affirm a harmful

512
00:28:49,800 --> 00:28:55,240
Speaker 1: existing worldview that actually ends up endangering marginalized people. For instance,

513
00:28:55,440 --> 00:28:58,920
Speaker 1: there was a very common skit format on TikTok for

514
00:28:58,960 --> 00:29:00,880
Speaker 1: a while, but I've seen a less of it lately.

515
00:29:01,200 --> 00:29:05,960
Speaker 1: Go figure where it was attacking trans people or like

516
00:29:06,040 --> 00:29:10,200
Speaker 1: the idea of transness or queerness in classrooms. So these

517
00:29:10,360 --> 00:29:14,040
Speaker 1: videos would purport to show situations that would be described

518
00:29:14,120 --> 00:29:18,120
Speaker 1: as like mom has had enough of trans teacher pushing

519
00:29:18,120 --> 00:29:20,640
Speaker 1: her agenda on her kid, and then it would show

520
00:29:20,640 --> 00:29:24,000
Speaker 1: a woman coming in and yelling at a teacher who

521
00:29:24,080 --> 00:29:26,440
Speaker 1: we are as the audience is to assume as trans.

522
00:29:26,680 --> 00:29:30,280
Speaker 1: But then you would see another video where you'd see

523
00:29:30,280 --> 00:29:32,520
Speaker 1: that same woman that we were just told as an

524
00:29:32,560 --> 00:29:35,920
Speaker 1: angry mom, but this time she's a transparent who is

525
00:29:36,040 --> 00:29:38,720
Speaker 1: yelling at a teacher for telling her kid the truth

526
00:29:38,760 --> 00:29:42,040
Speaker 1: that there are only two genders or something like these

527
00:29:42,080 --> 00:29:47,400
Speaker 1: incredibly staged skits in staged classrooms that are meant to

528
00:29:47,480 --> 00:29:52,640
Speaker 1: affirm sort of an existing attitude around trans folks. And again,

529
00:29:52,680 --> 00:29:54,920
Speaker 1: you can't act like this kind of content as popping

530
00:29:54,920 --> 00:29:57,480
Speaker 1: off in a vacuum, because it is actually happening against

531
00:29:57,520 --> 00:30:01,760
Speaker 1: the backdrop of trans and queer folks being threatened, targeted, criminalized,

532
00:30:01,800 --> 00:30:04,720
Speaker 1: and so on. So of course, skit after skit after

533
00:30:04,800 --> 00:30:07,840
Speaker 1: skit that makes them look threatening or foolish is going

534
00:30:07,880 --> 00:30:09,760
Speaker 1: to be used to provide justification for the kinds of

535
00:30:09,800 --> 00:30:13,960
Speaker 1: anti trans bigotry that we see today only massed as entertainment.

536
00:30:14,320 --> 00:30:17,719
Speaker 1: So again, there isn't necessarily anything inherently wrong with this

537
00:30:17,800 --> 00:30:20,280
Speaker 1: kind of content, but the issue is that people either

538
00:30:20,360 --> 00:30:23,240
Speaker 1: can't tell that their skits or maybe worse, don't even

539
00:30:23,280 --> 00:30:25,960
Speaker 1: really care that their skits. They are just thinking this

540
00:30:26,000 --> 00:30:28,880
Speaker 1: is mindless entertainment on their phone, and that the casual

541
00:30:29,000 --> 00:30:31,480
Speaker 1: viewer is probably not stopping to think about the impact

542
00:30:31,520 --> 00:30:34,920
Speaker 1: this kind of content has, especially if it is reaffirming

543
00:30:34,920 --> 00:30:36,760
Speaker 1: a worldview that they already might hold.

544
00:30:37,400 --> 00:30:39,880
Speaker 2: That's something we've talked about a lot on this show.

545
00:30:40,080 --> 00:30:44,600
Speaker 2: Is like one of the most dangerous aspects of AI

546
00:30:44,840 --> 00:30:49,040
Speaker 2: is the way it's facilitating a further breakdown of people's

547
00:30:49,040 --> 00:30:52,760
Speaker 2: ability to distinguish what's real from what isn't. I feel

548
00:30:52,800 --> 00:30:55,520
Speaker 2: like that comes up again and again when we're talking

549
00:30:55,760 --> 00:31:01,040
Speaker 2: about the risks and harms that are currently existing on

550
00:31:01,120 --> 00:31:05,000
Speaker 2: the Internet and potentially getting worse now that AI is

551
00:31:05,360 --> 00:31:08,320
Speaker 2: getting so much better, so much cheaper and more accessible.

552
00:31:08,240 --> 00:31:11,600
Speaker 1: Exactly, and so with AI, you can really create this

553
00:31:11,760 --> 00:31:15,160
Speaker 1: kind of content at scale. And if you already think

554
00:31:15,200 --> 00:31:19,480
Speaker 1: that black women are loud, ghetto, violent, et cetera, et cetera,

555
00:31:20,000 --> 00:31:22,160
Speaker 1: it sort of does not matter that these skits are

556
00:31:22,200 --> 00:31:25,960
Speaker 1: obviously not real, because they still reinforce that belief, whether

557
00:31:26,040 --> 00:31:27,000
Speaker 1: they are real or not.

558
00:31:30,240 --> 00:31:42,760
Speaker 5: More after a quick break, let's get right back into it.

559
00:31:44,880 --> 00:31:47,520
Speaker 1: In the comments of one of those videos, I watched

560
00:31:47,520 --> 00:31:50,280
Speaker 1: of a black woman threatening a white woman who was

561
00:31:50,360 --> 00:31:53,600
Speaker 1: talking about her hair. Someone in the comments wrote, why

562
00:31:53,640 --> 00:31:57,440
Speaker 1: are they all caps so aggressive? And you know, as

563
00:31:57,480 --> 00:31:59,920
Speaker 1: a black person on the internet, I know exactly who's

564
00:32:00,120 --> 00:32:03,680
Speaker 1: they is in that comment, And like, even though this

565
00:32:03,880 --> 00:32:07,760
Speaker 1: video was AI, that does not depict any real human

566
00:32:07,960 --> 00:32:11,800
Speaker 1: black or otherwise, it still reaffirmed the idea that black

567
00:32:11,840 --> 00:32:15,280
Speaker 1: women are like this, and that commenter's comment just further

568
00:32:15,360 --> 00:32:18,840
Speaker 1: reaffirms that to anybody reading that comment. Now, I also,

569
00:32:18,960 --> 00:32:21,360
Speaker 1: I mean not to get too down the rabbit hole

570
00:32:21,440 --> 00:32:23,640
Speaker 1: more than I already am, because you know, I can

571
00:32:23,680 --> 00:32:27,000
Speaker 1: talk about this forever. Then I was thinking, like, is

572
00:32:27,040 --> 00:32:31,800
Speaker 1: it possible that that comment is a bot? Like dead

573
00:32:31,880 --> 00:32:36,880
Speaker 1: Internet theory? Is this bots making bot content for bot commentators?

574
00:32:36,960 --> 00:32:39,200
Speaker 1: Is it just like bots the whole way down?

