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Speaker 1: There's a lot of goofiness happening here, and somebody needs

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Speaker 1: to take accountability for it.

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Speaker 2: There are no Girls on the Internet.

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Speaker 3: As a production of iHeartRadio and Unbossed Creative, I'm brigitad

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Speaker 3: and this is there are no girls on the Internet.

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Speaker 3: You've probably heard of open Ai, the company that makes

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Speaker 3: chat GPT.

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Speaker 2: Last week, open.

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Speaker 3: Ai had major drama and a major board shakeup. Now

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Speaker 3: there's been no shortage of coverage of what happened. We'll

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Speaker 3: get into the broad strokes in this episode. But even

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Speaker 3: before all of this, the truth is that open Ai,

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Speaker 3: this company that has taken up so much space and

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Speaker 3: conversations about what kind of future we're going to have,

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Speaker 3: was already very white and very male. And that's even

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Speaker 3: more true after this week's board shakeup. So what does

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Speaker 3: all of this say about gender and identity in tech

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Speaker 3: and beyond and what does it mean for the rest

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Speaker 3: of us? Doctor Misty heganis Associate professor in the School

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Speaker 3: of Public Affairs and Administration at University of Kansas studies

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Speaker 3: how gender plays out in places like tech company boardrooms.

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Speaker 3: How did you come to be somebody who cares about

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Speaker 3: how women show up in workplaces? In the economy and

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Speaker 3: in data.

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Speaker 1: Well, I am a woman who lives in this society

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Speaker 1: and tries to thrive.

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Speaker 4: In this economy.

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Speaker 1: And so, you know, I guess I'll just say I

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Speaker 1: came by it naturally.

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Speaker 4: You know, I'm.

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Speaker 1: A data nerd. I'm an economist by training. I've always

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Speaker 1: been interested and driven to really try to understand kind

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Speaker 1: of how we can all live our best lives and

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Speaker 1: to figure out what are the barriers and challenges that.

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Speaker 4: Hold people back.

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Speaker 3: So last week, Misty and I both watched the open

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Speaker 3: Ai CEO drama unfold. There are lots of AI companies

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Speaker 3: and organizations out there, but open Ai and their CEO,

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Speaker 3: Sam Altman have kind of become the face of AI

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Speaker 3: right now, and pretty unexpectedly. Open AI's board voted to

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Speaker 3: terminate Sam Altman as the CEO last week. In a

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Speaker 3: statement the kind of statement that seems to be signaling

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Speaker 3: that the ousted person did something bad. The board said

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Speaker 3: Altman quote was not consistently candid in his communications with

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Speaker 3: the board, hindering its ability to exercise its responsibilities. To

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Speaker 3: this day, we still don't know what communications he was

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Speaker 3: not candid about specifically, but this was just the start so,

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Speaker 3: as someone who cares about the way that women show

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Speaker 3: up in places like boardrooms, I have to know your

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Speaker 3: thoughts on the Open Ai CEO drama. When I watched

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Speaker 3: it unfold, all I could think was like, Wow, these

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Speaker 3: men really do not feel like competent, stable leaders to me,

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Speaker 3: What were your initial thoughts?

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Speaker 4: Same?

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Speaker 3: Misty is an economist and she specifically studies high skilled

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Speaker 3: workers like the kind whose staff tech companies like open Ai.

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Speaker 3: Her work doesn't have a specific AI focus, but she

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Speaker 3: saw the ways the Open Ai saga wasn't just a

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Speaker 3: story about who runs this company, it's a story about gender.

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Speaker 3: In an op ed for Fast Company called how the

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Speaker 3: Open Ai Saga Illustrates Tech's toxic masculinity problem, she breaks

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Speaker 3: down with the entire things has about male leadership in

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Speaker 3: tech and beyond.

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Speaker 1: You know, there's a story here about the women, but

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Speaker 1: there's perhaps even a more interesting story about the men.

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Speaker 1: And I just couldn't get over the feelings that I

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Speaker 1: was having of the way in which male privilege and

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Speaker 1: this ability to refuse to back down when told Noh

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Speaker 1: was really showing up in this story, and the gender

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Speaker 1: piece was so glaring for me that I just couldn't

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Speaker 1: not see it, and I think that was happening for

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Speaker 1: a lot of us.

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Speaker 2: I completely agree.

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Speaker 3: And what's funny is that I think it took a

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Speaker 3: while for that narrative to sort of like become the conversation.

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Speaker 3: I think early on the conversation was look at these

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Speaker 3: powerful men like disagreeing with each other in public, like

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Speaker 3: what's going on? But I think after a while people

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Speaker 3: were like, Hey, this is a conversation about gender, about

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Speaker 3: the dynamics at play with male leadership, and we should

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Speaker 3: be paying attention to that. I think that a lot

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Speaker 3: of people might have you believe that when you're only

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Speaker 3: talking largely about men, there are no gender dynamics at play,

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Speaker 3: Like this is something that I've often thought that, like,

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Speaker 3: you know, when it's all men, like, for there to

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Speaker 3: be a gender dynamic at play, there has to be

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Speaker 3: someone who's not a man, And so we've just sort

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Speaker 3: of like accepted maleness as the default gender in a

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Speaker 3: way that I think invites people to not see when

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Speaker 3: there are very obvious gender dynamics shaping what's happening.

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Speaker 4: Totally.

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Speaker 1: I will tell you that you know, a couple of

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Speaker 1: the men around me when I started thinking about this

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Speaker 1: opinion piece were really like the reaction was, well, what

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Speaker 1: does this have to do with gender? Like they just

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Speaker 1: didn't get it. And I think this is where the

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Speaker 1: criks of the conversation needs to happen, because we all

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Speaker 1: live together in the.

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Speaker 4: Society, you know, we all show up in spaces and you.

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Speaker 1: Know, have our own realities, and what ends up happening

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Speaker 1: is you know, I think what ends up happening is

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Speaker 1: people who have been given privilege, either through their own

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Speaker 1: knowledge or not, in the way that they live with

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Speaker 1: their lives.

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Speaker 4: It's really hard for them.

