Speaker 1: I'm Emily Chang, and this is the Circuit. For as
Speaker 1: long as I've been covering tech, I've covered the resistance
Speaker 1: to it, the critics, and the whistleblowers who've turned up
Speaker 1: the volume. Doing this is incredibly risky because these companies
Speaker 1: are just so powerful they basically make you take a
Speaker 1: vow of silence to work there. It's called signing a
Speaker 1: non disclosure agreement. In this episode of the Circuit, I
Speaker 1: meet Efoma Ozoma, a former pinteress, public policy and social
Speaker 1: impact manager who essentially blew the whistle on the system itself.
Speaker 1: More recently, she left Silicon Valley for a quieter life
Speaker 1: on a farm in Santa Fe, where we find her now.
Speaker 2: So this is.
Speaker 3: Where the coats live and the chickens and the rabbits,
Speaker 3: And yeah, I couldn't imagine doing all of this living
Speaker 3: in the Bay Area, but I built this.
Speaker 1: We're joined by two women who've also spoken out about tech.
Speaker 1: Timney Gabrew, founder of the Distributed Artificial Intelligence Research Institute,
Speaker 1: and a former Google ethical AI researcher. She says she
Speaker 1: was fired, Google says she resigned. UCLA professor Sofia Noble
Speaker 1: wrote the book algorithms of oppression, how search engines reinforce racism. Together,
Speaker 1: you might say the three of them make up a
Speaker 1: small part of a growing tech resistance. Here's my conversation
Speaker 1: with Efoma Ozoma, Tiamnique Gebrew, and Sofia Noble.
Speaker 4: At what point did you realize I need to speak up,
Speaker 4: like enough is enough?
Speaker 5: I saw her on Twitter rab.
Speaker 6: And we actually spoke before before I spaking.
Speaker 3: Yeah, So, after Pinterest pushed me out, I knew at
Speaker 3: some point that I was going to talk about my story.
Speaker 3: I didn't realize it was going to be so soon.
Speaker 3: But Pinterest, along with many other companies who posted statements
Speaker 3: after George Floyd's murder about how.
Speaker 6: They stood with their black employees.
Speaker 3: And what was particularly galling for me was I knew
Speaker 3: the team who would have drafted that statement, and so
Speaker 3: I felt I had to say something.
Speaker 4: Yeah, And to me, didn't you call I Foma the
Speaker 4: day before it all went down?
Speaker 7: I was just at that point, I had been also
Speaker 7: tweeting about, like, you know, whistle blower pretection and being
Speaker 7: silenced in all of that and if you must sell whatever.
Speaker 7: I tweeted about whistle blower protection and was like, hey,
Speaker 7: I'm working on this thing, which ended up being the
Speaker 7: Tech Worker Book, right, And so she was describing to
Speaker 7: me the handbook that she was working on, and I
Speaker 7: was like, you know, I feel like they're really harassing me.
Speaker 7: She's like, you know, you gotta take notes and all
Speaker 7: of that. The next day, you know, I found out
Speaker 7: I was disconnected if I resigned. Apparently by then, I probably,
Speaker 7: like you, had tried many other avenues. During the Black
Speaker 7: Lives Matter movement, we organized an entire thing for the
Speaker 7: research organization, giving them five points to act on after.
Speaker 5: Taking so many people's input and all that.
Speaker 7: Like, that was a few months before I got fired, Right,
Speaker 7: So what gave you the courage to speak up?
Speaker 3: I don't know that anything gave me the courage. The
Speaker 3: way I've thought about speaking up always is what are
Speaker 3: you afraid of? And what would keep you from speaking up?
Speaker 3: And for me personally, the only thing that I've ever
Speaker 3: been afraid of was my mom passing away, and that happened,
Speaker 3: So honestly, what else do I have to lose?
Speaker 2: How about you?
Speaker 8: Two?
Speaker 2: Yeah?
Speaker 7: I think that for me, it's like what am I
Speaker 7: willing to lose in online? A position in my life,
Speaker 7: in my career right now.
Speaker 5: To lose that.
Speaker 7: And I was actually compared to a lot of people
Speaker 7: who have to think about putting food on the table kids,
Speaker 7: you know, they can't. I have been in situations in
Speaker 7: my life like, for instance, before I got my citizenship,
Speaker 7: when I had political asylum, I would never go to
Speaker 7: a protest like I wasn't about to risk that. So
Speaker 7: I was no longer in that position, and I tried
Speaker 7: not speaking up, and it wasn't like things weren't getting better, So,
Speaker 7: you know, so I really was at a place in
Speaker 7: my life where I think, you know, if I was
Speaker 7: never going to get a job in those kinds of
Speaker 7: places anymore, I was okay with that.
Speaker 6: I think you made a great point.
Speaker 3: We have a lot of privilege sitting here, and I
Speaker 3: think it's important to acknowledge that I wrote shortly after
Speaker 3: coming forward about pinterest that if I had kids, if
Speaker 3: I had family who were on my health insurance, I
Speaker 3: never would have even hired an attorney while I was there,
Speaker 3: because I knew from the point I hired a lawyer
Speaker 3: what the end would be and I couldn't have risked
Speaker 3: that if I had people who dependent on me. So
Speaker 3: there is a level of privilege in even being able
Speaker 3: to say something.
Speaker 4: Sophia, you've been critiquing the tech industry for years. What
Speaker 4: was it like on the outside watching their stories people?
Speaker 8: I mean, I had so much respect and felt like,
Speaker 8: and still feel like, my work is in service of
Speaker 8: making it possible for you all to do what you've
Speaker 8: done in your careers, and also to be the person
Speaker 8: who holds up the studies and the research and says,
Speaker 8: you know, these things are happening, these things are real,
Speaker 8: and these are the people who pay the price, as
Speaker 8: well as millions of other people who look like us,
Speaker 8: who pay the price for the kinds of terrible.
Speaker 2: Worker practices, labor practices, but also.
Speaker 8: Product development that comes out of the tech industry. You know,
Speaker 8: I remember the night that to meet was being let
Speaker 8: go of Google. I'm going to put that generously. People
Speaker 8: were watching it happen and unfold because you were live
Speaker 8: tweeting what was happening, and I was watching, and I
Speaker 8: remember like sliding into your DMS and I was like,
Speaker 8: hey girl, are you okay?
Speaker 2: And are you going to be all right? And we
Speaker 2: got you?
Speaker 6: What do we need to do?
Speaker 2: What do you need?
Speaker 8: Do you need a fellowship like we've got to make
Speaker 8: sure that you can still pay your bills. I don't
Speaker 8: think I fully thought through that you were leaving Google,
Speaker 8: so you probably have money of many but at least
Speaker 8: you weren't going to be like out next month. But
Speaker 8: you know, but that had been you know, my orientation
Speaker 8: in my own career, which was many of us who
Speaker 8: were taking risks in critiquing the tech industry were untenured,
Speaker 8: vulnerable graduate students, you know, people who there would have
Speaker 8: been a high price to pay if there had been retaliation.
