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Speaker 1: This is Master's in Business with Barry Ridholts on Boomberg Radio.

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Speaker 1: This week on the podcast, I have a special guest.

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Speaker 1: His name is a Neil Dash. He is a leading technician, entrepreneur,

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Speaker 1: founder uh in the world of micro publishing and blogging.

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Speaker 1: I know his work from back when six Apart was

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Speaker 1: an early pioneer in the world of blogging. They put

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Speaker 1: out type Pad, which was really the first robust, whizzywig

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Speaker 1: what you see is what you get sort of blogging platform.

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Speaker 1: Before that, you had companies like Yahoo Geo Cities. My

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Speaker 1: first blog was on Geo Cities and I say this

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Speaker 1: it's It's really not a joke. It's true. I say

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Speaker 1: it as a joke, but it's true. I would take

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Speaker 1: fift twenty minutes to write something and then two hours

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Speaker 1: to code in an HTM out in order for it

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Speaker 1: to work. On Geo Cities. It was you were literally

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Speaker 1: coding everything. Every every indent, every bold, every underlying, every

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Speaker 1: paragraph had an htmail code arout it. So to reduce

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Speaker 1: that process of of micro publishing to something that was

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Speaker 1: like it very much was like working on a document

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Speaker 1: on Microsoft Word. If you wanted to format it, you

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Speaker 1: just clicked the button that said, here's your underline, here's

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Speaker 1: your talles, here's your footnote, here's your and it was.

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Speaker 1: It was absolutely game changing. It went from a tent

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Speaker 1: to one ratio of of coding to writing to hundreds

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Speaker 1: to one in the opposite direction. You would take a

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Speaker 1: half hour to write something and maybe thirty seconds to

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Speaker 1: format it. It was easy as pie. My first blog

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Speaker 1: was big Picture dot type head dot com. It's still

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Speaker 1: up there, by the way. Not only did they create

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Speaker 1: the software for this, but they also created the hosting

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Speaker 1: for it. And I find six apart was a game

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Speaker 1: changer for the world of publishing. I found this to

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Speaker 1: be an absolutely fascinating conversation. If you're into blogging, technology, entrepreneurship,

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Speaker 1: venture capital, et cetera, you're gonna find this conversation fascinating. So,

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Speaker 1: with no further ado, my conversation with a Neil Dash,

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Speaker 1: My special guest today is a Neil Dash. He was

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Speaker 1: an advisor to the Obama White House's Office of Digital Strategy.

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Speaker 1: He is a technical advisor to Vox Media advises the

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Speaker 1: company medium on its publishing. He is also on the

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Speaker 1: National Advisory Council of Donors Choose. His day job is

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Speaker 1: CEO of fog Create Software, which has created such products

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Speaker 1: as stack overflow and trell Oh were they involved in

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Speaker 1: Marker Bass or is that something separate? Was a startup

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Speaker 1: was doing right before this? Before that, he writes a

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Speaker 1: monthly opinion column on the impact of technology on society

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Speaker 1: for Wired magazine. I know him as employee number one

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Speaker 1: at six Apart, behind the seminal blogging software type Pad.

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Speaker 1: He also serves on the board of the Data and

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Speaker 1: Society Research Institute. Neil Dash Welcome to Bloomberg. Thanks so

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Speaker 1: much for having me here. So I mentioned type head,

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Speaker 1: I really have to jump right into that. I know

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Speaker 1: who you are because I actually was a beta tester

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Speaker 1: for type pad, and that's where I rolled out. Thank

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Speaker 1: you for being one. That's where I rolled out the

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Speaker 1: big picture blogged tell us about your role with the

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Speaker 1: company six Sure. So I started blogging back and there

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Speaker 1: were a couple dozen bloggers on the internet, and I thought,

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Speaker 1: what were you using? Two blog? I was manually doing it.