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Speaker 1: To see beyond that, to understand what's going on with

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Speaker 1: the person across from them, across the table from them,

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Speaker 1: who perhaps doesn't have that same level of privilege. So

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Speaker 1: I searched up Sam Altman, you know, I Wikipedia him

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Speaker 1: if you will, and you know, here's a guy who

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Speaker 1: if I was to look at his CV and not

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Speaker 1: know anything about how he's been trumping around the globe

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Speaker 1: and trying to you know, really a crew funding for

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Speaker 1: this this venture and and you know, this innovative space, like,

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Speaker 1: I'm not sure that I would be too impressed with

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Speaker 1: his CV. And he, you know, has hopped around a

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Speaker 1: lot and I just couldn't help but think, you know,

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Speaker 1: if his gender was different. There's some assumption that happened

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Speaker 1: in the media, you know, that this guy was ousted

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Speaker 1: out of this business, and we couldn't let that happen,

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Speaker 1: Like the world would crumble if that happened. And I

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Speaker 1: feel like that's kind of the attitude that he and

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Speaker 1: his colleagues took as well, like the world will crumble

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Speaker 1: if I don't get to stay on top here. And

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Speaker 1: you know, women rarely, if ever, are given, you know,

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Speaker 1: are allowed to portray themselves in that light, and I

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Speaker 1: just I think we can't, Like it would be a

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Speaker 1: lost opportunity if we got through this whole saga and

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Speaker 1: we're no more aware of how gender plays a role

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Speaker 1: in the space than previously. And so I think, you know,

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Speaker 1: that's why I wrote the opinion piece. That's why, you know,

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Speaker 1: for me, it was really important to kind of name

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Speaker 1: some of this behavior that we were seeing for what

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Speaker 1: it actually was, which was just, you know, somebody had

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Speaker 1: enough privilege and enough gumption to believe that they should

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Speaker 1: be there no matter what, and they were going to

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Speaker 1: fight for it in whatever way possible and in a

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Speaker 1: very visible way. And you know, documenting all of it

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Speaker 1: on x or Twitter, and you know women would never

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Speaker 1: get away with that.

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Speaker 2: She's right.

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Speaker 3: Can you imagine if everyone at open Ai was a

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Speaker 3: woman or a person of color, how differently the entire

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Speaker 3: thing would have been reported and framed. Misty says, the

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Speaker 3: entire saga provides context for how identity shapes decisions and

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Speaker 3: how they get made at tech companies like open Ai

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Speaker 3: and Thust will impact us all. She writes, this story

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Speaker 3: went from Pallas intrigue to gossip Girl all in the

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Speaker 3: span of forty eight hours and made it clear that

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Speaker 3: the men of today are not okay. The shock and

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Speaker 3: awe quickly turned into a sad case of the state

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Speaker 3: of male leadership, the kind where hot headed frustration and

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Speaker 3: anger drives impulsive decision making and where society bends over

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Speaker 3: backward to accommodate the male ego as it oozes privilege.

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Speaker 2: That line.

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Speaker 3: I was like, yes, double click underline plus plus plus snap,

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Speaker 3: snap snap, what do you so like given this open

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Speaker 3: Ai saga as a template, but also like it's it's

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Speaker 3: about open Ai, but it's also not about open Ai,

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Speaker 3: Like it's about like, as someone who covers tech, I

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Speaker 3: think this is tailor's old as time, you know, sole

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Speaker 3: young white male leader who has been able to spin up,

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Speaker 3: whether earned or unearned, this attitude around him that he

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Speaker 3: is a genius, He is a singular savior. We all

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Speaker 3: need him if like he and only he is the

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Speaker 3: key to all of this not falling apart and really

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Speaker 3: getting the media to sort of go along with it.

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Speaker 3: Like it's really a clever trick they pulled. And so yeah,

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Speaker 3: I'm wondering, like what do you see as the state

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Speaker 3: of male leadership today and how how it's impacting what's

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Speaker 3: going on and how we're thinking about it.

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Speaker 1: Yeah, you know, and it's not only convincing the media

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Speaker 1: to go along with it, but also convincing.

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Speaker 4: You know, funders and donors.

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Speaker 1: Right like Microsoft was one hundred percent ready to go

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Speaker 1: to bat, you know, like they were willing to except

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Speaker 1: the change until they weren't. Right until I'm assuming there

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Speaker 1: was some like you know, behind the curtain conversation phone

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Speaker 1: calls between like, you know, Sam and his folks at Microsoft.

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Speaker 3: So here's what happened. After the announcement that Sam Altman

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Speaker 3: had been fired as CEO of open Ai, Microsoft open

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Speaker 3: AI's largest investor immediately announced that they were hiring Autman

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Speaker 3: to lead their AI shop, along with former open ai

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Speaker 3: president Greg Brockman, who resigned in protest after Aughtman was canned.

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Speaker 3: The remaining open ai staff was very vocally against Altman's firing.

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Speaker 3: Almost all of them, over seven hundred staffers signed a

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Speaker 3: letter demanding the board that austed him, resigned themselves, and

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Speaker 3: for Aughtman to be reinstated. The letter reads, your actions

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Speaker 3: made it obvious that you are incapable of overseeing open Ai.

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Speaker 3: We are unable to work for or with people that

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Speaker 3: lack competence, judgment and care for our mission, and employee,

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Speaker 3: investors and funders threaten to pull out to Miramrati, Open

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Speaker 3: AI's chief technology officer was appointed interim CEO in Sam's absence.

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Speaker 3: That is, in to negotiations when Sam Altman was brought

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Speaker 3: back and reinstated a CEO of open Ai with a

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Speaker 3: new board in tow too, like an episode of Succession

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Speaker 3: meets Silicon Valley. The whole thing was dizzying to watch.

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Speaker 4: Women know that this happens.

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Speaker 1: Right. You can think about this in terms of gender,

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Speaker 1: but you can also think about it in terms of

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Speaker 1: race and ethnicity, or sexuality or there's like lots of

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Speaker 1: different demographic ways in which we can think about, if

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Speaker 1: you will, the people who are allowed to live in

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Speaker 1: ignorant bliss, and then like the rest of us who

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Speaker 1: see these things happening, And I think, what in this space, like,

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Speaker 1: if we're to learn anything, I think what I would

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Speaker 1: want us to learn is I would want more men

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Speaker 1: to take accountability for their actions and to call out

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Speaker 1: this behavior. I you know, it's it's really amazing to

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Speaker 1: me that you have a board that was constructed in

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Speaker 1: a certain way with rules, and these rules are followed,

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Speaker 1: and somebody gets ousted, refuses to follow the rules of

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Speaker 1: being ousted, and you know, kind of in some sense

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Speaker 1: bullies his way back in. And I don't know if

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Speaker 1: he bullied, but like, you know, getting the staff to

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Speaker 1: go along with him, getting you know, the funders to

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Speaker 1: go along to kind of get back into that space.