Speaker 8: So I identified so much with that. And then when
Speaker 8: if Yoma and I met, I remember we met in
Speaker 8: person at a meeting. And then in the meeting, I
Speaker 8: remember they said, everybody who's like energized in your work,
Speaker 8: you know, go to this side of the room, and
Speaker 8: everyone who's like really circling the drain and struggling, go
Speaker 8: to that side of the room. And she and I
Speaker 8: went fighting for last place, you know, on our line,
Speaker 8: and that was where most of the black women were,
Speaker 8: in fact, on that side. And I remember that what
Speaker 8: we started talking, and I was so attuned to the
Speaker 8: price you were paying for the work you were doing,
Speaker 8: and I was like, you know, I identify. I identify with
Speaker 8: both of you, and you're not alone. You're not going
Speaker 8: to have to go through these things, like we're in
Speaker 8: this together.
Speaker 7: So if Yuma was working in the background every I
Speaker 7: feel like so many of them were working in the
Speaker 7: background on my behalf, Like you were finding lawyers, you know,
Speaker 7: writing letters and everything.
Speaker 4: So there's a network.
Speaker 6: Was this network?
Speaker 4: If you will, Can you characterize what it's like being
Speaker 4: inside these companies and trying to raise these issues and
Speaker 4: the struggle of.
Speaker 1: That, like are they trying to squash you?
Speaker 4: Does it feel incredibly lonely? Oh?
Speaker 6: Yeah?
Speaker 3: My situation is unique in that, not that I experienced
Speaker 3: it very much, not unique, but in that it was
Speaker 3: written about. There's one particular situation where the company had
Speaker 3: been a call to task for years on elevating plantations
Speaker 3: as wedding venues. Plantations you would not elevate any other
Speaker 3: place where people were tortured and murdered as a wedding venue.
Speaker 3: And civil rights organization came to us said, hey, we
Speaker 3: want to work with you, but if you don't make
Speaker 3: this policy change, we are going to go to the
Speaker 3: press and talk about it. I brought it to the company,
Speaker 3: aid out all of the options that we had for
Speaker 3: changing the policy, did it in what I thought was
Speaker 3: a very diplomatic way, and the company was praised for
Speaker 3: it for taking my recommendations in the end, and in
Speaker 3: my performance review after fifty plus articles came out praising
Speaker 3: the company the kind of pr boost you can't pay for.
Speaker 3: I got a negative performance review for the work that
Speaker 3: I did on.
Speaker 6: That because I was biased, is.
Speaker 3: What my white male manager said in my performance review
Speaker 3: for it.
Speaker 2: Ended the promotion of plantations.
Speaker 3: That's that's correct, and you were criticized and I was
Speaker 3: criticized for it, specifically for being biased, is what he said.
Speaker 3: As if there's an unbiased position to take, Apparently there's
Speaker 3: a pro plantation stance that could have been taken that
Speaker 3: I guess I should have taken. I mean, I got
Speaker 3: to the point where my sister would call me and
Speaker 3: she'd say, I just heard you on NPR, Like, aren't
Speaker 3: they afraid that one day you're going to be in
Speaker 3: a live interview and you're going to just say I'm
Speaker 3: being treated like trash at this company.
Speaker 6: Here's what's going on.
Speaker 3: And there was this dissonance that they believed that my
Speaker 3: work was good enough to be on all things considered
Speaker 3: to be the one who's out there talking about the company.
Speaker 3: Because my work was good, my face was the right
Speaker 3: face for it. But I wasn't worth being paid and
Speaker 3: respected the way that others were to me.
Speaker 4: What was it like agitating for the stuff that you
Speaker 4: were agitating or advocating for inside Google?
Speaker 7: So, like two months after I joined, I would say,
Speaker 7: was the Google walkout?
Speaker 6: Yeah?
Speaker 7: And I sent this email being like I am so
Speaker 7: glad this is happening because I've only been here for
Speaker 7: two months and this is ridiculous, you know. And ever
Speaker 7: since then, I think I didn't really make friends and
Speaker 7: with the higher ups, you know, and I think we
Speaker 7: what the way I tried to do it at Google
Speaker 7: is me and Meg were always a duo, and so
Speaker 7: my co leead Meg was in trouble when I got in,
Speaker 7: and yeah, so I always went to her HR meetings
Speaker 7: with her and they're like, what are you doing?
Speaker 5: Like I'm with her, you know.
Speaker 7: And they're like, I'm complaining about all the issues she's
Speaker 7: facing when they asked me like what what should be better?
Speaker 7: And I and they're like, but what about you? And
Speaker 7: I said, look, that's going to be me in like
Speaker 7: two years. So we tried to go as a team
Speaker 7: and back each other up every time we complained about
Speaker 7: whatever it is, like gender discrimination, racial discrimination, et cetera.
Speaker 5: And they didn't ding.
Speaker 7: Me on my performance review because my manager was trying
Speaker 7: to protect us. But it always felt like they were
Speaker 7: waiting for something, because you know, we always get that
Speaker 7: policing and it was really exhausting, and so I felt
Speaker 7: like that they found that one thing when I, you know,
Speaker 7: with my paper.
Speaker 4: Sofia, when it comes to sort of the broader state
Speaker 4: of tech workers.
Speaker 2: Is history repeating itself? I think it's the same history.
Speaker 2: It's just a new industry.
Speaker 8: There's this way of critiquing people who have something to
Speaker 8: say about technology, calling us ledites, right.
Speaker 2: I mean, this is like a you know.
Speaker 8: A group of people of workers who understood that new
Speaker 8: technological inventions were going to reshape the labor force and
Speaker 8: we're actually going to take away the creativity, the creative
Speaker 8: labor in fact that the Ledites did.
Speaker 2: You know.
Speaker 8: I find that to be so similar today that people
Speaker 8: who are saying, listen, so many of these products that
Speaker 8: are being brought to bear in the marketplace are not
Speaker 8: only harmful, but they they steal our creative imagination, they
Speaker 8: steal our human agency. They are you know, these are
Speaker 8: dangerous to humanity. We get kind of I think marked
Speaker 8: as some type of not innovative, not forward thinking.
Speaker 2: You know, Luddites, and I think we're in fact that's
Speaker 2: a compliment.
Speaker 8: I mean we are actually people who have, like many
Speaker 8: people who are trying to say some technological innovations are
Speaker 8: actually going to undermine workers, the quality of work, the
Speaker 8: nature of work, the creative expression and joy that also
Speaker 8: can be tied to work. They are going to flatten
Speaker 8: our human experiences in so many ways, rob people of
Speaker 8: opportunity for close opportunity. Those kinds of criticisms many people
Speaker 8: have made for centuries when we have seen industries extract
Speaker 8: to the point of absurdity and leave workers holding the bag,
Speaker 8: or leave workers unable, in the case of tech workers,
Speaker 8: unable to live in the Bay Area, unable to afford
Speaker 8: unable to afford to raise children. I mean, I can't
Speaker 8: even tell you how any women I've met who feel
Speaker 8: that they have to choose between working in certain industries
Speaker 8: or having a family. I mean, these are ludicrous ideas,
Speaker 8: especially in an industry that is making more money than
Speaker 8: any other industry on the planet.
