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Speaker 1: Hi guys, and welcome back to another new episode of

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Speaker 1: You Need Therapy Podcast. My name is Kat and I

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Speaker 1: am the host, and you guys are in for a

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Speaker 1: treat today. I am so excited about this conversation. Before

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Speaker 1: I get into talking about our guests, I do want

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Speaker 1: to say really quick, remember that this podcast is not therapy.

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Speaker 1: It's just a therapist hosting a podcast, and you know what,

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Speaker 1: it might lead to therapy, but it's not. And now

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Speaker 1: that we have that out of the way, we can

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Speaker 1: get back to why I'm excited for you guys to

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Speaker 1: be able to finally hear this conversation. I've been itching

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Speaker 1: to get it out as soon as I had it

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Speaker 1: and my guest, which I'm so grateful to have had.

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Speaker 1: I'm so grateful to be able to have the conversation.

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Speaker 1: Even if that was a private conversation it wasn't for

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Speaker 1: the podcast. This was one of those where like this

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Speaker 1: challenged and changed my life and I really just loved

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Speaker 1: and it was a conversation with a freaking badass woman

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Speaker 1: named the Bisa, who is the president of the Markup,

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Speaker 1: which is a new investigative journalism startup. We talk all

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Speaker 1: about that in the episode, so I'm going to let

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Speaker 1: the conversation we have do the work there. But I

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Speaker 1: want you guys to know before you walk into this,

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Speaker 1: how freaking amazing this human is one you're going to

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Speaker 1: get to know this because she's captivating and she's easy

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Speaker 1: to understand, and she she has a presence and an

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Speaker 1: energy that you just like want to hang out with her.

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Speaker 1: Side note like I want to be her friend. I quesse.

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Speaker 1: She lived in Nashville. If you ever come to Nashville,

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Speaker 1: please call me. But she is such an intelligent, accomplished

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Speaker 1: human and also humble because you did not hear her

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Speaker 1: talking about how great she is in the episode. You

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Speaker 1: just heard her being a human. But she has done

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Speaker 1: a lot. She worked at BuzzFeed for a while. She

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Speaker 1: was the vice president and associate general counsel at BuzzFeed

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Speaker 1: and was the company's first newsroom lawyer. She been described

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Speaker 1: as one of the best emerging free speech lawyers by Forbes.

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Speaker 1: She's worked at leading media law firms, and she has

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Speaker 1: worked on legal access issues at Guantamino Bay. She's represented

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Speaker 1: asylum seekers in South Texas. She's counseled people on whether

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Speaker 1: to publish hacked materials, spoke about misinformation at the inaugural

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Speaker 1: Obama Foundation Summit. She's incredible and for a lot of

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Speaker 1: all of her work. She's been named forty under forty

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Speaker 1: Rising Star by the New York Law Journal. She was

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Speaker 1: a finalist for the Outstanding Young Lawyer of the Year

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Speaker 1: Award from the International Bar Association, and she has in

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Speaker 1: seventeen I mean, she is one award after award and

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Speaker 1: was named one of Forbes thirty under thirty. She holds

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Speaker 1: a law degree from Yale Law School, and she's just incredible.

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Speaker 1: Like I'm not even naming all the awards because she

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Speaker 1: had so many. And I just want you guys to

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Speaker 1: know that before we go into this conversation, because she

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Speaker 1: is somebody that I want you to trust what she's

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Speaker 1: I want you to walk into this being able to

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Speaker 1: really trust her. Now, I don't think you would even

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Speaker 1: need to know that, because her presence is a very

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Speaker 1: just like captivating one, like I said, and I immediately

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Speaker 1: was like trusting her. But she's just freaking cool. She is,

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Speaker 1: and she's like has a family and as a mom

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Speaker 1: as a two year old, and she lives in New

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Speaker 1: York and she's just great. So I'm excited about this conversation.

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Speaker 1: We talk about social media, We talk about tech and

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Speaker 1: how it sometimes is a scary world and how to

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Speaker 1: gain power and agency back. It is a I opening

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Speaker 1: conversation has changed the way that I am looking at

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Speaker 1: and approaching things in my life, and I just loved

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Speaker 1: having it. And on that I was having a conversation

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Speaker 1: with a friend today about Instagram and how I feel

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Speaker 1: like sometimes it feels as though everybody is privy to

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Speaker 1: all of our lives, like every part of our lives,

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Speaker 1: because now we have the ability to share all of

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Speaker 1: our life with everybody, and so I just feel like

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Speaker 1: this is a conversation that is is so needed and

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Speaker 1: so special and so important, and it talks about how

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Speaker 1: we can gain power from that feeling back again. And

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Speaker 1: I'm excited to have this conversation so I can go

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Speaker 1: back to it and remind myself. So I bet you

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Speaker 1: guys can tell in the energy of my voice, like

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Speaker 1: I am so excited to share this with you. So

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Speaker 1: I'm gonna stop talking about it, and I'm going to

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Speaker 1: let you guys hear my amazing conversation with Nabiha. Thank

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Speaker 1: you for having this with me. You are incredible, And

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Speaker 1: for everybody else please enjoy. I hope that you are

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Speaker 1: just as captivated and inspired as I am. So here

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Speaker 1: it is. Okay, well, welcome to the show. Thank you

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Speaker 1: for having me. I am such a hyper fan, so

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Speaker 1: I can't wait. Okay, Well, I love that because I'm

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Speaker 1: a hyper fan of you. Um, And this is gonna

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Speaker 1: be a conversation that I think is going to be

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Speaker 1: different than any one that I've had yet. And I'm

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Speaker 1: going to give you full disclosure. I understand about negative

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Speaker 1: of anything that has to do with like the law

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Speaker 1: and a lawyer and that kind of stuff. And recently

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Speaker 1: I had to hire a lawyer for some stuff I

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Speaker 1: should have done a long time ago, and it just

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Speaker 1: is so confusing to me. But I feel like you're

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Speaker 1: the kind of person who can help it makes sense.

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Speaker 1: I love breaking things down so and I love explaining things.

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Speaker 1: And it's honestly, the law is confusing, and especially if

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Speaker 1: anything with free speech or tech or like privacy, it's

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Speaker 1: confusing even for the lawyers. So we're going to do

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Speaker 1: our best get into it. You've done a lot of

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Speaker 1: impressive things and exciting things that I want to hear about.

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Speaker 1: I want us to a full circle come and talk

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Speaker 1: about the markup. But I also know that you did

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Speaker 1: a lot of things before that, including kind of what

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Speaker 1: you're saying and working at buzzfeeds. I'm very interested in

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Speaker 1: your history, what you were doing in BuzzFeed and all that,

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Speaker 1: and then what brought you full circle. So can you

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Speaker 1: give us like a history off in the internutshell my life?

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Speaker 1: First things first, I grew up on the Internet in

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Speaker 1: a way that I should not have. My parents got

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Speaker 1: these a O L free CD thirty day c d s.

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Speaker 1: I don't know if anyone else remembers those. We can

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Speaker 1: get the lid c d's mailed to you. So you

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Speaker 1: could have dial up modem internet through a O well,

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Speaker 1: and I got that in second grade. And so I'm

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Speaker 1: just like totally unsupervised because my parents were like internet computer,

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Speaker 1: this is educational. So I grew up loving the Internet

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Speaker 1: like I was with the kids would now call thick,

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Speaker 1: but that was not the word we used in the nineties. Um,

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Speaker 1: and I had never seen like bodies like mine except

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Speaker 1: for on the Internet. I'd be like, oh, like, here's

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Speaker 1: all kinds of people, all kinds of shapes that I

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Speaker 1: don't see on Self magazine or Vogue or certainly TV

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Speaker 1: or like anything in Orange County, California, where I grew up.

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Speaker 1: So I always loved the Internet. That's the journey that

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Speaker 1: went on. Now. So when I, you know, I went

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Speaker 1: to law school, I was so interested in how the

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Speaker 1: Internet was changing these expectations of of what the law

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Speaker 1: prescribed for like newspapers and TV. There's a whole new

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Speaker 1: medium that had needed a whole new rules. So I

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Speaker 1: went to a law firm New York Times, and when

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Speaker 1: the opportunity came to go to BuzzFeed, it felt like

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Speaker 1: someone was saying, welcome, would you like to come to

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Speaker 1: the Internet. Do you want to be a lawyer for

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Speaker 1: the Internet. And I was like, yes, I do. I've

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Speaker 1: been waiting for this since so thank you, Oh my god.

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Speaker 1: But what I what I also just heard you say

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Speaker 1: is when you were introduced to the Internet, it was

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Speaker 1: like a really safe, helpful tool. Yeah, I mean it

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Speaker 1: was a wild It was definitely a wild world West, right,

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Speaker 1: like early nineties. Internet through a O well had a

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Speaker 1: whole lot of stuff that I probably shouldn't have seen either.

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Speaker 1: But there was also it was like message boards. So

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Speaker 1: I used to go to this place called chick Click,

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Speaker 1: which does not sand as nefarious as the phrase sand Now.

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Speaker 1: It was a feminist message board that was just like

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Speaker 1: all kinds of wonderful women talking about all kinds of

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Speaker 1: things in their life, like hey, my breasts are uneven,

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Speaker 1: one bigger than the other, which just like all kinds

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Speaker 1: of things that like I was the eldest girl in

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Speaker 1: an immigrant household, Like I'd never heard this kind of stuff,

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Speaker 1: and so read this kind of stuff, right because everyone

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Speaker 1: reading at that stage in the Internet, you weren't watching,

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Speaker 1: and I think that's an important description. You'd see like pictures,

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Speaker 1: people post pictures of themselves and I'm like, okay, alright, alright,

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Speaker 1: it's normal to look that way. It's normal to be

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Speaker 1: like this, it's normal to hear about feminism. And that

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Speaker 1: part was amazing. I guess it was new too, So

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Speaker 1: there was all this like craziness out there. There was

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Speaker 1: a ton of craziness, right, So and be reading something

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Speaker 1: and all of a sudden be like, oh what did

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Speaker 1: I just be? Oh no, well, I guess I remember

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Speaker 1: when I was younger, all the pop ups that would

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Speaker 1: they were like I was like, wait, I didn't want that. Yes,

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Speaker 1: You're like, oh do not want that? Click x out

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Speaker 1: x out I do not want that, but it somehow

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Speaker 1: felt felt more organic and kind of unintentional when that

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Speaker 1: pop up would come up. And now you know, these

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Speaker 1: platforms feel very curated, and then it just kind of

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Speaker 1: felt like turned a corner, saw something weird, turned that

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Speaker 1: corner again, like keep going yeah, okay. So then so

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Speaker 1: you got to BuzzFeed and you're like, I'm going to

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Speaker 1: be a lawyer for the inner exactly what does that

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Speaker 1: even mean? It meant that I was around to answer

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Speaker 1: or any kinds of questions that people had. So and

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Speaker 1: people are like, hey, can I use this music in

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Speaker 1: the background of a video? And I'm like, well, let's

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Speaker 1: think about what Madam Queenbiance might have to say about that.

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Speaker 1: The answer is no, she does not want you to

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Speaker 1: use her songs in your video. But also really interesting

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Speaker 1: things like when we had reporters who wanted to dig

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Speaker 1: into allegations of sexual harassment happening at schools right and

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Speaker 1: they're like, I want to and this is before me too.