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Speaker 1: It's like an unwillingness to accept the reality. And then

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Speaker 1: the rest of us are watching, and you know, after

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Speaker 1: the reality becomes just so unreal, somehow the stories that

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Speaker 1: are coming out are justifying the craziness, you know, or

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Speaker 1: just saying like oh now it'll be all okay, and

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Speaker 1: it's like no, I mean, I don't know if I'm

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Speaker 1: not watching the same drama as others are, but it's

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Speaker 1: really not okay what happened. Yes, innovation is cool, Yes,

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Speaker 1: you know, venture capital projects and like pushing the envelope.

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Speaker 1: I mean, I study high skilled workforce, I you know,

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Speaker 1: study innovation and all of these things, and they're great,

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Speaker 1: but we need to hold people accountable. And I think

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Speaker 1: in this instance, and again I don't know any of

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Speaker 1: the dynamics of what happened and whether it was justified

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Speaker 1: or not. I only know that there were certain rules

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Speaker 1: that the company and the board had and that those

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Speaker 1: were followed, you know, until they weren't, you know, or

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Speaker 1: until exceptions were made. And I think we need to

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Speaker 1: critically ask ourselves why did that play out the way

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Speaker 1: it did. Why are we not calling out this insistence

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Speaker 1: on not accepting the reality, and where are we making

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Speaker 1: that normative in a culture, in an environment that is

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Speaker 1: already struggles to keep women, you know, like engaged in

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Speaker 1: the industry.

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Speaker 3: Tech is already a field where people who are not white,

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Speaker 3: cisender men don't always feel represented, don't always feel included,

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Speaker 3: And so when you are projecting that like oh no,

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Speaker 3: it's okay for this this person to not follow the rules.

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Speaker 3: You are sort of sending a message that there's a

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Speaker 3: rule book for one kind of person and then a

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Speaker 3: different rule book for another. Because, as you pointed out

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Speaker 3: in your piece, if I was if I was Sam

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Speaker 3: Altman and I was a black woman, certainly this kind

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Speaker 3: of behavior would be framed very different. I'll just say

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Speaker 3: that I think that's a given.

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Speaker 2: Let's take a quick break at her back.

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Speaker 3: The double standard for what kind of behavior is acceptable

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Speaker 3: for men versus people who are not mad in workplaces

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Speaker 3: is real, and this is something Misty knows all too well.

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Speaker 3: She's had to navigate these tensions in her own career.

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Speaker 1: So I worked in a federal statistical agency for over

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Speaker 1: a decade, and I can tell you that when I

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Speaker 1: was kind of in an upper level of management position,

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Speaker 1: if I asked things of people like I once had

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Speaker 1: a junior to me who was male on my team

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Speaker 1: come on my team and I asked him to schedule

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Speaker 1: forward the rest of the team meetings. And even it

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Speaker 1: wasn't even twenty four hours, his supervisor was at my desk.

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Speaker 1: Why are you asking him to do that? That's your job.

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Speaker 1: If I was a man that would have never happened,

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Speaker 1: and you know, and so I think this is where

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Speaker 1: the rubber hits the road. This is where I would like, like,

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Speaker 1: if we're gonna learn anything from this experience, can we

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Speaker 1: learn that not everybody can get away with everything, but

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Speaker 1: certain people can? And then what are we gonna do

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Speaker 1: to you know, specifically in this instance? In my head,

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Speaker 1: I'm like, what are men gonna do to fix this, uh,

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Speaker 1: you know environment for the women around them? I mean

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Speaker 1: I am honestly worried about the women in open Aye,

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Speaker 1: Like what is going to happen to them?

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Speaker 2: You know?

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Speaker 1: Are our others going to want to come and join?

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Speaker 1: You know, I think we need to be having these conversations.

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Speaker 1: And you know, I think there's some folks who need

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Speaker 1: to really eat some home pie, like really a lot

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Speaker 1: of it.

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Speaker 3: The entire open Ai shakeup left a bad taste in

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Speaker 3: the mouths of anybody who cares about things like gender

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Speaker 3: representation and inclusion in tech. The open Ai board who

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Speaker 3: voted to sack Altman included two women, Helen Toner and

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Speaker 3: Tasha McCauley, but after bringing Altman back to the company,

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Speaker 3: only one member of the board who voted to oust

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Speaker 3: him remained Adam DiAngelo, So that means the only two

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Speaker 3: women on the board are gone replaced by men, men

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Speaker 3: like Larry Summers, economist and former Obama administration Secretary of

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Speaker 3: the Treasury, and who you might recall was kind of

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Speaker 3: pressured into resigning as the president of Harvard University after

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Speaker 3: a pretty poorly received talk that speculated that innate gender

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Speaker 3: differences might be why so few women are represented in

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Speaker 3: STEM and Miramuradi, that former open ai Chief technology officer

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Speaker 3: who was named interim CEO. She was only CEO for

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Speaker 3: just a few days until Altman was reinstated, and she

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Speaker 3: publicly signaled support for his return. It's like women are

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Speaker 3: being shuffled around to make room for more men. Once

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Speaker 3: Sam Appman was back at the helm and a new

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Speaker 3: board was in place, Greg Brockman, open AI's former president,

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Speaker 3: now reinstated, tweeted a picture of the team captioned we

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Speaker 3: are so back and a quick glance tells you all

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Speaker 3: you need to know about the demographics. This was my

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Speaker 3: reaction when my producer first showed it to me on Twitter. Okay,

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Speaker 3: so it is definitely mostly white men. Let's talk about that,

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Speaker 3: because you know, we know now that the only two

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Speaker 3: women on open AI's board are now gone. They brought

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Speaker 3: in men like Larry Summers, who we know was famously

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Speaker 3: forced to resign as president of Harvard for making like

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Speaker 3: deeply misogynistic and sexist remarks about women in stem I

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Speaker 3: get the sense that, like, you don't necessarily feel like

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Speaker 3: people are really looking out for the women at these companies.

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Speaker 3: And I do think, like, or do you think there's

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Speaker 3: a dynamic in some of these tech companies that just

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Speaker 3: women as support or like pieces to be moved along

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Speaker 3: a game board to further support the leadership of the

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Speaker 3: men in the space.

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Speaker 1: Yeah, so you know, again, I don't know the details

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Speaker 1: behind the screen of what happened, but it seems to

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Speaker 1: me like Miro was one of those pawns, right like

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Speaker 1: she was just asked to be temporary CEO. She lasted

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Speaker 1: you know.

