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The AI Gender Gap · Stuff Mom Never Told You

• 0:05
  Speaker 1: Hey, this is Sanny and Samantha.
• 0:06
  Speaker 2: I'm welcome to Steffan never told you a production of
• 0:08
  Speaker 2: iHeart Ratio, and today we are once again so happy
• 0:21
  Speaker 2: to be joined by the incredible, the irreplaceable Bridget Todd.
• 0:24
  Speaker 2: Welcome Bridget, thanks for having me so lovely to be back. Yes,
• 0:29
  Speaker 2: thank you so much for being back. You and I
• 0:32
  Speaker 2: were chatting about how stressful these times can be, so
• 0:36
  Speaker 2: the holidays, those times being so thank you for making
• 0:40
  Speaker 2: the time. We always love talking to you. How are you, Brigid,
• 0:45
  Speaker 2: How have you been?
• 0:46
  Speaker 3: I'm not bad. We were talking off Mike about how
• 0:49
  Speaker 3: it is a known issue with me.
• 0:51
  Speaker 4: I'm a grinch. I don't like the holidays. When people ask,
• 0:55
  Speaker 4: you know, this time of year, people are like, what.
• 0:57
  Speaker 3: Are you doing for the holiday? I like my fur.
• 1:00
  Speaker 3: I can feel my fur go up. You know, I
• 1:02
  Speaker 3: just don't like it.
• 1:03
  Speaker 4: My heart beats a little bit faster, and I just
• 1:06
  Speaker 4: I just find the holiday season extremely stressful. And especially
• 1:11
  Speaker 4: when you're someone who is self employed, it's like, hey,
• 1:14
  Speaker 4: you know the work that you usually do, What if
• 1:16
  Speaker 4: you did that work plus a week's worth of work
• 1:19
  Speaker 4: on top of it, and then that'll buy you a
• 1:22
  Speaker 4: week off what will you be doing with that time?
• 1:24
  Speaker 4: Going to see your family? Notably not stressful activity. It's
• 1:28
  Speaker 4: like I just find it like a stress sandwich. Essentially,
• 1:32
  Speaker 4: I can't handle it. I cannot hang with the holidays.
• 1:35
  Speaker 2: Well, as I said, Samantha, you and I would agree
• 1:41
  Speaker 2: on this. I mean I also think they're very stressful.
• 1:44
  Speaker 2: I yesterday we had a we went to the office
• 1:48
  Speaker 2: for a Sminty team meeting. We go, like Samantha and
• 1:51
  Speaker 2: I go once a year, and our our producer Christina was.
• 1:55
  Speaker 3: Like, how are you? And I was like, I'm so
• 2:01
  Speaker 3: tired just a deep sigh. Yeah.
• 2:04
  Speaker 4: And then it's the end of the year. It just
• 2:06
  Speaker 4: I just always feel like it's like everything catching up
• 2:11
  Speaker 4: with you all of the year. It's been a heavy year.
• 2:16
  Speaker 4: It's something about like by the time it hits December,
• 2:18
  Speaker 4: I'm just so freaking done, just done, spent.
• 2:23
  Speaker 2: Yeah, and then you have the new year barreling in
• 2:26
  Speaker 2: on you and you're like, well, it's still gonna be here,
• 2:30
  Speaker 2: but as all these expectations of maybe something will change
• 2:34
  Speaker 2: and not really Yeah, the.
• 2:38
  Speaker 4: New year I'm actually okay with because you get to
• 2:40
  Speaker 4: have those couple of days where you buy a new
• 2:42
  Speaker 4: journal and some new pens and if you for a
• 2:45
  Speaker 4: brief moment you're like, this is gonna be my year,
• 2:48
  Speaker 4: this is the year, then it all I get it
• 2:51
  Speaker 4: all together. It doesn't usually last for me. I usually
• 2:54
  Speaker 4: get about a week out of that. But you get
• 2:55
  Speaker 4: that week, which is not bad. And you and Smanita
• 2:59
  Speaker 4: did Bondo.
• 2:59
  Speaker 1: For last time.
• 3:01
  Speaker 5: Oh yeah, I got a new set. I was gifted
• 3:04
  Speaker 5: a new set, Bridget, just to give you an.
• 3:05
  Speaker 3: Update, and how are they writing.
• 3:08
  Speaker 5: I had to get used to it because it was
• 3:09
  Speaker 5: a lot free flowing, a lot more free flowing than
• 3:12
  Speaker 5: my previous one. So I had to practice with them
• 3:15
  Speaker 5: so I didn't mess up my tiny coloring books.
• 3:19
  Speaker 4: A good set of pans, a good set of markers.
• 3:21
  Speaker 4: It really will have you believing this is going to
• 3:23
  Speaker 4: turn everything around.
• 3:24
  Speaker 5: It's for a split second I was like, I can
• 3:27
  Speaker 5: color within the lines, and then I was like, no,
• 3:29
  Speaker 5: I cannot.
• 3:33
  Speaker 2: Well, the topic you've bought today for us, Bridget is
• 3:38
  Speaker 2: so so timely. I've been thinking about this because I mean,
• 3:41
  Speaker 2: it's hard to escape. But also you get to the
• 3:44
  Speaker 2: end of the year and you have, like Miriam Webster
• 3:46
  Speaker 2: chooses their word of the year and it's slop as
• 3:49
  Speaker 2: an AI slop and then you have time chooses their
• 3:52
  Speaker 2: persons a year and it's like the architects of AI
• 3:56
  Speaker 2: and it's like all dudes. And yesterday when we were
• 4:01
  Speaker 2: at the office, we were having kind of a team
• 4:04
  Speaker 2: meeting and it came up we were talking about AI
• 4:07
  Speaker 2: and our jobs and what does that look like?
• 4:10
  Speaker 1: So what are we talking about specifically today, bridget.
• 4:13
  Speaker 4: Today you're talking about the reality that women are using
• 4:17
  Speaker 4: AI tools a lot less than men in the workplace.
• 4:21
  Speaker 4: There's a definite, well studied, well documented gender gap when
• 4:25
  Speaker 4: it comes to the usage of AI. And I feel
• 4:29
  Speaker 4: you because I think as a podcaster especially, but any
• 4:33
  Speaker 4: kind of creative the first conversation that comes up when
• 4:36
  Speaker 4: it's a bunch of podcasters together is are you using
• 4:38
  Speaker 4: AI and your work? How are you seeing AI show up?
• 4:40
  Speaker 4: Or people asking are you afraid of AI? Do you
• 4:44
  Speaker 4: see AI taking your job?
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  Speaker 3: One day? Like you won't have a job.
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  Speaker 4: People will be listening to AI podcasts all of that, right,
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  Speaker 4: Those conversations are everywhere, but and I think often time
• 4:55
  Speaker 4: those conversations can be grounded in a kind of hype.
• 4:58
  Speaker 4: And so I think the the act that AI is
• 5:01
  Speaker 4: not being adopted equally by people of all genders at
• 5:05
  Speaker 4: the same rates.
• 5:05
  Speaker 3: Is pretty interesting.
• 5:07
  Speaker 4: So I wanted to talk through what we know about
• 5:09
  Speaker 4: the data when it comes to the gender gap in AI.
• 5:12
  Speaker 4: But I think I might be coming at this from
• 5:15
  Speaker 4: a little bit of a different place, right. You know,
• 5:17
  Speaker 4: in a lot of the research, they automatically assume two
• 5:21
  Speaker 4: points that I want to call out early that I'll
• 5:24
  Speaker 4: return to one, women adopting AI less is going to
• 5:28
  Speaker 4: be bad for women. I'll talk about this later, but
• 5:30
  Speaker 4: I don't know about treating that like a foregone conclusion.
• 5:34
  Speaker 4: And then this is kind of an offshoot of something
• 5:36
  Speaker 4: that I hear a ton when talking about AI. AI
• 5:39
  Speaker 4: is inevitable. If you don't get with the program, you're
• 5:42
  Speaker 4: going to be left behind. I have people who tell
• 5:45
  Speaker 4: me that not being into AI right now is like
• 5:49
  Speaker 4: not using email. You know, it will be the same
• 5:52
  Speaker 4: kind of thing in a few years, and you know,
• 5:54
  Speaker 4: if women are adopting it less, the idea that we're
• 5:57
  Speaker 4: going to be less employable, less competitive, making less money overall.
• 6:01
  Speaker 4: And so I want to be clear that I don't
• 6:04
  Speaker 4: really have the answer here, but and I want to
• 6:06
  Speaker 4: look at what the research says, but I don't like
• 6:09
  Speaker 4: this idea that frames widespread AI adoption as an inevitable
• 6:14
  Speaker 4: thing that everyone is going to be doing, because it
• 6:16
  Speaker 4: really doesn't leave a lot of room for criticism away
• 6:19
  Speaker 4: around the way that AI is being adopted. It's just
• 6:21
  Speaker 4: repeating it's inevitable, it's inevitable, it's inevitable, get on board.
• 6:24
  Speaker 4: I do think that when it comes to adopting any
• 6:27
  Speaker 4: new technology in this way, we shouldn't just be being
• 6:30
  Speaker 4: told to get on board it's inevitable, just fram it
• 6:33
  Speaker 4: down people's throats, especially when people are saying, hey, maybe
• 6:37
  Speaker 4: we don't actually like this technology.
• 6:38
  Speaker 3: Hey, maybe this technology isn't good.
• 6:41
  Speaker 2: Right.