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Speaker 1: I was the people who use Windows who remember an

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Speaker 1: app called notepad, and I was manually writing HTML, the

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Speaker 1: language of webpages, in Notepad and saving it onto a

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Speaker 1: web server by myself, which is the cutting edge or

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Speaker 1: technology back into the last So I was using Yahoo

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Speaker 1: geo Cities, which you're telling me is more advanced. I

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Speaker 1: was just cutting and pasting content and then having to

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Speaker 1: wrap the HTML code around, right. So that was the

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Speaker 1: state of the art. And then in late ninety nine

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Speaker 1: a couple of the first blogging tools came along and

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Speaker 1: then and so I started using those like Blogger and

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Speaker 1: which Google later bought and other things like that, and

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Speaker 1: uh and Friends shortly thereafter built this tool called movable

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Speaker 1: type and it was the first sort of serious blogging platform.

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Speaker 1: Almost immediately people used it to build Gawker, huffing and post.

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Speaker 1: What was behind movable type, Uh, they were then husband

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Speaker 1: and wife couple Ben trot A, Mina trot Um and um,

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Speaker 1: and really we're sort of visionaries about the idea that

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Speaker 1: we should take this medium seriously. It was going to

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Speaker 1: be something big. It wasn't just h you know, people

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Speaker 1: sharing their feelings in a journal online like this was

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Speaker 1: going to be where media was head. And this is

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Speaker 1: this is pre Facebook, pre Twitter. Oh yeah, this is

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Speaker 1: way earlier. Yeah before friends stir you even remember that one,

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Speaker 1: so way way back there, and consumer internet was dead

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Speaker 1: deader than dead in two thousand one. I mean you

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Speaker 1: couldn't you know. We we did it a round that

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Speaker 1: was six grand that we raised, and people were like, wow,

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Speaker 1: that's all the money in the world. You know, I

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Speaker 1: was here. I mean, it's it's it's like the catering

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Speaker 1: budget for a launch party for one of these startups today.

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Speaker 1: And uh. And so we did that and what was

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Speaker 1: interesting was people almost immediately recognized this is important, this

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Speaker 1: is something new in media. There's something really powerful enabling here.

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Speaker 1: And we thought it's still not easy enough. It was

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Speaker 1: still you had to have a lot of technical knowledge.

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Speaker 1: And that was where Type came from. You know, I

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Speaker 1: think the predecessor to today. You see the word presses

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Speaker 1: and mediums and tumblers of the world, and all of

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Speaker 1: them I think would say, you know, Type had as

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Speaker 1: a direct antecedent to that. And it was the first,

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Speaker 1: as far as I can recall, is the first whizzy

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Speaker 1: wig sort of blogging software. What you see is what

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Speaker 1: you get. It was like operating within a word perfect

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Speaker 1: or a word doc. Since it was since it was

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Speaker 1: seventeen years ago, I could say word perfect exactly like

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Speaker 1: anyone knows what that for The old timers. But I think,

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Speaker 1: you know, the other thing really interesting was we were

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Speaker 1: experimenting with today you know, a lot of things that

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Speaker 1: we take for granted and consumer web. So just the

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Speaker 1: fact that we had a consumer pay model those five

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Speaker 1: bucks a month, ten bucks a month. I mean, now

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Speaker 1: you know, everybody's paying for Spotify and Netflix and it's nothing, right,

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Speaker 1: Nobody was really thinking in terms of recurring revenue stream

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Speaker 1: in a monthly Yeah, hits a credit card. Yeah. The

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Speaker 1: idea that that we were even gonna ask people to

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Speaker 1: do that was radical. I mean, this stuff sounds like

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Speaker 1: ridiculous because we all do it now, but you know,

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Speaker 1: it was this sixteen years ago. Fifteen years ago, people

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Speaker 1: were really really taken aback by that. The other thing

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Speaker 1: that I think in retrospect was a bigger deal, huge deal,

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Speaker 1: and we sort of just took it for granted, was

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Speaker 1: we were probably the first consumer product to use Amazon

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Speaker 1: Web services on the back end, so were we had

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Speaker 1: some features that would let you list books you were

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Speaker 1: reading and music you were listening to, and they would

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Speaker 1: talk to Amazon and link up you know, buy my

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Speaker 1: book or or or you know by this back then CD.

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Speaker 1: And the interesting thing about that is some of us

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Speaker 1: still buy CDs just as every one's in a great while,

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Speaker 1: I will say so for collecting purposes, that's right. And

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Speaker 1: and so it was an interesting thing was that, um,

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Speaker 1: we had this this app talking to web services from Amazon. Um,

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Speaker 1: you know, years and years before I think that became commonplace.