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Speaker 3: Like a weekend, like such a sort amount of time,

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Speaker 3: you know.

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Speaker 1: And then I mean, and then she you know, through

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Speaker 1: the reporting, you could see like she had Sam's back,

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Speaker 1: you know, And that's one of the reasons why so

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Speaker 1: like all the saga, but I am just really worried

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Speaker 1: about all of the housekeeping that she has been having

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Speaker 1: to do over the past handful of weeks dealing with

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Speaker 1: these egos like you know, how is she managing and

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Speaker 1: and we don't we're not hearing from her, you know.

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Speaker 1: I think the board that was put in place is

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Speaker 1: honestly laughable in terms of giving any sort of confidence

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Speaker 1: that they're actually thinking about these issues. I know that

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Speaker 1: there were statements put out after the fact after this,

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Speaker 1: like three board member, you know, and by the way,

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Speaker 1: the men survived, right, so the women on the board

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Speaker 1: were out. The men survived in different roles or you know,

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Speaker 1: one of them kept their role on the board. But

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Speaker 1: I know there were statements put out after it came out,

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Speaker 1: like Larry Summers and these other people, where it was like, well,

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Speaker 1: we're we're not done, We're not done filling the board yet.

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Speaker 1: We're you know, we'll put women on. It's like the

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Speaker 1: damage is already done. You know, if you're thinking about

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Speaker 1: women as an afterthought, if you're thinking about women as

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Speaker 1: like a way to salvage your reputation, like that is

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Speaker 1: exactly backwards. And I think the current board gives even

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Speaker 1: less confidence that it's a good environment for women to thrive.

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Speaker 1: You know, I personally, I don't have any confidence in that.

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Speaker 1: I mean, you know, Larry, you know, has a very

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Speaker 1: big name in the field of economics, but it's not

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Speaker 1: clear to me that he understands any of these gender dynamics.

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Speaker 1: And he's a very privileged person himself. So I'm just

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Speaker 1: I worry about that.

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Speaker 4: And you know.

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Speaker 1: I'm just shocked. It just like shocks me the way

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Speaker 1: this all unfolded. I just I don't even know. I'm

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Speaker 1: like in a loss of words.

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Speaker 2: More after a quick break, let's get right back into it.

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Speaker 3: Men like Sam Autman are being put in charge of

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Speaker 3: building and ushering in the future for all of us,

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Speaker 3: and we're being told they're all geniuses, so smart and

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Speaker 3: so visionary that we can trust them to be in charge.

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Speaker 3: And I bet that now Sam Autman, it is more

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Speaker 3: empowered than ever. They tried to get rid of him.

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Speaker 3: We still don't even really know why they couldn't. And

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Speaker 3: now he's back. He has got to believe that there's

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Speaker 3: no line that he could cross that would lead to

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Speaker 3: him actually being successfully ousted. A blank check endorsement for

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Speaker 3: his own leadership deserved or not. So what does that

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Speaker 3: mean for the rest of us who are kind of

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Speaker 3: along for the ride. It is shocking. And I guess

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Speaker 3: what is shocking to me, and maybe it shouldn't be,

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Speaker 3: is how you have this incredibly like clumsy. I would

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Speaker 3: be embarrassed, I guess I'll say that, and then to

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Speaker 3: still be told like, no, no, these are the smartest

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Speaker 3: guys around. These are the men that you can trust

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Speaker 3: with safely architecting the future for all of us. They're like,

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Speaker 3: you're in good hands. Like I can't like those two things,

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Speaker 3: Like I can't square that circle, the math's not mathing.

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Speaker 2: I don't.

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Speaker 3: I can't watch something like this unfold and then be like, oh,

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Speaker 3: I trust these guys. I wouldn't trust these guys to

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Speaker 3: like drive the first leg of a long car trip,

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Speaker 3: you know what I mean, let alone be ushering in

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Speaker 3: this like incredibly important tech enabled future for all of us.

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Speaker 3: It's just like it's just a lot. Yeah, it's just

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Speaker 3: a lot to be asked to swallow.

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Speaker 4: Totally. It totally is.

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Speaker 1: And you know, I think the big question that I

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Speaker 1: have right now is like what's going on with the funders?

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Speaker 4: Like what you know?

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Speaker 1: So, I mean, who's pushing you know, who's pushing against

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Speaker 1: this grain. I'm starting to wonder about the composition, demographic

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Speaker 1: composition of funders. You live in a society where change

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Speaker 1: move moves at a glacial pace, and you know, lots

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Speaker 1: of times it feels like two steps forward, one step back.

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Speaker 1: Sometimes it feels like one step forward, two steps back.

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Speaker 1: You know, like there's just and then something like this happens,

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Speaker 1: and it kind of in some sense makes you feel

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Speaker 1: like a total loss for all of humanity that you know,

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Speaker 1: this can be so played out so blatantly, you know,

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Speaker 1: in such a public way, and that there are still

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Speaker 1: investors and still people who have hope or belief that

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Speaker 1: the clowns leading the show are going to really like

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Speaker 1: be able to salvage trust and confidence in the company again,

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Speaker 1: you know, loss of words for trying to figure out

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Speaker 1: why this isn't more of an issue that's being talked

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Speaker 1: about on a broader national level, Like why you know,

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Speaker 1: I think when everything first played out, there was like

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Speaker 1: this chakunah and then you know, and I said it

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Speaker 1: in my piece and then it turned into like, you know,

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Speaker 1: gossip girl, like what this craziness like that you know,

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Speaker 1: this company cannot survive because of the behavior of their

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Speaker 1: ousted leader doing all these shenanigans trying to like squirm

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Speaker 1: his way back in, and you know, and then here

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Speaker 1: we are, and I've seen pieces come out that are like,

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Speaker 1: oh uh, you know, it's all good now, and you

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Speaker 1: know Sam's reputation is better than it's ever been.

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Speaker 2: Because that's what you really care about.

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Speaker 1: I can't figure out, you know, there's a lot of

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Speaker 1: goofiness happening here, and somebody needs to take accountability for it.

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Speaker 1: And I don't know whether it's like the investors or

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Speaker 1: the leaders of this company, or you know, us as

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Speaker 1: a society for like not being louder about you know,

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Speaker 1: are tolerant or intolerance or tolerance for these shenanigans.

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Speaker 4: I just don't know.