• 6:41
  Speaker 4: I love technology. I'm an advocate for knowing the basics
• 6:44
  Speaker 4: of all kinds of technology. But if a technology is
• 6:46
  Speaker 4: showing itself to be ineffective, biased, problematic, full of lies,
• 6:50
  Speaker 4: actually adds work to your plate. I don't know that
• 6:52
  Speaker 4: we should be just to be telling people get on
• 6:54
  Speaker 4: board with that it's inevitable if that's actually what they're experiencing,
• 6:57
  Speaker 4: you know.
• 6:58
  Speaker 2: Yes, yes, And this has come up a lot at
• 7:03
  Speaker 2: our office of the at least right now, it seems
• 7:06
  Speaker 2: to be adding more work. It's not like actually helping,
• 7:11
  Speaker 2: but that you're told like, no, it's going to really
• 7:13
  Speaker 2: help you out and streamline things. I have to say,
• 7:16
  Speaker 2: I had not considered this gender gap in AI usage.
• 7:21
  Speaker 2: So I'm really interested about the research.
• 7:24
  Speaker 1: That you found.
• 7:25
  Speaker 3: Yeah, let's get into it.
• 7:28
  Speaker 4: So I took a look at some of the studies
• 7:30
  Speaker 4: and they all basically confirm that women are using AI
• 7:33
  Speaker 4: in the workplace a lot less than our mail counterparts.
• 7:36
  Speaker 4: Let's look at a meta analysis called Global Evidence on
• 7:38
  Speaker 4: Gender Gaps in Generative AI published in the Harvard Business Review.
• 7:42
  Speaker 4: So they took a look at eighteen surveys and studies
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  Speaker 4: covering one hundred and forty three thousand plus individuals across
• 7:47
  Speaker 4: many countries, sectors, and occupations. They also combined this survey
• 7:51
  Speaker 4: data with Internet traffic and mobile app download data for
• 7:55
  Speaker 4: major generative AI platforms like Quad and chackbut platforms that
• 7:59
  Speaker 4: have one hundred of millions of users. They found a large,
• 8:03
  Speaker 4: nearly universal gender gap. Here's what they found. They found
• 8:07
  Speaker 4: that the gender gap in generative AI usage is global, persistent,
• 8:11
  Speaker 4: and not fully explained by access or occupation, pointing to
• 8:14
  Speaker 4: some deeper social, cultural, and institutional frictions.
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  Speaker 3: So overall, it just seems like women.
• 8:20
  Speaker 4: Are not the ones when when people are saying it's inevitable,
• 8:24
  Speaker 4: get on board, you got to use it.
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  Speaker 3: It sounds like, by and large that is not coming
• 8:28
  Speaker 3: from women.
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  Speaker 4: I'm curious, do these findings surprise you, like as women
• 8:35
  Speaker 4: in media, as women in tech and podcasting, Like, is
• 8:38
  Speaker 4: this surprising information for me?
• 8:41
  Speaker 1: It's not.
• 8:42
  Speaker 2: I don't think i'd ever clocked it until I was
• 8:44
  Speaker 2: looking at your outline. But once I looked at the outline,
• 8:48
  Speaker 2: I was like, yeah, yeah, because most people I know
• 8:52
  Speaker 2: who are into AI are men, and they usually have
• 8:56
  Speaker 2: a very like but it's this global technology thing about it,
• 9:00
  Speaker 2: and I can't say I have really anyone I can
• 9:04
  Speaker 2: think of, but as a woman, that's like that. And
• 9:08
  Speaker 2: I mean, we're going to go over some of the
• 9:10
  Speaker 2: reasons why this is, and I thought a lot of
• 9:12
  Speaker 2: them were interesting, but they did resonate with me, and
• 9:16
  Speaker 2: I thought like, yeah, that makes sense, Like I get
• 9:21
  Speaker 2: I can't why there's a hesitance, but I guess I
• 9:26
  Speaker 2: hadn't until I read this, I hadn't picked up on it,
• 9:29
  Speaker 2: but I do.
• 9:30
  Speaker 1: It resonates with me now, and I'm like, yeah, that
• 9:33
  Speaker 1: seems right, that seems right.
• 9:34
  Speaker 5: I think being on like the ex lineal community. That's
• 9:39
  Speaker 5: kind of one of those things that I don't think about.
• 9:41
  Speaker 5: But my partner, who was heavily, like even employed into
• 9:44
  Speaker 5: the industry of AI, the difference between him and I
• 9:47
  Speaker 5: are so vast that it's not surprising the way that
• 9:52
  Speaker 5: he has integrated that into his systems, into his life,
• 9:55
  Speaker 5: but also understands how he has to be cautious and
• 9:57
  Speaker 5: how it is one of those things that has to
• 10:00
  Speaker 5: be operated with responsibility. I think that there's a level
• 10:04
  Speaker 5: of understanding, but he is also very very excited by
• 10:07
  Speaker 5: the possibilities of what AI could do. So there's this
• 10:11
  Speaker 5: level like in our in my life specifically now our
• 10:16
  Speaker 5: responses to AI as me being a little more like
• 10:18
  Speaker 5: dismissive and very much more like negative about the whole
• 10:23
  Speaker 5: thing as where he is trying to play it to
• 10:26
  Speaker 5: his cards. That makes sense.
• 10:28
  Speaker 4: That makes so much sense, And it's funny because you
• 10:31
  Speaker 4: are basically living a microchasm of what the data suggests.
• 10:34
  Speaker 3: And that's kind of what it feels like when I'm
• 10:36
  Speaker 3: like thinking about it.
• 10:37
  Speaker 5: I'm like, honestly, i feel like I'm living as the
• 10:39
  Speaker 5: stereotype that is just or like in this conversation.
• 10:43
  Speaker 4: Absolutely so in this meta analysis, they found that across
• 10:48
  Speaker 4: almost all the data sets they looked at, women are
• 10:50
  Speaker 4: about twenty to twenty five percent less likely than men
• 10:53
  Speaker 4: to be using generative AI. The meta analysis shows women
• 10:56
  Speaker 4: have twenty two percent lower odds of using AI than men.
• 11:00
  Speaker 4: The gap appears across regions, industries, education levels, and occupations.
• 11:04
  Speaker 4: So you might hear that and think, okay, but maybe
• 11:07
  Speaker 4: the people who did this these surveys got it wrong,
• 11:10
  Speaker 4: looked at the wrong information. That gap, however, cannot be
• 11:14
  Speaker 4: explained by things like survey bias, because they also, as
• 11:17
  Speaker 4: they said, looked at who is downloading tools like Claud
• 11:20
  Speaker 4: and chat sheebut, and that data showed that women compromise
• 11:24
  Speaker 4: about forty two percent of chatjept website users globally, twenty
• 11:28
  Speaker 4: seven percent of chat sheepet mobile app users, and even
• 11:32
  Speaker 4: lower shares of women are using the tool Claud for manthropic.
• 11:36
  Speaker 4: So this really suggests that the gender gap is at
• 11:38
  Speaker 4: a pretty massive global scale.
• 11:42
  Speaker 3: A couple of notable findings. If women are more senior
• 11:46
  Speaker 3: or have more experience.
• 11:47
  Speaker 4: It does narrow that gender gap a little bit, but
• 11:50
  Speaker 4: it does not completely eliminate that gap. Senior women in
• 11:54
  Speaker 4: technical roles sometimes match or exceed men's usage, but also
• 11:59
  Speaker 4: junior women and women in non technical roles show much
• 12:02
  Speaker 4: larger gaps. So there are a couple of interesting, notable
• 12:06
  Speaker 4: outliers there, But in general, just like what's happening in
• 12:10
  Speaker 4: Samantha's household, men are even cautiously sort of gung ho,
• 12:15
  Speaker 4: experimenting with it, thinking pretty optimistically about what AI might be.
• 12:19
  Speaker 3: Able to do. Women are a little more skeptical.
• 12:23
  Speaker 1: We'll say. I wonder.
• 12:38
  Speaker 2: Just because we've been talking a lot on the show
• 12:42
  Speaker 2: about like the quote male loneliness epidemic, which women are
• 12:46
  Speaker 2: also very lonely, but that's what we're talking about. But
• 12:49
  Speaker 2: I see a lot of stories of men like forming
• 12:51
  Speaker 2: these bonds with AI and these relationships with AI, and
• 12:57
  Speaker 2: I have no idea, but I wonder if that's also
• 13:00
  Speaker 2: part of it, because women usually have more of a
• 13:02
  Speaker 2: support group than this.
• 13:03
  Speaker 3: Yeah, yeah, I mean, I absolutely think that.
• 13:09
  Speaker 4: Some of the way that AI is talked about by
• 13:12
  Speaker 4: people who make it, some of the marketing language and
• 13:15
  Speaker 4: decisions around it, I think reinforce some attitudes that I
• 13:21
  Speaker 4: think are are kind of sexist.
• 13:23
  Speaker 3: Right.
• 13:23
  Speaker 4: I remember very clearly it was like a grand opening
• 13:27
  Speaker 4: when sam Altman the CEO of open Ai, was introducing
• 13:32
  Speaker 4: this new vocal chatbot for open AI's chatbot named Sky,
• 13:38
  Speaker 4: and he basically said that he wanted the experience to
• 13:41
  Speaker 4: be like the experience that people had in the movie Her,
• 13:44
  Speaker 4: which is Folks seventeen. That movie Looking Phoenix is basically
• 13:47
  Speaker 4: having a romantic and sexual relationship with an AI chatbot
• 13:51
  Speaker 4: voice by Scarlett Johanson.