Speaker 4: And this is global too, right, I mean, isn't aren't
Speaker 4: there workers propping up tech around the world? Yeah?
Speaker 7: I mean we had an event a Dare called Stochastic
Speaker 7: Parents Day, which is about a paper that I got
Speaker 7: fired for, and Sophia and I were actually on a
Speaker 7: panel there with somebody whose name was A Richard, and
Speaker 7: he was one of the workers who was labeling the
Speaker 7: outputs of the models of open A models like chat
Speaker 7: GPT or these text image models, and he was talking
Speaker 7: about how traumatic it was, and he was detailing for
Speaker 7: us the PTSD that comes with it, and how much
Speaker 7: worse it is when it's actually synthetic data, right, like
Speaker 7: generated content, because you go home wondering if this is actually,
Speaker 7: if this happens, if people do this in the real world,
Speaker 7: because you can just generate any kind of content you want, right, So,
Speaker 7: people like him, we're getting paid like an a one
Speaker 7: dollar something an hour, and workers like that are left
Speaker 7: dealing with the trauma that they.
Speaker 5: Experienced and they have no resources to do that.
Speaker 7: So it's similar to the extraction industry. It is global
Speaker 7: and it preys on vulnerable people.
Speaker 4: Open AI was accused of using workers in Kenya, paying
Speaker 4: them less than two dollars an hour to make chat
Speaker 4: GBT less toxic. I asked the CTO about this, and
Speaker 4: she said, we chose this particular contractor because of their
Speaker 4: known safety standards, and since then they've stopped using them.
Speaker 4: This is difficult work and we recognize that, and we
Speaker 4: have mental and wellness standards.
Speaker 7: This is a known tactic to offload to a third
Speaker 7: contractor so that you are not the one who is
Speaker 7: being held accountable.
Speaker 8: So yeah, they borrowed that right from the fashion and
Speaker 8: just and other industries. So there are many industries that
Speaker 8: have done that. The tech industry has pulled a page
Speaker 8: right out of those playbooks. And I teach my students
Speaker 8: at ECLA about all.
Speaker 2: Kinds of different social movements.
Speaker 8: One of the things that people feel about what's happening
Speaker 8: with tech is that it's just kind of it's totalizing,
Speaker 8: it's a fata complete. These are the technologies that we have.
Speaker 8: They're here now, there's nothing we can do. We have
Speaker 8: to live with them, make the best of it. And
Speaker 8: of course, people who live during the era of the
Speaker 8: Transatlantic slave trade, people who lived in the Americas during
Speaker 8: the time of the period of enslavement also got up
Speaker 8: every day and got their kids ready for school. They
Speaker 8: completely normalize the experience of enslavement. And so this is
Speaker 8: I think an important thing to invoke is that people
Speaker 8: build societies that they think are normal when they are
Speaker 8: the beneficiaries of them for the most part.
Speaker 2: And also people who are oppressed.
Speaker 8: Inside those systems come to accommodate in some ways because
Speaker 8: it is totalizing and overwhelming to live under those kinds
Speaker 8: of oppressive systems.
Speaker 2: And there are.
Speaker 8: Also people who seek to abolish who resist and are
Speaker 8: like absolutely not, no way, not in my lifetime, not
Speaker 8: in my children's, my grandchildren's.
Speaker 2: I think we are, in fact.
Speaker 8: All three of us the descendants of people who refused
Speaker 8: in one way or another.
Speaker 3: And I think it's important to say we're not anti technology.
Speaker 3: My entire career was at Google, Facebook, Pinterest. I'm working
Speaker 3: on issues within the industry, but we're pro human dignity,
Speaker 3: and currently in the industry, unfortunately, human dignity is not
Speaker 3: even on the list of issues.
Speaker 6: It's not there.
Speaker 4: Algorithms are a complete mystery to most of us on
Speaker 4: the outside, a black box. You know, we know the
Speaker 4: recommending videos or targeting ads, but how are algorithms influencing
Speaker 4: us in ways that we are completely unaware of.
Speaker 7: You know, sometimes I don't even know myself right when
Speaker 7: you're on social media and you're super angry and you're
Speaker 7: responding to everything versus not, you don't realize that that's
Speaker 7: because the algorithms that they're using maximize for engagement of
Speaker 7: any kind, and when you're angry, you're engaging with the
Speaker 7: site more So, I feel personally, even as someone in
Speaker 7: this field, I'm still learning about all the different ways
Speaker 7: in which my day to day life is being influenced
Speaker 7: by a bunch of decisions that companies are making.
Speaker 4: Decisions like to release chat GPT.
Speaker 3: Yes, I mean that so chat GPT absolutely is important
Speaker 3: and we should discuss it. But even that using that
Speaker 3: is a choice. Currently, using social media the companies that
Speaker 3: I worked for, using their product is a choice. But
Speaker 3: where algorithms are particularly dangerous is where we don't have
Speaker 3: a choice. There are algorithms that determine what kind of
Speaker 3: care you're going to get if you're black and you
Speaker 3: have kidney disease. There are algorithms that determine like, for instance,
Speaker 3: when I went to purchase this house, I could have
Speaker 3: ended up in a situation where I wasn't able to
Speaker 3: get a mortgage depending on the algorithm that the mortgage
Speaker 3: company was using. And that's where we really have to
Speaker 3: be careful because it's not consumer choice. It's not that
Speaker 3: consumers are ignorant, and so the responsibility is theirs. The
Speaker 3: responsibility really lays with the companies and with regulating agencies
Speaker 3: who don't understand or just don't care.
Speaker 4: So when chat GPT comes out and there is so
Speaker 4: much buzz so fast, what goes through your minds?
Speaker 7: Eye roll so hard that COMPLI roll to the back
Speaker 7: of my head, you know, Like I wrote a paper
Speaker 7: about large LA models like two years ago, and most
Speaker 7: people didn't know what it was. I'm not surprised at
Speaker 7: the rate, I would say, of deployment, but I am
Speaker 7: surprised at the constant daily hype, the free pr that's
Speaker 7: being given some of these companies, completely uncritical right of
Speaker 7: dear claims like it's disheartening personally speaking, What are.
Speaker 4: Your what are your biggest concerns about AI? Now that
Speaker 4: it's not in a lab at Google anymore, it is
Speaker 4: out and everybody knows about it.
Speaker 6: What worries you most?
Speaker 8: I think the thing that keeps me up at night
Speaker 8: is the amount of data that's collected on us every
Speaker 8: single day just by having a data collection device in
Speaker 8: our bag or our pocket, the phone, and all the
Speaker 8: kinds of things that we're interacting with, and the predictions
Speaker 8: that get made then from that data that's collected about
Speaker 8: us that will foreclose opportunity. Kathy O'Neill talks about this
Speaker 8: in her book Weapons of Maths Destruction that these types
Speaker 8: of prediction, predictive algorithms and AI make things better for
Speaker 8: people who are already doing great and things worse for
Speaker 8: people who are not faring well. And that is probably
Speaker 8: the thing that it stresses me out the most, is
Speaker 8: that those types of AI that get embedded in every
Speaker 8: industry as again a tool of alleged efficiency, are using
Speaker 8: data sets and also data collected about us to over
Speaker 8: determine what our futures will be.