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Speaker 1: I think it's a sad state of affairs what happened

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Speaker 1: with that company, And it's a sad state of it

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Speaker 1: demonstrates a lot of the really core issues of what

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Speaker 1: happens in the tech industry and what happens in innovative spaces.

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Speaker 1: You know, when you have people who haven't been trained

437
00:26:13,240 --> 00:26:20,399
Speaker 1: in how to appropriately manage and how to appropriately lead

438
00:26:21,200 --> 00:26:24,640
Speaker 1: a diverse workforce, you know, you're left with these type

439
00:26:24,680 --> 00:26:26,359
Speaker 1: of situations, which is unfortunate.

440
00:26:26,720 --> 00:26:29,760
Speaker 3: Yeah, and I think you really ground it in something

441
00:26:29,760 --> 00:26:31,800
Speaker 3: that I think is important to repeat, which is that

442
00:26:32,080 --> 00:26:36,360
Speaker 3: this really matters. Right, Like, we are all having these

443
00:26:36,400 --> 00:26:40,760
Speaker 3: conversations about the way that AI is poised to perhaps

444
00:26:40,760 --> 00:26:43,360
Speaker 3: deeply change our world and change the way that we work,

445
00:26:43,440 --> 00:26:44,800
Speaker 3: change the way that we do a lot of things.

446
00:26:44,880 --> 00:26:47,879
Speaker 3: And so if the people who are leading in that

447
00:26:48,080 --> 00:26:51,199
Speaker 3: change are not able to do so in a way

448
00:26:51,200 --> 00:26:54,639
Speaker 3: where they are effectively managing inclusive and diverse workforces to

449
00:26:54,680 --> 00:26:56,800
Speaker 3: do that, I think it hurts all of us. Like,

450
00:26:56,840 --> 00:26:59,920
Speaker 3: I know that you're not necessarily like an AI per,

451
00:27:00,280 --> 00:27:02,040
Speaker 3: but I did want to get your thoughts on this.

452
00:27:02,119 --> 00:27:02,280
Speaker 2: So.

453
00:27:02,840 --> 00:27:05,919
Speaker 3: Lynette Mukami is a social search and analytics editor at

454
00:27:05,960 --> 00:27:10,080
Speaker 3: Kennya's Nation media group, and she argues that conversations around

455
00:27:10,080 --> 00:27:13,560
Speaker 3: AI has up until now really centered around things like power,

456
00:27:13,880 --> 00:27:17,240
Speaker 3: profit and efficiencies, with little focus on its potential for

457
00:27:17,320 --> 00:27:19,600
Speaker 3: social good. She says a lot of this has to

458
00:27:19,600 --> 00:27:22,000
Speaker 3: do with who is leading the conversation, which is it's

459
00:27:22,040 --> 00:27:24,880
Speaker 3: white men, So it's all the perspectives of white men.

460
00:27:25,119 --> 00:27:28,000
Speaker 3: And if we had more female techies and thought leaders

461
00:27:28,040 --> 00:27:31,240
Speaker 3: in that conversation, we might see different AI solutions.

462
00:27:31,600 --> 00:27:33,640
Speaker 2: So I guess do you think that the way that we.

463
00:27:33,600 --> 00:27:37,680
Speaker 3: Are centering the voices of white men in these conversations

464
00:27:38,000 --> 00:27:42,160
Speaker 3: are really just leaving us all having like limited insights

465
00:27:42,359 --> 00:27:46,240
Speaker 3: and views and perspectives because we're just reflecting a very

466
00:27:46,640 --> 00:27:49,840
Speaker 3: pacific kind of mindset.

467
00:27:50,359 --> 00:27:52,080
Speaker 4: I agree.

468
00:27:52,160 --> 00:27:55,280
Speaker 1: So again, not in the AI space, but I am

469
00:27:55,320 --> 00:27:58,240
Speaker 1: in the statistics space and the official statistics you know,

470
00:27:58,359 --> 00:28:01,840
Speaker 1: national statistics space, and so I have done a lot

471
00:28:01,840 --> 00:28:06,320
Speaker 1: of thinking and writing and research on the idea of,

472
00:28:07,840 --> 00:28:10,679
Speaker 1: you know, the stories that we know, the stories that

473
00:28:10,720 --> 00:28:14,480
Speaker 1: we tell about who we are, are very much reflected

474
00:28:14,840 --> 00:28:19,600
Speaker 1: by the voice of people in power. And one example

475
00:28:19,640 --> 00:28:24,480
Speaker 1: of that which I think overlays this idea of whose

476
00:28:24,560 --> 00:28:29,080
Speaker 1: story is AI telling. Think about economic statistics, right, and

477
00:28:29,119 --> 00:28:34,040
Speaker 1: you think about how we capture economic statistics. At the

478
00:28:34,119 --> 00:28:37,600
Speaker 1: end of the day, you know, economics is really about

479
00:28:37,880 --> 00:28:41,320
Speaker 1: doing something that produces a good, or produces a benefit,

480
00:28:41,440 --> 00:28:44,200
Speaker 1: or produces something for somebody else or something for yourself.

481
00:28:44,920 --> 00:28:51,960
Speaker 1: Women have been extremely economically active throughout the entire existence

482
00:28:52,080 --> 00:28:57,120
Speaker 1: of humans, and yet when you look at economic statistics

483
00:28:57,240 --> 00:29:03,200
Speaker 1: like labor force participation, you see really big gap between

484
00:29:03,600 --> 00:29:07,440
Speaker 1: women and men's labor force participation. And it's partly because

485
00:29:07,640 --> 00:29:10,480
Speaker 1: the only type of economic activity who captures the type

486
00:29:10,480 --> 00:29:13,240
Speaker 1: of economic activity that historically has been done by men.

487
00:29:13,840 --> 00:29:16,800
Speaker 1: We just completely ignore all the economic activity that women

488
00:29:16,840 --> 00:29:20,360
Speaker 1: do in their homes, for their families, et cetera, you know,

489
00:29:20,400 --> 00:29:21,640
Speaker 1: all the unpaid work.

490
00:29:21,760 --> 00:29:22,080
Speaker 4: And so.