• 13:53
  Speaker 3: And I love that movie. It's one of my favorite movies.
• 13:55
  Speaker 3: But obviously, within the framing of.
• 13:57
  Speaker 4: The movie, it is about a man you and technology
• 14:00
  Speaker 4: to satisfy his emotional and sexual needs on top of
• 14:04
  Speaker 4: his you know, admin that needs that you might be
• 14:07
  Speaker 4: using AI for already. And so when the head of
• 14:10
  Speaker 4: open Ai gets on a stage and promises people that
• 14:13
  Speaker 4: they will be able to use technology the same way
• 14:15
  Speaker 4: it is used in this movie, well, I can understand
• 14:17
  Speaker 4: why that might hit women in a kind of a
• 14:21
  Speaker 4: weird way, right, I can understand why it's like, well,
• 14:23
  Speaker 4: what are you really saying about this technology that that
• 14:26
  Speaker 4: is your frame of reference for how you envision people
• 14:29
  Speaker 4: using it?
• 14:29
  Speaker 3: Do you know what I mean?
• 14:31
  Speaker 2: Yes, yes, absolutely, And going back to one of the
• 14:35
  Speaker 2: other points he made at the beginning that comes up
• 14:38
  Speaker 2: in these arguments of why women aren't using AI as much.
• 14:43
  Speaker 2: It did kind of remind me of the argument around STEM,
• 14:46
  Speaker 2: like a lot of STEM things, where it's like, well
• 14:50
  Speaker 2: they just that's not how their brain works, or that
• 14:53
  Speaker 2: they don't pursue those films because of whatever X y Z.
• 14:58
  Speaker 2: So that feels very similar to me.
• 15:01
  Speaker 4: Oh yes, I'm so glad that you brought that up,
• 15:03
  Speaker 4: because when you look at how the other conversations around
• 15:06
  Speaker 4: gender gaps that we know exist in workplaces more broadly,
• 15:10
  Speaker 4: in leadership roles more broadly, stam rolls more broadly. Often,
• 15:13
  Speaker 4: just as you said, the pushback is that women maybe
• 15:16
  Speaker 4: are picking less lucrative.
• 15:17
  Speaker 3: Work or fields.
• 15:18
  Speaker 4: If you're Larry Summers, maybe it's the idea that women
• 15:21
  Speaker 4: are just innately less good at these fields or something. Now,
• 15:25
  Speaker 4: never mind that that really discounts the question of why
• 15:28
  Speaker 4: fields that are associated with women are historically devalued and underpaid.
• 15:33
  Speaker 4: So even if you know there was a time where
• 15:35
  Speaker 4: computing was seen as women's administrative or secretarial work. When
• 15:40
  Speaker 4: women were associated with it, it was lower paid ad
• 15:43
  Speaker 4: men work. When men became associated with it, very clearly,
• 15:46
  Speaker 4: it became a different kind of work. So that's clearly
• 15:48
  Speaker 4: not the women's fault for you know, for what roles
• 15:51
  Speaker 4: they happen to be choosing. But in any event, not
• 15:55
  Speaker 4: only is that not what's really going on and not
• 15:57
  Speaker 4: telling the full story of what's happening in these workplaces,
• 16:00
  Speaker 4: nor is it really what's going on or telling the
• 16:02
  Speaker 4: full story of AI adoption. That's not me saying this,
• 16:06
  Speaker 4: that's according to this meta analysis, as social scientists Katie
• 16:10
  Speaker 4: Jin puts it in a piece called There's a reason
• 16:13
  Speaker 4: why women aren't swooning over AI like men are, which
• 16:15
  Speaker 4: I love that title, She writes, The off proposed explanation
• 16:20
  Speaker 4: is that women understand this new technology less, largely because
• 16:23
  Speaker 4: they work in roles with lower exposure to it. Women are,
• 16:26
  Speaker 4: after all, still outnumbered in STEM degrees and careers, including
• 16:30
  Speaker 4: AI specific roles. The same is true in AI leadership,
• 16:33
  Speaker 4: women hold fewer than fourteen percent of senior executive positions
• 16:37
  Speaker 4: in the industry. But Harvard's study also found that the
• 16:40
  Speaker 4: usage gap remains even when women are explicitly given opportunities
• 16:44
  Speaker 4: to learn and use AI roles. So it's not just
• 16:47
  Speaker 4: that women have less training or less access to AI.
• 16:51
  Speaker 4: Even when the people who did this meta analysis equalized
• 16:54
  Speaker 4: for that, they still found that this AI gender gap persist.
• 16:59
  Speaker 4: They looked at a study out of Kenya where women
• 17:01
  Speaker 4: were exuplicitly offered training and access to AI, yet those
• 17:05
  Speaker 4: women still used chat GPT thirteen percent less than men.
• 17:09
  Speaker 3: So this seems to suggest.
• 17:11
  Speaker 4: These barriers aren't really about access or awareness about AI,
• 17:16
  Speaker 4: it's something else going on.
• 17:21
  Speaker 5: I feel like there's so many things as I'm trying
• 17:22
  Speaker 5: to work out when it comes to this conversation about
• 17:25
  Speaker 5: whys that seem like, well, obviously A equals B, or
• 17:29
  Speaker 5: A is because of B. And one of the things
• 17:31
  Speaker 5: that I'm thinking about is like maybe just what I'm
• 17:34
  Speaker 5: seeing when it comes to things like chat gpt, which
• 17:37
  Speaker 5: feels like just an advanced version of Google where we
• 17:41
  Speaker 5: made that that the thing in researching, But it gives
• 17:44
  Speaker 5: the mediocre man who has a lot more confidence than
• 17:48
  Speaker 5: women in general, even more confidence, I guess in a
• 17:52
  Speaker 5: way because they think they're getting that answer without having
• 17:55
  Speaker 5: to go to the people who actually found those answers
• 17:58
  Speaker 5: in some weird ways, Like there's so many thoughts like
• 18:01
  Speaker 5: maybe what are some of these reasons that we are
• 18:05
  Speaker 5: finding that men are more likely to use it and
• 18:07
  Speaker 5: not for me like, that just seems like a rational
• 18:10
  Speaker 5: I think that's true.
• 18:12
  Speaker 4: I think twice now, I've gotten into a back and
• 18:14
  Speaker 4: forth with somebody on Reddit, and I guess I don't
• 18:17
  Speaker 4: know their gender, but I can tell that they were
• 18:19
  Speaker 4: responding to me using chat sheep put and I'm like, Oh,
• 18:22
  Speaker 4: you didn't.
• 18:22
  Speaker 3: You couldn't. It wasn't worth it.
• 18:24
  Speaker 4: You just wanted to keep the like argument going, but
• 18:26
  Speaker 4: it wasn't worth it for you to come up with
• 18:27
  Speaker 4: your own answer. We're going to take the chat sepeute
• 18:29
  Speaker 4: really right. So the meta analysis gave some answers as
• 18:35
  Speaker 4: to what might be going on here, what might explain
• 18:37
  Speaker 4: some of these gaps. I'll tell y'all what they said,
• 18:39
  Speaker 4: and then i'll kind of give you my thoughts on it,
• 18:41
  Speaker 4: because I'm not some of these I'm not so sure about.
• 18:43
  Speaker 4: So the first, it's a lower familiarity and knowledge with AI,
• 18:46
  Speaker 4: So they said women are more likely to report not
• 18:50
  Speaker 4: knowing how generative AI works or.
• 18:51
  Speaker 3: How to use it.
• 18:53
  Speaker 4: I'm not totally sold on this. You know it is
• 18:56
  Speaker 4: in their meta analysis, so I wanted to include it.
• 18:58
  Speaker 4: But this is just my tabe. AI is not difficult
• 19:02
  Speaker 4: to understand. It is not difficult to use, nor is
• 19:05
  Speaker 4: it terribly complex. There is nobody listening to the sound
• 19:09
  Speaker 4: of my voice who could not figure it out who
• 19:12
  Speaker 4: it is outside of the realm of their ability to
• 19:14
  Speaker 4: comprehend it is not terribly complex. I think that what
• 19:18
  Speaker 4: this study is actually highlighting here is I think this
• 19:21
  Speaker 4: tendency for the people who make technology and talk about
• 19:24
  Speaker 4: technology to do so in a way where it seems
• 19:28
  Speaker 4: like the technology they're talking about is so complex and
• 19:32
  Speaker 4: your puty little lady brains could never figure out what
• 19:36
  Speaker 4: we're talking about here. Think about the way that people
• 19:39
  Speaker 4: like Elon Musk, Mark Zuckerberg, Sam Altman talk about technology.
• 19:42
  Speaker 4: They talk about it in this way where it gives
• 19:44
  Speaker 4: it this gravity toss that I think is oftentimes unearned,
• 19:48
  Speaker 4: because you don't need any kind of special training to
• 19:52
  Speaker 4: understand the basics of AI. And so I think the
• 19:54
  Speaker 4: fact that tech leaders, who, let's be real, often happen
• 19:59
  Speaker 4: to be not just me, but a specific kind of man,
• 20:01
  Speaker 4: not just white men, but a specific kind of white guy.
• 20:04
  Speaker 4: I think the fact that they are consistently talking about
• 20:07
  Speaker 4: this technology in a way that makes it seem like
• 20:10
  Speaker 4: you're ordinary person could never understand it. I think it's
• 20:12
  Speaker 4: sort of at play here, and I think that is
• 20:14
  Speaker 4: with intention. I think they do this because they want
• 20:17
  Speaker 4: people to feel I couldn't possibly understand what they're talking about.