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Speaker 1: So you have these super talented reporters like just Testa

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Speaker 1: Katie Baker, who like before this sort of me too

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Speaker 1: movement in the press, were like, how do we report

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Speaker 1: on what girls in schools are saying about their teachers

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Speaker 1: and their principles. Knowing that we get the story wrong,

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Speaker 1: the school is going to sue us. How do we

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Speaker 1: appropriately reach out to these students and like, you know,

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Speaker 1: give them a microphone for their truth while also understanding

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Speaker 1: the complications here. And so I got to advise on

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Speaker 1: those kinds of stories too, which is really meaningful for me,

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Speaker 1: and you know hard the national security stories, like publishing

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Speaker 1: all kinds of things about politics. But I was the

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Speaker 1: My job was to be the one that made sure

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Speaker 1: people didn't get in trouble for speaking truth and the

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Speaker 1: way they wanted to, which is really cool and also

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Speaker 1: like that's kind of scary too. Yeah, I thought it

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Speaker 1: was a lot of fun. I mean, it's really fun

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Speaker 1: when you work with reporters who you trust and you

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Speaker 1: know where their heart is and you know where their

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Speaker 1: head is. Right, So if they want to make sure

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Speaker 1: that the right people stories are getting to the Internet,

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Speaker 1: it's on her to be able to help. Yeah, So

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Speaker 1: there's this one part of the Internet and all of

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Speaker 1: the things that have been given to us and offered

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Speaker 1: and been able to be created for the good, Like

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Speaker 1: it's an easier way to access information. I talked about

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Speaker 1: this all the time, even with like TikTok and like Instagram,

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Speaker 1: how that's changed. I'm so grateful and like podcasts like,

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Speaker 1: I'm so grateful that there is a way for people

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Speaker 1: to get information that otherwise would never have, that where

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Speaker 1: we can be more educated and we can learn more

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Speaker 1: and it can connect us. But then there's also this

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Speaker 1: space where it's like, wait a second, is this a

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Speaker 1: conspiracy theory? Who's brainwashing us? Is this information true? Why

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Speaker 1: should I believe this person? Anybody can say anything? Why

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Speaker 1: am I getting this ad? Okay, now I bought this

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Speaker 1: thing that I got this ad seventeen times? Like did

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Speaker 1: I even want that? What do I like? What should

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Speaker 1: bodies look like? It's so much and so I don't

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Speaker 1: even know the right question to ask. But how are

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Speaker 1: you sitting in? The Internet is good? Internet is scary

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Speaker 1: that it makes a ton of sense, and it's the

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Speaker 1: trickiest because here's how I think of the Internet, especially

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Speaker 1: these days. You know, like every science fiction series, um,

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Speaker 1: there's always that episode where someone can start listening to

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Speaker 1: everyone else's internal monologue and they start hearing all these

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Speaker 1: things in their minds and they're like oh no, I'm

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Speaker 1: hearing everyone else's thoughts. That is literally what the Internet is.

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Speaker 1: You're hearing everyone's thoughts. And the only way to manage

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Speaker 1: that is to build defenses and structure around it, right

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Speaker 1: to say, okay, so let me tell you my TikTok role.

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Speaker 1: My TikTok role is that I can only watch TikTok

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Speaker 1: at the end of any hour for leftover time until

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Speaker 1: the top of the hour. So if we were to

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Speaker 1: finish at eleven fifty seven, I have three minutes and

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Speaker 1: I can just be on TikTok because you've got to

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Speaker 1: control your time otherwise, these platforms are designed for you

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Speaker 1: to give them all of your attention and all of

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Speaker 1: your time, right, So you need time structure. I also

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Speaker 1: think you have to remind yourself often that a lot

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Speaker 1: of what you see isn't real, and you have to

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Speaker 1: remind yourself that constantly. And that's really tricky because you

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Speaker 1: want to relate and connect to people. That's what's beautiful

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Speaker 1: about it. But it's kind of like your friends, right.

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Speaker 1: You have people you run into, you have your acquaintances,

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Speaker 1: you have your friends, and you have your besties. That's

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Speaker 1: a structure that we have in our real life. You

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Speaker 1: got to bring that to social Not everybody is your best,

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Speaker 1: no matter how much they say they might be. You

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Speaker 1: got to understand who's like you're the D team, Like,

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Speaker 1: I'm not going to trust everything you say. You're around

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Speaker 1: sometimes you're funny. I'm not gonna like hang my life

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Speaker 1: on what you have to say. And just like you

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Speaker 1: do that in real life, you have to do that

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Speaker 1: here too. What what do you think because I think

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Speaker 1: that's hard for people to to actually put into action.

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Speaker 1: It's like, I know that not everything I see on

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Speaker 1: Instagram is reel. I know that there are filters. I

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Speaker 1: know that, yet I still get tricked. This is not

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Speaker 1: even a professional question, but in your own just personal opinion,

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Speaker 1: why do you think it's hard for people to remember that.

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Speaker 1: I think it all boils down to to proximity and relatability.

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Speaker 1: And here's what I mean by that. Magazines existed for

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Speaker 1: decades and decades. We all saw images of people who

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Speaker 1: were something to attain right. I would look at tier

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Speaker 1: Banks and be like, I don't look like tire Banks.

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Speaker 1: Fun fact, no one looks like Tira Banks. So that

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Speaker 1: was a very easy to be to be like, oh,

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Speaker 1: you're over there, But these are devices we hold in

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Speaker 1: our hand all the time. It's not up on a

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Speaker 1: billboard or on a TV. It's the same device you

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Speaker 1: use to text your mom or your best friend. It's

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Speaker 1: the same device you used to send messages to people

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Speaker 1: you care about. It's so intimate. The proximity makes it

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Speaker 1: really get into your mind. And the other thing is

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Speaker 1: the relatability. Right when I didn't look like tire Banks,

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Speaker 1: it was okay, I was like, I don't go to

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Speaker 1: school of tire Banks. I don't really see her at

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Speaker 1: the grocery store. But what you see for so many

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Speaker 1: influencers on Instagram and TikTok is the entire brand is

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Speaker 1: based off relatability, right, Like here I am looking beautiful

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Speaker 1: at the grocery store, and that gets into your brain

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Speaker 1: right where you're like, am I supposed to look great

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Speaker 1: at the grocery store? Like I found a band aid

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Speaker 1: in my own hair when I was at the grocery

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Speaker 1: store yesterday, so like that's That's where I'm coming from.

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Speaker 1: And so it's like that sort of relatability of seeing

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Speaker 1: this kind of appearance situated in otherwise where you want

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Speaker 1: to looking things, and that just gets it will just

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Speaker 1: get in you and I think you have I'm really

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Speaker 1: ruthless about on following if I'm like, oh, I had

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Speaker 1: a bad feeling when I looked at this, even if

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Speaker 1: it's a little feeling of envy, a little flicker of jealousy,

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Speaker 1: and just like, unfollowed, get out of this. I also

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Speaker 1: a a Saudi fashion blogger that I follow who is amazing.

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Speaker 1: Her name is La Buffi. She's at Allah. She had

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Speaker 1: this really interesting experiment over the summer where she unfollowed

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Speaker 1: everybody on Instagram. She has hundreds of thousands of followers.

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Speaker 1: She just went down to zero because she wanted to

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Speaker 1: see what it was like to create in a space

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Speaker 1: where she didn't feel like she was getting inputs from

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Speaker 1: other people. And she said it for a month, but

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Speaker 1: she said it was like a palate cleanser. And so

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Speaker 1: I think you've got to be super in tune with

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Speaker 1: where you are and then know that you might need

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Speaker 1: those retreat moments, whether it's quitting the app. I find

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Speaker 1: that hard or that kind of like just palate cleanser,

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Speaker 1: like you gotta do what you need. Well, I find

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Speaker 1: it hard to to quit because that brings in this

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Speaker 1: like black and whiteness, and for a lot of people,

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Speaker 1: like there's so much good that can come from this

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Speaker 1: and so much education and so much connection and so

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Speaker 1: and creativity and fun that when we are like, oh,

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Speaker 1: I'll just I'll just quit for six months, okay, But

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Speaker 1: why because then when you add it again, what's going

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Speaker 1: to be different exactly? And that's why I so I'm

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Speaker 1: not I I can't quit. It's just that's not how

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Speaker 1: I work. So I'm all about putting in structure around

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Speaker 1: like what are the times of day where I know

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Speaker 1: like this is like fun for me? Right? Who are

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Speaker 1: the people that I find real generative and enriching, of

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Speaker 1: which there are a lot, And who are the people

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Speaker 1: that sometimes I see this and I'm like I just

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Speaker 1: feel bad, Like I just I just feel bad when

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Speaker 1: I see this, right, Um, And for like for me,

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Speaker 1: it was and this you know, just personal, like for

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Speaker 1: people who are really into documenting their weight loss journey

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Speaker 1: all the time and like what they're eating and stuff,

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Speaker 1: I'll just be like, you know what, good for you.

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Speaker 1: I wish you well for what you want to do.

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Speaker 1: I Am not going to be on this like national

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Speaker 1: geographic like voyeuristic endeavor for you I'm out, Like I'm out.

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Speaker 1: I'll follow you back later, but not right now. I can't. Yeah,

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Speaker 1: and that doesn't feel good for me to watch that. No,

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Speaker 1: it doesn't. And again I don't want to police or

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Speaker 1: judge what anyone wants to do with their body. But

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Speaker 1: I don't need to have a front row seat to this.

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Speaker 1: I'm glad you want to share. I don't need to

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Speaker 1: be here for it. Thank you for saying that, because

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Speaker 1: I think a lot of times when you unfollow somebody,

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Speaker 1: I feel like we're getting off topic. But I don't

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Speaker 1: even care when you unfollow somebody. It's like, you know,

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Speaker 1: people have like apps that they can see like who

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Speaker 1: unfollowed them, which I think that is so unhealthy. But again,

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Speaker 1: do what you need to do. It's like, oh, that

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Speaker 1: is like an attack on me, like they hate me

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Speaker 1: or they don't like me, or how could they unfollow me?

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Speaker 1: But that doesn't mean that what you just said is,

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Speaker 1: I'm not saying she's doing anything wrong or bad. Do

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Speaker 1: what you need to do to be the person you

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Speaker 1: want to be. I don't want to watch it because

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Speaker 1: it doesn't feel good to me. It's boundaries, its period exactly, period,

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Speaker 1: and that's just boundaries, and I feel like what I

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Speaker 1: am really intrigued by is as we come to these

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Speaker 1: realizations that tech is like can be good, can also

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Speaker 1: be really bad for people's self esteem. I am seeing

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Speaker 1: from a lot of entrepreneurs and innovators I know, attempts

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Speaker 1: at solving this through providing more opportunities for structure. So

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Speaker 1: what does that mean. I was just talking to this

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Speaker 1: person who was like, wouldn't it be cool if I

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Speaker 1: could create a plug in into Instagram and you could

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Speaker 1: just decide that I don't want to see anything that's

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Speaker 1: like hashtag weight, lost, journey, hashtag shredded for summer, hashtag whatever,

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Speaker 1: and some people I follow, it would just like it

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Speaker 1: just block those out for me, right I'm not there,

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Speaker 1: And that way it sort of speaks to what you're saying.

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Speaker 1: It's like I'm not on following you. I'm just saying

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Speaker 1: I'm not here for that hashtag right now, like I

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Speaker 1: can't be Yeah, And like I have a friend who

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Speaker 1: unfortunately like went through a miscarriage and she just was like,

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Speaker 1: I can't see everyone's baby announcements right now, Like I

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Speaker 1: just I'm not there. I wish there was something that

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Speaker 1: she could just be like, yeah, it's not right now,

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Speaker 1: just not right now for me. I want to be

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Speaker 1: on the platform, but just not that. But I think

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Speaker 1: there are people who are dabbling in the in those

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Speaker 1: kinds of solutions, and I'm excited for that. Yes, I

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Speaker 1: want that. I want that right because it does feel

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Speaker 1: like how do I set up my boundaries? I can

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Speaker 1: set up my boundaries of who I follow, who I mute,

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Speaker 1: how much I'm on it, But sometimes it's just like

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Speaker 1: the pop up, It's like I didn't want to see that,

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Speaker 1: like I'm not here for this. I didn't want to

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Speaker 1: see that. And I think, but this is what I

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Speaker 1: think is so good about surfacing these harms, right, about

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Speaker 1: having these news articles, of having people talk about this openly,

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Speaker 1: because once we identify what the harms are and how

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Speaker 1: people are honestly feeling, we can design around that. And

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Speaker 1: for some people, look, depending on the platform, it might

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Speaker 1: be yeah, maybe that shouldn't exist, but I think there

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Speaker 1: might be a layer below that, right, that's like, how

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00:19:14,280 --> 00:19:17,359
Speaker 1: do we make these platforms responsive and designed for people

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Speaker 1: so they can set their boundaries in a healthy way.