491
00:29:24,120 --> 00:29:26,040
Speaker 1: You know, part of like what I've been trying to

492
00:29:26,080 --> 00:29:30,480
Speaker 1: do in the field of economics is really kind of

493
00:29:30,560 --> 00:29:35,280
Speaker 1: force this reckoning of an awareness that we need to

494
00:29:35,280 --> 00:29:39,120
Speaker 1: stop telling the economic stories of women through the lenses

495
00:29:39,160 --> 00:29:41,320
Speaker 1: of men, and we need to start telling the economic

496
00:29:41,360 --> 00:29:45,640
Speaker 1: stories of women through the lenses of women. And that

497
00:29:45,680 --> 00:29:49,480
Speaker 1: means we need to stop tying ourselves to these storylines

498
00:29:49,480 --> 00:29:52,160
Speaker 1: that men have built. And I think that the same

499
00:29:52,240 --> 00:29:54,920
Speaker 1: is true in AI, like you know, to the extent

500
00:29:54,960 --> 00:29:59,600
Speaker 1: that it's using training data that's historical and was built

501
00:29:59,680 --> 00:30:04,200
Speaker 1: to describe, you know, the world in which white men live,

502
00:30:04,760 --> 00:30:07,720
Speaker 1: Like that is what is going to start predicting back

503
00:30:07,760 --> 00:30:11,120
Speaker 1: out to us. And you know, that's not okay, and

504
00:30:11,160 --> 00:30:15,040
Speaker 1: we need to be thinking harder about that. And I'll

505
00:30:15,040 --> 00:30:17,400
Speaker 1: just say those current turn of events that open AI

506
00:30:17,600 --> 00:30:21,320
Speaker 1: gives me zero confidence in the company's ability to take

507
00:30:21,840 --> 00:30:23,120
Speaker 1: those things seriously.

508
00:30:24,120 --> 00:30:27,720
Speaker 3: We need people from more backgrounds and identities making decisions

509
00:30:27,720 --> 00:30:31,080
Speaker 3: about technology, like AI, not just because it's nice or

510
00:30:31,120 --> 00:30:33,840
Speaker 3: it's good to have diversity, but because it is critical

511
00:30:33,880 --> 00:30:37,320
Speaker 3: to making technology that safely and effectively serves the most people.

512
00:30:37,920 --> 00:30:41,600
Speaker 3: Those voices are out there too. On Mozilla's podcast Irl,

513
00:30:41,680 --> 00:30:44,520
Speaker 3: the other podcast I host, we talk to them and

514
00:30:44,600 --> 00:30:47,240
Speaker 3: about their work, asking who has the power in AI.

515
00:30:47,960 --> 00:30:51,160
Speaker 3: But these same voices are often at best ignored or

516
00:30:51,200 --> 00:30:53,720
Speaker 3: at worse punished when they speak up about ethics and

517
00:30:53,760 --> 00:30:57,720
Speaker 3: technology like AI, and it hurts all of us. For instance,

518
00:30:58,280 --> 00:31:01,920
Speaker 3: when Jeffrey Hinton, some times called the godfather of AI,

519
00:31:02,520 --> 00:31:06,040
Speaker 3: recently spoke out about his fears around AI technology he

520
00:31:06,040 --> 00:31:10,240
Speaker 3: helped build, he was championed. Meanwhile, women and women of

521
00:31:10,240 --> 00:31:12,680
Speaker 3: color like tim net Gabru, who was pushed out of

522
00:31:12,720 --> 00:31:15,360
Speaker 3: Google for being critical about the risks associated with AI,

523
00:31:15,760 --> 00:31:20,960
Speaker 3: are punished for it. Shutting already traditionally marginalized people out

524
00:31:21,000 --> 00:31:23,560
Speaker 3: of the rooms where decisions are being made and power

525
00:31:23,600 --> 00:31:26,320
Speaker 3: is being held. Is not just bad because like it's

526
00:31:26,360 --> 00:31:29,640
Speaker 3: not nice or like just like ya diversity. It's as

527
00:31:29,680 --> 00:31:33,080
Speaker 3: I've seen men joking about on Twitter, Like if you

528
00:31:33,160 --> 00:31:36,520
Speaker 3: searched open AI and women on Twitter, you have men,

529
00:31:36,640 --> 00:31:38,640
Speaker 3: some of whom like work in tech and like have

530
00:31:38,800 --> 00:31:41,320
Speaker 3: the place that they work in their bio. When people

531
00:31:41,360 --> 00:31:43,600
Speaker 3: are complaining that, like oh, the women are pushed out

532
00:31:43,600 --> 00:31:45,480
Speaker 3: of the board, they're like, oh, it's not a bad

533
00:31:45,680 --> 00:31:48,520
Speaker 3: open AI is not a battered women's shelter. It turns

534
00:31:48,520 --> 00:31:50,640
Speaker 3: out like things like that that it's like, you really

535
00:31:50,720 --> 00:31:54,680
Speaker 3: don't get it because it harms us all when technology

536
00:31:55,000 --> 00:31:58,600
Speaker 3: and economic decisions that are connected to that technology are

537
00:31:58,880 --> 00:32:03,080
Speaker 3: made by just not enough kinds of people, like, it's

538
00:32:03,120 --> 00:32:06,840
Speaker 3: actually dangerous. It makes technology, Like we've already seen all

539
00:32:06,880 --> 00:32:09,800
Speaker 3: the different ways that technology harms people of color, harms

540
00:32:09,840 --> 00:32:13,280
Speaker 3: non native English speakers, harms women, or you know, at best,

541
00:32:13,280 --> 00:32:15,760
Speaker 3: doesn't see us. At worse harms us. And so it's

542
00:32:15,800 --> 00:32:19,920
Speaker 3: not just something to do because it's nice. It actually

543
00:32:20,040 --> 00:32:23,440
Speaker 3: matters for all of us that we are included in

544
00:32:23,480 --> 00:32:25,840
Speaker 3: a meaningful way. And I think the fact that so

545
00:32:25,920 --> 00:32:30,000
Speaker 3: many men are just unable to see that. They still

546
00:32:30,040 --> 00:32:33,080
Speaker 3: think it's like people like we got to have women

547
00:32:33,080 --> 00:32:35,280
Speaker 3: on the board because it looks good, or because it's nice,

548
00:32:35,360 --> 00:32:38,040
Speaker 3: or because it's diversity and it's woke in twenty twenty three,

549
00:32:38,240 --> 00:32:41,200
Speaker 3: as opposed to really not seeing the way that it

550
00:32:41,920 --> 00:32:45,959
Speaker 3: truly does matter for everybody them included really does not

551
00:32:45,960 --> 00:32:47,040
Speaker 3: fill me with confidence.