• 20:20
  Speaker 4: How could I hold these people accountable? How could I
• 20:23
  Speaker 4: expect things to be better for me? How could I
• 20:24
  Speaker 4: even you know, know, you know, Oftentimes they are telling people, oh, no, no,
• 20:30
  Speaker 4: you want AI.
• 20:31
  Speaker 3: AI is good. People will say, no, I know what
• 20:35
  Speaker 3: I like, and I know.
• 20:35
  Speaker 4: What my experiences are, and I know that I'm not enjoying,
• 20:38
  Speaker 4: you know, opening my email, not even be able to
• 20:40
  Speaker 4: use it because AI tools are being foisted on me
• 20:43
  Speaker 4: non consensually, and they're like, no, no, no, it's actually
• 20:46
  Speaker 4: great for you. Right that if people truly innately felt
• 20:50
  Speaker 4: like they understood this technology, they would tech leaders wouldn't
• 20:53
  Speaker 4: be able to do that anymore.
• 20:55
  Speaker 5: Right. It really does feel like they're just inflating the
• 20:57
  Speaker 5: importance of it so that we'll believe it, and then
• 21:00
  Speaker 5: that when we are forced to use it because we
• 21:02
  Speaker 5: have no way of pushing back and there's actually no
• 21:05
  Speaker 5: regulation anymore on how it's being used, that will just
• 21:08
  Speaker 5: accept how great it is without actually knowing how great
• 21:11
  Speaker 5: it is. In the midst of the conversation of knowing
• 21:14
  Speaker 5: how inaccurate it has been in the past. Also, how
• 21:17
  Speaker 5: hard is it when you literally do not have a
• 21:20
  Speaker 5: choice if you use what used to be Google and
• 21:23
  Speaker 5: what you thought would be something that would give you
• 21:25
  Speaker 5: trusted sources, and the top of it is literally AI
• 21:28
  Speaker 5: results that you did not ask for. So how hard
• 21:31
  Speaker 5: is it to use when you're not given a choice
• 21:33
  Speaker 5: to whether or not you have to use it?
• 21:35
  Speaker 3: Right? And this is what I'm saying.
• 21:37
  Speaker 4: It goes back to what I was when I started
• 21:39
  Speaker 4: the conversation with of how we talk about it as
• 21:41
  Speaker 4: this inevitable technology and we all have to get on board.
• 21:44
  Speaker 4: Things that are good, you don't have to talk about
• 21:46
  Speaker 4: them that way. Things that people want you don't. That's
• 21:48
  Speaker 4: not how that's not how you have to frame them.
• 21:50
  Speaker 4: So Sam Wiles said on threads If AI is a
• 21:53
  Speaker 4: good thing, why are we constantly told it's inevitable. You
• 21:56
  Speaker 4: don't have to do that with good things. No one's
• 21:58
  Speaker 4: ever like iced coffee is inevitable, So you may as
• 22:00
  Speaker 4: well get used to it whole. This is so correct, right,
• 22:03
  Speaker 4: This is things that are good. You do not have
• 22:05
  Speaker 4: to continue over and over and over again to tell
• 22:08
  Speaker 4: people that they better get on board with this good thing, like, no,
• 22:11
  Speaker 4: that's not how we talk about things that people like
• 22:14
  Speaker 4: and are good.
• 22:15
  Speaker 1: Right.
• 22:16
  Speaker 5: Also, it's not forced upon us by the government, like
• 22:19
  Speaker 5: we are not the ice coffee being told you have
• 22:22
  Speaker 5: to buy ice coffee when it gets to this temperature,
• 22:25
  Speaker 5: and no state can regulate whether or not you can
• 22:27
  Speaker 5: use it, even though it can be harmful for you.
• 22:29
  Speaker 5: And we have seen harm done by this.
• 22:31
  Speaker 3: Sorry exactly that.
• 22:45
  Speaker 4: Another thing this meta analysis found was lower confidence with
• 22:49
  Speaker 4: it and sort of persistence or lower levels of persistence,
• 22:52
  Speaker 4: and so, according to the meta analysis, women report less
• 22:55
  Speaker 4: confidence in prompting and are less likely to persist after
• 22:58
  Speaker 4: poor AI outputs. Men, however, are more likely to experiment repeatedly.
• 23:04
  Speaker 4: So I think this is one of those things where
• 23:08
  Speaker 4: essentially what is being said there is women have tried
• 23:10
  Speaker 4: this technology and have identified that it can be janky
• 23:14
  Speaker 4: and have reasonably concluded that maybe it's not worked the
• 23:17
  Speaker 4: pain in the butt to keep trying with it, and
• 23:19
  Speaker 4: men are like, I'm going to keep on trying.
• 23:21
  Speaker 3: I think that it's like framing women taking like gleaning.
• 23:27
  Speaker 4: From their experiences of AI being full of vies hallucinations
• 23:31
  Speaker 4: actually being more work for them, which has been my
• 23:33
  Speaker 4: experience when I when I've tried to use AI a
• 23:35
  Speaker 4: lot of times, I'm like, Okay, well, I could have
• 23:38
  Speaker 4: done this in the time, in the time it took
• 23:40
  Speaker 4: me to get to finally get AI to do, I
• 23:42
  Speaker 4: could have done this myself and done a better job
• 23:43
  Speaker 4: at it.
• 23:43
  Speaker 3: So why should it is on that to begin with
• 23:45
  Speaker 3: wasted time?
• 23:46
  Speaker 4: But I don't like how this is framed as women
• 23:48
  Speaker 4: being risk averse, when in reality, I think it's more
• 23:52
  Speaker 4: like women making reasonable deductions about the time they want
• 23:56
  Speaker 4: to spend on something that has proved itself to be ineffective,
• 23:59
  Speaker 4: and like, that's that's not risk averse.
• 24:01
  Speaker 3: That's something else.
• 24:02
  Speaker 5: That's being tired of arguing with an inanimate object, which
• 24:05
  Speaker 5: is what I've had to do when I'm yelling back
• 24:08
  Speaker 5: at Google I want you Siri, but any of those
• 24:10
  Speaker 5: days because they did not understand what I was saying
• 24:12
  Speaker 5: and I just stare at it and like, why am
• 24:14
  Speaker 5: I doing this with you? You're and then being told
• 24:17
  Speaker 5: also they remember when you're reading them.
• 24:20
  Speaker 4: Listen, I told this story on my own podcast, there
• 24:23
  Speaker 4: are our goals on the Internet. After I did the
• 24:26
  Speaker 4: episode with you all about Larry Summers, who was formerly
• 24:29
  Speaker 4: on the board of Open AI, stepping down because of
• 24:31
  Speaker 4: those emails that were revealed between him and convicted child
• 24:35
  Speaker 4: sex criminal Jeffrey Epstein.
• 24:37
  Speaker 3: I was trying to get.
• 24:38
  Speaker 4: I was like, oh, maybe chatchepet can help me come
• 24:40
  Speaker 4: up with like metadata and all of that. So I
• 24:42
  Speaker 4: put in what I have to Chattebaut and Chattebet says
• 24:46
  Speaker 4: this is not correct. There is no link between Larry
• 24:50
  Speaker 4: Summers and Jeffrey Epstein. And I was like, oh, really, wow,
• 24:53
  Speaker 4: we don't have emails linking the two and they're like
• 24:56
  Speaker 4: and then Chattebet is like, Okay, well, yeah, maybe there's emails,
• 25:01
  Speaker 4: but you're suggesting that something illegal happened if you don't
• 25:05
  Speaker 4: know anything about that.
• 25:05
  Speaker 3: And I was like, I said the emails were creepy.
• 25:08
  Speaker 4: How would you define emails where a grown married man
• 25:11
  Speaker 4: is going to a convicted pedophile for advice on how
• 25:14
  Speaker 4: we can have text with his mentee.
• 25:16
  Speaker 3: You wouldn't define those as creepy. We got into a
• 25:19
  Speaker 3: huge argument to the point where I asked it. I
• 25:23
  Speaker 3: was like, cut the crap. Are you being so cagey
• 25:28
  Speaker 3: because Larry Summers used to be on the board of
• 25:30
  Speaker 3: open AI.
• 25:31
  Speaker 4: That makes you CHATCHYPT. CHATCHYPT says, let's be clear, Larry
• 25:36
  Speaker 4: Summers was never on the board of open AI. Larry
• 25:39
  Speaker 4: Summers has been on the board of open ai since
• 25:40
  Speaker 4: like twenty twenty three, so it's.
• 25:42
  Speaker 3: Been kind of a while.
• 25:43
  Speaker 4: So it's like, not only was that infuriating, think the
• 25:47
  Speaker 4: work it took for me to to like take stop
• 25:50
  Speaker 4: my work day and have an argument, a real no
• 25:54
  Speaker 4: argument with CHATCHPT. This is the technology they're saying is
• 25:57
  Speaker 4: the legiten of our king economy right now.
• 25:59
  Speaker 3: I don't think so.
• 26:00
  Speaker 5: Oh, you literally spent emotions with a computer who is
• 26:03
  Speaker 5: just trying to protect their reputation, which.
• 26:05
  Speaker 3: Is weird because they're not a human.
• 26:08
  Speaker 4: This is what I'm saying, Like, like, I'll tell you something,
• 26:11
  Speaker 4: I have not asked chat gpt a single thing since then.