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Speaker 1: So I didn't say this when we started, but my

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00:19:28,800 --> 00:19:32,480
Speaker 1: best friend connected us Tory Pool and she's been on

401
00:19:32,520 --> 00:19:35,800
Speaker 1: the show before. She's freaking amazing. She's awesome. She's like

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Speaker 1: you she does seven things and I'm like, how are

403
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Speaker 1: you doing that? I text her the other day, I'm like,

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00:19:40,520 --> 00:19:42,639
Speaker 1: I can't even make my bed and you're planning a

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Speaker 1: birthday party, a christening. You work a full time job,

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00:19:45,840 --> 00:19:48,520
Speaker 1: you teach its soul cycle, You're freaking smart people. How

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Speaker 1: do you do all this? She is amazing though, she

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Speaker 1: I mean, she's like the next level amazing human. She

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Speaker 1: really is. So anyways, when she was talking to me,

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Speaker 1: I was like, oh, this makes me think about that

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Speaker 1: documentary that came out. I guess it was Last Your

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Speaker 1: The Social Dilemma. I didn't watch the whole thing full disclosure,

413
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Speaker 1: because I was like, this is information overloading. Now I'm scared.

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Speaker 1: But what I remember from the beginning of it is

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Speaker 1: it was a bunch of people who helped with the

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Speaker 1: start of these big I think with like Twitter and

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Speaker 1: like Google and stuff like that that were then coming

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Speaker 1: and be like, oh, we didn't mean to create this.

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Speaker 1: This is not what we meant to create. And so

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Speaker 1: I want to kind of talk about that a little bit,

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Speaker 1: and then I want you to tell us about what

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Speaker 1: the markup is and what what that is doing because

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Speaker 1: what I saw with me and my own clients, what

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00:20:35,400 --> 00:20:37,880
Speaker 1: I was working with two When that came out, everybody

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Speaker 1: was like, I can't be on the internet anymore, and

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Speaker 1: I was like, well, we have to, So what do

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00:20:42,800 --> 00:20:46,119
Speaker 1: we do and how can we help ourselves? The boundaries

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00:20:46,160 --> 00:20:47,800
Speaker 1: and all that over over there? But kind of what

429
00:20:47,840 --> 00:20:49,879
Speaker 1: I was talking about in the beginning too, it's like

430
00:20:49,960 --> 00:20:52,800
Speaker 1: I find myself buying things that I'm like, I didn't

431
00:20:52,800 --> 00:20:55,520
Speaker 1: want this? Why is it in my home now? So

432
00:20:55,560 --> 00:20:57,000
Speaker 1: I don't know what the question is, but can you

433
00:20:57,080 --> 00:21:00,680
Speaker 1: tell can we talk about that? Well? First, I think

434
00:21:00,800 --> 00:21:03,560
Speaker 1: I think we're in a really exciting and interesting moment

435
00:21:03,680 --> 00:21:07,600
Speaker 1: right because these conversations are happening, And what these conversations

436
00:21:07,680 --> 00:21:11,480
Speaker 1: mean is Okay, does it have to be this way? Right?

437
00:21:11,600 --> 00:21:14,119
Speaker 1: Does it have to be this way? Is this inevitable?

438
00:21:14,359 --> 00:21:16,239
Speaker 1: Is this the future we're in? And I think if

439
00:21:16,359 --> 00:21:19,320
Speaker 1: enough of us are like, no, I don't want this.

440
00:21:19,520 --> 00:21:23,040
Speaker 1: I don't want to be persuaded into mindlessly buying things

441
00:21:23,440 --> 00:21:26,240
Speaker 1: or feeling bad about myself because of something I saw,

442
00:21:26,640 --> 00:21:29,320
Speaker 1: or questioning whether anything is real. Because all of the

443
00:21:29,359 --> 00:21:31,679
Speaker 1: information is out there if we don't want it to

444
00:21:31,720 --> 00:21:34,800
Speaker 1: be this way. First things first, we have to understand

445
00:21:34,840 --> 00:21:36,840
Speaker 1: how we got here, and that goes back to the

446
00:21:36,840 --> 00:21:39,600
Speaker 1: first part of your question, right, Like all of these

447
00:21:39,640 --> 00:21:43,080
Speaker 1: people built these systems. They built Google, they built Twitter,

448
00:21:43,160 --> 00:21:46,760
Speaker 1: they built Facebook. I don't think this is where they

449
00:21:46,800 --> 00:21:49,280
Speaker 1: wanted us to be. They made a ton of money

450
00:21:49,280 --> 00:21:51,399
Speaker 1: getting here, but I don't think that was the dream

451
00:21:51,440 --> 00:21:55,720
Speaker 1: at the outset. So we have to understand, like what happened? Right,

452
00:21:55,720 --> 00:21:58,080
Speaker 1: How did we get from this sort of like fun

453
00:21:58,240 --> 00:22:02,400
Speaker 1: wild internet to this place that feels like a digital

454
00:22:02,440 --> 00:22:05,240
Speaker 1: prison for our minds and our behavior? Like what happened?

455
00:22:05,720 --> 00:22:08,680
Speaker 1: And so there's a lot of interesting, I think things

456
00:22:08,720 --> 00:22:11,800
Speaker 1: to say in this space. One artist that I love.

457
00:22:12,080 --> 00:22:13,879
Speaker 1: I didn't think a lawyer talk about art, but I

458
00:22:13,880 --> 00:22:16,280
Speaker 1: do love art, and I think it's important in this time.

459
00:22:16,720 --> 00:22:19,240
Speaker 1: There's this artist, his name is Ben Grosser, and he

460
00:22:19,280 --> 00:22:21,840
Speaker 1: has this exhibit up called Software for Less, and in

461
00:22:21,960 --> 00:22:26,120
Speaker 1: it he redesigns all of these platforms to be optimized

462
00:22:26,160 --> 00:22:30,400
Speaker 1: for less, not more. So imagine these platforms like Instagram,

463
00:22:30,480 --> 00:22:32,000
Speaker 1: they want you to post all the time, right, The

464
00:22:32,000 --> 00:22:35,080
Speaker 1: algorithm is hungry, You've got to feed it constantly. What

465
00:22:35,119 --> 00:22:37,879
Speaker 1: would it look like if actually you signed up for

466
00:22:37,920 --> 00:22:39,919
Speaker 1: Instagram and it just gave you a hundred posts for

467
00:22:39,960 --> 00:22:43,360
Speaker 1: your whole life and said you've got a hundred choose wisely,

468
00:22:43,720 --> 00:22:46,840
Speaker 1: what do you want to share? Like, think about how

469
00:22:47,160 --> 00:22:50,399
Speaker 1: the incentive for growth was built into this platform from

470
00:22:50,480 --> 00:22:54,119
Speaker 1: day one, and that may create a whole set of

471
00:22:54,240 --> 00:22:57,320
Speaker 1: incentives and patterns and structures on the app. But if

472
00:22:57,320 --> 00:23:00,720
Speaker 1: you had designed that day one differently scarcity and not growth,

473
00:23:00,960 --> 00:23:04,040
Speaker 1: how would that feel different? How would people approach things?

474
00:23:04,280 --> 00:23:06,000
Speaker 1: And I love that because a lot of times the

475
00:23:06,080 --> 00:23:09,560
Speaker 1: scarcity mindset leads us down. We talk about like dating

476
00:23:09,640 --> 00:23:12,359
Speaker 1: or taking jobs or this or that. Sometimes it's not great.

477
00:23:12,480 --> 00:23:15,360
Speaker 1: But with this, it's like, wait, that would be helpful.

478
00:23:15,720 --> 00:23:17,720
Speaker 1: I wouldn't be worried about every day I have to

479
00:23:17,760 --> 00:23:19,720
Speaker 1: post five things so people see my stuff. It's like,

480
00:23:19,960 --> 00:23:22,080
Speaker 1: I don't want to post this because it's not that important,

481
00:23:22,160 --> 00:23:24,400
Speaker 1: right And I think it's because I shared the same

482
00:23:24,520 --> 00:23:27,760
Speaker 1: perspective on scarcity mindset. It often leads to dysfunction. But

483
00:23:27,800 --> 00:23:29,840
Speaker 1: the one thing that is truly scarce in this world

484
00:23:30,240 --> 00:23:32,800
Speaker 1: is actually time. Like you can't get more, you can't

485
00:23:32,840 --> 00:23:36,160
Speaker 1: get anything. It is actually the scarce thing what could

486
00:23:36,160 --> 00:23:39,160
Speaker 1: it look like if we designed for the future and said,

487
00:23:39,480 --> 00:23:42,600
Speaker 1: let's design differently, right, And that's actually the exercise we're

488
00:23:42,640 --> 00:23:44,639
Speaker 1: in at the moment. It's thinking about what the design

489
00:23:44,680 --> 00:23:48,400
Speaker 1: should be because what we have isn't working. And that's

490
00:23:48,440 --> 00:23:52,320
Speaker 1: where the innovation around. Okay, if we want more boundaries

491
00:23:52,320 --> 00:23:55,040
Speaker 1: and structure, how do we design for control? How do

492
00:23:55,080 --> 00:23:58,600
Speaker 1: we add those layers on it? How do we grow up? Right?

493
00:23:58,600 --> 00:24:01,480
Speaker 1: Because what we're seeing is like the Internet is an adolescent,

494
00:24:01,720 --> 00:24:04,679
Speaker 1: it's young, and we're growing up and figuring out what

495
00:24:04,720 --> 00:24:06,880
Speaker 1: boundaries we need. And I think that is what's really

496
00:24:06,920 --> 00:24:09,439
Speaker 1: fun about this time. Wait, can we do that? It

497
00:24:09,480 --> 00:24:11,760
Speaker 1: feels like we're going backwards, but can we be like Instagram?

498
00:24:11,760 --> 00:24:14,240
Speaker 1: We're changing? Like, how do we do that? So I

499
00:24:14,280 --> 00:24:17,399
Speaker 1: think that's that's so fun about this moment, right, because

500
00:24:17,400 --> 00:24:20,560
Speaker 1: it might not be Instagram. It might be that Instagram

501
00:24:20,920 --> 00:24:23,119
Speaker 1: decides we want to stay the way we are, sorry,

502
00:24:23,200 --> 00:24:25,840
Speaker 1: take it or leave it, and then there's enough. There

503
00:24:25,880 --> 00:24:28,600
Speaker 1: are so many people working in the space, we're like, Okay,

504
00:24:28,680 --> 00:24:31,480
Speaker 1: first of all, you may get sued by the Federal

505
00:24:31,520 --> 00:24:35,160
Speaker 1: Trade Commission Instagram for a variety of your privacy practices,

506
00:24:35,240 --> 00:24:39,800
Speaker 1: and like there's all this legislation and other government movement

507
00:24:39,880 --> 00:24:42,119
Speaker 1: to break up these platforms. So maybe that if they

508
00:24:42,119 --> 00:24:44,480
Speaker 1: decide to stay the way they are, they're not allowed to.

509
00:24:45,040 --> 00:24:48,400
Speaker 1: It may also be that enough people want other competitors,

510
00:24:48,400 --> 00:24:50,080
Speaker 1: that people are like I don't want to be on

511
00:24:50,119 --> 00:24:52,679
Speaker 1: a platform that's like this, I want to be on

512
00:24:52,720 --> 00:24:55,520
Speaker 1: this different kind of place, and that we see that

513
00:24:55,600 --> 00:24:58,760
Speaker 1: movement happened too, because remember my Space was a big

514
00:24:58,760 --> 00:25:01,240
Speaker 1: deal not that long ago, right, everyone was on my Space?