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Speaker 1: And then the third thing that that type Pad did,

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Speaker 1: I think nobody really remembers. Um So the you know,

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Speaker 1: the iPhone launch, you didn't have an app store. You know,

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Speaker 1: Steve Jobs is like, you gotta use against it originally

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Speaker 1: and then and then a year later, so they said, okay,

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Speaker 1: we're gonna introduce the app store. At that initial rollout

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Speaker 1: on stage with Jobs, we had our head of product

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Speaker 1: for type Pad showing type Pad taking photos on your phone,

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Speaker 1: uploading them to the web from your iPhone, you know,

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Speaker 1: in real time. This was, you know, the sort of

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Speaker 1: the years long before Instagram took off. The very first

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Speaker 1: initial launch of the app store, type Pad was one

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Speaker 1: of the first apps they ever future and type head

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Speaker 1: is still around, still support, still doing this. They they

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Speaker 1: changed ownership a bunch of times. I don't I literally

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Speaker 1: have even followed because I've been so busy with other stuff.

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Speaker 1: For the the last several years. But they I mean, I

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Speaker 1: know the old big picture, which I did not take

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Speaker 1: down when I moved toward press in in oh eight.

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Speaker 1: I picked September oh eight is perfect time in the

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Speaker 1: middle of the financial crisis. It was like six months

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Speaker 1: in advance, and then the world blew up. I kept

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Speaker 1: both that and I had a fun Essays and a

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Speaker 1: Fluvia for just random of fluvia. Um and they're still

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Speaker 1: up and running. I still at one point in time

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Speaker 1: it was fifty percent of the traffic to wear Press

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Speaker 1: and then it gradually, you know, as as people move

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Speaker 1: their bookmarks and RSS feeders which no longer. Yeah, there's

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Speaker 1: a lot. I mean, there's a lot of technology that's

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Speaker 1: sort of come, come and gone, and I think some

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Speaker 1: of these things will come back around again. But it's

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Speaker 1: been an interesting thing to watch. Um, a lot of

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Speaker 1: these ideas we thought were really radical around Oh, you

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Speaker 1: might take a picture on your camera on your phone

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Speaker 1: and then share with people instantly, and you might store

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Speaker 1: that on Amazon web services, and you might use a

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Speaker 1: service that's got a consumer subscription model as the way

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Speaker 1: of accessing it. All those things, Um, you know, we

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Speaker 1: weren't necessarily what we were first on some of them,

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Speaker 1: but we weren't, you know, the only ones doing them.

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Speaker 1: I think to have been certainly popularized that I think

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Speaker 1: to bet that that was the way the Internet was headed,

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Speaker 1: where some of the things that we're just as important

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Speaker 1: as the idea that blogs were going to be media

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Speaker 1: that matter. Here's the quote of yours that I like,

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Speaker 1: any form of electronic communication will first be dismissed as

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Speaker 1: trivial and worseless until it produces a profound result, after

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Speaker 1: which it will be described as obvious and boring. Yeah,

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Speaker 1: that's been my experience for sure. You've been blogging since?

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Speaker 1: Was this the plan all along? To keep keep? You know?

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Speaker 1: It was really one of those I was underemployed, not

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Speaker 1: real happy with my place in life, and thought, I'm

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Speaker 1: gonna have a creative outlet to put stuff out there.

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Speaker 1: And I can't sing, and I can't, you know, I can't,

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Speaker 1: I can't do a radio show, so let me do this,

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Speaker 1: and uh, it was an interesting thing to to sort

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Speaker 1: of just have this outlet. And then realized this media

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Speaker 1: mattered enough and that I had been early, you know,

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Speaker 1: I thought it was late, starting at nine. That's funny

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Speaker 1: because when I started on type head. It was oh

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Speaker 1: three the song I even remember July, and it was

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Speaker 1: essentially a handful of college uh economics p fessors, nobody

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Speaker 1: really writing about markets, nobody really writing about investing, and

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Speaker 1: you end up my experience was similar to yours, and

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Speaker 1: that I'm not thrilled with what I'm doing. I'm kinda,

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Speaker 1: you know, looking for a creative outlet. But it was

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Speaker 1: clear that the mainstream media they take some young kid

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Speaker 1: out of school and throw them. Uh. Nobody wants to

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Speaker 1: cover the FED. Nobody wants to do economics back then,

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Speaker 1: and they were frequently, if not wrong, then lacking context.