• 26:14
  Speaker 3: That was a little experiment to see if it was
• 26:16
  Speaker 3: gonna work.
• 26:16
  Speaker 4: It went so astronomically left and I'm like, okay, well
• 26:19
  Speaker 4: that's a waste of my time and I got my
• 26:21
  Speaker 4: blood pressure up, so it's a double bad.
• 26:23
  Speaker 5: I don't I don't need this from you too.
• 26:26
  Speaker 4: If I'm gonna argue with someone, it's gonna be a
• 26:27
  Speaker 4: flesh and blood human in my life, that freaking chat GPT.
• 26:31
  Speaker 2: Well, I think that's also a good point of like
• 26:33
  Speaker 2: we've we've talked about this before several times, who makes
• 26:36
  Speaker 2: this technology and the fear of like the biases and
• 26:38
  Speaker 2: all that stuff in there. And I know, like Elon
• 26:41
  Speaker 2: Musk and Gronkipedia has had a lot of things come
• 26:45
  Speaker 2: up with what it is saying that are just flat
• 26:48
  Speaker 2: out ridiculous and like these flight out lies, and so
• 26:51
  Speaker 2: I do think that that is a concern, and I
• 26:57
  Speaker 2: would I would pause it that that influences like I
• 27:03
  Speaker 2: would guess that women are not getting the answers they
• 27:06
  Speaker 2: want more often than men are getting the answers that
• 27:09
  Speaker 2: they do want.
• 27:10
  Speaker 3: Yes, And something to remember about AI.
• 27:13
  Speaker 4: If there's one thing, even if you're thinking, I'm not
• 27:16
  Speaker 4: a teche, I'm not a computer person.
• 27:18
  Speaker 3: This is not my forte. If there's one thing to
• 27:21
  Speaker 3: remember is that AI.
• 27:22
  Speaker 4: It's easy to think of it as robot computer brains
• 27:26
  Speaker 4: that know everything's all knowing.
• 27:28
  Speaker 3: It's not.
• 27:28
  Speaker 4: It's trained and built by all of us humans and
• 27:31
  Speaker 4: so the same kind of biases that we know humans have,
• 27:35
  Speaker 4: AI is just trained on all of that to replicate it, right,
• 27:38
  Speaker 4: And so keep that in mind when you're thinking about AI.
• 27:41
  Speaker 4: And we have so much documentation about the ways that
• 27:44
  Speaker 4: AI is biased when it comes to reflecting women in workplaces.
• 27:47
  Speaker 4: It's more likely to reflect women as younger than they
• 27:50
  Speaker 4: actually are. And so if the majority of let's say,
• 27:54
  Speaker 4: for instance, if the majority of women who are engineers
• 27:57
  Speaker 4: are over forty, it's like a documented fact. AI will
• 28:02
  Speaker 4: will tell people, oh, they're actually younger than they are,
• 28:05
  Speaker 4: because it's reflecting a bias that against more mature women.
• 28:09
  Speaker 4: You know, there have been studies that when women ask
• 28:12
  Speaker 4: CHATGBT for negotiation advice, it regularly tells them to ask
• 28:16
  Speaker 4: for less money. Right, so all of the biases that
• 28:19
  Speaker 4: exist in society, AI is simply replicating those because it
• 28:22
  Speaker 4: was trained on all of us. And so really keep
• 28:25
  Speaker 4: that in mind, Like I can understand why women are
• 28:28
  Speaker 4: not keen about going to this technology to help them
• 28:32
  Speaker 4: understand the world around them and their workplace when we
• 28:35
  Speaker 4: know it has these biases.
• 28:38
  Speaker 5: Right, I mean it comes to the other point and
• 28:40
  Speaker 5: that we already understand and know that the data research
• 28:45
  Speaker 5: are based on men and there's not enough based on
• 28:48
  Speaker 5: women or those marginalized communities at all. Like we just
• 28:51
  Speaker 5: got to the point of realizing, hey, we need more,
• 28:53
  Speaker 5: so more people have been doing it, but all of
• 28:56
  Speaker 5: that information is not there to provide a background for chat,
• 29:00
  Speaker 5: GPT to pick up or whatever AI company. And that's
• 29:03
  Speaker 5: really concerning that we're acting like the information we know
• 29:06
  Speaker 5: now is all we need to know when we know
• 29:07
  Speaker 5: that's not true exactly.
• 29:09
  Speaker 3: That is such a good way to put it.
• 29:12
  Speaker 4: And another concern that women report about using AI why
• 29:16
  Speaker 4: they're kind of skeptical about it, is that women have
• 29:18
  Speaker 4: stronger what the meta analysis called kind of ethical concern.
• 29:22
  Speaker 4: So women are more likely to view using AI, especially
• 29:25
  Speaker 4: in professional settings or education settings, as unethical or cheating.
• 29:29
  Speaker 3: So I don't disagree with this. This totally makes sense
• 29:33
  Speaker 3: to me anecdotally.
• 29:34
  Speaker 4: However, I think it's more complex than that, because I
• 29:38
  Speaker 4: don't think it's just that women see AI is cheating.
• 29:42
  Speaker 4: It is that, But I also think that in workplaces
• 29:44
  Speaker 4: and in educational settings, women are more likely to be scrutinized.
• 29:47
  Speaker 3: That our male counterparts, right, and that's just the way.
• 29:51
  Speaker 4: Then it is, like women aren't wrong for being like, oh,
• 29:53
  Speaker 4: I feel like everybody's checking my work extra hard and
• 29:55
  Speaker 4: harder than they're checking Joe's work or whatever. The BBC
• 29:59
  Speaker 4: spoke to techlogist Lee Chambers, who said women are more
• 30:02
  Speaker 4: likely to be accused of not being competent, so they
• 30:04
  Speaker 4: have to emphasize their credentials more or demonstrate their subject
• 30:07
  Speaker 4: matter expertise in a particular field. There could be this
• 30:09
  Speaker 4: feeling that if people know that you, as a woman,
• 30:12
  Speaker 4: use AI, it is suggesting that you might not be
• 30:14
  Speaker 4: as qualified as you actually are. Women are already discredited
• 30:17
  Speaker 4: and have their ideas taken by men and passed off
• 30:19
  Speaker 4: as their own, So having people knowing that you use
• 30:22
  Speaker 4: AI might also play into this narrative that you're not
• 30:25
  Speaker 4: qualified enough. It's just another thing debasing your skills, your
• 30:28
  Speaker 4: competence and your value. Now that makes total sense to me.
• 30:32
  Speaker 3: And I am in.
• 30:35
  Speaker 4: Professional spaces of all kinds, and in some of these
• 30:38
  Speaker 4: professional spaces, I've been around very accomplished men in tech
• 30:43
  Speaker 4: who will not blink an eye at submitting like an
• 30:47
  Speaker 4: op ed or something, or a piece of writing that
• 30:49
  Speaker 4: was clearly written by AI. And it's just like and
• 30:52
  Speaker 4: I would never like the way. I would be so
• 30:57
  Speaker 4: embarrassed to have anybody be like, oh did you submit this?
• 31:01
  Speaker 4: And it was generated? I can tell by whatever, whatever,
• 31:04
  Speaker 4: I would crawl into a hole and die. I would
• 31:06
  Speaker 4: be so embarrassed. And the way that I can confirm
• 31:08
  Speaker 4: that there are a lot of men in high up
• 31:13
  Speaker 4: positions who do not feel that level of scrutiny. And
• 31:16
  Speaker 4: it goes back to like marginalized people in these settings.
• 31:19
  Speaker 4: Are we're so used to carrying that the extra eyes,
• 31:23
  Speaker 4: you know, extra scrutiny of why we're here at all,
• 31:26
  Speaker 4: our work, our value, our competence. Why would you want
• 31:30
  Speaker 4: to inject another reason to give somebody to continue.
• 31:33
  Speaker 3: To do that when you're already facing that in multiple levels.
• 31:37
  Speaker 2: I have to bring this back to fan fiction, you
• 31:40
  Speaker 2: know I do. So there's there's a big, like concern
• 31:46
  Speaker 2: in the fan fiction space of like using AI, and
• 31:50
  Speaker 2: it's become such a thing, and as discussed, a lot
• 31:55
  Speaker 2: of fan fiction is mostly written by women or non
• 31:58
  Speaker 2: binary people. People will go out of their way to say,
• 32:01
  Speaker 2: like in the tags I use M dashes, but it's
• 32:04
  Speaker 2: not AI. They go way out of their way to
• 32:06
  Speaker 2: be like I sawyar, it's not AI. And it's just
• 32:10
  Speaker 2: it's so clear to me that people don't want you
• 32:13
  Speaker 2: to think like, oh, this is not worth Like I
• 32:15
  Speaker 2: didn't even put in the time to do this, whereas yeah,
• 32:19
  Speaker 2: I do think I don't think men would see it
• 32:23
  Speaker 2: necessarily in that way. They would see it as like, oh, yeah,
• 32:26
  Speaker 2: it just saved me some time. But meanwhile, and now
• 32:28
  Speaker 2: I know that AI uses a lot of M dashes
• 32:30
  Speaker 2: because of fiction.
• 32:33
  Speaker 4: Yeah, that doesn't surprise me at all, because I think
• 32:37
  Speaker 4: the fan fiction community is definitely a community that values
• 32:41
  Speaker 4: human creativity, Like you wouldn't be in the fan fiction
• 32:44
  Speaker 4: community if you didn't value human creativity, and it's not.