515
00:25:01,880 --> 00:25:04,399
Speaker 1: So everyone was and now we're like, who what what

516
00:25:04,560 --> 00:25:07,040
Speaker 1: is my space? Right? So movement is but we've got

517
00:25:07,040 --> 00:25:09,399
Speaker 1: to remember that too. We do have agency, we do

518
00:25:09,480 --> 00:25:12,960
Speaker 1: have control, and quitting one platform doesn't mean quitting the

519
00:25:13,000 --> 00:25:15,920
Speaker 1: Internet or social It means that we might evolve to

520
00:25:16,000 --> 00:25:18,760
Speaker 1: something else. Okay, that is something that I think we

521
00:25:18,800 --> 00:25:21,199
Speaker 1: need to remember. Going back to my example of like

522
00:25:21,240 --> 00:25:22,760
Speaker 1: why do I have this shirt in my closet? I

523
00:25:22,800 --> 00:25:24,280
Speaker 1: don't like it and I bought it. I'm like I

524
00:25:24,320 --> 00:25:26,280
Speaker 1: just want this ad to go away almost, or like

525
00:25:26,320 --> 00:25:29,600
Speaker 1: I guess I need this, But I do have agency

526
00:25:29,600 --> 00:25:32,800
Speaker 1: and control and that platform sometimes makes me feel like

527
00:25:32,840 --> 00:25:37,320
Speaker 1: I don't. So rather than Instagram's changing, if we all

528
00:25:37,359 --> 00:25:39,119
Speaker 1: start because we a lot of us are feeling this

529
00:25:39,160 --> 00:25:41,919
Speaker 1: way and something else is created. We have the power

530
00:25:42,000 --> 00:25:43,840
Speaker 1: to say I don't want to use this platform anymore.

531
00:25:43,840 --> 00:25:47,440
Speaker 1: There's something that fits my needs. I have power, yeah,

532
00:25:47,480 --> 00:25:49,840
Speaker 1: And I think that is the thing for people to remember.

533
00:25:49,920 --> 00:25:52,160
Speaker 1: And these platforms don't want to remind you that they

534
00:25:52,160 --> 00:25:54,520
Speaker 1: have power, right, that's not in their incentive. They don't

535
00:25:54,560 --> 00:25:57,240
Speaker 1: want you to feel like empowered or that you have agency.

536
00:25:57,600 --> 00:25:59,680
Speaker 1: But that is the reality of this moment and that

537
00:25:59,760 --> 00:26:03,080
Speaker 1: we've on this before. People left my Space and they

538
00:26:03,080 --> 00:26:05,959
Speaker 1: went to Facebook, and people went left Facebook, and they

539
00:26:05,960 --> 00:26:07,719
Speaker 1: went to Twitter, and they went to Twitter, and they

540
00:26:07,720 --> 00:26:10,399
Speaker 1: went to Instagram, and they're leaving Instagram. They're going to

541
00:26:10,440 --> 00:26:12,639
Speaker 1: TikTok and it'll be something else we haven't heard about.

542
00:26:12,680 --> 00:26:16,399
Speaker 1: Like this happens, people do it. And also like the

543
00:26:16,480 --> 00:26:19,360
Speaker 1: smartphone is just over what ten years old? T fift

544
00:26:19,520 --> 00:26:22,880
Speaker 1: years old? Like this isn't gravity, okay, Like this isn't

545
00:26:22,920 --> 00:26:26,480
Speaker 1: a lot of physics. This stuff is choices and they're hard.

546
00:26:26,520 --> 00:26:28,639
Speaker 1: So I want to just be very honest about the

547
00:26:28,680 --> 00:26:31,640
Speaker 1: fact that it's hard, but we we can do hard things. Right,

548
00:26:31,680 --> 00:26:33,679
Speaker 1: It's hard, but we can do hard We can't we

549
00:26:33,720 --> 00:26:36,639
Speaker 1: can't and also I just have a question that I

550
00:26:36,640 --> 00:26:38,879
Speaker 1: don't know if you can fully answer. With all of

551
00:26:38,920 --> 00:26:43,280
Speaker 1: the stuff on those platforms, specifically Instagram and Facebook, what's

552
00:26:43,320 --> 00:26:46,360
Speaker 1: the legality that's even the right word, like for them

553
00:26:46,400 --> 00:26:49,520
Speaker 1: to gather all our information and then expan us like

554
00:26:49,600 --> 00:26:52,600
Speaker 1: that feels wrong? Yes, And so this is I think

555
00:26:52,760 --> 00:26:56,720
Speaker 1: an area where I call it regulatory imagination, Like legislators

556
00:26:56,720 --> 00:26:58,960
Speaker 1: and regulators are imagining what they can do in this

557
00:26:59,000 --> 00:27:01,520
Speaker 1: space in the way that they not ten years ago, right,

558
00:27:01,560 --> 00:27:05,040
Speaker 1: because everyone's like, what can we do? And so for

559
00:27:05,240 --> 00:27:08,240
Speaker 1: many of these platforms, they're looking at, well, what is

560
00:27:08,280 --> 00:27:11,199
Speaker 1: the data you're collecting from children? Is that allowed? Do

561
00:27:11,280 --> 00:27:14,959
Speaker 1: we allow you to collect this much information from kids?

562
00:27:15,200 --> 00:27:17,639
Speaker 1: Do we let kids say, um, hi sorry, Facebook, I

563
00:27:17,680 --> 00:27:19,760
Speaker 1: turned eight team get rid of everything that you had

564
00:27:19,800 --> 00:27:22,800
Speaker 1: about me from before, which is actually a law in California, right,

565
00:27:22,840 --> 00:27:26,679
Speaker 1: you're able, Yeah, And so like states are experimenting with this,

566
00:27:26,840 --> 00:27:30,160
Speaker 1: Europe is experimenting with this. So to answer your question,

567
00:27:30,160 --> 00:27:32,760
Speaker 1: like what's the legality here, we get to make it

568
00:27:33,080 --> 00:27:37,359
Speaker 1: and everyone is trying, right. So in in Europe there's

569
00:27:37,720 --> 00:27:40,480
Speaker 1: something called the g DPR, which is a data protection

570
00:27:40,520 --> 00:27:45,760
Speaker 1: regulation and they're implementing all kinds of ideas of Hey,

571
00:27:45,800 --> 00:27:48,560
Speaker 1: what does content moderation look like? Here? Should a human

572
00:27:48,560 --> 00:27:51,240
Speaker 1: being be the one who's deciding to take something down?

573
00:27:51,320 --> 00:27:54,640
Speaker 1: So Facebook can't just say, oops, sorry, plus sized woman,

574
00:27:54,760 --> 00:27:57,920
Speaker 1: I took your picture down by accident because the algorithm

575
00:27:57,920 --> 00:28:01,240
Speaker 1: did it right. How do we in pose this kind

576
00:28:01,280 --> 00:28:04,240
Speaker 1: of structure on what these platforms are doing. This is

577
00:28:04,240 --> 00:28:07,560
Speaker 1: all happening in real time now, and everyone's trying different things.

578
00:28:07,800 --> 00:28:09,840
Speaker 1: But there's a lot of rules around privacy and the

579
00:28:09,880 --> 00:28:16,320
Speaker 1: collection of data to target you. That targeting information be like, hey, Katherine,

580
00:28:16,480 --> 00:28:18,880
Speaker 1: I think you're gonna like this pair of like wide

581
00:28:18,960 --> 00:28:20,840
Speaker 1: leg pants. Like you're gonna like it, I'm going to

582
00:28:20,920 --> 00:28:22,800
Speaker 1: just push it to you a thousand times a day.

583
00:28:23,200 --> 00:28:27,719
Speaker 1: There is a lot of legislative scrutiny of do we

584
00:28:27,800 --> 00:28:31,480
Speaker 1: want to allow that, Should Catherine be able to opt out,

585
00:28:31,840 --> 00:28:34,160
Speaker 1: should she be able to say no, I don't want

586
00:28:34,160 --> 00:28:35,840
Speaker 1: you to have I don't want you to set target

587
00:28:35,880 --> 00:28:38,160
Speaker 1: me with clothes. I don't want you to target I

588
00:28:38,440 --> 00:28:39,840
Speaker 1: want you to get rid of all the data you

589
00:28:39,920 --> 00:28:42,840
Speaker 1: collected about me for this. I want you to only

590
00:28:42,880 --> 00:28:45,920
Speaker 1: be able to use data that you got from this app,

591
00:28:46,040 --> 00:28:48,560
Speaker 1: not buying it on the open market to target me

592
00:28:48,600 --> 00:28:50,840
Speaker 1: as a profile, you know, as a profile. All of

593
00:28:50,840 --> 00:28:53,520
Speaker 1: that's happening now, which feels good. When I was making

594
00:28:53,960 --> 00:28:57,160
Speaker 1: one of my websites, I was working with a business consultant,

595
00:28:57,200 --> 00:29:00,000
Speaker 1: and I have a newsletter, well, I had a newsletter,

596
00:29:00,160 --> 00:29:02,200
Speaker 1: sign up for it. I'm gonna get it back back

597
00:29:02,200 --> 00:29:05,520
Speaker 1: and running soon. But we were creating like the pop

598
00:29:05,600 --> 00:29:08,120
Speaker 1: up forward and whatever and then opt out whatever he

599
00:29:08,200 --> 00:29:10,680
Speaker 1: and he. I don't remember the language because it's over

600
00:29:10,760 --> 00:29:14,200
Speaker 1: my head, but I just remember him being so serious about, well,

601
00:29:14,280 --> 00:29:16,040
Speaker 1: they need to be able to opt out or you

602
00:29:16,080 --> 00:29:18,400
Speaker 1: can't just take their stuff or you can't. And I

603
00:29:18,440 --> 00:29:20,280
Speaker 1: was like why other people do it? To me? Like

604
00:29:20,320 --> 00:29:21,880
Speaker 1: I just wanted to know why. I'm a why person?

605
00:29:21,880 --> 00:29:23,480
Speaker 1: And I'm like, I get emails all the time, and

606
00:29:23,520 --> 00:29:26,720
Speaker 1: I've never signed up for this email subscription. I've unchecked

607
00:29:26,720 --> 00:29:29,520
Speaker 1: the box when I've checked out at let's say, like

608
00:29:29,640 --> 00:29:32,040
Speaker 1: I don't know, like Lulu Lemon, I actually checked the

609
00:29:32,040 --> 00:29:34,720
Speaker 1: box for that. I want those emails, but like there's

610
00:29:34,800 --> 00:29:37,160
Speaker 1: plenty of things and I'm like, I bought something from

611
00:29:37,240 --> 00:29:38,960
Speaker 1: here one time. I know I didn't check that box.

612
00:29:39,000 --> 00:29:42,240
Speaker 1: Why am I getting four emails a day that seems

613
00:29:42,280 --> 00:29:45,320
Speaker 1: like it should be illegal. Yeah, and it is, and

614
00:29:45,440 --> 00:29:47,800
Speaker 1: so I think, okay, And the question is because there's

615
00:29:47,840 --> 00:29:50,240
Speaker 1: all of this sale happening of your data. But those

616
00:29:50,280 --> 00:29:52,320
Speaker 1: opt outs are real for a reason. And when people

617
00:29:52,360 --> 00:29:55,440
Speaker 1: do don't comply, right, which happens so they're like, oh, sorry,

618
00:29:55,440 --> 00:29:58,800
Speaker 1: we're gonna keep emailing you. They can and do get

619
00:29:58,800 --> 00:30:02,840
Speaker 1: in trouble by state regulators and federal regulators. The problem

620
00:30:02,920 --> 00:30:06,400
Speaker 1: is often had the fines haven't been that much money,

621
00:30:06,480 --> 00:30:09,440
Speaker 1: and it's like jaywalking, right, You're like a like, what

622
00:30:09,480 --> 00:30:11,320
Speaker 1: are the chances I'm gonna get in trouble this time?