Speaker 5: To me.
Speaker 4: When you left Google, it sort of triggered this wave
Speaker 4: of agitation within you. Now were hearing that some Google
Speaker 4: employees begged for Bard to not be released.
Speaker 1: They said it was a pathological line.
Speaker 6: Is the tension building, you know?
Speaker 7: Unfortunately, I would say that there was a moment that
Speaker 7: we had where people were speaking up, and now it's
Speaker 7: like backlash all the way down, and I feel like
Speaker 7: they're making the calculation that they don't even need to
Speaker 7: pretend anymore.
Speaker 4: The tension is it building in like a progressive way,
Speaker 4: like a way that leads to progress, or.
Speaker 5: So I think that we need regulation.
Speaker 7: So perhaps that kind of momentum is building. More people
Speaker 7: are thinking about regulation. But in terms of worker protection
Speaker 7: and workers inside these organizations pushing back, they're facing so
Speaker 7: much backlash with a lot of the layoffs of these
Speaker 7: ethics teams at Microsoft, at Google, at Twitch.
Speaker 5: I'm sure there's more too.
Speaker 9: I mean, let's not even here's where policy as I'm
Speaker 9: not a computer scientist, I'm not an academic, but I
Speaker 9: know policy, and here's where policy makers are really dropping
Speaker 9: the ball.
Speaker 3: We had an opportunity to move forward on something like
Speaker 3: healthcare and disentangling health care from employment. That's one piece
Speaker 3: that would allow people to speak up, because if your
Speaker 3: access to healthcare, if your family's access to healthcare isn't
Speaker 3: dependent on your employer, then you can talk about harms
Speaker 3: that you're seeing in the technology that's being created. If
Speaker 3: policymakers were willing to step up and actually regulate some
Speaker 3: of these things before they're an issue, or as they're
Speaker 3: an issue, then we wouldn't be in this place where
Speaker 3: you have lawmakers in Utah who think that it's a
Speaker 3: solution to ban kids from using social media and disconnect
Speaker 3: them from communities that are actually life giving and life
Speaker 3: affirming for people who are in marginalized communities.
Speaker 2: Right, or just pushing the onus of.
Speaker 8: Like control from being harmed to the individual. The thing
Speaker 8: that people forget is that so much of the R
Speaker 8: and D for these kinds of technologies is offloaded already
Speaker 8: it's the riskiest part of the business, and it's offloaded
Speaker 8: to the public. The public pays for the most dangerous
Speaker 8: dimensions of what the companies do because most of those
Speaker 8: companies have partnerships with academic labs and they get NSF
Speaker 8: National Science Foundation funding and other kinds of government funding
Speaker 8: to do that experiment. So here the public pays for
Speaker 8: the experiments and then never benefits from the profitability of
Speaker 8: any of these companies. And then they regulate downstream and
Speaker 8: say it's on you to figure out whether it's safety.
Speaker 7: I mean, Silicon Valley got most of its money from
Speaker 7: the government. Right during World War two, and after that, right,
Speaker 7: like Elon Musk the amount of money California taxpayer money
Speaker 7: that he got, and they talk about, you know, pulling
Speaker 7: yourself up with the straps.
Speaker 4: There's this perception that artificial intelligence is magic, but what's
Speaker 4: really happening.
Speaker 3: There are human beings like the one who you mentioned
Speaker 3: who are tagging things. They're human beings who are ensuring
Speaker 3: that we, those of us in polite society, don't have
Speaker 3: to see the murders that are being captured, the beheadings
Speaker 3: that are being played live on Facebook or on YouTube
Speaker 3: or anyone else.
Speaker 6: Someone is seeing that it's just not us, and.
Speaker 5: They don't think it's magic.
Speaker 7: The people who are doing the data labeling, the people
Speaker 7: who are content content moderation, and a lot of the
Speaker 7: people whose work is being stolen to train these models,
Speaker 7: like the artists whose images have been taken without any
Speaker 7: sort of attribution or payment, or the writers who you know,
Speaker 7: I was just at a conference listening to artists and
Speaker 7: writers talk about some of the issues that they see
Speaker 7: with these generative AI models, right, and what the future
Speaker 7: holds for them. And they don't see it as magic.
Speaker 7: They see it as plagiarism and theft. So you know,
Speaker 7: and I want to say that in my field, there
Speaker 7: is a concerted effort to make it sound like magic.
Speaker 7: It's this obfuscation that happens on purpose so that you
Speaker 7: don't see where the data is coming from, who it's
Speaker 7: being stolen from, because they would have to compensate everybody,
Speaker 7: how the workers are being exploited. And then something's something
Speaker 7: in the cloud, right, it's not the cloud is data
Speaker 7: centers taking lots of water. I mean we were just
Speaker 7: hearing about the water usage of CHATCHPT. You know, when
Speaker 7: you really make it visible, it's not magic. You know,
Speaker 7: it's not sentience or magic or anything like that.
Speaker 3: Oh, there's nothing wrong with convenience. We all appreciate convenience,
Speaker 3: but I don't want my convenience at the expense of
Speaker 3: another human being.
Speaker 4: What's your long term view about how many jobs this
Speaker 4: will disappear and create? Because you know, we're talking about
Speaker 4: more not so great jobs, right the tagging of chat GPT, like, like,
Speaker 4: how do you see this playing out?
Speaker 7: So I'm very worried about like the centralization of power
Speaker 7: that this type of technology is enabling. So if you
Speaker 7: whether you believe their claims or not, the claims of
Speaker 7: these companies or not right, what they're striving for is
Speaker 7: one model that does everything for you. You you want to
Speaker 7: go to a doctor, talk to a chatbot, a lawyer,
Speaker 7: talk to their chatbots. So what they're planning on having
Speaker 7: is they're like the super renter where everybody else builds.
Speaker 5: On top of them.
Speaker 7: They have APIs on top of one or two or
Speaker 7: three companies for everything. So this is not the world
Speaker 7: I want to live in.
Speaker 1: So what does society even look like?
Speaker 2: In this world?
Speaker 1: Is there like a massive wealth gap? Is there on casts?
Speaker 5: I mean?
Speaker 4: Or is everyone happy because we're on universal basic income?
Speaker 7: Not the last one because I mean they're not, but
Speaker 7: they could do that now. Like it's just like according
Speaker 7: to open I Ah, you know, utopia is just around
Speaker 7: the corner any day now, and we're all gonna be happy.
Speaker 7: I don't think that we're all gonna like work less.
Speaker 7: I think that's not what's going to happen. But I
Speaker 7: think that the work, certain people's work, I feel like
Speaker 7: it's gonna get degraded, degraded. So a lot of artists
Speaker 7: are very worried about losing their jobs, and not because
Speaker 7: the image generator thing is going to be as good
Speaker 7: as an artist, but someone's gonna think that it's good
Speaker 7: enough or something like that, and so they won't hire one.