• 32:46
  Speaker 4: It doesn't surprise me that that's a community that it's
• 32:48
  Speaker 4: also full of women.
• 32:51
  Speaker 2: Yes, yes, And then people always put this thing too
• 32:54
  Speaker 2: at the top where they're like, please don't feed my
• 32:56
  Speaker 2: work to AI, and I'm like, that's just not going
• 32:58
  Speaker 2: to help you, but I appreciate the effort.
• 33:01
  Speaker 5: Well, that's the other part to that is when you
• 33:03
  Speaker 5: start thinking about using chat GPT or any of the situations,
• 33:07
  Speaker 5: you don't know who you're taking from, and there is
• 33:09
  Speaker 5: this level of guilt for me on the end of
• 33:12
  Speaker 5: like not being the creative. But if I'm researching things
• 33:15
  Speaker 5: and I'm just basing it on one small bit of
• 33:17
  Speaker 5: information that's you know, from CHATJPT or Gemini or whatever whatnot,
• 33:22
  Speaker 5: which is constant, and I can't stand it. It feels
• 33:24
  Speaker 5: unethical in that manner of like we already know artists
• 33:29
  Speaker 5: are really really on edge because their work is feeling
• 33:32
  Speaker 5: constantly stolen. Creators who are writers, who are part of this,
• 33:36
  Speaker 5: researchers who are doing lots of work to get their
• 33:38
  Speaker 5: educations and to be in this field like using that
• 33:41
  Speaker 5: information and like oftentimes it's not cited. It just becomes
• 33:45
  Speaker 5: one big blob of information. It feels so gross to
• 33:48
  Speaker 5: see that play out.
• 33:50
  Speaker 3: Yeah, said such a good point.
• 33:52
  Speaker 4: There was this like micro controversy online a couple of
• 33:55
  Speaker 4: weeks ago about this literary festival, the Black Romance Literary Festival,
• 33:59
  Speaker 4: where the question was, do the people who run this festival,
• 34:02
  Speaker 4: the organizers, will they accept people who use AI in.
• 34:06
  Speaker 3: Their work at this organization? Will those people be allowed
• 34:09
  Speaker 3: to be included in panels?
• 34:10
  Speaker 4: And so it sounded that they were really talking about
• 34:12
  Speaker 4: illustrations like cover art, and so the organization gave what
• 34:16
  Speaker 4: to a lot of people in the community felt like
• 34:18
  Speaker 4: not a great answer, just sort of what they wrote.
• 34:21
  Speaker 4: The people the organizer said, we don't use AI in
• 34:24
  Speaker 4: our work, but we're not turning away people who do
• 34:26
  Speaker 4: use AI. We want to provide resources and education to
• 34:31
  Speaker 4: those folks, but we don't want to disclude them. One
• 34:33
  Speaker 4: of my listeners made a very good point that it
• 34:35
  Speaker 4: seemed like that was a kind of attempt, a harm
• 34:39
  Speaker 4: reduction kind of position, But maybe they didn't say it
• 34:41
  Speaker 4: like that, and they perhaps they shouldn't have quarified that.
• 34:43
  Speaker 4: But you know, I think at a time when artists,
• 34:49
  Speaker 4: particularly marginalized artists, are really having a hard like anybody
• 34:54
  Speaker 4: who tries to make make money from making a thing
• 34:56
  Speaker 4: is having a hard time of it right now. And
• 34:59
  Speaker 4: I I think when, as you said, Sam, we know
• 35:03
  Speaker 4: when you ask AI to generated image, it's not generating
• 35:07
  Speaker 4: a new piece, it's just taking.
• 35:10
  Speaker 3: From what's out there, right.
• 35:11
  Speaker 4: I remember there was a time where people were using
• 35:15
  Speaker 4: an AI tool to make those futuristic selfies. Half of
• 35:18
  Speaker 4: them had watermarks or logos in them somewhere. That's how
• 35:22
  Speaker 4: much they were just taking from other artists copyrighted work.
• 35:25
  Speaker 3: So I don't think that.
• 35:26
  Speaker 4: The creatives who are saying, hey, we need this to
• 35:30
  Speaker 4: be clarified, Hey, we need to put a line on
• 35:32
  Speaker 4: the stand of how what we're going to do when
• 35:34
  Speaker 4: it comes to taking other artists work in this way.
• 35:38
  Speaker 4: I don't think they're wrong for being anxious about that
• 35:40
  Speaker 4: and expecting and deserving some answers around it.
• 35:43
  Speaker 3: Frankly so, when it comes to kind of the.
• 35:56
  Speaker 4: Reasons why women might not be adopting AI like their
• 35:59
  Speaker 4: male counterparts, I did find this meta analysis pretty useful
• 36:03
  Speaker 4: and under like giving us the scope of the issue,
• 36:06
  Speaker 4: giving us the scope of the gender gap, and some
• 36:08
  Speaker 4: reasons as to why that might be. However, I just
• 36:11
  Speaker 4: don't think that some of the answers really spoke to
• 36:13
  Speaker 4: the nuance that I see in that experience as a
• 36:16
  Speaker 4: woman that's a little bit skeptical of AI. So I
• 36:18
  Speaker 4: found this piece in the Stanford Social Innovation Review by
• 36:21
  Speaker 4: Mara Bolis, who is the founder of First Prompt and
• 36:23
  Speaker 4: a fellow at the Harvard Kennedy School, called the AI
• 36:26
  Speaker 4: gender Gap Paradox, and I think that this piece does
• 36:30
  Speaker 4: a really good job of getting at some of the
• 36:32
  Speaker 4: nuances that's not just women aren't smart enough to get
• 36:35
  Speaker 4: AI or whatever right. And so one bit that she
• 36:38
  Speaker 4: pointed out is that women are already doing a lot
• 36:41
  Speaker 4: of work. She writes, more than half a professional say
• 36:44
  Speaker 4: that learning AI feels like a second job, which for
• 36:47
  Speaker 4: most women is actually a third job when you consider
• 36:50
  Speaker 4: the continued disparities in time spent on childcare and housework.
• 36:55
  Speaker 4: And so that I thought was such a good point,
• 36:58
  Speaker 4: right that doing your current job or your current educational
• 37:02
  Speaker 4: workload or whatever is already a lot of work. If
• 37:04
  Speaker 4: you're a woman, you're probably taking on more of the
• 37:08
  Speaker 4: labor at home, or of the emotional labor, or of
• 37:10
  Speaker 4: the care work, all of that. And on top of it,
• 37:13
  Speaker 4: now people are telling you that if you don't take
• 37:15
  Speaker 4: the time to learn how to integrate AI into that work,
• 37:18
  Speaker 4: you don't really care about your career and you're holding
• 37:20
  Speaker 4: yourself back. I just, yeah, it's like that, Like that
• 37:23
  Speaker 4: has to be part of the conversation if we're going
• 37:25
  Speaker 4: to actually address the gender gap in AI usage. Yes. Yeah,
• 37:30
  Speaker 4: And this piece I think also just does a great
• 37:32
  Speaker 4: job of reframing fear or knowledge gaps into what I
• 37:37
  Speaker 4: suspect they actually are, which is the ability to competently
• 37:41
  Speaker 4: analyze risk. Women aren't looking at AI and saying I'm
• 37:45
  Speaker 4: afraid of it or like I can never learn it.
• 37:47
  Speaker 4: I think what they're actually saying is I have analyzed
• 37:50
  Speaker 4: the risk that using it might bring into my work,
• 37:53
  Speaker 4: and I've made a decision based on that that I'm
• 37:56
  Speaker 4: not gonna be using it like that. That piece in
• 38:00
  Speaker 4: the Stanford Innovation Review looked at studies from Deloitte and Pew.
• 38:04
  Speaker 4: Both of them showed that women predict AI will bring
• 38:07
  Speaker 4: less benefit and do more harm across personal, professional and
• 38:11
  Speaker 4: public life. Men, however, tend to be more optimistic, confident,
• 38:15
  Speaker 4: and self assured in their competence.
• 38:18
  Speaker 3: Doesn't that really say at all?
• 38:20
  Speaker 5: Well, there's so much Like when I'm thinking about the
• 38:23
  Speaker 5: amount that we research and the amount that we try
• 38:26
  Speaker 5: to make sure that we are noting who is you know,
• 38:29
  Speaker 5: referencing and giving credit to whom ever, so we're not
• 38:32
  Speaker 5: doing any violent violations, copyright law, any of those things.
• 38:37
  Speaker 5: And again we know that chat, GPT or any of
• 38:40
  Speaker 5: the AI really care.
• 38:42
  Speaker 3: They don't care where the sources are coming from.
• 38:44
  Speaker 5: And so as people who know A that it is
• 38:48
  Speaker 5: not one hundred percent proof and we are trying to
• 38:51
  Speaker 5: be doing our due diligence and give correct information. Yeah,
• 38:56
  Speaker 5: that is more work to go back to whatever we
• 38:58
  Speaker 5: thought we could use with AI, to actually verify that
• 39:03
  Speaker 5: where this information is coming from. Like it's kind of
• 39:05
  Speaker 5: funny when we talk about having research help and having
• 39:08
  Speaker 5: someone else do the research, it feels like more work
• 39:11
  Speaker 5: because I'm like, I don't know if this is true.
• 39:13
  Speaker 3: I gotta go read the whole article again, you know.