575
00:32:39,760 --> 00:32:43,320
Speaker 2: It does make one crazy, but also I don't think

576
00:32:43,320 --> 00:32:46,320
Speaker 2: you're crazy for it saying then there's a lot of bots. Yeah,

577
00:32:46,480 --> 00:32:50,800
Speaker 2: it's but maybe it doesn't even matter. Like if you know,

578
00:32:50,840 --> 00:32:55,600
Speaker 2: if some human reads that comment, it still has an

579
00:32:55,600 --> 00:32:58,760
Speaker 2: impression on them, regardless of who wrote that comment, what

580
00:32:58,800 --> 00:33:03,480
Speaker 2: their intention was. It gets pretty circular in ways that

581
00:33:04,160 --> 00:33:05,760
Speaker 2: quickly become disoriented.

582
00:33:06,240 --> 00:33:10,240
Speaker 1: This reminds me. This is on a side. But on Instagram,

583
00:33:10,320 --> 00:33:14,360
Speaker 1: I made a video about a like not trusting AI content,

584
00:33:14,440 --> 00:33:16,840
Speaker 1: and somebody left me a comment that was like, I mean,

585
00:33:16,920 --> 00:33:19,280
Speaker 1: aren't pretty rich for you to say, aren't you AI?

586
00:33:19,960 --> 00:33:23,560
Speaker 1: And I thought, ooh, and literally I'm not even kidding.

587
00:33:23,560 --> 00:33:28,240
Speaker 1: For a minute, I was like, am I.

588
00:33:28,320 --> 00:33:29,560
Speaker 2: You would be the last to know.

589
00:33:30,040 --> 00:33:32,000
Speaker 1: Like like, that's that's what I'm saying. Like I was

590
00:33:32,040 --> 00:33:34,640
Speaker 1: sort of like I thought I had a childhood and

591
00:33:34,800 --> 00:33:37,360
Speaker 1: parent and like I thought I had gotten blood drawn

592
00:33:37,360 --> 00:33:39,120
Speaker 1: at the doctor. But then I was like, if you

593
00:33:39,200 --> 00:33:42,080
Speaker 1: were AI, you probably wouldn't know you were AI. So

594
00:33:42,160 --> 00:33:45,240
Speaker 1: that comment was like am I AI? And then I

595
00:33:45,560 --> 00:33:48,239
Speaker 1: have to say I was weirdly sort of flattered that

596
00:33:48,280 --> 00:33:51,480
Speaker 1: she thought I was Ai. That this is probably revealing

597
00:33:51,520 --> 00:33:53,840
Speaker 1: all kinds of messed up ways about the way I think.

598
00:33:53,880 --> 00:33:55,640
Speaker 1: But I was like, oh, if I'm AI, that means

599
00:33:55,680 --> 00:33:57,400
Speaker 1: like my skin must be looking good and my hair

600
00:33:57,480 --> 00:33:59,920
Speaker 1: must be looking good, and I must be sounding, you know,

601
00:34:00,000 --> 00:34:02,880
Speaker 1: so well spoken or something. I'm not making all kinds

602
00:34:02,880 --> 00:34:05,360
Speaker 1: of ticks and likes and beeps and bloops like she

603
00:34:05,440 --> 00:34:07,840
Speaker 1: must I must be really like on my gain if

604
00:34:07,840 --> 00:34:08,920
Speaker 1: she thinks I'm AI.

605
00:34:10,719 --> 00:34:13,080
Speaker 2: I don't know, bridget. I don't think aspiring to be

606
00:34:13,239 --> 00:34:15,759
Speaker 2: AI is the right direction here. I feel there might

607
00:34:15,800 --> 00:34:18,239
Speaker 2: be some negative consequences of that.

608
00:34:18,800 --> 00:34:21,000
Speaker 1: I'm not saying I'm a suspiring to be AI. I

609
00:34:21,120 --> 00:34:25,280
Speaker 1: just thought that thinking getting confused that I am AI

610
00:34:25,960 --> 00:34:28,920
Speaker 1: because like AI doesn't get zits, you know, AI doesn't

611
00:34:28,920 --> 00:34:30,520
Speaker 1: have like bad skin. I was like, oh, this must

612
00:34:30,520 --> 00:34:32,000
Speaker 1: to be like like I don't know I was. I

613
00:34:32,040 --> 00:34:34,520
Speaker 1: was weirdly flattered and it's probably not worth unpacking why

614
00:34:34,520 --> 00:34:35,680
Speaker 1: I've had his Let's just move on.

615
00:34:35,960 --> 00:34:38,399
Speaker 2: We need to move on. This is unsettling.

616
00:34:40,560 --> 00:34:41,919
Speaker 1: It's just what an AI would say.

617
00:34:42,840 --> 00:34:45,319
Speaker 2: I feel like this every time I have to do

618
00:34:45,360 --> 00:34:47,600
Speaker 2: a catcha I'm so bad at captures.

619
00:34:48,600 --> 00:34:50,480
Speaker 1: Oh you're bad at capture to the point that I

620
00:34:50,520 --> 00:34:51,880
Speaker 1: think that you are a robot.

621
00:34:52,120 --> 00:34:55,080
Speaker 2: It makes me wonder, and the instructions often are like

622
00:34:55,400 --> 00:34:59,719
Speaker 2: confirm your humanity and then I fail to test. It's

623
00:34:59,760 --> 00:35:02,240
Speaker 2: like deeply threatening and upsetting.

624
00:35:02,840 --> 00:35:04,640
Speaker 1: Oh my god, So I mean talk about like bots

625
00:35:04,640 --> 00:35:07,520
Speaker 1: talking to bots. I'm Ai. I'm making a podcast with

626
00:35:07,600 --> 00:35:11,000
Speaker 1: my bot producer. Like it it's all bots that the

627
00:35:11,000 --> 00:35:11,640
Speaker 1: whole way.

628
00:35:11,480 --> 00:35:15,160
Speaker 2: Down, and it's all for that one human listener out there,

629
00:35:16,520 --> 00:35:20,200
Speaker 2: We know who you are. This is all for you.

630
00:35:20,680 --> 00:35:25,520
Speaker 1: So even if these are bots, you know, responding to

631
00:35:25,560 --> 00:35:28,000
Speaker 1: this commentary, and it's all just bots the whole way down,

632
00:35:28,080 --> 00:35:31,280
Speaker 1: and you know, there's no human black women being depicted

633
00:35:31,280 --> 00:35:35,560
Speaker 1: in these AI generated viral videos, that does not mean

634
00:35:35,600 --> 00:35:39,160
Speaker 1: that they aren't saying something about our culture. And just

635
00:35:39,320 --> 00:35:43,200
Speaker 1: like that rise in popularity in minstrel shows was against

636
00:35:43,239 --> 00:35:47,760
Speaker 1: the backdrop of a very real, very dark, difficult political

637
00:35:47,760 --> 00:35:50,160
Speaker 1: and social climate for black folks in the United States,

638
00:35:50,480 --> 00:35:53,160
Speaker 1: coinciding with the rise of Jim Crow after the end

639
00:35:53,200 --> 00:35:57,000
Speaker 1: of Reconstruction. I would argue that these racist AI skits

640
00:35:57,280 --> 00:36:00,439
Speaker 1: are taking off in popularity at a time when black

641
00:36:00,480 --> 00:36:04,400
Speaker 1: people's contributions to history are being literally erased at the

642
00:36:04,440 --> 00:36:08,000
Speaker 1: federal level. Black women, black folks, folks of color, we