Speaker 5: I think that the content moderation.
Speaker 7: Requirements are going to be exploding with the amount of
Speaker 7: synthetic media that we have on the Internet, and so
Speaker 7: I feel like we'll have a lot more content moderation
Speaker 7: kind of jobs.
Speaker 5: But then we know what those jobs are like. So
Speaker 5: I'm not looking, you know, I'm not optimistic.
Speaker 4: There's a lot of doom mongering about the capabilities of AI.
Speaker 1: For the people who are scared, what do you want
Speaker 1: them to know?
Speaker 2: They're not wrong wrong, that's right, they're not wrong.
Speaker 8: Well, I mean, I would say that degradation is a
Speaker 8: really helpful word in this, because people have a sense
Speaker 8: that something is off and something is going to be
Speaker 8: lost with these technologies. I will tell you right now
Speaker 8: in classrooms around the country, and I'm seeing this already
Speaker 8: in our university system. Some people think something like generative
Speaker 8: AI helps level the playing field.
Speaker 2: So there's a lot of mythologies.
Speaker 8: Right if you're not a great writer and you're in
Speaker 8: the sciences or you're a math student, you don't have
Speaker 8: to worry about that when you're those English classes. Now
Speaker 8: because you've got open AI is going to help you
Speaker 8: write those essays.
Speaker 2: What is lost?
Speaker 8: Imagine not learning the things that you learn when you
Speaker 8: put yourself in an environment to learn something. So I
Speaker 8: think we will have a transformation in the field of
Speaker 8: education that will not be what we want.
Speaker 2: I don't think it will help us think critically.
Speaker 8: A lot of us are doing experience experiments where we're
Speaker 8: looking up certain types of things where we are subject
Speaker 8: matter experts and we know a lot about that, and
Speaker 8: we're asking open AI and it's giving us terrible answers.
Speaker 2: That look good enough.
Speaker 8: And so the loss of expertise, the loss of knowledge,
Speaker 8: those kinds of things are very important in societies that
Speaker 8: we have reliable information that we can all act upon
Speaker 8: as voters, as parents, as a residence, as people who
Speaker 8: live in communities.
Speaker 4: Fake it so you make it, and it's making it
Speaker 4: right now.
Speaker 2: I'm predicting the wrong things.
Speaker 3: One of the things that I think is important here
Speaker 3: misinformation disinformation have been a focus of mine is the
Speaker 3: shrimping of context, and that's one of my main concerns
Speaker 3: with chat, GPT and AI bots like that, because.
Speaker 4: We're losing, we're not gaining that.
Speaker 3: Yeah, because it's one thing, I think to present a
Speaker 3: bad answer. It's another thing to present it as though
Speaker 3: it's the only answer, and without showing your sources or
Speaker 3: anything else, so that if you're the person on the
Speaker 3: receiving end of that answer, you can say, Okay, well
Speaker 3: this came from this source. I can look that source
Speaker 3: up and make my own determination.
Speaker 4: You know, a bunch of people sign this letter, including
Speaker 4: Elon Musk, calling for a pause on the development of AI.
Speaker 2: What was your take on that?
Speaker 7: I mean, we had to write a statement responding to
Speaker 7: it because it really confused the conversation. A lot of
Speaker 7: people are like, great, that's what you've been asking for,
Speaker 7: this is what you want, and we had to put
Speaker 7: a stake in the ground and be like, no, we
Speaker 7: are different from those people.
Speaker 6: We called it unhinged.
Speaker 7: Yeah, yeah, it was completely unhinged because some of the
Speaker 7: things that all three of us are discussing right now
Speaker 7: are not sci fi scenarios. We're talking about people losing
Speaker 7: opportunities today. We're talking about people not getting a mortgage,
Speaker 7: people not getting care, people being sentenced, you know, have
Speaker 7: really high sentences because of some mundane, not sci fi
Speaker 7: algorithms that are right now currently deployed, and then we're
Speaker 7: currently talking about worker exploitation Monday, not sci fi, you know.
Speaker 7: And in this pause letter they're talking about as if
Speaker 7: it's magic, it's this magical thing. It's it's we've created
Speaker 7: something too powerful.
Speaker 5: We don't even know how it's gonna Oh.
Speaker 8: No, they just want to slow down so they can
Speaker 8: get catch up. That is like my take on it
Speaker 8: is that not only do they are they trying to
Speaker 8: positive as magic, but they're doing that as a tactic
Speaker 8: so they can catch up because they're behind.
Speaker 7: Well he started Elon Musk started this truth Chat truth
Speaker 7: GPT thing now right right after he's signed saying stop,
Speaker 7: It's like, oh, I have.
Speaker 6: My own things.
Speaker 8: Know. What they mean is slow down so we can
Speaker 8: catch up, Sophia, to use your term algorithms of oppression
Speaker 8: algorithms supercharged on AI.
Speaker 4: Given all the bias and misrepresentation and misinformation issues that
Speaker 4: already exist, how much damage could we do?
Speaker 6: What could the fallout be?
Speaker 2: We are already doing a lot of damage.
Speaker 8: We have products in this industry, in the tech industry,
Speaker 8: that are made up and launched out of the public,
Speaker 8: no oversight, no one checking for whether these are going
Speaker 8: to do damage until the kinds of communities of researchers
Speaker 8: and technologists that we're part of start to end. Community
Speaker 8: organizers and journalists start exposing the evidence of harm.
Speaker 4: AI is so much more than chatbots. What are all
Speaker 4: the other ways that AI is developing. I mean, we're
Speaker 4: talking about surveillance and facial recognition and all of these
Speaker 4: other things that are very.
Speaker 3: Consequential surveillance in ways that people can't opt out of
Speaker 3: and people can't defend themselves from. They are people who
Speaker 3: have been arrested because their face came up in a
Speaker 3: police database where it wasn't actually their face.
Speaker 6: There's no way.
Speaker 3: To opt out of being included in this database. And
Speaker 3: there are no guardrails for both the police departments that
Speaker 3: are buying this technology using our dollars, our taxpayer dollars,
Speaker 3: and then the companies that are scraping this content from
Speaker 3: the Internet. There are no guardrails anywhere, and actual people
Speaker 3: are paying the price.
Speaker 4: And by the way, you've got a handful of companies
Speaker 4: that are based in Silicon Valley deciding what the next
Speaker 4: tech platform will be.
Speaker 1: Where most of the people who work there are white men.
Speaker 4: Let's be honest, are you thinking to yourselves like here
Speaker 4: we are, here, we've been going.
Speaker 8: And the consequences of that are really mundane in ways,
Speaker 8: like maybe this app can help me track my period
Speaker 8: better than I could in my diary, so I use that,
Speaker 8: and now law enforcement has about door to come and
Speaker 8: arrest me because it might look like I'm planning to
Speaker 8: have an abortion from some type of analysis of my period.
Speaker 5: Trekker.