623
00:30:11,680 --> 00:30:13,840
Speaker 1: But the more attention we put to it, the more

624
00:30:13,960 --> 00:30:17,160
Speaker 1: the public is like, hey, I don't like this and

625
00:30:17,200 --> 00:30:20,760
Speaker 1: I'm going to report you. The more room you're giving

626
00:30:20,800 --> 00:30:23,280
Speaker 1: these regulators to be like you know what, yeah, last

627
00:30:23,280 --> 00:30:26,240
Speaker 1: time we find you five hundred dollars and you company

628
00:30:26,280 --> 00:30:30,760
Speaker 1: acts you didn't care because five hundred dollars to you like, okay,

629
00:30:30,840 --> 00:30:33,880
Speaker 1: you sell you know, five pairs of Lululemon leggings, and

630
00:30:33,920 --> 00:30:36,400
Speaker 1: there we are like that's fine, it's worth it. Let's

631
00:30:36,480 --> 00:30:40,320
Speaker 1: raise the fine amount. Let's stop paying attention to lobbyists

632
00:30:40,320 --> 00:30:42,240
Speaker 1: who are saying no, no, no, no, it'll self correct.

633
00:30:42,880 --> 00:30:45,200
Speaker 1: Enough time has past, you didn't fix it on your own.

634
00:30:45,480 --> 00:30:48,760
Speaker 1: And that's really like, I want people to be so

635
00:30:49,040 --> 00:30:52,400
Speaker 1: empowered by the moment that we're in because there were

636
00:30:52,440 --> 00:30:56,560
Speaker 1: all of these beliefs that people had before. It'll fix itself. Eventually,

637
00:30:57,000 --> 00:31:00,000
Speaker 1: people are still figuring it out. There aren't that many

638
00:31:00,120 --> 00:31:03,560
Speaker 1: bad actors that now we're like, no, you had enough time,

639
00:31:03,880 --> 00:31:06,640
Speaker 1: we're changing it now. Yeah, okay, well then can we

640
00:31:06,720 --> 00:31:09,280
Speaker 1: now talk about the Markup then totally okay, tell us

641
00:31:09,280 --> 00:31:11,440
Speaker 1: what that is and why you created it and all

642
00:31:11,440 --> 00:31:16,320
Speaker 1: the The Markup is a new media organization that is

643
00:31:16,480 --> 00:31:20,240
Speaker 1: looking at a very simple question, how is technology reshaping

644
00:31:20,240 --> 00:31:22,480
Speaker 1: our world? And that means like the big tech that

645
00:31:22,520 --> 00:31:26,280
Speaker 1: we've been talking about, Amazon, Google, whatever, but also the

646
00:31:26,320 --> 00:31:29,600
Speaker 1: tech you haven't heard of, right, So tech technology like

647
00:31:30,040 --> 00:31:33,960
Speaker 1: universities using these things called student risk algorithms to determine

648
00:31:34,280 --> 00:31:37,000
Speaker 1: who they think is at high risk of failing out

649
00:31:37,040 --> 00:31:40,600
Speaker 1: of a particular subject. Surprise, the algorithm will say things

650
00:31:40,640 --> 00:31:44,160
Speaker 1: like women and black people usually aren't in STEM, so

651
00:31:44,200 --> 00:31:46,320
Speaker 1: they're at a high risk of failing out. I mean

652
00:31:46,320 --> 00:31:48,880
Speaker 1: really like, the algorithms are making these sort of stupid.

653
00:31:48,880 --> 00:31:50,880
Speaker 1: I'll call them stupid. I was gonna say that doesn't

654
00:31:50,880 --> 00:31:54,080
Speaker 1: make it doesn't make make sense. Here's why they algorithms

655
00:31:54,200 --> 00:31:58,760
Speaker 1: are making very stupid interpretations of historical data, saying, well,

656
00:31:59,440 --> 00:32:04,800
Speaker 1: we haven't seen women and people of color in science, technology, engineering,

657
00:32:04,800 --> 00:32:08,520
Speaker 1: and math, so we think that they're rare, so we

658
00:32:08,560 --> 00:32:10,920
Speaker 1: think they're at a high risk of failing out. Now,

659
00:32:11,000 --> 00:32:13,040
Speaker 1: you and I as human beings can be like, yeah, no,

660
00:32:13,160 --> 00:32:16,200
Speaker 1: that's wrong a billion different ways, right, Like, there's a

661
00:32:16,280 --> 00:32:20,120
Speaker 1: million reasons why the representative data of the past is

662
00:32:20,160 --> 00:32:23,760
Speaker 1: not actually indicative or instructive for the future. But again,

663
00:32:23,880 --> 00:32:26,000
Speaker 1: like a lot of these algorithms are stupid, right, Like

664
00:32:26,040 --> 00:32:28,040
Speaker 1: they're trained on the data they have and they make

665
00:32:28,080 --> 00:32:32,560
Speaker 1: inferences that are not full and robust, and sometimes they're nonsensical.

666
00:32:32,760 --> 00:32:34,680
Speaker 1: So this is an example of actually reporting that we

667
00:32:34,720 --> 00:32:38,280
Speaker 1: did earlier this year. We identified one of these algorithms

668
00:32:38,320 --> 00:32:41,000
Speaker 1: that had this kind of output. We published the story,

669
00:32:41,240 --> 00:32:45,000
Speaker 1: and we told four hundred different colleges and universities that

670
00:32:45,040 --> 00:32:47,920
Speaker 1: we're using this algorithm. Hey, you might want to take

671
00:32:47,920 --> 00:32:49,760
Speaker 1: a look at this thing that you've signed up for.

672
00:32:50,120 --> 00:32:52,480
Speaker 1: And I want to give major props to Texas and

673
00:32:52,600 --> 00:32:55,920
Speaker 1: m university that day was done. We're not using this algorithm.

674
00:32:55,960 --> 00:32:58,320
Speaker 1: Thank you for telling us. We did not know that

675
00:32:58,400 --> 00:33:00,960
Speaker 1: this was the conclusion that it was spitting it out

676
00:33:00,960 --> 00:33:03,120
Speaker 1: because if you're you're like sitting at the school, you're

677
00:33:03,120 --> 00:33:05,520
Speaker 1: just getting reports from this algorithm. Okay, you don't know

678
00:33:05,720 --> 00:33:08,400
Speaker 1: all of the ways that it's flawed. You trust it.

679
00:33:09,040 --> 00:33:11,760
Speaker 1: And so that's what we're doing. We are here to say, hey,

680
00:33:11,800 --> 00:33:14,520
Speaker 1: there's a lot going on behind the scenes for big

681
00:33:14,560 --> 00:33:16,960
Speaker 1: tech and this this other tech you don't know about,

682
00:33:17,440 --> 00:33:20,560
Speaker 1: and it has real impact on people's lives, on their schooling,

683
00:33:20,720 --> 00:33:25,320
Speaker 1: on their education, on their mortgages, on their businesses, and

684
00:33:25,360 --> 00:33:26,680
Speaker 1: we're gonna tell you what that is and you can

685
00:33:26,720 --> 00:33:29,600
Speaker 1: make better choices. That's what we do, which is so

686
00:33:29,840 --> 00:33:32,920
Speaker 1: cool because is anybody else doing that. You're like trying

687
00:33:32,920 --> 00:33:35,000
Speaker 1: to You're just trying to help people. We're just we

688
00:33:35,000 --> 00:33:38,040
Speaker 1: we call it service journalism, right, it's journalism as a service.

689
00:33:38,080 --> 00:33:40,320
Speaker 1: We're trying to help you. And one thing that our

690
00:33:40,400 --> 00:33:43,280
Speaker 1: team does, and like our team is just full of

691
00:33:43,520 --> 00:33:48,240
Speaker 1: rock star journalists, data scientists, technologists, engineers, like they're amazing.

692
00:33:48,400 --> 00:33:50,840
Speaker 1: They'll build these tools, like one tool that I love

693
00:33:50,960 --> 00:33:53,320
Speaker 1: is called black light anyone can use it. It's the

694
00:33:53,360 --> 00:33:55,920
Speaker 1: markup dot org slash black light. You can put in

695
00:33:56,200 --> 00:33:59,680
Speaker 1: your favorite website. So put in girl scouts dot org.

696
00:34:00,280 --> 00:34:03,280
Speaker 1: It will show you all of the data that's being

697
00:34:03,320 --> 00:34:07,040
Speaker 1: collected about you when you go to girl scouts dot org. So,

698
00:34:07,120 --> 00:34:09,439
Speaker 1: talking about the data collection that we just mentioned earlier

699
00:34:09,480 --> 00:34:11,759
Speaker 1: in the conversation, there's a lot of places you go

700
00:34:11,800 --> 00:34:14,080
Speaker 1: on the Internet and you don't think that data is

701
00:34:14,080 --> 00:34:16,000
Speaker 1: going to be collected about you, like you're just visiting

702
00:34:16,000 --> 00:34:18,760
Speaker 1: a website. So we built this tool to help people

703
00:34:18,840 --> 00:34:21,799
Speaker 1: understand in real time for the sites you go to,

704
00:34:22,400 --> 00:34:24,359
Speaker 1: what are they they're taking about you? And we did

705
00:34:24,360 --> 00:34:27,799
Speaker 1: a big investigation using this tool, and we found things

706
00:34:27,840 --> 00:34:30,319
Speaker 1: like when you go to an abortion provider website, the

707
00:34:30,400 --> 00:34:33,000
Speaker 1: data they're collecting on you. Now, I bet you if

708
00:34:33,040 --> 00:34:35,640
Speaker 1: you go to an abortion provider website, that's not a

709
00:34:35,640 --> 00:34:37,880
Speaker 1: moment in which you think someone's collecting data about you.

710
00:34:37,920 --> 00:34:42,600
Speaker 1: And we know that data could be extremely sensitive health wise,

711
00:34:43,080 --> 00:34:46,759
Speaker 1: I mean now criminality wise, if you're sitting in Texas, like,

712
00:34:46,960 --> 00:34:49,600
Speaker 1: collecting this data has consequences, and we want people to

713
00:34:49,680 --> 00:34:53,480
Speaker 1: know what's happening and where Wait a second that I

714
00:34:53,520 --> 00:34:56,960
Speaker 1: feel fear right now, because I'm like no in the

715
00:34:57,000 --> 00:34:59,200
Speaker 1: sense that like, if I go to this right now, well,

716
00:34:59,560 --> 00:35:02,319
Speaker 1: can I test us our while we're talking? Okay, so

717
00:35:02,800 --> 00:35:05,520
Speaker 1: the markup dot org slash black light. I go to

718
00:35:05,600 --> 00:35:07,640
Speaker 1: there and then I type in a website. Just enter

719
00:35:07,680 --> 00:35:10,360
Speaker 1: a website. Okay, what's a website that I don't even know? Well,

720
00:35:10,440 --> 00:35:12,719
Speaker 1: let's just go to lulu Lemon. Oh, that's a fun one.

721
00:35:12,760 --> 00:35:15,879
Speaker 1: Now I'm curious about Lulua Lemon. I haven't tried that one,

722
00:35:15,880 --> 00:35:18,840
Speaker 1: and honestly I should have. I also like their leggings,

723
00:35:19,360 --> 00:35:21,439
Speaker 1: I know, I'm like please. Okay, So I just type

724
00:35:21,480 --> 00:35:24,799
Speaker 1: so you'll see testing for ad trackers, third party cookies,

725
00:35:25,160 --> 00:35:27,880
Speaker 1: tracking the evades, cookie blockers. So you may think I

726
00:35:27,920 --> 00:35:29,919
Speaker 1: have a cookie blocker. I'm fine, No, no, If there's

727
00:35:29,960 --> 00:35:35,080
Speaker 1: tracking the evades, that session monitoring scripts, key stroke capturing,

728
00:35:35,520 --> 00:35:38,880
Speaker 1: Facebook and Google, this website sending dad about your Facebook.

729
00:35:39,080 --> 00:35:41,440
Speaker 1: Wait a second, Wait, okay, here's a question. I have.

730
00:35:41,960 --> 00:35:45,000
Speaker 1: I log in through Facebook and so many things because

731
00:35:45,040 --> 00:35:47,919
Speaker 1: it's just easier. What is that doing? Is that giving

732
00:35:48,000 --> 00:35:51,160
Speaker 1: Facebook all of the information they have agreed to gather

733
00:35:51,200 --> 00:35:53,759
Speaker 1: from that website about you. So let's say you use

734
00:35:53,800 --> 00:35:57,359
Speaker 1: Facebook to log into like a calendar app that you love.