643
00:36:08,040 --> 00:36:12,320
Speaker 1: are all being attacked and threatened in new and increasing

644
00:36:12,360 --> 00:36:15,319
Speaker 1: ways every day. You know, there was this really meaty

645
00:36:15,400 --> 00:36:17,480
Speaker 1: piece in ProPublica that I'll link in the show, not

646
00:36:17,600 --> 00:36:20,160
Speaker 1: just because it's like a fascinating piece of journalism and

647
00:36:20,200 --> 00:36:24,040
Speaker 1: I love ProPublica about how Trump and Musk Stage and

648
00:36:24,760 --> 00:36:28,080
Speaker 1: all of their pundits attacks on so called DII was

649
00:36:28,160 --> 00:36:31,840
Speaker 1: really an attack on black women with stable federal government jobs,

650
00:36:32,160 --> 00:36:35,400
Speaker 1: and that these attacks targeted and are still targeting the

651
00:36:35,440 --> 00:36:39,479
Speaker 1: government careers of highly educated civil servants. Even though many

652
00:36:39,520 --> 00:36:42,160
Speaker 1: of these people their jobs didn't have anything to do

653
00:36:42,200 --> 00:36:44,440
Speaker 1: with DEI, they were not connected or involved with the

654
00:36:44,480 --> 00:36:48,880
Speaker 1: EI at any capacity, their careers were derailed under this

655
00:36:49,000 --> 00:36:51,840
Speaker 1: false premise that they were diversity hires. This might have

656
00:36:51,960 --> 00:36:55,560
Speaker 1: nothing to do with DEI have and instead have everything

657
00:36:55,600 --> 00:36:58,400
Speaker 1: to do with being just being black women and becoming

658
00:36:58,520 --> 00:37:03,279
Speaker 1: an easy target for administration hostile to marginalize people. Right,

659
00:37:03,360 --> 00:37:06,279
Speaker 1: and so if all of that is happening at the

660
00:37:06,320 --> 00:37:09,080
Speaker 1: same time where we have this rise of this new

661
00:37:09,160 --> 00:37:13,600
Speaker 1: form of digital media that uses AI to reaffirm hurtful,

662
00:37:14,040 --> 00:37:17,279
Speaker 1: harmful stereotypes about black women like me, about how we're

663
00:37:17,680 --> 00:37:20,200
Speaker 1: not able to behave ourselves in polite society, how we

664
00:37:20,239 --> 00:37:22,920
Speaker 1: can't really figure out a way to solve conflicts without

665
00:37:22,960 --> 00:37:25,759
Speaker 1: resorting to violence, how we really are like loud and

666
00:37:25,800 --> 00:37:28,400
Speaker 1: obnoxious and stupid and aggressive, and all of these things.

667
00:37:28,880 --> 00:37:32,040
Speaker 1: When you hear about real life black women getting pushed

668
00:37:32,080 --> 00:37:35,959
Speaker 1: out of their stable employment, folks might think, well, maybe

669
00:37:36,000 --> 00:37:37,840
Speaker 1: it's for the best, because they're not suited for that

670
00:37:37,960 --> 00:37:41,560
Speaker 1: work anyway, just like we saw with minstrel shows of yesteryear.

671
00:37:41,640 --> 00:37:43,680
Speaker 1: I do think that this kind of content is not

672
00:37:43,719 --> 00:37:46,600
Speaker 1: a coincidence, but this kind of content is rising in

673
00:37:46,640 --> 00:37:49,920
Speaker 1: popularity against the backdrop of all of these other social

674
00:37:49,960 --> 00:37:53,880
Speaker 1: and political attacks on black women. It's simply using AI

675
00:37:54,080 --> 00:37:57,680
Speaker 1: to reaffirm this worldview that real life human Black women

676
00:37:58,080 --> 00:38:00,960
Speaker 1: are not self actualized human beings, where it's a collection

677
00:38:01,040 --> 00:38:04,680
Speaker 1: of tropes and stereotypes and characters who really don't have

678
00:38:04,760 --> 00:38:08,920
Speaker 1: a place in like mainstream modern society. When you actually

679
00:38:09,000 --> 00:38:11,880
Speaker 1: sit down and think about it, it's incredibly harmful, and

680
00:38:11,920 --> 00:38:15,520
Speaker 1: I think it contributes to an incredibly hostile environment for

681
00:38:15,640 --> 00:38:17,400
Speaker 1: Black women, both online and off.

682
00:38:18,120 --> 00:38:22,200
Speaker 2: It feels like white supremacy has been ascended over the

683
00:38:22,239 --> 00:38:25,919
Speaker 2: past few years, you know, in pretty scary ways, and

684
00:38:26,320 --> 00:38:29,759
Speaker 2: this AI is just being used to reinforce that. And

685
00:38:29,880 --> 00:38:34,719
Speaker 2: there is a time when social media platforms were more

686
00:38:34,800 --> 00:38:38,600
Speaker 2: aggressive than they are today, it seems, in fighting this

687
00:38:38,760 --> 00:38:42,920
Speaker 2: kind of stuff, and we know that I think all

688
00:38:42,920 --> 00:38:46,160
Speaker 2: of the platforms have really loosened or in some cases

689
00:38:47,000 --> 00:38:51,759
Speaker 2: eliminated their moderation around this stuff. Kiktok also in a

690
00:38:51,800 --> 00:38:56,719
Speaker 2: weird changing situation right now, but with these videos being

691
00:38:57,880 --> 00:39:01,320
Speaker 2: so harmful, aren't they against TikTok's community guidelines.

692
00:39:01,840 --> 00:39:07,040
Speaker 1: Well, not technically, but maybe so. These kinds of videos

693
00:39:07,080 --> 00:39:10,520
Speaker 1: are not technically against TikTok's moderation policies because they do

694
00:39:10,680 --> 00:39:15,000
Speaker 1: disclose that their AI. However, TikTok's community guidelines do say

695
00:39:15,000 --> 00:39:19,359
Speaker 1: that videos that traffic in stereotypes about protective classes are

696
00:39:19,400 --> 00:39:23,400
Speaker 1: not eligible to be on people's for you page recommendations. However,

697
00:39:23,520 --> 00:39:26,520
Speaker 1: since these videos are all over my for you page,

698
00:39:26,840 --> 00:39:30,000
Speaker 1: TikTok is clearly not moderating these videos in that way.

699
00:39:30,160 --> 00:39:31,480
Speaker 1: They could, but they're definitely not.

700
00:39:32,040 --> 00:39:34,760
Speaker 2: Maybe they should, Maybe they should.