552
00:32:48,480 --> 00:32:51,480
Speaker 1: Yeah, I agree, I mean, and I do think that,

553
00:32:51,840 --> 00:32:56,040
Speaker 1: you know, the kind of space where we need to

554
00:32:56,080 --> 00:32:59,400
Speaker 1: really focus in on moving forward.

555
00:33:01,200 --> 00:33:03,600
Speaker 4: Is a space that really.

556
00:33:04,920 --> 00:33:08,800
Speaker 1: Forces kind of all of the voices to the table.

557
00:33:09,160 --> 00:33:13,560
Speaker 1: And you know, one way that I think is sometimes

558
00:33:13,760 --> 00:33:18,600
Speaker 1: powerful in getting men to understand the dynamic or how

559
00:33:18,720 --> 00:33:23,200
Speaker 1: women can be disadvantaged by the world we live in

560
00:33:23,720 --> 00:33:26,720
Speaker 1: is to really for them to see it through the

561
00:33:26,760 --> 00:33:30,120
Speaker 1: eyes of their children, through the eyes of their daughters, Like,

562
00:33:30,240 --> 00:33:33,240
Speaker 1: is this the legacy that they want to leave for

563
00:33:33,320 --> 00:33:37,760
Speaker 1: their children? Is this you know, these stifled opportunities that

564
00:33:37,800 --> 00:33:42,200
Speaker 1: women often have, or you know, the additional challenges that

565
00:33:42,240 --> 00:33:45,720
Speaker 1: women experience and engaging in leadership roles, Like is that

566
00:33:46,560 --> 00:33:48,720
Speaker 1: is that the legacy that they want to leave for

567
00:33:48,760 --> 00:33:51,160
Speaker 1: the next generation and for their own daughters? And you know,

568
00:33:52,040 --> 00:33:54,480
Speaker 1: hopefully the answer would be no, but maybe it would

569
00:33:54,520 --> 00:33:56,640
Speaker 1: be yes. I mean, you know, part of the problem

570
00:33:56,720 --> 00:33:59,640
Speaker 1: is that when people have power, you know, they rarely

571
00:33:59,680 --> 00:34:03,680
Speaker 1: want to give it away. So it's like, you know

572
00:34:03,800 --> 00:34:08,000
Speaker 1: that that's right there is the core of this struggle

573
00:34:08,280 --> 00:34:10,880
Speaker 1: is like how do we get people to understand that

574
00:34:11,560 --> 00:34:15,280
Speaker 1: by being more inclusive, you're not actually giving your power away.

575
00:34:15,880 --> 00:34:20,520
Speaker 1: You're actually strengthening your power because you're allowing for more

576
00:34:20,520 --> 00:34:24,880
Speaker 1: diverse voices to be heard, which allows you to improve

577
00:34:25,200 --> 00:34:27,920
Speaker 1: whatever it is that you're doing. Like, I think a

578
00:34:27,920 --> 00:34:30,319
Speaker 1: lot of people just don't get that we have this

579
00:34:30,480 --> 00:34:33,880
Speaker 1: idea that there's only a certain amount of the pie,

580
00:34:34,600 --> 00:34:38,719
Speaker 1: and you know, if I have to share any of

581
00:34:38,760 --> 00:34:41,360
Speaker 1: my pie with somebody else, that's going to be less

582
00:34:41,360 --> 00:34:47,239
Speaker 1: for me. And I think that's a really shortsighted perspective

583
00:34:47,320 --> 00:34:47,680
Speaker 1: to have.

584
00:34:49,120 --> 00:34:53,640
Speaker 3: Yeah, I mean it's true, and it doesn't always feel

585
00:34:53,680 --> 00:34:57,000
Speaker 3: good to talk about. It's like kind of heavy and grim,

586
00:34:57,120 --> 00:34:59,600
Speaker 3: but I have to say, like reading your work, you

587
00:34:59,640 --> 00:35:04,560
Speaker 3: actually strike me as somebody who is despite all of

588
00:35:04,600 --> 00:35:08,239
Speaker 3: that dark stuff, is actually kind of like positive and

589
00:35:08,280 --> 00:35:11,239
Speaker 3: hopeful when it comes to women and our place and

590
00:35:11,760 --> 00:35:17,480
Speaker 3: in economics, bonus question, what does Taylor Swift tell us

591
00:35:17,560 --> 00:35:19,440
Speaker 3: about women and our place.

592
00:35:19,160 --> 00:35:20,319
Speaker 2: In the economy right now?

593
00:35:20,400 --> 00:35:22,480
Speaker 3: I mean people can't see because this is a podcast,

594
00:35:22,520 --> 00:35:24,960
Speaker 3: but you're I assume you're in your office and there's

595
00:35:24,960 --> 00:35:30,960
Speaker 3: that Taylor Swift eras tour poster behind you. Yes, what

596
00:35:30,760 --> 00:35:33,360
Speaker 3: is what is what is swift? What is swift Enomics

597
00:35:33,400 --> 00:35:35,000
Speaker 3: and what does it tell us about where we are

598
00:35:35,000 --> 00:35:35,839
Speaker 3: as women right now.

599
00:35:36,360 --> 00:35:38,440
Speaker 4: Yeah, I'm so glad you asked this question.

600
00:35:38,680 --> 00:35:42,520
Speaker 1: So you know, I lived the first portion of my life,

601
00:35:43,040 --> 00:35:48,480
Speaker 1: like I said, feeling very frustrated that the struggle was

602
00:35:48,520 --> 00:35:52,000
Speaker 1: real for women, and that it was you know, we

603
00:35:52,160 --> 00:35:55,319
Speaker 1: had to think more, we had to process more in

604
00:35:55,400 --> 00:35:58,000
Speaker 1: terms of like leadership and how we wanted to present

605
00:35:58,040 --> 00:36:00,759
Speaker 1: ourselves because people would react to us different way. And

606
00:36:02,120 --> 00:36:03,920
Speaker 1: I finally got to a point where I was just

607
00:36:03,960 --> 00:36:08,040
Speaker 1: tired of being frustrated, and so I thought, you know,

608
00:36:08,120 --> 00:36:13,640
Speaker 1: can we flip the storyline here. Men have enormous amounts

609
00:36:13,640 --> 00:36:16,880
Speaker 1: of privilege in you know, our nation, but also across

610
00:36:16,880 --> 00:36:20,080
Speaker 1: the globe, and they have a lot of men have

611
00:36:20,160 --> 00:36:22,960
Speaker 1: something that I call care privilege, meaning that they have

612
00:36:23,080 --> 00:36:26,960
Speaker 1: other people taking care of their care needs. I don't

613
00:36:27,000 --> 00:36:29,359
Speaker 1: have anybody taking care of my care needs, okay, And

614
00:36:29,400 --> 00:36:33,279
Speaker 1: I have two children in a spouse, you know, an

615
00:36:33,360 --> 00:36:37,320
Speaker 1: aging mom, so you know, I am always having to

616
00:36:37,360 --> 00:36:39,400
Speaker 1: give care and that means that the way that I

617
00:36:39,400 --> 00:36:42,080
Speaker 1: present myself at my job and at work looks different.