Speaker 8: So that seems so sci fi, but that's actually happening today, right,
Speaker 8: very mundane kinds of ways. We do these things in
Speaker 8: education where students have to use these learning management systems
Speaker 8: and upload papers and give comments and do all of
Speaker 8: these things in these tech systems, and then algorithms are
Speaker 8: run on them that predict which students are going to
Speaker 8: be the most successful. In fact, financial aid officers and
Speaker 8: a mission officers now in universities are people who need
Speaker 8: to be skilled in CRM databases because what they're doing
Speaker 8: is they're looking to see who's most likely to matriculate
Speaker 8: in four years.
Speaker 2: Well, you know who that is.
Speaker 8: It's not somebody like me who had to work thirty
Speaker 8: hours a week to get through undergrad his parents couldn't
Speaker 8: pay for them to go to college.
Speaker 2: I would definitely fail the.
Speaker 8: Statistical model right of who the most idea kind of
Speaker 8: university that seems so banal. These kinds of things are
Speaker 8: really they're not part of the doomsday machine, but they
Speaker 8: actually are the kinds of things that, even if you
Speaker 8: don't think you're ever going to get entrapped in a
Speaker 8: mugshot database, you care about whether your kids get an
Speaker 8: opportunity to go to school. When the Trump administration announced
Speaker 8: that they were going to adopt a new software that
Speaker 8: was going to predict who the next mass shooter was,
Speaker 8: I thought to myself, this will be the moment that
Speaker 8: white men care about these conversations because it's going to
Speaker 8: be them that's going to be in the database, because
Speaker 8: they're the profile of the mass shooter. And you're telling
Speaker 8: me you're going to apply an algorithm to determine who
Speaker 8: the next mass shooter is.
Speaker 2: You've got to be kidding me. There couldn't be more
Speaker 2: snake oil to be sold. So everybody's in on this.
Speaker 8: Everybody needs to be concerned because everybody could potentially be harmed.
Speaker 4: The issues that you're raising sound like what a lot
Speaker 4: of the tech leaders say they care about. Reid Hoffman
Speaker 4: and Sam Altman and Sacha Nadella and so Darkachai and
Speaker 4: even Elon Musk who said we want AI that benefits society.
Speaker 1: Where do you diverge?
Speaker 2: I mean, I don't think we say what they say.
Speaker 2: I don't think.
Speaker 8: I mean I would say, I think there are a
Speaker 8: lot of types of AI that should be abolished, that
Speaker 8: should not be in the marketplace, that are making claims
Speaker 8: that are unfounded and are actually proven to be harmful.
Speaker 8: And I'm not convinced in fact that AI can be
Speaker 8: used for good.
Speaker 2: I'm not one of those people.
Speaker 8: I also think that they have adopted the language of
Speaker 8: the people who have been raising the criticisms and have
Speaker 8: incorporated those criticisms and then put themselves in charge of
Speaker 8: solving the very problems that they're being critiqued for.
Speaker 2: So this is where you know.
Speaker 8: To me, and you know, I always laugh with her
Speaker 8: because I remember the day that Google announced that it
Speaker 8: was forming like an ethical.
Speaker 2: AI team, and I was like, am I being punked?
Speaker 8: Like there's just no way in the world that the
Speaker 8: people who have been denying that their products are harmful
Speaker 8: for a long time are now in charge of addressing
Speaker 8: that there are some harms. It's profitable for them to
Speaker 8: look socially responsible. Companies have been trying to put posit
Speaker 8: themselves as socially responsible at the point that consumers start
Speaker 8: to be concerned about the lack of social responsibility of
Speaker 8: those companies.
Speaker 2: But I don't think that we're actually saying the same
Speaker 2: thing at all.
Speaker 4: What's been more communication, like with tech workers on the
Speaker 4: inside of Google and Apple and other companies where there
Speaker 4: has been organizing.
Speaker 7: It seems like everybody we've been communicating with has been
Speaker 7: getting fired. We have you back channels, and we have
Speaker 7: some kind of channels of organizing. But my sense is
Speaker 7: that right now a lot of people are scared because
Speaker 7: of the layoffs, and a lot of people are Yeah,
Speaker 7: So that's that's been my sense recently.
Speaker 4: Should people speak up, walk out, leave if they see injustice?
Speaker 4: Is there any way to communicate your concerns internally effectively.
Speaker 3: I'm glad you asked that because my view is and
Speaker 3: always has been, no one should make themselves a martyr.
Speaker 6: I don't believe in martyrdom.
Speaker 3: I think if you feel the conviction, if you are
Speaker 3: able to because of your familial situation, your financial situation,
Speaker 3: to speak up, then you should. But we live in
Speaker 3: a capitalist society. Capitalism all has us all by the throat,
Speaker 3: and so if you need money to shelter, to have shelter,
Speaker 3: to have healthcare, to have food, to care for your family,
Speaker 3: I don't want anyone to risk all of that because
Speaker 3: of harm that are continuing. But for the people who
Speaker 3: are and the people who are standing up, we have
Speaker 3: to do everything that we can to protect and support
Speaker 3: them and do what we're able to on the outside
Speaker 3: now to ensure that their work isn't for vain and
Speaker 3: are in vain.
Speaker 4: You help get the Silence No More Act pasted in California.
Speaker 4: You've got the attention of Governor Gavin Newsom.
Speaker 6: Yep.
Speaker 4: This means that companies can't use NDAs to prevent employees
Speaker 4: from speaking out about certain things.
Speaker 6: Right.
Speaker 5: Is that enough protection?
Speaker 3: I mean it's protection for forty million people for both
Speaker 3: non disclosure and non disparagement agreements. So it's more than
Speaker 3: existed before. But the work is continuing. A similar bill
Speaker 3: was passed in Washington State. My hope if we ever
Speaker 3: get a function in Congress would be to have federal
Speaker 3: protections because as we know, workforces are distributed and so
Speaker 3: there are people working all over the country right now,
Speaker 3: who are on teams where their manager may be protected
Speaker 3: in California at a headquarter of a tech company, but
Speaker 3: the people who are actually being harmed may be in
Speaker 3: Texas or Louisiana or New York and not have those protections.
Speaker 4: You also created the Tech Workers Handbook R What can
Speaker 4: workers find?
Speaker 5: There?
Speaker 3: Resources on how to seek legal help, resources on how
Speaker 3: to speak with reporters. One of the things that I've
Speaker 3: talked about a lot is one of the advantages and
Speaker 3: privileges that I had when I came forward is I
Speaker 3: had experienced speaking with people like you. It's not easy
Speaker 3: to sit down and talk about a traumatic experience you've had,
Speaker 3: and it's not easy to sit down and answer questions
Speaker 3: without training. That's training that I got on the inside
Speaker 3: of these companies speaking on behalf of the companies, and
Speaker 3: of course I was going to use that to speak
Speaker 3: on my behalf and on the behalf of other workers.
Speaker 1: The circuit continues after this quick break.
Speaker 4: So is regulation the only way to keep us in check.