701
00:39:35,680 --> 00:39:40,200
Speaker 1: I mean, I would argue that having a racist Bigfoot

702
00:39:40,280 --> 00:39:43,680
Speaker 1: skit that depicts Bigfoot as a black woman is probably

703
00:39:43,680 --> 00:39:46,319
Speaker 1: not making your platform any better. You don't have to,

704
00:39:47,080 --> 00:39:51,040
Speaker 1: like say people can't make videos like that. I personally

705
00:39:51,040 --> 00:39:53,560
Speaker 1: don't think people should make videos like that. But TikTok

706
00:39:53,880 --> 00:39:56,719
Speaker 1: can allow people to make those videos, but they don't

707
00:39:56,719 --> 00:39:59,200
Speaker 1: have to amplify them by putting them on people's for

708
00:39:59,239 --> 00:40:02,040
Speaker 1: you pages by allowing people to monetize them like. There

709
00:40:02,040 --> 00:40:04,239
Speaker 1: are all kinds of ways that they can illustrate that

710
00:40:04,280 --> 00:40:06,480
Speaker 1: this is not something that we think makes our platform

711
00:40:06,600 --> 00:40:10,759
Speaker 1: a better space. That is not preventing people from making

712
00:40:10,840 --> 00:40:12,560
Speaker 1: these kinds of videos if that's how they choose to

713
00:40:12,600 --> 00:40:13,200
Speaker 1: spend their time.

714
00:40:13,960 --> 00:40:17,840
Speaker 2: Absolutely, because we're talking about the for you page, the

715
00:40:18,040 --> 00:40:23,360
Speaker 2: platforms are not neutral in deciding what videos get boosted

716
00:40:23,480 --> 00:40:27,360
Speaker 2: and don't get boosted. Like every single platform is making

717
00:40:27,520 --> 00:40:31,360
Speaker 2: active decisions about what types of videos take off and don't.

718
00:40:31,440 --> 00:40:36,200
Speaker 2: And so if you're seeing that bigfoot video, it's because

719
00:40:36,840 --> 00:40:40,840
Speaker 2: they are actively deciding to allow it to be boosted.

720
00:40:41,120 --> 00:40:43,720
Speaker 1: And not only that. You know, as we talked about

721
00:40:43,719 --> 00:40:47,520
Speaker 1: with the Jesus shrimp metaphor, when one of these videos

722
00:40:47,560 --> 00:40:51,480
Speaker 1: gets five million views, six million views, it only encourages

723
00:40:51,560 --> 00:40:55,239
Speaker 1: other people to make similar videos. So by allowing it

724
00:40:55,280 --> 00:40:58,600
Speaker 1: to get rack up lots of views on people's FYP pages,

725
00:40:58,880 --> 00:41:00,920
Speaker 1: you are only ensuring that more people make this kind

726
00:41:00,920 --> 00:41:02,440
Speaker 1: of content. And if it's not that kind of content

727
00:41:02,480 --> 00:41:05,720
Speaker 1: you want flooding your platform, if I were running that platform,

728
00:41:05,719 --> 00:41:08,239
Speaker 1: I probably do something about it, especially when you have

729
00:41:09,040 --> 00:41:12,320
Speaker 1: multiple avenues of doing something about it at your disposal.

730
00:41:12,840 --> 00:41:15,480
Speaker 2: Yeah, so maybe this is a good sponsored transition into

731
00:41:16,200 --> 00:41:19,840
Speaker 2: the text that's behind this because you know, even just

732
00:41:19,880 --> 00:41:24,760
Speaker 2: the few months ago, I feel that AI video creation

733
00:41:25,160 --> 00:41:30,040
Speaker 2: software from prompts really wasn't quite there yet, but it

734
00:41:30,040 --> 00:41:33,399
Speaker 2: seems like something has changed. It's allowing all of these

735
00:41:33,480 --> 00:41:36,239
Speaker 2: videos to blood the algorithm.

736
00:41:36,480 --> 00:41:40,160
Speaker 1: Well, that thing that has changed is probably Google's VO three,

737
00:41:40,680 --> 00:41:43,840
Speaker 1: which is Google's latest AI video generation model, which is

738
00:41:43,840 --> 00:41:46,880
Speaker 1: designed to create realistic videos from text prompts with the

739
00:41:46,920 --> 00:41:50,960
Speaker 1: added capability of incorporating synchronized audio like dialogue, sound effects,

740
00:41:51,000 --> 00:41:54,600
Speaker 1: and music. With this kind of technology, creators can push

741
00:41:54,600 --> 00:41:57,879
Speaker 1: out content like this at scale. It came out about

742
00:41:57,920 --> 00:41:59,959
Speaker 1: a month ago and it's really been taking off since.

743
00:42:00,640 --> 00:42:02,920
Speaker 1: I will say it's one of those AI models where

744
00:42:02,920 --> 00:42:06,560
Speaker 1: people were like, this is gonna change everything. Every animator

745
00:42:06,600 --> 00:42:08,400
Speaker 1: is going to lose their job. Every actor is going

746
00:42:08,480 --> 00:42:10,440
Speaker 1: to be out of a job because of this technology.

747
00:42:10,800 --> 00:42:13,759
Speaker 1: It was a lot like the conversation around Google's kind

748
00:42:13,760 --> 00:42:17,440
Speaker 1: of audio version of this notebook LM, which can create

749
00:42:17,520 --> 00:42:20,359
Speaker 1: sort of very realistic sounding podcasts out of any kind

750
00:42:20,360 --> 00:42:23,279
Speaker 1: of text prompt but that everybody said the same thing,

751
00:42:23,560 --> 00:42:26,040
Speaker 1: like this is going to change everything. Podcasters are all

752
00:42:26,040 --> 00:42:27,480
Speaker 1: going to be out of a job. AI is going

753
00:42:27,520 --> 00:42:30,520
Speaker 1: to be doing podcasts. Human podcasters are all gonna get fucked.

754
00:42:30,800 --> 00:42:34,239
Speaker 1: But guess what y'all listening to me right now? Not

755
00:42:34,360 --> 00:42:36,799
Speaker 1: an AI version of me that I know of, So

756
00:42:36,960 --> 00:42:40,440
Speaker 1: I don't think that tool from Google actually changed everything

757
00:42:40,640 --> 00:42:43,920
Speaker 1: just yet, considering I'm still a human as far as

758
00:42:43,920 --> 00:42:46,240
Speaker 1: I know, hosting this podcast, Yeah.

759
00:42:46,080 --> 00:42:48,279
Speaker 2: As far as I know can confirm you are still

760
00:42:48,280 --> 00:42:48,880
Speaker 2: a huge.

761
00:42:51,760 --> 00:43:05,000
Speaker 5: More after a quick break, let's get right back into it.

762
00:43:06,680 --> 00:43:10,640
Speaker 1: Google's VIEO three has really taken off with creators online

763
00:43:10,840 --> 00:43:14,320
Speaker 1: trying to use this platform to create everything from AI

764
00:43:14,400 --> 00:43:18,440
Speaker 1: skits to AI muckbangers to AI influencers. I am in

765
00:43:18,480 --> 00:43:23,000
Speaker 1: a few spaces online for like women in AI, and

766
00:43:23,280 --> 00:43:27,839
Speaker 1: so many of them are asking for help learning about

767
00:43:27,840 --> 00:43:30,839
Speaker 1: how to create AI influencers that they hope they can

768
00:43:30,920 --> 00:43:35,400
Speaker 1: monetize via brand deals or even AI OnlyFans models to

769
00:43:35,480 --> 00:43:39,640
Speaker 1: do like explicit sexual content. Side note, Only Fans doesn't

770
00:43:39,680 --> 00:43:43,200
Speaker 1: actually allow AI content unless it's from a registered human

771
00:43:43,239 --> 00:43:46,920
Speaker 1: creator in sort of that person's likeness, so you couldn't

772
00:43:46,960 --> 00:43:51,000
Speaker 1: just theoretically make an AI OnlyFans model and then start

773
00:43:51,080 --> 00:43:55,120
Speaker 1: raking in money on only fans. However, other similar platforms

774
00:43:55,280 --> 00:43:57,719
Speaker 1: do have different rules around that, but in a lot

775
00:43:57,760 --> 00:44:01,279
Speaker 1: of these spaces designed for women and other people, to

776
00:44:01,360 --> 00:44:04,360
Speaker 1: learn about AI. So much of it is like how

777
00:44:04,360 --> 00:44:09,160
Speaker 1: can I create an AI avatar influencer to make money?