• 39:14
  Speaker 5: What, I'm like doing more work. And it feels the
• 39:17
  Speaker 5: same way in this type of conversation with AI, because
• 39:21
  Speaker 5: I don't completely trust once again and like analyzing the
• 39:24
  Speaker 5: risk that this is actually true.
• 39:26
  Speaker 3: This might sound way off dates, but when I was
• 39:29
  Speaker 3: reading some of the research about why women don't use
• 39:32
  Speaker 3: AI as much, I couldn't help thinking about what a
• 39:36
  Speaker 3: lot of heterosexual women who are married to man or
• 39:39
  Speaker 3: in relationships with men report, where if you ask a
• 39:42
  Speaker 3: man in your life to do something, what you're actually
• 39:45
  Speaker 3: creating is like work for you later when you have
• 39:48
  Speaker 3: to answer the follow up or correct what he's done wrong.
• 39:53
  Speaker 3: I hate that for us, find women who find themselves
• 39:56
  Speaker 3: in close relation with men hate I hate that for us,
• 40:00
  Speaker 3: But like that that is what we got, that we're
• 40:04
  Speaker 3: served that all the time we would be lying, Like I.
• 40:06
  Speaker 4: Think every woman listening has had that experience, and it's
• 40:09
  Speaker 4: so frustrating, But I think that's it really mirrors to
• 40:13
  Speaker 4: me what women are talking about when they talk about
• 40:16
  Speaker 4: how AI is used in their work. When you have
• 40:18
  Speaker 4: to go and correct the mistake, ask again, give the
• 40:21
  Speaker 4: ball whatever it's gonna be. That's just adding more and
• 40:24
  Speaker 4: more to your emotional load. It's been easier for you
• 40:27
  Speaker 4: to do it yourself in the first place. Right.
• 40:29
  Speaker 5: Also, that does feel like if we get something wrong,
• 40:32
  Speaker 5: as women are marginalized people, we're going to be penalized
• 40:34
  Speaker 5: a lot more than when men do. Men are given
• 40:37
  Speaker 5: excuses and are like, eh, you're fine as a one
• 40:40
  Speaker 5: time thing, or they feel like they can brush it off.
• 40:42
  Speaker 5: Whether it's just maybe they feel like they can do
• 40:45
  Speaker 5: that way as where women have the anxiety of like, no,
• 40:47
  Speaker 5: we're going to get the worst punishment everlash martinalized people.
• 40:50
  Speaker 5: So maybe that's also that level of confidence that we
• 40:52
  Speaker 5: don't have, which is delusional.
• 40:55
  Speaker 4: Yes, And I think this speaks to something else that
• 40:59
  Speaker 4: I saw the Stanford piece and I just thought was
• 41:01
  Speaker 4: so interesting, which is that women's self report not feeling
• 41:04
  Speaker 4: confident with how AI works. We might be offered AI
• 41:08
  Speaker 4: skills training, but what we're not really offered is a
• 41:11
  Speaker 4: chance that like actual knowledge into this technology, all the
• 41:15
  Speaker 4: issues that go into it, like an actual fundamental understanding
• 41:18
  Speaker 4: and crash course on how it works. The Peace Sites
• 41:20
  Speaker 4: a Federal Reserve Bank of New York survey that shows
• 41:22
  Speaker 4: that when women say they want generative AI training, they
• 41:25
  Speaker 4: are not just looking for skills. They're signaling awareness of
• 41:28
  Speaker 4: this technology's opacity and their unwillingness to trust a system
• 41:31
  Speaker 4: that they don't fully understand. A systemic review of gender
• 41:34
  Speaker 4: and AI adoption found that women consistently cite things like
• 41:37
  Speaker 4: lack of transparency and the opaque nature of AI tools
• 41:40
  Speaker 4: as barriers to trust.
• 41:42
  Speaker 3: And so it's exactly what you dis laid out, Sam,
• 41:45
  Speaker 3: And again, that's.
• 41:46
  Speaker 4: Not the same thing as not feeling smart enough or
• 41:50
  Speaker 4: competent enough to understand something. That it's reasonable to say
• 41:53
  Speaker 4: that people that make AI tools have intentionally designed them
• 41:56
  Speaker 4: and they intentionally talk about them with such a lack
• 41:59
  Speaker 4: of transparent garancy that I don't trust it. That's that's
• 42:02
  Speaker 4: that is a really reasonable position. That's not unreasonable. I
• 42:06
  Speaker 4: don't like the framing that this like totally reasonable way
• 42:10
  Speaker 4: to be is you know, bad in some way, or
• 42:14
  Speaker 4: that women are shooting themselves in the foot economically by
• 42:17
  Speaker 4: showing this like reasonable lack of trust.
• 42:20
  Speaker 5: Right, And you know, another thing to that is again,
• 42:23
  Speaker 5: I keep coming back to how we've seen the mistakes
• 42:25
  Speaker 5: and maybe that's what it is. This has been so rushed,
• 42:28
  Speaker 5: but the constant times that like we see things that
• 42:30
  Speaker 5: are not good are usually really bad for women. Like
• 42:33
  Speaker 5: I keep thinking about the AI videos of the deep
• 42:36
  Speaker 5: fakes that happened with that twitch switch streamer that we
• 42:38
  Speaker 5: talked about. Was it two years ago? And I don't
• 42:40
  Speaker 5: even remember we had, like cause we were really talking
• 42:42
  Speaker 5: about the fact things like this is super concerning because
• 42:46
  Speaker 5: it does go after women for like just being there.
• 42:50
  Speaker 4: Yeah, I mean that speaks to what I was talking
• 42:53
  Speaker 4: about earlier when we were talking about the way that
• 42:54
  Speaker 4: Sam Altman, the way that Sam Altman was presenting talking
• 42:58
  Speaker 4: about the chatbot they were creating Sky that there are
• 43:02
  Speaker 4: so many examples of the vibes just being suss for
• 43:08
  Speaker 4: women in these spaces, right. You know, I make a
• 43:12
  Speaker 4: podcast about the intersection of gender and technology, and oftentimes
• 43:17
  Speaker 4: when we talk about AI, we're talking about things like
• 43:20
  Speaker 4: non consensual sexualized deep fakes. We're talking about things like
• 43:24
  Speaker 4: Sam Altman, you know, saying people should be able to
• 43:27
  Speaker 4: have the kind of relationship that Joaquin Phoenix has with
• 43:30
  Speaker 4: the chatbot in the movie Her. We're talking about things
• 43:34
  Speaker 4: like Elon Musk creating a anime teenager kind of sex
• 43:40
  Speaker 4: fantasy chatbot. We're talking about men who build technology, who
• 43:46
  Speaker 4: fill their teams with other men. They lack gender diversity
• 43:50
  Speaker 4: and racial diversity or any kind of real inclusion, and
• 43:52
  Speaker 4: then they talk about women in these like misogynistic ways.
• 43:57
  Speaker 4: It's not surprising to me that women are being lower
• 44:00
  Speaker 4: to adopt this technology that is made in such a
• 44:03
  Speaker 4: misogynistic soup. And as Mara Boll has put it in
• 44:07
  Speaker 4: that Stanford Review piece, as in financial systems, women are
• 44:11
  Speaker 4: attuned to the weaknesses in generative AI systems that designers
• 44:14
  Speaker 4: didn't notice or prioritize things like bias, privacy risks, unreliable
• 44:18
  Speaker 4: outputs before putting their products out into the world, which
• 44:22
  Speaker 4: speaks to that that rushed quality that you were just
• 44:24
  Speaker 4: clocking earlier. Some of the industry's more misogynistic offerings see
• 44:28
  Speaker 4: rocks Annie fantasy chatbot, or disturbing policies see Facebook's Leach
• 44:33
  Speaker 4: policies on children and a list of content are enough
• 44:35
  Speaker 4: to send most users into a kindatonic depressive spiral. But
• 44:39
  Speaker 4: for women, beyond being offensive, such outputs are evidence of
• 44:43
  Speaker 4: what gets built when developmental teams lack gender diversity. When
• 44:47
  Speaker 4: women engage with systems that they've been largely left out
• 44:49
  Speaker 4: of creating, the products can feel foreign, awkward, or even hostile.
• 44:54
  Speaker 4: And so I think that is absolutely what's going on here.
• 44:57
  Speaker 4: The vibes around how this technology is made, who makes it,
• 45:00
  Speaker 4: who is in the room, who's who has the power
• 45:03
  Speaker 4: over it, and how how that power is being youthed
• 45:05
  Speaker 4: and wielded to shape the world. All of that sucks
• 45:08
  Speaker 4: for marginalized people. So yeah, surprise, surprise, those same marginalized
• 45:11
  Speaker 4: people are saying no, thank you, y'all can keep it, yep.
• 45:15
  Speaker 2: And it's not like we don't have historical, societal, systemic
• 45:20
  Speaker 2: evidence of this going wrong for us.
• 45:22
  Speaker 1: I could.
• 45:22
  Speaker 2: I love how men are like confident, optimistic. Oh, it's
• 45:26
  Speaker 2: gonna be great. I'm like, because its historically as for.
• 45:29
  Speaker 3: You, Yeah, guess what. Not so much over here, not
• 45:35
  Speaker 3: so much at all. And I wanted to end on this.
• 45:39
  Speaker 4: When I was researching this, I found this post on
• 45:40
  Speaker 4: Reddit that I thought really did a great job of
• 45:42
  Speaker 4: summarizing my thoughts. So there was a post in the
• 45:44
  Speaker 4: ask Feminists subreddit, and the post asks why are women
• 45:48
  Speaker 4: using generative AI lesson men and the redditor trooper s
• 45:52
  Speaker 4: JP answers.