735
00:35:57,680 --> 00:36:01,000
Speaker 1: Everything from that calendar app is now also going to Facebook.

736
00:36:01,040 --> 00:36:05,320
Speaker 1: And this is one reason Facebook has so much data

737
00:36:05,520 --> 00:36:10,440
Speaker 1: because every time you put on a Facebook little tracking pixel,

738
00:36:10,600 --> 00:36:12,560
Speaker 1: you know, like like me on Facebook, right, if you

739
00:36:12,560 --> 00:36:14,880
Speaker 1: put that on your website, they put a pixel on

740
00:36:14,920 --> 00:36:17,520
Speaker 1: that site and they collect information from all of your

741
00:36:17,640 --> 00:36:21,520
Speaker 1: people that come to your website. Stop it. Also, I

742
00:36:21,520 --> 00:36:24,760
Speaker 1: don't mind still loading. Is you're still loading? Mind still loading?

743
00:36:24,760 --> 00:36:28,439
Speaker 1: It is probably because too much stuff, man, I hope not.

744
00:36:28,760 --> 00:36:31,400
Speaker 1: When it is done, well, it just says it's currently testing,

745
00:36:31,719 --> 00:36:33,680
Speaker 1: so we'll just we'll just we just wait for it.

746
00:36:33,960 --> 00:36:37,680
Speaker 1: But it'll tell you like six ad trackers, this many cookies,

747
00:36:37,760 --> 00:36:39,840
Speaker 1: this many of this, it'll tell you all this stuff.

748
00:36:39,960 --> 00:36:42,440
Speaker 1: And if you scroll down you can also see the

749
00:36:42,560 --> 00:36:45,920
Speaker 1: articles that we wrote. Like so one notable one is

750
00:36:46,200 --> 00:36:48,799
Speaker 1: the high privacy cost of a free website. So we

751
00:36:48,960 --> 00:36:51,799
Speaker 1: get into you know, these websites look free, but what's

752
00:36:51,840 --> 00:36:55,719
Speaker 1: actually happening like a WordPress like or Square dot com

753
00:36:55,760 --> 00:36:57,960
Speaker 1: like those three things anything, Right, Like you go to

754
00:36:58,000 --> 00:37:00,280
Speaker 1: a website, you're like, I'm just checking you out. However,

755
00:37:00,719 --> 00:37:04,239
Speaker 1: there may be this invisible trade that happens of your

756
00:37:04,680 --> 00:37:06,799
Speaker 1: data and we just want you to know about it.

757
00:37:07,000 --> 00:37:10,560
Speaker 1: And you'll see our approach is very much like I'm

758
00:37:10,600 --> 00:37:13,200
Speaker 1: not trying to give you no solution. So another thing

759
00:37:13,239 --> 00:37:15,400
Speaker 1: you'll see in our website is at the bottom of

760
00:37:15,400 --> 00:37:17,840
Speaker 1: the black light page. I scanned websites I visit with

761
00:37:17,880 --> 00:37:20,920
Speaker 1: black light, and it's horrifying. Now what we always want

762
00:37:20,920 --> 00:37:22,759
Speaker 1: to give you, and now what I don't want you

763
00:37:22,960 --> 00:37:25,960
Speaker 1: to be sitting there on your sitting on your hands, terrified,

764
00:37:26,280 --> 00:37:29,080
Speaker 1: trying to throw your computer at the window. Right. We

765
00:37:29,160 --> 00:37:31,960
Speaker 1: want to give you things you can do about it.

766
00:37:32,080 --> 00:37:35,480
Speaker 1: So our advices. You might want to switch browsers, you

767
00:37:35,560 --> 00:37:38,000
Speaker 1: might want to add some privacy extensions. We give you

768
00:37:38,040 --> 00:37:40,279
Speaker 1: some examples of them in the site. So we just

769
00:37:40,320 --> 00:37:41,920
Speaker 1: want to give you what you need to be able

770
00:37:41,920 --> 00:37:44,040
Speaker 1: to take control of your life. You're not saying don't

771
00:37:44,040 --> 00:37:46,279
Speaker 1: ever go to this website again. You're like, Okay, now

772
00:37:46,320 --> 00:37:48,960
Speaker 1: you know, you know you have awareness. Here are things

773
00:37:49,000 --> 00:37:51,880
Speaker 1: you can do to protect yourself. I just think scaring

774
00:37:51,960 --> 00:37:54,759
Speaker 1: people and not giving them a pathway forward leads to

775
00:37:54,800 --> 00:37:57,000
Speaker 1: that sort of binary black and white thinking that you

776
00:37:57,040 --> 00:37:59,920
Speaker 1: mentioned earlier. It's like, it's like, well, now you know,

777
00:38:00,440 --> 00:38:02,600
Speaker 1: so if you care about it. You're gonna opt out,

778
00:38:02,719 --> 00:38:05,200
Speaker 1: and that's not real life. For real life doesn't mean

779
00:38:05,280 --> 00:38:08,080
Speaker 1: you can opt out. And by the way, in real life,

780
00:38:08,120 --> 00:38:09,800
Speaker 1: if you were driving on the road and there was

781
00:38:09,800 --> 00:38:12,040
Speaker 1: a pothole and you drove on the pothole and you've

782
00:38:12,040 --> 00:38:14,680
Speaker 1: got a busted tire, imagine if people were like, that's

783
00:38:14,680 --> 00:38:17,120
Speaker 1: what you get for driving, Okay, you shouldn't been driving

784
00:38:17,120 --> 00:38:19,160
Speaker 1: on the road. That it would be insane. We would

785
00:38:19,160 --> 00:38:22,240
Speaker 1: look at that person and be like, you are bananagrams.

786
00:38:22,360 --> 00:38:24,800
Speaker 1: So that's not a real that's not a real solution.

787
00:38:25,160 --> 00:38:28,200
Speaker 1: We would say, there's a pothole, I'm calling the city government.

788
00:38:28,200 --> 00:38:30,040
Speaker 1: I'm letting them know about the pothole, and I want

789
00:38:30,080 --> 00:38:32,360
Speaker 1: to make sure that pothole is filled. That is what

790
00:38:32,600 --> 00:38:35,160
Speaker 1: I want us to move to. The sort of civic

791
00:38:35,239 --> 00:38:39,319
Speaker 1: understanding and responsibility of the internet as a utility. We're

792
00:38:39,320 --> 00:38:41,719
Speaker 1: all using it, okay, so we want it to be better.

793
00:38:42,040 --> 00:38:44,239
Speaker 1: We're not saying stop driving on the road. We're saying

794
00:38:44,320 --> 00:38:47,640
Speaker 1: fix the road right because we can't not drive. We

795
00:38:47,680 --> 00:38:49,880
Speaker 1: can't not drive. We can, but like, but what's there's

796
00:38:49,960 --> 00:38:52,560
Speaker 1: what's the consequence of not driving? So what's the consequence

797
00:38:52,600 --> 00:38:54,240
Speaker 1: of never being able to go on the internet again.

798
00:38:54,400 --> 00:38:57,359
Speaker 1: It's I mean, it's just it's not realistic. And if

799
00:38:57,480 --> 00:38:59,680
Speaker 1: if that's the advice that you give people, they're not

800
00:38:59,719 --> 00:39:01,799
Speaker 1: going to take it. And so they're just going to

801
00:39:01,840 --> 00:39:04,960
Speaker 1: either ignore the issue or feel bad all the time

802
00:39:05,200 --> 00:39:07,439
Speaker 1: that something is being done to them and they can't

803
00:39:07,480 --> 00:39:10,239
Speaker 1: stop it. And that's that's not the society that I

804
00:39:10,239 --> 00:39:12,720
Speaker 1: think we live it. Like I, I believe that people

805
00:39:12,760 --> 00:39:16,759
Speaker 1: have agency, and so one of our amazing engineers has

806
00:39:16,800 --> 00:39:20,120
Speaker 1: this phrase called agency not apathy. We want people to

807
00:39:20,160 --> 00:39:23,359
Speaker 1: feel agency, not apathy about what's going on, and that's

808
00:39:23,400 --> 00:39:26,600
Speaker 1: the heart of the markup. I like this idea because

809
00:39:26,719 --> 00:39:28,560
Speaker 1: I had the feeling of like, I'm going to see

810
00:39:28,560 --> 00:39:30,239
Speaker 1: all the stuff that these websites are taking from me.

811
00:39:30,719 --> 00:39:33,239
Speaker 1: But that fear can be a motivator in the sense

812
00:39:33,280 --> 00:39:36,520
Speaker 1: that I'm scared because I care about what people are

813
00:39:36,520 --> 00:39:39,480
Speaker 1: doing and what's happening. And so rather than I'm I'm

814
00:39:39,520 --> 00:39:42,440
Speaker 1: feeling fear, I'm just going to hide, I'm gonna never

815
00:39:42,520 --> 00:39:45,120
Speaker 1: drive again, I'm gonna whatever, I'm never going to enter again,

816
00:39:45,280 --> 00:39:47,960
Speaker 1: it's I feel fear, I care about this. Therefore I'm

817
00:39:47,960 --> 00:39:50,839
Speaker 1: going to do something differently. And you're saying here are

818
00:39:50,840 --> 00:39:53,239
Speaker 1: the tools and here's what you can do, which thank

819
00:39:53,280 --> 00:40:01,839
Speaker 1: you for doing that. You're welcome. So black lights one

820
00:40:01,880 --> 00:40:04,120
Speaker 1: of the tools. There's three that I saw. Can we

821
00:40:04,120 --> 00:40:06,919
Speaker 1: talk about that, of course? So we have black Light.

822
00:40:07,040 --> 00:40:10,160
Speaker 1: We have a tool called split screen, so you know,

823
00:40:10,200 --> 00:40:12,879
Speaker 1: we all kind of intuitively know that our neighbors might

824
00:40:12,920 --> 00:40:15,719
Speaker 1: not be seeing the same thing on Facebook that we do, right,

825
00:40:16,120 --> 00:40:19,319
Speaker 1: Like I have my portfolio things that I read that

826
00:40:19,320 --> 00:40:22,080
Speaker 1: I'm targeted with news wise on Facebook, and I know

827
00:40:22,280 --> 00:40:24,719
Speaker 1: that other folks that I know they're getting news from

828
00:40:24,800 --> 00:40:28,280
Speaker 1: very different sources. So we have this tool called split

829
00:40:28,320 --> 00:40:32,319
Speaker 1: screen that is a almost real time tool to see

830
00:40:32,440 --> 00:40:35,200
Speaker 1: like what are women seeing on Facebook? What are men

831
00:40:35,280 --> 00:40:39,080
Speaker 1: seeing on Facebook? What are boomer seeing on Facebook? What

832
00:40:39,200 --> 00:40:42,279
Speaker 1: are millennial seeing on Facebook? And the way we're able

833
00:40:42,320 --> 00:40:45,280
Speaker 1: to do that is that we actually built a representative

834
00:40:45,320 --> 00:40:48,960
Speaker 1: statistical panel across the country and said, hey, folks, use

835
00:40:49,000 --> 00:40:51,440
Speaker 1: this tool that we made called Citizen Browser. We're not

836
00:40:51,480 --> 00:40:53,960
Speaker 1: going to collect any of your private information, but we

837
00:40:54,000 --> 00:40:57,239
Speaker 1: want to know what news articles are being pushed to

838
00:40:57,320 --> 00:41:01,839
Speaker 1: you by Facebook because it's interesting to us. We want

839
00:41:01,840 --> 00:41:06,280
Speaker 1: to know just how different are people's news universes. After

840
00:41:06,440 --> 00:41:10,319
Speaker 1: something like the January six incident, right, So like what

841
00:41:10,360 --> 00:41:12,560
Speaker 1: are Trump voters seeing in terms of the news that's

842
00:41:12,560 --> 00:41:15,040
Speaker 1: been pushed to them, and what are Biden voters seeing? Right?