778
00:44:09,200 --> 00:44:12,120
Speaker 1: Like people are treating this like a business enterprise.

779
00:44:12,600 --> 00:44:17,279
Speaker 2: Makes sense, people would want to monetize this, and it

780
00:44:17,320 --> 00:44:19,799
Speaker 2: seems like a good way to get rich quick if

781
00:44:19,800 --> 00:44:23,480
Speaker 2: you could spin up one hundred or a thousand different influencers,

782
00:44:23,480 --> 00:44:26,200
Speaker 2: all of them out there racking up followings and selling products.

783
00:44:26,280 --> 00:44:29,840
Speaker 2: But are people actually making money from doing that?

784
00:44:30,400 --> 00:44:34,080
Speaker 1: Great question? So there are definitely big name AI influencers

785
00:44:34,080 --> 00:44:36,480
Speaker 1: who have been around for a long time, like the

786
00:44:36,600 --> 00:44:41,440
Speaker 1: very first AI generated influencer, Little Mikayla, who came out

787
00:44:41,480 --> 00:44:43,920
Speaker 1: in twenty sixteen, who we've previously talked about on the show.

788
00:44:44,200 --> 00:44:46,920
Speaker 1: I am certain that she makes tons of money for

789
00:44:46,960 --> 00:44:50,920
Speaker 1: the people who created her, which is a duo. She

790
00:44:51,360 --> 00:44:54,719
Speaker 1: has done brand deals for huge brands like Chanelle. She's

791
00:44:54,760 --> 00:44:59,200
Speaker 1: done like collabs with like human celebrities. She's huge. However,

792
00:45:00,080 --> 00:45:02,080
Speaker 1: she was really the first one, and she's like the

793
00:45:02,120 --> 00:45:04,920
Speaker 1: og who's been in the game the longest. It has

794
00:45:04,960 --> 00:45:09,120
Speaker 1: been difficult for me personally to confirm that normal people

795
00:45:09,320 --> 00:45:12,160
Speaker 1: who have not been doing this since twenty sixteen are

796
00:45:12,280 --> 00:45:16,080
Speaker 1: making real money on AI influencers right now, like nine

797
00:45:16,160 --> 00:45:18,920
Speaker 1: years later, when AI is more ubiquitous. I don't know

798
00:45:19,040 --> 00:45:22,320
Speaker 1: that people are actually making real money from doing that.

799
00:45:22,320 --> 00:45:24,840
Speaker 1: That doesn't mean that they're not, I'm saying I personally

800
00:45:25,080 --> 00:45:27,600
Speaker 1: have not seen any evidence of it. What I am

801
00:45:27,719 --> 00:45:30,040
Speaker 1: seeing is people who are sort of betting that there

802
00:45:30,160 --> 00:45:33,080
Speaker 1: is real money to be made soon and wanting to

803
00:45:33,120 --> 00:45:35,239
Speaker 1: be ahead of the curve by getting in on it

804
00:45:35,320 --> 00:45:37,160
Speaker 1: now and like learning about it now and setting it

805
00:45:37,200 --> 00:45:39,080
Speaker 1: up now, which like I can't even really fault them

806
00:45:39,120 --> 00:45:41,640
Speaker 1: for that, it makes sense to me. It's also kind

807
00:45:41,680 --> 00:45:45,600
Speaker 1: of hard to say because so much of the conversation

808
00:45:45,719 --> 00:45:49,920
Speaker 1: right now feels a little bit scammy. And by scamming,

809
00:45:50,000 --> 00:45:53,280
Speaker 1: I mean it's a lot of pay me to teach

810
00:45:53,400 --> 00:45:57,320
Speaker 1: you how to make money setting up an AI influencer vibe.

811
00:45:57,480 --> 00:46:00,880
Speaker 1: So everybody is talking about how much big money they're making,

812
00:46:00,920 --> 00:46:03,840
Speaker 1: how much money there is in this enterprise, and you

813
00:46:03,880 --> 00:46:06,040
Speaker 1: know all of that, But I cannot say that I

814
00:46:06,040 --> 00:46:08,640
Speaker 1: have personally seen evidence of all of this big money made.

815
00:46:08,680 --> 00:46:10,080
Speaker 1: And of course, if you're trying to get people to

816
00:46:10,120 --> 00:46:12,680
Speaker 1: pay you because you're the expert of making money at something,

817
00:46:13,239 --> 00:46:15,960
Speaker 1: of course you're going to say, oh, the business is booming.

818
00:46:16,040 --> 00:46:18,840
Speaker 1: I'm making so much money hand over fist. I cannot

819
00:46:18,880 --> 00:46:20,600
Speaker 1: confirm that. I can't demy it either, but I cannot

820
00:46:20,640 --> 00:46:23,239
Speaker 1: confirm myself. And it does kind of remind me of

821
00:46:23,280 --> 00:46:25,880
Speaker 1: the way that people talked about other kinds of online

822
00:46:26,040 --> 00:46:29,080
Speaker 1: side hustles to make money, like drop shipping, or creating

823
00:46:29,160 --> 00:46:33,000
Speaker 1: Canva templates, or creating online courses that you sell like

824
00:46:33,400 --> 00:46:35,680
Speaker 1: everybody who was really looking for a way to passively

825
00:46:35,760 --> 00:46:38,759
Speaker 1: generate money online, and so you would see all of

826
00:46:38,800 --> 00:46:41,840
Speaker 1: these side hustles popping up all over social media, and

827
00:46:41,840 --> 00:46:45,240
Speaker 1: then eventually the hustle will turn into I'm not selling Canva,

828
00:46:45,640 --> 00:46:48,359
Speaker 1: I'm selling a toolkit to teach people how they can

829
00:46:48,400 --> 00:46:50,840
Speaker 1: make money doing Canva, and that I always sort of

830
00:46:50,880 --> 00:46:52,640
Speaker 1: sniff that out as like a little bit of a

831
00:46:52,640 --> 00:46:55,400
Speaker 1: get rich quick scheme. And so I'm not saying that

832
00:46:55,480 --> 00:46:57,960
Speaker 1: nobody out there is making money off of AI influencing,

833
00:46:58,320 --> 00:47:00,600
Speaker 1: but just something about the way people are talking about

834
00:47:00,600 --> 00:47:03,799
Speaker 1: it gives me pause. The same way that people will

835
00:47:03,840 --> 00:47:06,680
Speaker 1: talk about drop shipping as using technology to get a

836
00:47:06,719 --> 00:47:09,920
Speaker 1: little money to make cheap junks that nobody really needs.