Speaker 3: It's the most important way because it's the way that
Speaker 3: impacts the largest number of people, and we want everyone
Speaker 3: operating under the same framework and protections. We may be
Speaker 3: shareholders of a company, but we're small fry. I mean
Speaker 3: the banks, the folks who are really making the decisions
Speaker 3: because they own one to three percent of a company,
Speaker 3: They could step in, and they should step in because
Speaker 3: long term their investments are impacted by the harms that
Speaker 3: these companies are perpetrating.
Speaker 2: Yeah, I would say just a build on that too.
Speaker 8: Workers should be looking at their pensions and where their
Speaker 8: investments and their four one ks are. We remember there
Speaker 8: were so many people I remember just two decades ago
Speaker 8: who were organizing around making sure that they were not
Speaker 8: investing in prisons or in military weapons and other kinds
Speaker 8: of things. They did not want to see their pensions
Speaker 8: and Furrow and Kay's invested in. So those are other
Speaker 8: ways that everyday people can also be asking the kinds
Speaker 8: of questions of the companies where they work and how
Speaker 8: their assets are being managed.
Speaker 4: If you had one year to run these companies, what
Speaker 4: would you do.
Speaker 3: I like my life here raising my goats and chickens,
Speaker 3: so I wouldn't. But I am happy to continue the
Speaker 3: work that I'm doing now. I mean there's so much harm,
Speaker 3: like I said, that's been done that before you figure
Speaker 3: out the plan for what's next.
Speaker 6: There needs to be repair work that's done.
Speaker 2: So what does that look.
Speaker 3: Like actually paying people for the harms that they've endured,
Speaker 3: whether that's consumers who have been harmed by privacy violations
Speaker 3: or the workers who have been harmed through wage theft
Speaker 3: and asking physical harm to themselves.
Speaker 8: Let's say your Google's search algorithm is populating some kind
Speaker 8: of disinformation about you, and you can't get that off
Speaker 8: of the search engine and it's precluding you from employment.
Speaker 2: You need repair from that.
Speaker 8: You can't just submit online a request for Google to
Speaker 8: take that down. They have hundreds of thousands of takedown
Speaker 8: requests that are never going to be attended to.
Speaker 2: So you need to have these spaces, these.
Speaker 8: Intermediaries where people can go and say I have been harmed,
Speaker 8: this product is faulty. There needs to be liability both
Speaker 8: for the company, but also I need to be able
Speaker 8: to litigate or have some type of repair.
Speaker 2: We don't really have.
Speaker 8: The laws on the bark action so that people can
Speaker 8: in fact get the remedies that they need through courts.
Speaker 8: We also don't have a judiciary that is properly educated
Speaker 8: yet so on how.
Speaker 2: To resolve some of these things.
Speaker 8: So we need human and civil rights laws that give
Speaker 8: people the kinds of protections that they need to and
Speaker 8: when really, I think Congress is not caught up with
Speaker 8: the digital age and the kinds of harms and civil
Speaker 8: rights violations.
Speaker 2: So this is also another place of enforcement.
Speaker 4: So civil rights for the digital age, which is absolutely
Speaker 4: been calling for.
Speaker 5: What about you to meet?
Speaker 4: If you could go back to Google and you were
Speaker 4: in charge for a year, what would you do.
Speaker 7: I wouldn't put out a chat bought version of a
Speaker 7: search engine, you know. I think open Ai can do that,
Speaker 7: because that's the only thing really people expect from them.
Speaker 7: Search is not their bread and butter, and so I
Speaker 7: think that, in my opinion, Google just trying to act
Speaker 7: like they're also innovative or.
Speaker 5: Something like that.
Speaker 6: I don't know.
Speaker 7: They wanted to be in the hype cycle too, I suppose,
Speaker 7: and they just put something out there, I would say, Okay,
Speaker 7: this is our bread and butter. Search is our bread
Speaker 7: and butter. You know, we have to maintain the integrity
Speaker 7: of the information ecosystem. As a researcher. Also, I think
Speaker 7: a lot of researchers in computer science can.
Speaker 5: Do something, can choose to do something different.
Speaker 7: There was just a professor at University of Chicago who
Speaker 7: created a tool called Glaze that artists can use to
Speaker 7: when so that when they put out their work, they
Speaker 7: can't be used to mimic their styles. So it fools
Speaker 7: tools like Dally and some of the other texts to
Speaker 7: image generators. So, because you know, when artists are in
Speaker 7: these lawsuits, it takes years for their course to decide,
Speaker 7: they don't have time to wait for this kind of stuff.
Speaker 7: So tech workers could actually choose to use their skills
Speaker 7: to help them protect their art. A lot of us
Speaker 7: talk about the tech industry, but it's not just the
Speaker 7: tech industry. It's the whole ethos of the entire computer
Speaker 7: science engineering, you know, machine learning or whatever research community
Speaker 7: as well that's led to this. It's not just you know,
Speaker 7: the corporations.
Speaker 3: So policymakers too, who are bought and paid for by
Speaker 3: the companies that they're supposedly legislating against and meant to
Speaker 3: be regulating.
Speaker 6: When when you look at.
Speaker 3: The spending that Google and others do in campaigns that
Speaker 3: they make sure is fifty to fifty on either side,
Speaker 3: they're funding absolutely everyone. Who is it that we can
Speaker 3: turn to as a champion when they're all accepting money
Speaker 3: from these companies.
Speaker 5: So are we stuck?
Speaker 1: I mean, is there a glimmer of hope?
Speaker 8: Like, yeah, absolutely, we know we know many how many
Speaker 8: people who are glimmers of hope.
Speaker 2: And you know, it's interesting because ten years ago it
Speaker 2: was very hard to have this conversation.
Speaker 8: So we know that a lot of envelopes are being
Speaker 8: pushed and that we're even in a space to bring
Speaker 8: these conversations up and have them understood. So of course
Speaker 8: there's lots of hope. I mean, this is why I think,
Speaker 8: you know, scholars and journalists and tech workers and artists,
Speaker 8: we're able to make those conversations legible to everyday pe
Speaker 8: And to me, that is incredibly hopeful.
Speaker 4: If the CEOs of Google and Microsoft and Amazon and Apple, Facebook,
Speaker 4: we're in this room right now.
Speaker 5: What would you say to them?
Speaker 6: Nothing?
Speaker 3: That nothing that would be super effective if their gcs
Speaker 3: weren't also here, Because some of these CEOs may want
Speaker 3: to do things differently, but they have legal counsel who's
Speaker 3: ensuring they don't. And so what I have found, even
Speaker 3: when I've been in conversations with CEOs and decision makers
Speaker 3: is they are looking to the people who really make
Speaker 3: the decisions, and those are the ones who are mitigating
Speaker 3: for risk. And right now, it's not a risk to
Speaker 3: harm workers, it's not a risk to harm consumers. It's
Speaker 3: not more of a risk than harming shareholders. And so
Speaker 3: we have to speak to the people who are actually
Speaker 3: the decision makers. And it's not always the CEOs.
Speaker 8: Well it was to say, I mean are of course,
Speaker 8: but also the fines that they pay to when they
Speaker 8: violate the law, and you know, the court cases that
Speaker 8: they settle.