843
00:41:15,360 --> 00:41:17,279
Speaker 1: And so we built this to answer those questions. We

844
00:41:17,400 --> 00:41:21,080
Speaker 1: kind of all intuitively new, right, like, oh, yeah, you're

845
00:41:21,120 --> 00:41:23,239
Speaker 1: seeing different stuff than me. But we wanted to know

846
00:41:23,280 --> 00:41:25,359
Speaker 1: the answer with data, right. We wanted to know it

847
00:41:25,360 --> 00:41:28,400
Speaker 1: with science because we think if you know with certainty,

848
00:41:28,520 --> 00:41:31,400
Speaker 1: then you can fix it in reality. But if you

849
00:41:31,520 --> 00:41:34,600
Speaker 1: just operate with these stereotypes, right, like, it's not you

850
00:41:34,640 --> 00:41:36,160
Speaker 1: can't move the ball. And all I want to do

851
00:41:36,200 --> 00:41:38,840
Speaker 1: is move the ball to a better future. So anyone

852
00:41:38,880 --> 00:41:41,160
Speaker 1: can check out the mark up split screen and just

853
00:41:41,239 --> 00:41:43,640
Speaker 1: kind of see like what's going on? Well, and that

854
00:41:44,080 --> 00:41:47,680
Speaker 1: is fascinating too, because I'm a big believer in Again,

855
00:41:47,719 --> 00:41:49,359
Speaker 1: this goes with everything we're saying, but like, you start

856
00:41:49,440 --> 00:41:52,880
Speaker 1: to believe what you see. So if I'm this demographic

857
00:41:53,000 --> 00:41:56,319
Speaker 1: and I'm getting all this, and let's say my grandfather

858
00:41:56,600 --> 00:42:00,279
Speaker 1: is obviously a different demographic, no wonder we might have

859
00:42:00,719 --> 00:42:03,560
Speaker 1: different views and we have different information when we're talking

860
00:42:03,560 --> 00:42:05,759
Speaker 1: about something that's happening in the world, because we're both

861
00:42:05,760 --> 00:42:10,080
Speaker 1: getting different information and probably an influx of like not

862
00:42:10,200 --> 00:42:14,480
Speaker 1: even information. Agree. What you see creates your reality. So

863
00:42:14,520 --> 00:42:18,160
Speaker 1: we have to understand what are these platforms doing to

864
00:42:18,239 --> 00:42:21,239
Speaker 1: create that different reality and then be able to call

865
00:42:21,320 --> 00:42:24,479
Speaker 1: them on it, right to be like, hey, you said,

866
00:42:24,600 --> 00:42:27,520
Speaker 1: Like an article that we wrote at the Markup was, Hey, Facebook,

867
00:42:27,600 --> 00:42:30,800
Speaker 1: you said that you weren't going to push election related

868
00:42:30,840 --> 00:42:35,319
Speaker 1: information election news right before the election, right like Mark

869
00:42:35,400 --> 00:42:39,400
Speaker 1: Zuckerberg said, We're not going to recommend these political groups

870
00:42:39,520 --> 00:42:42,120
Speaker 1: is what he said. We're like, okay, but we were

871
00:42:42,120 --> 00:42:45,480
Speaker 1: collecting data with our split screen, our sitist browser panel,

872
00:42:45,880 --> 00:42:48,319
Speaker 1: and we were able to see the in fact, you

873
00:42:48,400 --> 00:42:51,880
Speaker 1: were pushing these Facebook groups two people right around the

874
00:42:51,880 --> 00:42:55,000
Speaker 1: election and continuing afterwards, Like you said that you weren't

875
00:42:55,000 --> 00:42:57,920
Speaker 1: going to but you did. So what are we going

876
00:42:57,960 --> 00:43:00,680
Speaker 1: to do about that? Yeah, And that's a difference of like, Okay,

877
00:43:00,760 --> 00:43:03,839
Speaker 1: anybody can say anything, but we're showing you, guys what's

878
00:43:03,840 --> 00:43:07,040
Speaker 1: really happening exactly. I appreciate that. Okay, I have my

879
00:43:07,320 --> 00:43:10,560
Speaker 1: black light thinking up. I did Athleta instead. I don't

880
00:43:10,560 --> 00:43:13,360
Speaker 1: know why you have Lululemon on your you just closed

881
00:43:13,400 --> 00:43:16,439
Speaker 1: it out. I have New York Times, that's fine, which

882
00:43:16,440 --> 00:43:19,719
Speaker 1: has a lot, so you can help explain this to me.

883
00:43:19,719 --> 00:43:21,560
Speaker 1: So it's one ad tracker found in this site. This

884
00:43:21,640 --> 00:43:24,400
Speaker 1: is less than half of the average of seven that

885
00:43:24,440 --> 00:43:26,839
Speaker 1: we found on popular sites. What is that? So it'll

886
00:43:26,880 --> 00:43:28,920
Speaker 1: tell you, Um, if you click on it, it it can

887
00:43:28,960 --> 00:43:31,000
Speaker 1: give you a little bit more explanation, I think. But

888
00:43:31,440 --> 00:43:34,680
Speaker 1: we see that on average there are seven on different

889
00:43:34,680 --> 00:43:37,520
Speaker 1: websites that are around the world or around around the Internet,

890
00:43:37,680 --> 00:43:40,200
Speaker 1: and so Athleta on that front is doing better than

891
00:43:40,239 --> 00:43:41,799
Speaker 1: the average. And that's like a good thing to know,

892
00:43:41,880 --> 00:43:44,560
Speaker 1: to be like, all right, thank you friends. And then

893
00:43:44,560 --> 00:43:46,000
Speaker 1: when you click into it, it it will give you an

894
00:43:46,000 --> 00:43:49,560
Speaker 1: explanation of like, well, what's an ad tracker? Right? Because again,

895
00:43:49,680 --> 00:43:52,920
Speaker 1: like I don't want to assume that anyone knows anything

896
00:43:53,080 --> 00:43:56,640
Speaker 1: about the internet, because we all have full lives. Okay,

897
00:43:56,680 --> 00:43:59,280
Speaker 1: people have expertise in different things. It's not your fault

898
00:43:59,320 --> 00:44:01,279
Speaker 1: that you don't know the cookie is or an AD

899
00:44:01,320 --> 00:44:04,800
Speaker 1: tracker or something. It's not anyone's fault. Our job is

900
00:44:04,840 --> 00:44:06,439
Speaker 1: to be like, Okay, well you want to know, here

901
00:44:06,440 --> 00:44:09,720
Speaker 1: you go. Yeah, I appreciate that because I have no idea, okay,

902
00:44:09,760 --> 00:44:13,120
Speaker 1: And it says third party cookie. Fourteen third party cookies

903
00:44:13,120 --> 00:44:16,200
Speaker 1: were found this is more than average of three that

904
00:44:16,239 --> 00:44:18,880
Speaker 1: we found on this site. Okay, what does that means?

905
00:44:18,920 --> 00:44:21,400
Speaker 1: So a third party cookie is something that tracks you

906
00:44:21,480 --> 00:44:24,680
Speaker 1: around as you follow the internet. So like, let's say

907
00:44:24,760 --> 00:44:27,160
Speaker 1: you go to one website. If there's a cookie on

908
00:44:27,200 --> 00:44:29,839
Speaker 1: that website, it can see not only like what are

909
00:44:29,840 --> 00:44:32,040
Speaker 1: you where are you scrolling? What are you clicking through?

910
00:44:32,040 --> 00:44:34,800
Speaker 1: What kind of leggings did you linger on? What? What

911
00:44:34,880 --> 00:44:37,560
Speaker 1: don't you put into your basket? It can do that

912
00:44:37,600 --> 00:44:40,120
Speaker 1: for that website, and potentially, depending on the cookie, you

913
00:44:40,160 --> 00:44:42,359
Speaker 1: can also follow you to other places that you go,

914
00:44:42,440 --> 00:44:45,080
Speaker 1: even when you leave athleta dot com. Okay, so they're

915
00:44:45,080 --> 00:44:47,799
Speaker 1: not doing good there. This website loads trackers on your

916
00:44:47,800 --> 00:44:51,720
Speaker 1: computer that are designed to evade third party cookie blockers, sneaking. Yeah,

917
00:44:52,000 --> 00:44:53,520
Speaker 1: I don't like that. And that's all that found. So

918
00:44:53,560 --> 00:44:56,319
Speaker 1: that I mean, I guess that's generally not horrible. So

919
00:44:56,360 --> 00:44:58,160
Speaker 1: you said New York Times is pretty scary, and New

920
00:44:58,239 --> 00:45:02,040
Speaker 1: York Times wasn't the greatest although but you know, but

921
00:45:02,040 --> 00:45:06,440
Speaker 1: but like here's the thing, So they have third party cookies. Remember,

922
00:45:06,480 --> 00:45:09,080
Speaker 1: the third party cookies can actually be good. And this

923
00:45:09,120 --> 00:45:11,919
Speaker 1: is where the explanations matter. So let's say you put

924
00:45:11,960 --> 00:45:14,759
Speaker 1: something in your basket Athleta, and then you like click

925
00:45:14,800 --> 00:45:17,279
Speaker 1: away for a second and you come back and remembers

926
00:45:17,280 --> 00:45:19,600
Speaker 1: stuff is in your basket. Okay, Well cookies are important

927
00:45:19,680 --> 00:45:22,080
Speaker 1: for that, but that might not be a third party cookie.

928
00:45:22,080 --> 00:45:23,960
Speaker 1: So you want to What we want to do with

929
00:45:24,040 --> 00:45:25,960
Speaker 1: black Light is that we want to give you the

930
00:45:25,960 --> 00:45:29,080
Speaker 1: opportunity to like, okay, you have twenty four cookies. What

931
00:45:29,160 --> 00:45:32,520
Speaker 1: are these cookies? Right? Like, let's dig into this. So

932
00:45:32,560 --> 00:45:34,640
Speaker 1: when I put an athleta and went to athleta dot

933
00:45:34,680 --> 00:45:37,160
Speaker 1: gap dot com, and it tells me that the cookies

934
00:45:37,200 --> 00:45:40,000
Speaker 1: are Twitter. Okay. All that means is they have like

935
00:45:40,000 --> 00:45:42,799
Speaker 1: a little Twitter thing on their on their site, so

936
00:45:42,840 --> 00:45:44,720
Speaker 1: you could click Twitter and then go straight to their Twitter.

937
00:45:44,840 --> 00:45:49,760
Speaker 1: That seems fine. New Relic, who's that bien Tellect? Who's

938
00:45:49,840 --> 00:45:54,000
Speaker 1: that monotype imaging? Okay? Microsoft? Oh I know them. Maybe

939
00:45:54,040 --> 00:45:58,680
Speaker 1: it's related to service they're using Verizon? Okay, I pawn web.

940
00:45:59,560 --> 00:46:01,319
Speaker 1: And then you look at all these names and you're like,

941
00:46:01,520 --> 00:46:03,759
Speaker 1: who are these people? Let me google them? And so

942
00:46:03,760 --> 00:46:05,040
Speaker 1: what we want to give you is like, look, we

943
00:46:05,080 --> 00:46:06,840
Speaker 1: can't tell you everything you need to know, but we

944
00:46:06,880 --> 00:46:09,520
Speaker 1: can tell you where you can keep going. So maybe

945
00:46:09,560 --> 00:46:12,520
Speaker 1: you should go google b Intellect Inc. And see what

946
00:46:12,560 --> 00:46:15,000
Speaker 1: they do. You might decide that they're okay. You might

947
00:46:15,040 --> 00:46:16,960
Speaker 1: be like, I, actually they're fine. I don't care if

948
00:46:17,280 --> 00:46:20,360
Speaker 1: they are Verizon or Warner Media. Have my information that

949
00:46:20,440 --> 00:46:23,040
Speaker 1: seems all right. But we want you to make that

950
00:46:23,120 --> 00:46:26,440
Speaker 1: decision with agency, which is probably part of that article

951
00:46:26,480 --> 00:46:27,839
Speaker 1: that you were talking about, is like, it tells you

952
00:46:27,840 --> 00:46:30,800
Speaker 1: what to do with the information. Okay, So that's just interesting.