837
00:47:10,280 --> 00:47:12,120
Speaker 1: I feel that the way that people are talking about

838
00:47:12,160 --> 00:47:14,719
Speaker 1: AI content is a bit similar, like, how could I

839
00:47:14,840 --> 00:47:17,120
Speaker 1: use this powerful tool to make a little bit of

840
00:47:17,160 --> 00:47:20,960
Speaker 1: money pushing cheap AI garbage slop that doesn't make anybody

841
00:47:21,000 --> 00:47:25,160
Speaker 1: better informed, but maybe provide somebody a quick, cheap dopamine hit.

842
00:47:25,400 --> 00:47:28,160
Speaker 1: So yeah, I can't really confirm or deny that there

843
00:47:28,239 --> 00:47:31,120
Speaker 1: is big money to be made here, but in my opinion,

844
00:47:31,360 --> 00:47:33,279
Speaker 1: the smell I'm getting off of this is a little

845
00:47:33,320 --> 00:47:35,840
Speaker 1: bit of a desperate get rich quick scheme.

846
00:47:36,320 --> 00:47:38,680
Speaker 2: I also have to wonder if if that does turn

847
00:47:38,760 --> 00:47:43,040
Speaker 2: out to be something that works that people regular people

848
00:47:44,080 --> 00:47:49,840
Speaker 2: want to see AI generated influencers on their feeds. Meta

849
00:47:50,120 --> 00:47:52,920
Speaker 2: is going to take all of that, right, Like they're

850
00:47:52,960 --> 00:47:59,000
Speaker 2: already trying out AI characters in your social network to

851
00:47:59,040 --> 00:48:01,520
Speaker 2: talk to you. And I don't really see how this

852
00:48:01,719 --> 00:48:05,120
Speaker 2: is all that different from what they're trying to do.

853
00:48:05,760 --> 00:48:08,279
Speaker 2: And so if there's a nut to be cracked here,

854
00:48:08,360 --> 00:48:11,040
Speaker 2: as soon as somebody figures it out, Meda is gonna

855
00:48:11,360 --> 00:48:12,640
Speaker 2: just take it and it will be there.

856
00:48:13,280 --> 00:48:15,200
Speaker 1: Well, it's funny that you mentioned this because we actually

857
00:48:15,200 --> 00:48:18,120
Speaker 1: have an episode about this coming up about I mean,

858
00:48:18,480 --> 00:48:21,719
Speaker 1: Meta tried this back in January. They were rolling out

859
00:48:21,760 --> 00:48:26,759
Speaker 1: these AI chatbock character Instagram profiles and wouldn't you know it,

860
00:48:26,840 --> 00:48:29,600
Speaker 1: the first one they started with was a black queer woman,

861
00:48:30,200 --> 00:48:34,320
Speaker 1: and the outcry about that everybody it was a collective

862
00:48:34,440 --> 00:48:37,799
Speaker 1: films down, a collective boo. We hate it, we hate it,

863
00:48:37,800 --> 00:48:41,400
Speaker 1: we hate it. Then Zuckerberg was like, oh, JK, we

864
00:48:41,480 --> 00:48:44,120
Speaker 1: actually just rolled that out by mistake. It wasn't meant

865
00:48:44,160 --> 00:48:47,520
Speaker 1: to go live, and now we pulled it. We just

866
00:48:47,560 --> 00:48:51,160
Speaker 1: bullied him right out of that. But people, I mean,

867
00:48:51,360 --> 00:48:54,000
Speaker 1: Mark Zuckerberg has been saying that he thinks the future

868
00:48:54,120 --> 00:48:58,440
Speaker 1: of social media is AI, that it's AI, avatars, AI content,

869
00:48:58,600 --> 00:49:02,560
Speaker 1: AI influencers, everything AI, and that we will be really

870
00:49:02,600 --> 00:49:05,200
Speaker 1: satisfied and happy in a future where a big chunk

871
00:49:05,239 --> 00:49:08,000
Speaker 1: of our relationships and people that we connect with is

872
00:49:08,080 --> 00:49:11,080
Speaker 1: AI and not our human friends and a human community.

873
00:49:11,320 --> 00:49:14,319
Speaker 1: And so I do think like it does seem to

874
00:49:14,360 --> 00:49:17,920
Speaker 1: be the future that tech leaders who are poised to

875
00:49:17,920 --> 00:49:20,960
Speaker 1: make more money on it are pushing. For sure, whether

876
00:49:21,000 --> 00:49:24,440
Speaker 1: it's a future that solves an actual need or creates

877
00:49:24,480 --> 00:49:27,400
Speaker 1: actual value, I don't know if I agree with that,

878
00:49:27,600 --> 00:49:29,919
Speaker 1: And I just kind of hate that The big use

879
00:49:30,000 --> 00:49:32,839
Speaker 1: case of AI that people are jumping all over right

880
00:49:32,880 --> 00:49:37,680
Speaker 1: now is like, how can I displace black human creators

881
00:49:37,880 --> 00:49:42,480
Speaker 1: and voices to make AI creations that traffic and harmful

882
00:49:42,600 --> 00:49:45,120
Speaker 1: racist stereotypes to make a quick book. To be clear,

883
00:49:45,920 --> 00:49:50,880
Speaker 1: Meta's black woman chatbot also, I would argue did traffic

884
00:49:51,040 --> 00:49:55,960
Speaker 1: in stereotypes like she's spoken aave, she was really for

885
00:49:56,200 --> 00:49:58,480
Speaker 1: someone who is not human, really taking a lot of

886
00:49:58,560 --> 00:50:02,239
Speaker 1: liberties around black idea. And yeah, so I do think

887
00:50:02,280 --> 00:50:05,000
Speaker 1: it's all kind of related in terms of, like it's

888
00:50:05,040 --> 00:50:08,799
Speaker 1: not just you know, Joe Blow AI contact creator, it's

889
00:50:08,800 --> 00:50:10,400
Speaker 1: also Mark fucking Zuckerberg.

890
00:50:10,880 --> 00:50:17,239
Speaker 2: Right, so many people want all the value of an

891
00:50:17,320 --> 00:50:24,600
Speaker 2: expansive capitalists enterprise without the expense of humans being part

892
00:50:24,640 --> 00:50:27,560
Speaker 2: of it. If that's what the world is heading towards,

893
00:50:28,360 --> 00:50:31,920
Speaker 2: the ordinary people who are trying to hustle and like

894
00:50:32,000 --> 00:50:34,440
Speaker 2: throw together an AI avatar, they're not going to be

895
00:50:34,480 --> 00:50:36,360
Speaker 2: the ones who benefit from that. It's going to be

896
00:50:36,560 --> 00:50:38,520
Speaker 2: the Zuckerbergs and the Musks of the world.