Speaker 2: It's like pocket.
Speaker 6: Lint to these companies.
Speaker 2: It's not their money.
Speaker 8: So for sure we know that CEOs, if they were
Speaker 8: personally liable in any way for what happens in those companies,
Speaker 8: well it would be slim pickens for who would want
Speaker 8: to be the CEO of most of these companies. I
Speaker 8: think that if American tech companies in particular really wanted
Speaker 8: to seal their legacy and reputations, they would take these
Speaker 8: conversations to heart and say, all right, you know, we
Speaker 8: are the so called innovators. And this is how they
Speaker 8: frame themselves as being the most imaginative, the best innovators,
Speaker 8: the best thinkers. It's strange how they can't solve these problems.
Speaker 8: Will you stay in kind of a race to the
Speaker 8: bottom to extract profits at all costs, or could you
Speaker 8: innovate a different kind of labor and cooperative model. Could
Speaker 8: you share in the profits with your employees. Could you
Speaker 8: think of different kinds of economic models. I mean, they
Speaker 8: actually could, and that could be transformative, but I don't
Speaker 8: think that there's the will. And I think, you know,
Speaker 8: maybe if they were thinking like good ancestors, like what's
Speaker 8: the legacy that they leave for three or four or
Speaker 8: five generations from now, maybe they would make different kinds
Speaker 8: of choices.
Speaker 3: I also want to add really quickly, I think some
Speaker 3: of the responsibility is on your industry as well, because
Speaker 3: we have living Hagary Graffi's that are done about these people.
Speaker 3: Like we were watching the harms, we're sometimes talking about
Speaker 3: the harm, sometimes honestly, often not very honestly. But then
Speaker 3: they put out something that's new and shiny, and almost
Speaker 3: every outlet runs to cover it and runs to cover
Speaker 3: it using the talking points that the comms and pr
Speaker 3: folks from the companies supply, and so there's a lot
Speaker 3: of responsibility there in the way that things are covered
Speaker 3: and therefore the way that people understand them.
Speaker 6: Yeah, fair point.
Speaker 4: It matters what stories are told, how the stories are told,
Speaker 4: who's telling the stories, whose voices are lifted, So thank
Speaker 4: you for lifting your voices with us today. It sounds
Speaker 4: in many ways like this is an impossible problem to solve.
Speaker 2: Is it impossible?
Speaker 3: No, we're I mean, we're providing solutions there, and we're
Speaker 3: we are following the work of many, many, many other
Speaker 3: people who are not represented here, who are never asked
Speaker 3: to be on camera, who are never asked for a quote,
Speaker 3: and you just have to look at the work that
Speaker 3: they're doing, and the work that communities are asking for
Speaker 3: and that people are stepping up and saying is important
Speaker 3: and necessary.
Speaker 4: If things don't change, what does the future look like?
Speaker 7: I think, you know, I'm worried about the fundamental remaking
Speaker 7: of society the same way it happened with cars. For instance,
Speaker 7: I was just reading this book called The Road to
Speaker 7: Nowhere by Paris Marx talking about that that in the beginning,
Speaker 7: you know, in like the nineteen twenties, nineteen tens, it
Speaker 7: was not okay when cars killed people, people protested people,
Speaker 7: you know, out in the streets. And now it's completely
Speaker 7: normalized and we have a completely different sort of society
Speaker 7: than the one without individual cars. You know, we don't
Speaker 7: have public transportations. So many places talk about Silicon Valley,
Speaker 7: like you fix that. Yeah, And so what I'm worried
Speaker 7: about is a similar type of remaking of society with
Speaker 7: some of these tools right that are out.
Speaker 5: There, where by the time we.
Speaker 7: Regulate things, the society has already been remade, you know,
Speaker 7: in ways that we weren't you know, that we don't
Speaker 7: want and then normalized.
Speaker 8: Yeah, we are pummeling toward a type of global inequality
Speaker 8: that will be very hard to come back from, and
Speaker 8: that will also have incredible consequences, social consequences. You know.
Speaker 8: I think of us and so many other women like
Speaker 8: us and people like us as like the canaries and
Speaker 8: the coal mine. You know, we're we're like chirping, we're trying,
Speaker 8: and then we're gonna go silent.
Speaker 2: And what that.
Speaker 8: Means is we're dead because the fumes have taken us over.
Speaker 8: And that that part seems so tragic and unnecessary when
Speaker 8: we know that there's enough evidence to pivot in other directions.
Speaker 4: If things do change for the better, what could the
Speaker 4: future look like?
Speaker 3: Oh man, I was just looking outside at the goats
Speaker 3: and thinking that my dream, Like what I want for
Speaker 3: my kids, what I want for everyone is work to
Speaker 3: not define your life. I want you to be able
Speaker 3: to make a living that enables you to do what
Speaker 3: brings you joy. If that's milking goats, if that's taking
Speaker 3: eggs from your chickens, like, that's what you should be doing.
Speaker 3: Whatever joy looks like for everyone, and whatever joy looks like,
Speaker 3: specifically for black women, is what I want us to
Speaker 3: be able to get because when black women are taken
Speaker 3: care of, everyone is, and so that's that's the future
Speaker 3: that I want.
Speaker 8: Yeah, I mean, I feel like there's so much there's
Speaker 8: so much wealth in the world.
Speaker 2: Really everybody could have a high quality of life.
Speaker 8: Yeah, you know, like, let's spread a high quality of
Speaker 8: life for everyone.
Speaker 2: I want.
Speaker 8: I don't just want to save incredible world, a joyous
Speaker 8: world like you're talking about. I'm not sure if I
Speaker 8: would do the animals, but I'm just saying, like my
Speaker 8: urban city version of that, I want that for everybody's kids,
Speaker 8: you know, I want that for everybody's generations.
Speaker 2: For everyone, for everyone. Thank you. That was amazing.
Speaker 1: Pinterest said in a statement that it has quote introduced
Speaker 1: pay transparency tools for employees, and taken steps to continually
Speaker 1: monitor employee pay to ensure that we're achieving equal pay
Speaker 1: for comparable work. We've increased the percentage of women in
Speaker 1: leadership and continued to set goals for increasing diversity. The
Speaker 1: company set it's committed to ensuring that every employee feels
Speaker 1: quote empowered to raise any concerns about their work experience.
Speaker 1: Google said in a statement that it seeks to develop
Speaker 1: quote AI in a way that maximizes the positive benefits
Speaker 1: to society while addressing the big challenges guided by our
Speaker 1: AI principles and that quote large language models have known limitations,
Speaker 1: which is why we launched barred as an experiment and
Speaker 1: develop safeguards to provide people with a positive experience. Thanks
Speaker 1: so much for listening to this episode of The Circuit.
Speaker 1: I'm Emily Chang. You can follow me on Twitter and
Speaker 1: on Instagram at Emily Chang TV. You can watch new
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Speaker 1: I'm your host and executive producer. Our senior producer is
Speaker 1: Lauren Ellis. Our associate producer is Lizzie Phillip. Our editor
Speaker 1: is Sarah Lives. Thanks so much for listening.