953
00:46:30,880 --> 00:46:32,880
Speaker 1: I'm going to play with that all day. Now. I

954
00:46:32,880 --> 00:46:36,239
Speaker 1: feel wonderful. What's the best way for people to go

955
00:46:36,320 --> 00:46:38,799
Speaker 1: and get all this information? Because I know that I'm

956
00:46:39,120 --> 00:46:41,160
Speaker 1: very interested in in it and want to learn more,

957
00:46:41,160 --> 00:46:43,319
Speaker 1: and I'm assuming people hearing this are going to be too.

958
00:46:43,520 --> 00:46:46,359
Speaker 1: So we have a newsletter called Clauson that you can

959
00:46:46,360 --> 00:46:48,560
Speaker 1: sign up for, and Clauson will just send you a

960
00:46:48,600 --> 00:46:51,600
Speaker 1: little newsletter, like just a little message every time we've

961
00:46:51,640 --> 00:46:54,080
Speaker 1: a new article. We published twice a week, so it's

962
00:46:54,080 --> 00:46:56,560
Speaker 1: not again, it's not like a ton to keep up with.

963
00:46:56,719 --> 00:46:59,399
Speaker 1: We want to make sure it's a manageable amount so

964
00:46:59,680 --> 00:47:02,160
Speaker 1: you can actually wrap your mind around it. And we

965
00:47:02,200 --> 00:47:05,640
Speaker 1: also have a series called Ask the Markup. So if

966
00:47:05,640 --> 00:47:08,200
Speaker 1: you're like, um, this thing is happening on the internet.

967
00:47:08,200 --> 00:47:10,640
Speaker 1: I've seen it. I've always wondered what is you know,

968
00:47:10,760 --> 00:47:13,440
Speaker 1: what's the deal here? Um, you can send in those

969
00:47:13,480 --> 00:47:16,280
Speaker 1: kinds of questions to us too. We had a question

970
00:47:16,280 --> 00:47:18,920
Speaker 1: where someone was like, Hey, what's going on with Venmo?

971
00:47:19,280 --> 00:47:22,440
Speaker 1: And like everyone can see my interact with my transactions,

972
00:47:22,480 --> 00:47:25,000
Speaker 1: just like, explain Venmo to me. And that's the article

973
00:47:25,000 --> 00:47:27,520
Speaker 1: that we did. We didn't one about Klarina and after

974
00:47:27,600 --> 00:47:30,680
Speaker 1: pay and like anything that you I was reading the

975
00:47:30,760 --> 00:47:33,520
Speaker 1: after pay one. I think I was reading that people.

976
00:47:33,680 --> 00:47:37,439
Speaker 1: We were here for people's questions. You know, it's complicated,

977
00:47:37,680 --> 00:47:39,319
Speaker 1: and so we want to put the tools in your

978
00:47:39,320 --> 00:47:41,319
Speaker 1: hands to make better choices. Let us know how we

979
00:47:41,320 --> 00:47:44,160
Speaker 1: can help. I'm interested in the Venmo one because why

980
00:47:44,239 --> 00:47:46,120
Speaker 1: is there a social feed on Venmo? You can turn

981
00:47:46,160 --> 00:47:49,480
Speaker 1: it off? It makes no sense, so I didn't know

982
00:47:49,520 --> 00:47:51,399
Speaker 1: you could. You can turn it off. You can turn off,

983
00:47:51,440 --> 00:47:53,160
Speaker 1: you can go in through privacy settings. Yeah, but there

984
00:47:53,160 --> 00:47:54,520
Speaker 1: you go. So that's the thing you can do. Now,

985
00:47:54,560 --> 00:47:56,319
Speaker 1: go in through privacy settings. You can turn it off

986
00:47:56,560 --> 00:47:59,680
Speaker 1: so people don't see things. But like you just snoop

987
00:47:59,760 --> 00:48:01,920
Speaker 1: on everyone's life if they haven't turned it off or

988
00:48:02,000 --> 00:48:04,920
Speaker 1: you're like okay, and why do I need to know that?

989
00:48:04,960 --> 00:48:07,240
Speaker 1: And you know what that makes me think of, like, gosh,

990
00:48:07,280 --> 00:48:10,040
Speaker 1: like dating, And you know, I'm a therapist, so I

991
00:48:10,080 --> 00:48:12,359
Speaker 1: hear a lot about people's daily lives and and I'm

992
00:48:12,400 --> 00:48:14,200
Speaker 1: a human, so I talk to people and hear about

993
00:48:14,200 --> 00:48:15,839
Speaker 1: their dating lives and I have one too, But like

994
00:48:16,040 --> 00:48:18,359
Speaker 1: the amount of people that are like I saw so

995
00:48:18,400 --> 00:48:20,719
Speaker 1: and so pay so and so on benmo, and I'm like,

996
00:48:20,840 --> 00:48:24,440
Speaker 1: oh my gosh, Like we have enough ways to stalk people.

997
00:48:24,760 --> 00:48:27,480
Speaker 1: We don't need to know who's paying who for tacos exactly.

998
00:48:27,880 --> 00:48:30,120
Speaker 1: And then because I hear it from my friends all

999
00:48:30,160 --> 00:48:33,799
Speaker 1: the time, like so and so had the little champagne

1000
00:48:33,800 --> 00:48:37,160
Speaker 1: emoji with another person, what's that about? And it's like,

1001
00:48:37,320 --> 00:48:40,279
Speaker 1: you know, it's probably nothing. And actually, we don't need

1002
00:48:40,360 --> 00:48:42,759
Speaker 1: to live in a surveillance state where we're watching every

1003
00:48:42,760 --> 00:48:46,239
Speaker 1: single thing what every other person does. Just yeah, don't

1004
00:48:46,360 --> 00:48:48,919
Speaker 1: do that. We don't need to do that. Well, I've

1005
00:48:48,960 --> 00:48:51,240
Speaker 1: loved talking to you. This was so much. This is great.

1006
00:48:51,360 --> 00:48:53,720
Speaker 1: I feel like I'm going to have about five questions

1007
00:48:53,719 --> 00:48:55,719
Speaker 1: for you after I dig into all this stuff. That's

1008
00:48:55,719 --> 00:48:58,680
Speaker 1: what I love. I really am so grateful for all

1009
00:48:58,719 --> 00:49:00,880
Speaker 1: of this because I knew this is going to be

1010
00:49:00,880 --> 00:49:04,240
Speaker 1: a different kind of episode. But the amount of time

1011
00:49:04,280 --> 00:49:08,759
Speaker 1: I spend talking about the media, social media, just all

1012
00:49:08,800 --> 00:49:11,759
Speaker 1: this stuff with people in therapy and just like in

1013
00:49:11,840 --> 00:49:15,200
Speaker 1: my life, like we need people like you who are

1014
00:49:15,239 --> 00:49:18,279
Speaker 1: like helping us keep all of this but in a

1015
00:49:18,280 --> 00:49:21,200
Speaker 1: way that is helpful to us. What I've gotten out

1016
00:49:21,200 --> 00:49:23,600
Speaker 1: of this conversation is like, we don't need to like

1017
00:49:23,760 --> 00:49:27,000
Speaker 1: kill the internet. We just need to remember why we

1018
00:49:27,080 --> 00:49:29,560
Speaker 1: have it, what we wanted to actually do for us,

1019
00:49:29,760 --> 00:49:32,880
Speaker 1: and how do we put our efforts into that direction.

1020
00:49:33,200 --> 00:49:36,080
Speaker 1: That's absolutely right, that's and that honestly, like that's like

1021
00:49:36,120 --> 00:49:38,520
Speaker 1: a our new mission statement, but that's what it is.

1022
00:49:38,560 --> 00:49:41,760
Speaker 1: It's like preserve the good, get rid and fixed the bad,

1023
00:49:42,280 --> 00:49:46,239
Speaker 1: and we are in a really special opportunity space right

1024
00:49:46,239 --> 00:49:49,880
Speaker 1: now to do that. So let's do it. Let's freaking

1025
00:49:49,920 --> 00:49:52,400
Speaker 1: do it. I've been getting in my head the past

1026
00:49:52,440 --> 00:49:55,280
Speaker 1: probably a couple of months, of being like I hate TikTok,

1027
00:49:55,440 --> 00:49:57,920
Speaker 1: I hate this, but like I don't hate it, but

1028
00:49:57,960 --> 00:49:59,600
Speaker 1: like I feel like I have to hate it because

1029
00:49:59,640 --> 00:50:01,919
Speaker 1: of the little bits of things that it doesn't help.

1030
00:50:01,960 --> 00:50:04,200
Speaker 1: And now I feel like refreshed of like I don't

1031
00:50:04,200 --> 00:50:06,360
Speaker 1: have to hate this stuff. I just have to remember

1032
00:50:06,640 --> 00:50:08,319
Speaker 1: why can it be good? And how do I put

1033
00:50:08,320 --> 00:50:11,640
Speaker 1: my attention to that? Thank you. Also, we can talk

1034
00:50:11,640 --> 00:50:13,799
Speaker 1: at another time about how much I love TikTok and

1035
00:50:13,800 --> 00:50:16,160
Speaker 1: how much parenting advice I get from TikTok. We'll see

1036
00:50:16,160 --> 00:50:20,120
Speaker 1: how that turns out in eighteen years. Well that's the thing,

1037
00:50:20,200 --> 00:50:22,080
Speaker 1: like we should we need to talk about that another

1038
00:50:22,120 --> 00:50:24,960
Speaker 1: time because I love it too, and I love it

1039
00:50:24,960 --> 00:50:27,480
Speaker 1: because it helps me, like, you know, things that aren't

1040
00:50:27,480 --> 00:50:29,480
Speaker 1: so serious. I can laugh at things and it's funny

1041
00:50:29,480 --> 00:50:31,880
Speaker 1: and it's an easy way to access that. It helps

1042
00:50:31,880 --> 00:50:34,399
Speaker 1: people be creative, and it gives there's so much good

1043
00:50:34,400 --> 00:50:37,000
Speaker 1: to it, But it also sees so much misinformation that

1044
00:50:37,040 --> 00:50:40,920
Speaker 1: I'm like, stop saying that. And how many clients send

1045
00:50:40,920 --> 00:50:43,600
Speaker 1: me TikTok's and are like, is this true? Why have

1046
00:50:43,640 --> 00:50:45,120
Speaker 1: you never told me that? And I'm like, because it's

1047
00:50:45,160 --> 00:50:49,000
Speaker 1: not true. I never said think it's not true. Also,

1048
00:50:49,560 --> 00:50:51,520
Speaker 1: people sending me tiktoks and I'm like, I don't think

1049
00:50:51,520 --> 00:50:54,160
Speaker 1: that's information that I want you to have right now,

1050
00:50:54,200 --> 00:50:55,960
Speaker 1: Like it's information that I would give you in a

1051
00:50:55,960 --> 00:50:58,799
Speaker 1: session where we could process and all. There's so much

1052
00:50:58,800 --> 00:51:00,640
Speaker 1: to it I talked about all the time, but it

1053
00:51:00,680 --> 00:51:02,719
Speaker 1: can be used for good. They can't. There's I mean,

1054
00:51:02,719 --> 00:51:04,719
Speaker 1: I feel like there's a whole other hour on like

1055
00:51:04,800 --> 00:51:08,279
Speaker 1: the difference between expertise, knowledge and information. The Internet gives

1056
00:51:08,320 --> 00:51:12,359
Speaker 1: us information, but not expertise and not real knowledge because

1057
00:51:12,360 --> 00:51:15,160
Speaker 1: knowledge is structured. Right, No, this at this time, and

1058
00:51:15,200 --> 00:51:17,799
Speaker 1: then this and then this. That's it. Yeah, we can

1059
00:51:17,800 --> 00:51:20,680
Speaker 1: talk about that at a minute time. Okay, I can't wait.

1060
00:51:20,719 --> 00:51:22,880
Speaker 1: Then that last part, I'm like, okay, that's what I

1061
00:51:22,920 --> 00:51:25,560
Speaker 1: needed that in words, Well, thank you so much, thank you,

1062
00:51:25,920 --> 00:51:33,799
Speaker 1: talk soon, bye bye.