897
00:50:38,800 --> 00:50:42,160
Speaker 1: Absolutely, and already tech leaders are betting on this being

898
00:50:42,160 --> 00:50:45,879
Speaker 1: the future of content. Gizmodo reported about this last week

899
00:50:46,080 --> 00:50:48,680
Speaker 1: was the end of the con festival, and the CEO

900
00:50:48,760 --> 00:50:51,960
Speaker 1: of YouTube, Neil Mohan, spoke and basically he said that

901
00:50:52,000 --> 00:50:57,480
Speaker 1: YouTube is doubling down on this as the big bet

902
00:50:57,520 --> 00:51:00,520
Speaker 1: for the future of creators on the platform, and they're

903
00:51:00,560 --> 00:51:04,319
Speaker 1: basically for their shorts for YouTube shorts. They are going

904
00:51:04,360 --> 00:51:07,920
Speaker 1: to be partnering with Google's vo three AI generator, so

905
00:51:07,960 --> 00:51:10,880
Speaker 1: it's going to be like a one stop shop for

906
00:51:11,080 --> 00:51:15,719
Speaker 1: easily creating this kind of AI generated video content. And

907
00:51:15,760 --> 00:51:20,960
Speaker 1: so you're absolutely right that tech leaders are really betting

908
00:51:21,080 --> 00:51:24,080
Speaker 1: on this being the future of the creator economy.

909
00:51:24,680 --> 00:51:26,840
Speaker 2: Yeah, the creator economy without creators.

910
00:51:27,200 --> 00:51:30,120
Speaker 1: Well, so you know that black creator who made the

911
00:51:30,160 --> 00:51:32,840
Speaker 1: first big viral Karen video that we were talking about,

912
00:51:32,840 --> 00:51:34,239
Speaker 1: the one that I was like, Oh, it's not so bad.

913
00:51:34,840 --> 00:51:37,799
Speaker 1: He actually set thinks that more people need to be

914
00:51:37,920 --> 00:51:41,080
Speaker 1: using AI to make depictions of black women and black

915
00:51:41,120 --> 00:51:44,520
Speaker 1: people that are not rooted in stereotypes. He actually created

916
00:51:44,600 --> 00:51:48,440
Speaker 1: a kind of AI call to action wherein these black

917
00:51:48,480 --> 00:51:53,239
Speaker 1: AI avatars all came together to demand better representation of

918
00:51:53,360 --> 00:51:56,160
Speaker 1: black AI avatars. Here's what they had to say.

919
00:51:56,680 --> 00:51:59,040
Speaker 6: It's crazy how people are now using AI to make

920
00:51:59,080 --> 00:52:01,839
Speaker 6: the black woman look neat and aggressive. And I'm sure

921
00:52:01,880 --> 00:52:04,839
Speaker 6: these TikTok accounts don't be from people like us. I

922
00:52:04,880 --> 00:52:07,160
Speaker 6: get it, it's just AI and fun, but making racist

923
00:52:07,200 --> 00:52:09,600
Speaker 6: slaves videos or having us black women prompts to fight

924
00:52:09,640 --> 00:52:11,439
Speaker 6: white old ladies is just a bit too much.

925
00:52:12,080 --> 00:52:14,960
Speaker 1: I'm going to enforce others to make more prompts like me.

926
00:52:15,640 --> 00:52:18,879
Speaker 7: Stop sitting around and get into AI and make more

927
00:52:18,920 --> 00:52:21,800
Speaker 7: prompts like us and to help show black beauty.

928
00:52:22,000 --> 00:52:24,880
Speaker 6: We can use AI to make black women prompts just

929
00:52:24,920 --> 00:52:28,320
Speaker 6: to show beauty and black women doing positive things. Thankful

930
00:52:28,320 --> 00:52:30,879
Speaker 6: for being created from a prompt because AI just don't

931
00:52:30,920 --> 00:52:33,040
Speaker 6: like to show many meloded women and feel like AI

932
00:52:33,120 --> 00:52:35,640
Speaker 6: still holds some type of impression on black culture.

933
00:52:36,520 --> 00:52:39,680
Speaker 7: See people use AI to make us look bad, but

934
00:52:39,760 --> 00:52:40,600
Speaker 7: we should look good.

935
00:52:43,800 --> 00:52:46,640
Speaker 1: Even talking about this kind of makes me feel like

936
00:52:46,719 --> 00:52:49,640
Speaker 1: I am stone, Like I just don't know how I

937
00:52:49,719 --> 00:52:53,560
Speaker 1: feel about this, and I guess I do want a

938
00:52:53,680 --> 00:52:58,160
Speaker 1: future where we can expect thoughtful AI depictions of ourselves

939
00:52:58,160 --> 00:53:01,760
Speaker 1: that are not rooted in harmfulis stereotype. So I applaud

940
00:53:01,800 --> 00:53:05,439
Speaker 1: this creator for being interested and invested in the way

941
00:53:05,440 --> 00:53:08,799
Speaker 1: that black folks are depicted using AI. However, I also

942
00:53:08,880 --> 00:53:12,080
Speaker 1: in a future where we can expect better for ourselves

943
00:53:12,320 --> 00:53:15,719
Speaker 1: than just a more thoughtful, nuanced depiction of ourselves in

944
00:53:15,800 --> 00:53:19,080
Speaker 1: this AI that, like we know is displacing and threatening

945
00:53:19,200 --> 00:53:23,080
Speaker 1: actual black folks in places like Tennessee because it's there

946
00:53:23,160 --> 00:53:25,960
Speaker 1: they use so much energy, right, Like, I don't know

947
00:53:26,200 --> 00:53:30,280
Speaker 1: that this is the kind of representation that I actually

948
00:53:30,320 --> 00:53:33,560
Speaker 1: want when it comes to AI, Like, I'm glad he's

949
00:53:33,600 --> 00:53:38,680
Speaker 1: I'm glad he's starting the conversation. But something about this

950
00:53:38,880 --> 00:53:41,080
Speaker 1: just doesn't feel like liberation to me.

951
00:53:41,960 --> 00:53:45,480
Speaker 2: So it seems like Google's new tool is allowing this

952
00:53:45,520 --> 00:53:48,839
Speaker 2: to happen. Do you see them doing anything to try

953
00:53:48,880 --> 00:53:50,560
Speaker 2: to rein this in So, this was.

954
00:53:50,480 --> 00:53:53,880
Speaker 1: A question that was posed by the TikTok creator Robert Tolpy,

955
00:53:53,920 --> 00:53:56,960
Speaker 1: whose video really helped me in like working through and

956
00:53:57,000 --> 00:53:59,680
Speaker 1: thinking through all of this. He said that he didn't

957
00:53:59,680 --> 00:54:02,520
Speaker 1: really see Google doing anything about this because there is

958
00:54:02,600 --> 00:54:06,640
Speaker 1: nothing that might impact who Google's bottom line financially nor

959
00:54:06,719 --> 00:54:10,480
Speaker 1: provide them any kind of meaningful bad press, even though

960
00:54:10,520 --> 00:54:13,560
Speaker 1: there are certainly ways that Google could keep their platform

961
00:54:13,560 --> 00:54:16,040
Speaker 1: from being used to create this kind of imagery. Maybe

962
00:54:16,080 --> 00:54:18,480
Speaker 1: not entirely, but there are some guardrails they could do.

963
00:54:18,920 --> 00:54:21,360
Speaker 1: I get that it might not be super simple, Like

964
00:54:21,400 --> 00:54:24,200
Speaker 1: I remember when dall Lee first came out, the guardrails

965
00:54:24,200 --> 00:54:25,640
Speaker 1: were really over the top, to the point where it

966
00:54:25,680 --> 00:54:27,759
Speaker 1: was difficult to get it to generate any images of

967
00:54:27,760 --> 00:54:30,480
Speaker 1: black folks at all, So clearly that's not the right solution.