618
00:36:43,040 --> 00:36:47,200
Speaker 1: And I'm tired of feeling frustrated about that inequality, and

619
00:36:47,239 --> 00:36:50,720
Speaker 1: so I just have decided that it's time to flip

620
00:36:50,760 --> 00:36:53,040
Speaker 1: the script. And I'm tired of living in a man's

621
00:36:53,080 --> 00:36:55,359
Speaker 1: world and I just want to live in my own

622
00:36:55,560 --> 00:36:58,840
Speaker 1: and my own world looks different and represents itself differently,

623
00:36:58,960 --> 00:37:01,480
Speaker 1: and you know, I can can't feel bad about that anymore.

624
00:37:01,719 --> 00:37:05,280
Speaker 1: And you know, the Swifty Nomics, my book that's coming out,

625
00:37:06,080 --> 00:37:09,919
Speaker 1: is really about celebrating the ways in which, even though

626
00:37:10,920 --> 00:37:15,840
Speaker 1: adversity confronts all of us in different ways, it's really

627
00:37:15,920 --> 00:37:23,120
Speaker 1: about thriving through that adversity. It's about celebrating reinvention. So

628
00:37:23,200 --> 00:37:25,600
Speaker 1: we all know, you know, Taylor Swift is essentially my

629
00:37:25,719 --> 00:37:28,480
Speaker 1: muse for the book because she is the queen of

630
00:37:28,480 --> 00:37:31,239
Speaker 1: reinvention if you know anything about her story and how

631
00:37:31,280 --> 00:37:35,359
Speaker 1: she survived. And so it's really I think we need

632
00:37:35,400 --> 00:37:39,720
Speaker 1: to give ourselves more credit, and we need to create

633
00:37:40,000 --> 00:37:43,560
Speaker 1: a space for ourselves, just mentally and emotionally where we

634
00:37:43,640 --> 00:37:49,960
Speaker 1: can stop feeling like we need to fight the struggle

635
00:37:50,200 --> 00:37:53,520
Speaker 1: and just start living the life that we want to

636
00:37:53,560 --> 00:37:57,759
Speaker 1: live in whatever form that takes place. And yeah, calling

637
00:37:57,840 --> 00:38:00,360
Speaker 1: people out on their bullshit, you know, never gonna stop

638
00:38:00,360 --> 00:38:06,640
Speaker 1: doing that. But I just really want women to appreciate,

639
00:38:06,960 --> 00:38:09,960
Speaker 1: even through all the difficulties, all the amazingness that we

640
00:38:11,120 --> 00:38:14,279
Speaker 1: give out to the world and that we you know,

641
00:38:14,400 --> 00:38:16,640
Speaker 1: all of our successes. I think we need to celebrate

642
00:38:16,680 --> 00:38:17,839
Speaker 1: that more so.

643
00:38:17,960 --> 00:38:22,000
Speaker 3: Ultimately, would you say it's a love story that's meant

644
00:38:22,000 --> 00:38:23,000
Speaker 3: to be a Taylor Swift joke?

645
00:38:23,360 --> 00:38:25,000
Speaker 2: I don't know. I was like, I got to.

646
00:38:25,040 --> 00:38:26,400
Speaker 3: End on a Taylor Swich joke, but I was like

647
00:38:26,440 --> 00:38:29,279
Speaker 3: that one might be too like I love it.

648
00:38:29,360 --> 00:38:32,720
Speaker 4: I love it, Yes, one the love story.

649
00:38:32,840 --> 00:38:36,040
Speaker 3: You're asking women to live their wildest dreams.

650
00:38:35,800 --> 00:38:37,640
Speaker 4: That's right, You're so good.

651
00:38:38,120 --> 00:38:40,040
Speaker 3: I'm actually looking at a list of Taylor Swift songs

652
00:38:40,040 --> 00:38:40,560
Speaker 3: as we speak.

653
00:38:40,600 --> 00:38:43,160
Speaker 4: So I love it.

654
00:38:43,280 --> 00:38:44,919
Speaker 2: Missy. Thank you so much for being here.

655
00:38:45,000 --> 00:38:47,040
Speaker 3: Is there anything that I did not ask that you

656
00:38:47,040 --> 00:38:49,000
Speaker 3: want to make sure gets included in this conversation.

657
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Speaker 1: No, I just want to say thank you for inviting me.

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Speaker 1: This is such an important topic, and I really, I

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Speaker 1: really hope that as we move forward, things get better

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Speaker 1: and not worse in this space, and I hope that

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Speaker 1: more people start calling out kind of the inequalities that

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Speaker 1: we're seeing take place before our very eyes in a

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Speaker 1: very juvenile fashion.

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Speaker 3: Listeners, y'all heard it here. Your homework from this episode

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Speaker 3: is call somebody out. On their bullshit today.

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Speaker 4: That's great.

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Speaker 3: Got a story about an interesting thing in tech, or

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00:39:29,120 --> 00:39:30,960
Speaker 3: just want to say hi? You can reach us at

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Speaker 3: Hello at tangody dot com. You can also find transcripts

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Speaker 3: for today's episode at tengody dot com. There Are No

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Speaker 3: Girls on the Internet was created by me bridget Toad.

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Speaker 3: It's a production of iHeartRadio and Unbossed creative Jonathan Strickland

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00:39:42,120 --> 00:39:44,880
Speaker 3: as our executive producer. Tari Harrison is our producer and

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Speaker 3: sound engineer. Michael Amado is our contributing producer. I'm your host,

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00:39:48,680 --> 00:39:51,480
Speaker 3: bridget Toad. If you want to help us grow, rate

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Speaker 3: and review.

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Speaker 2: Us on Apple Podcasts.

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00:39:53,760 --> 00:39:56,600
Speaker 3: For more podcasts from iHeartRadio, check out the iHeartRadio app,

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Speaker 3: Apple Podcasts, or wherever you get your podcasts.

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Speaker 1: It was moha USh