• 45:53
  Speaker 3: I'm a university professor.
• 45:55
  Speaker 4: If female students are using chat EPT less than male students,
• 45:58
  Speaker 4: it is the male students should be worried about. There
• 46:01
  Speaker 4: have been studies showing that there is a negative cognitive
• 46:03
  Speaker 4: impact of using generative AI on learners. This includes loss
• 46:07
  Speaker 4: and ability to retain information, loss of critical thinking skills,
• 46:10
  Speaker 4: loss of empathy, degradation of writing and math skills, degradation
• 46:13
  Speaker 4: of problem solving skills, and on and on. Furthermore, generative
• 46:18
  Speaker 4: AI is bad for the environment, contributes to environmental racism,
• 46:21
  Speaker 4: is built on stolen data by corporations who will zealously
• 46:23
  Speaker 4: guard their own intellectual property while willingly violating yours and
• 46:27
  Speaker 4: capitalist excitement in replacing entry level workers with AI is
• 46:31
  Speaker 4: having an immediate negative impact on young job seekers aged
• 46:34
  Speaker 4: twenty two to twenty seven, but will have a much
• 46:37
  Speaker 4: more profound impact on all of us when we lose
• 46:40
  Speaker 4: a generation of entry level workers who won't get the
• 46:42
  Speaker 4: experience needed to become experienced workers when the experienced workers retire.
• 46:47
  Speaker 4: Chat GPT is also inaccurate, bland, and produces terrible work
• 46:51
  Speaker 4: full of false information. Furthermore, in classrooms, including mine, the
• 46:55
  Speaker 4: use of generative AI is considered an academic integrity violation
• 46:59
  Speaker 4: and will result in as zero for that assignment and
• 47:01
  Speaker 4: forwarding the case to the student Conduct Board. My students
• 47:04
  Speaker 4: would not appreciate it if I use chat cheapt to
• 47:06
  Speaker 4: create lesson plans, to grade their work, and to write
• 47:08
  Speaker 4: their letters of recommendation. I do not appreciate my students
• 47:11
  Speaker 4: passing off work they didn't write that has a direct
• 47:14
  Speaker 4: negative impact on themselves and the world as their own.
• 47:16
  Speaker 4: So I don't think it is bad that women are
• 47:18
  Speaker 4: less likely to be cheating by using chat cheapt in
• 47:20
  Speaker 4: their work than men. I think it is bad that
• 47:22
  Speaker 4: so many men are wasting their educations by cheating. And
• 47:27
  Speaker 4: I felt like that really summed up what I was
• 47:30
  Speaker 4: trying to say about this reframing. I don't like that
• 47:33
  Speaker 4: this conversation is simply framed as women aren't using AI
• 47:37
  Speaker 4: and thus sort of almost blaming women for all of
• 47:41
  Speaker 4: these systemic reasons and reasonable reasons as to why that
• 47:44
  Speaker 4: might be, and also sort of saying, well, if women
• 47:47
  Speaker 4: weren't so afraid and also stupid about AI, maybe they'd
• 47:51
  Speaker 4: be making more women.
• 47:52
  Speaker 3: It's not society, it's a stupid women.
• 47:54
  Speaker 4: I really think that we need to reframe that and say, well,
• 47:56
  Speaker 4: what are women telling us by not using this technology? Like,
• 48:00
  Speaker 4: should we really just be saying these women are making
• 48:02
  Speaker 4: a bad choice. Shouldn't we really be zeroing in on
• 48:04
  Speaker 4: what women are saying as that pertains to why we
• 48:07
  Speaker 4: are not so gung ho to be adopting this technology
• 48:11
  Speaker 4: the way that men are.
• 48:12
  Speaker 3: That's that's sort of my that's sort of my my.
• 48:13
  Speaker 3: So what in all this?
• 48:15
  Speaker 4: You know?
• 48:16
  Speaker 5: And I think in the future we were going to
• 48:17
  Speaker 5: come back and have a conversation about the red the
• 48:21
  Speaker 5: lining of this type of usage in this conversation and
• 48:25
  Speaker 5: the growing population of the red pill community, Yes, because
• 48:29
  Speaker 5: we're talking more and more like it has become even
• 48:31
  Speaker 5: more so. Worthy have come to the point of saying
• 48:33
  Speaker 5: of inceels saying being straight and having a relationship with
• 48:37
  Speaker 5: a woman is gay, Like literally, that's their like and soul?
• 48:41
  Speaker 3: Have you seen this? So really a man can do
• 48:44
  Speaker 3: is sleep with a woman having sex with a woman.
• 48:46
  Speaker 5: Right, Submitting and pleasing a woman essentially was kind of
• 48:48
  Speaker 5: like that kind of intake. But I really do wonder
• 48:51
  Speaker 5: if this conversation of using chat GPT to replace that
• 48:56
  Speaker 5: interaction again with a mal loneliness epidemic, and how it
• 48:58
  Speaker 5: becomes violent. If this conversation and if this push and
• 49:02
  Speaker 5: things like what Sam Allman was trying to do when
• 49:04
  Speaker 5: he first created that chatbot, as well as what Elon
• 49:08
  Speaker 5: Musk is trying to do creating his chatbot is just
• 49:12
  Speaker 5: opening up a bigger community, a bigger doorway for more
• 49:16
  Speaker 5: in cell activity and red pill activity, and we're gonna
• 49:19
  Speaker 5: have to come back and have to deal with the
• 49:20
  Speaker 5: consequence of things like AI being a part of this narrative.
• 49:25
  Speaker 4: Absolutely, I completely agree. I think those things are totally linked.
• 49:31
  Speaker 4: And I'm in the middle of doing a lot of
• 49:32
  Speaker 4: research about the kinds of sexual and romantic attachments that
• 49:36
  Speaker 4: people create with AI, and I think it's complicated because
• 49:41
  Speaker 4: I want people to feel like they have nourishing relationships
• 49:43
  Speaker 4: in their lives. But healthy nourishing relationships come with friction,
• 49:48
  Speaker 4: like that's what you get from being in relationship with
• 49:50
  Speaker 4: other humans. And I think that the availability of folks
• 49:54
  Speaker 4: to kind of engage in frictionless relationships where they can
• 50:00
  Speaker 4: just take and take and take an extract and extract
• 50:02
  Speaker 4: and extract and always get what they want out of
• 50:03
  Speaker 4: them in some ways I can see by that is therapeutic,
• 50:06
  Speaker 4: but that is not what builds healthy people like health
• 50:09
  Speaker 4: Like healthy people have to experience relationships with friction. And
• 50:13
  Speaker 4: that's just the bottom line.
• 50:16
  Speaker 1: Yes, yes, well topic for a future day.
• 50:20
  Speaker 3: Yeah, I love it.
• 50:23
  Speaker 2: I also have to say a dude told me the
• 50:25
  Speaker 2: other day. He was like, well, I love AI because
• 50:29
  Speaker 2: it gives me more leisure time. And I was like, well,
• 50:32
  Speaker 2: wait till you don't have a job, and then you're
• 50:34
  Speaker 2: not gonna have a way.
• 50:35
  Speaker 3: That time, it'll be all all the time and we
• 50:40
  Speaker 3: won't be able to do all those things because you
• 50:43
  Speaker 3: have no monies more leisure time.
• 50:48
  Speaker 2: Oh all right, well, thank you so much, Bridget for
• 50:51
  Speaker 2: coming during the stressful time. We always love talking to you.
• 50:55
  Speaker 2: Can't wait to see you in the new year twenty
• 50:57
  Speaker 2: twenty six.
• 50:58
  Speaker 3: Yes, we're almost.
• 50:59
  Speaker 1: There, almost there. In the meantime, where can the good
• 51:03
  Speaker 1: listeners find you?
• 51:04
  Speaker 4: You can find me at my podcast There are no
• 51:06
  Speaker 4: goals on the internet, where we explore all kinds of
• 51:08
  Speaker 4: issues of the intersection of gender and identity and technology
• 51:11
  Speaker 4: and social media. You can check me out on Instagram
• 51:13
  Speaker 4: at Bridget Marie in DC, or on YouTube. But there
• 51:16
  Speaker 4: are no girls on the internet.
• 51:17
  Speaker 1: Yes, and go do that.
• 51:19
  Speaker 2: If you have not already listeners, If you would like
• 51:22
  Speaker 2: to contact us, you can You can email us at
• 51:24
  Speaker 2: Hello at stuff onever Told You dot com. You can
• 51:26
  Speaker 2: find us on Blue skyte Mom Stuff Podcasts, or on
• 51:27
  Speaker 2: Instagram and TikTok at stuff one Never Told You.
• 51:29
  Speaker 1: We're also on YouTube.
• 51:30
  Speaker 2: We have some new merchandise at comp Bureau, and we
• 51:32
  Speaker 2: have a book you can get wherever you get your books.
• 51:34
  Speaker 2: Thanks as always too, our superducer PRIs Senior Executive Prius
• 51:36
  Speaker 2: my under contributor Joey, Thank you and thanks to you
• 51:39
  Speaker 2: for listening. Stuff Never Told You is production by Heart Radio.
• 51:41
  Speaker 2: For more podcasts from my heart Radio, you can check
• 51:43
  Speaker 2: out the heart Radio app Apple Podcasts wherever you listen
• 51:45
  Speaker 2: to your favorite shows.