968
00:54:30,960 --> 00:54:35,360
Speaker 1: But facilitating infinite copycat videos where each copy gets slightly

969
00:54:35,360 --> 00:54:37,680
Speaker 1: more racist and extreme to the one before it is

970
00:54:37,760 --> 00:54:40,240
Speaker 1: not a solution either. It's like the opposite of a solution.

971
00:54:40,680 --> 00:54:43,279
Speaker 1: And as a company who's making this kind of technology,

972
00:54:43,320 --> 00:54:45,400
Speaker 1: Google really does have the responsibility to make sure that

973
00:54:45,440 --> 00:54:48,520
Speaker 1: it's not being used to like increasingly harm us, And

974
00:54:48,800 --> 00:54:50,520
Speaker 1: I guess that is one of the reasons I wanted

975
00:54:50,560 --> 00:54:53,480
Speaker 1: to make this episode. I think that the leaders at

976
00:54:53,520 --> 00:54:57,080
Speaker 1: Google know this kind of thing is like being used

977
00:54:57,080 --> 00:54:59,960
Speaker 1: to harm marginalized people. But it's not like black women

978
00:55:00,440 --> 00:55:02,640
Speaker 1: really have a loud voice when it comes to technology.

979
00:55:02,719 --> 00:55:05,080
Speaker 1: So what kind of bad pass could it really get them?

980
00:55:05,200 --> 00:55:05,319
Speaker 3: Right?

981
00:55:05,360 --> 00:55:08,200
Speaker 1: Probably not a lot, I think that is the calculation

982
00:55:08,360 --> 00:55:11,120
Speaker 1: being made. But I think that they should be legitimately

983
00:55:11,160 --> 00:55:14,120
Speaker 1: embarrassed that this kind of technology that they are making

984
00:55:14,200 --> 00:55:16,799
Speaker 1: and banking on being the lynchpin of the future of

985
00:55:16,800 --> 00:55:20,239
Speaker 1: our global economy is being used to create this kind

986
00:55:20,280 --> 00:55:23,600
Speaker 1: of garbage right now, Like, why are we not associating

987
00:55:23,719 --> 00:55:28,400
Speaker 1: Google with these racist ai black bigfoot videos that Google

988
00:55:28,480 --> 00:55:31,879
Speaker 1: is being used to create like it is their creation, right,

989
00:55:31,880 --> 00:55:34,960
Speaker 1: Like why are we not associating these two things? I

990
00:55:35,000 --> 00:55:36,839
Speaker 1: think that we should be. Like if I had a

991
00:55:37,000 --> 00:55:40,080
Speaker 1: direct line the Sundar Pachai, the head of Google, I

992
00:55:40,080 --> 00:55:42,680
Speaker 1: would show him these videos and I would ask him

993
00:55:42,719 --> 00:55:45,200
Speaker 1: if this is what he has in mind for the

994
00:55:45,320 --> 00:55:47,920
Speaker 1: use of this tool, and does he think that creating

995
00:55:48,160 --> 00:55:52,239
Speaker 1: Ai Bigfoot as these racist characacters of black women like

996
00:55:52,360 --> 00:55:56,359
Speaker 1: me is making the Internet a better place for black

997
00:55:56,400 --> 00:55:59,040
Speaker 1: women like me who are human and actually have to

998
00:55:59,040 --> 00:56:01,239
Speaker 1: show up on the Internet every goddamn day. Like that

999
00:56:01,320 --> 00:56:03,479
Speaker 1: is the question I would ask him, Do you think

1000
00:56:03,560 --> 00:56:06,239
Speaker 1: that your platform is being used to create a better

1001
00:56:06,280 --> 00:56:09,720
Speaker 1: Internet for me? If anybody knows him, my dms are open.

1002
00:56:10,360 --> 00:56:14,720
Speaker 1: And it really does remind me of menstrual shows, because

1003
00:56:15,000 --> 00:56:18,040
Speaker 1: when menstrual shows were going on, it wasn't just the

1004
00:56:18,040 --> 00:56:20,759
Speaker 1: theater itself, right, that was a big part of it,

1005
00:56:21,000 --> 00:56:25,040
Speaker 1: but it was also an entire manufacturing enterprise where people

1006
00:56:25,080 --> 00:56:31,200
Speaker 1: made very good money selling racist blackfaced figurines as novelties.

1007
00:56:31,880 --> 00:56:34,600
Speaker 1: The New York Times spoke to David Pilgrim, the founder

1008
00:56:34,640 --> 00:56:37,280
Speaker 1: of the Jim Crow Museum of Racist Memorabilia at Farris

1009
00:56:37,280 --> 00:56:40,600
Speaker 1: State University in Michigan. He said they were everyday objects

1010
00:56:40,600 --> 00:56:44,040
Speaker 1: which portrayed black people as ugly different and fun to

1011
00:56:44,160 --> 00:56:48,279
Speaker 1: laugh at. They were, in a word, propaganda, and that

1012
00:56:48,400 --> 00:56:52,839
Speaker 1: is exactly what I think these AI generated racist videos are.

1013
00:56:53,440 --> 00:56:56,160
Speaker 1: People love to talk about racism like they're talking about

1014
00:56:56,360 --> 00:56:58,920
Speaker 1: fucking just a vibe in the air, right as opposed

1015
00:56:58,960 --> 00:57:03,960
Speaker 1: to a system that specifics people are personally perpetuating because

1016
00:57:04,000 --> 00:57:06,440
Speaker 1: they are making money from it. And I simply do

1017
00:57:06,520 --> 00:57:09,880
Speaker 1: not see how Google letting creators make this kind of

1018
00:57:09,920 --> 00:57:12,279
Speaker 1: content is any different, and we should be talking about

1019
00:57:12,280 --> 00:57:19,520
Speaker 1: it exactly like that. Got a story about an interesting

1020
00:57:19,560 --> 00:57:21,600
Speaker 1: thing in tech, or just want to say hi? You

1021
00:57:21,600 --> 00:57:23,880
Speaker 1: can reach us at Hello at tangodi dot com. You

1022
00:57:23,920 --> 00:57:26,920
Speaker 1: can also find transcripts for today's episode at tengody dot com.

1023
00:57:27,120 --> 00:57:28,800
Speaker 1: There Are No Girls on the Internet was created by

1024
00:57:28,800 --> 00:57:32,200
Speaker 1: me bridget Toad. It's a production of iHeartRadio, an unbossed creative.

1025
00:57:32,600 --> 00:57:35,600
Speaker 1: Jonathan Strickland is our executive producer. Tarry Harrison is our

1026
00:57:35,600 --> 00:57:39,080
Speaker 1: producer and sound engineer. Michael Almado is our contributing producer.

1027
00:57:39,360 --> 00:57:42,040
Speaker 1: I'm your host, bridget Toad. If you want to help

1028
00:57:42,120 --> 00:57:43,400
Speaker 1: us grow, rate and review.

1029
00:57:43,200 --> 00:57:44,560
Speaker 5: Us on Apple Podcasts.

1030
00:57:45,000 --> 00:57:47,840
Speaker 1: For more podcasts from iHeartRadio, check out the iHeartRadio app,

1031
00:57:47,880 --> 00:57:56,640
Speaker 1: Apple Podcasts, or wherever you get your podcasts.

1032
00:58:00,080 --> 00:58:00,120
Speaker 3: You