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Speaker 1: They were they weren't deep enough in it right. And

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Speaker 1: I think that was the thing. Is that then the

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Speaker 1: people writing the blogs, with the people who are like,

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Speaker 1: I'm obsessing over this whether there's an audience or not,

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Speaker 1: that's that nobody cares, you know. My view was, who

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Speaker 1: cares if there's an audience? There was a whole run

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Speaker 1: of expert amateurs. Is that is that a real thing?

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Speaker 1: I don't know, but I know exactly what you mean.

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Speaker 1: And I think that summer too was a particularly interesting time,

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Speaker 1: summer a GOO three, because we had folks coming up

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Speaker 1: that we're doing covering aspects of economics that people weren't covering. Um,

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Speaker 1: we brought some of the verse first. Well, really, I

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Speaker 1: think all the first vcs that started blog and came

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Speaker 1: out on type paths. We had Fred Wilson on, we

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Speaker 1: had yeah, David Hornick from August Capital, a bunch of

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Speaker 1: these folks, Joe Eto, who's now heading up the media,

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Speaker 1: and you know, all these folks were Reid Hoffman, um,

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Speaker 1: you know, like has a podcast exactly, the CEO of

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Speaker 1: of Lincoln and uh and so all these people were

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Speaker 1: you know, I knew them as investors, and I was

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Speaker 1: not at all fluent in m VC. You know, I

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Speaker 1: knew tech, but at that time you could actually build

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Speaker 1: an entire career writing software and never crossed paths with VC. Really, yeah,

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Speaker 1: you know it was it was pretty common. And because

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Speaker 1: it was a lot of big companies on the pop

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Speaker 1: shops that were building software and apps and they would

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Speaker 1: sort of grow organically out of that. And um, and

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Speaker 1: if you weren't in the valley in particular, you know,

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Speaker 1: you could easily. I was in New York. You could

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Speaker 1: just never cross paths. And so to read these blogs

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Speaker 1: was like opening up this whole new world, and they

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Speaker 1: were now I understand, like you know, to some degree,

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Speaker 1: was content marketing. They were marketing their their firms by

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Speaker 1: being better storytellers. I think that's what it's involved, right,

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Speaker 1: I think that's what it's evolved to, the same thing

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Speaker 1: with the freemium model. Here was a whole bunch of

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Speaker 1: free content owned by the way. If you want to

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Speaker 1: work with us, you can. But that's not I don't

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Speaker 1: think that was anyone's intent. It truly wasn't my intention.

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Speaker 1: Here's what I do. I'm gonna blog in obscurity for

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Speaker 1: twelve years and then have a radio show. Well, it's

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Speaker 1: so interesting because I had that where. You know, one

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Speaker 1: of the people I connected with back then, UM was

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Speaker 1: Joel Spolsky who was writing a blog called Joel on Software,

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Speaker 1: and he was really the first person to write about

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Speaker 1: sort of coding culture, technical culture, and it was one

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Speaker 1: of the things that those of us were coding for

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Speaker 1: a living, which is what I did back then. I

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Speaker 1: knew these things, but had never seen them addressed as

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Speaker 1: like you are you are you know people at the

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Speaker 1: place in society, and he was taking programmers very seriously. Um.

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Speaker 1: Part of the reason he was blogging. Then he was

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Speaker 1: explaining the ideas behind the new company he had just created,

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Speaker 1: which was Fall Creek Software. And so seventeen years later,

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Speaker 1: you know, for well sixteen years from that point that

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Speaker 1: I took over as CEO of that company. Uh, it

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Speaker 1: felt like I knew everything about how this company ran

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Speaker 1: and what its values were, and what his purpose was

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Speaker 1: in the world, because I had from day one followed

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Speaker 1: along with the storytelling. And you think he was not

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Speaker 1: content marketing, He was not. He didn't start writing this stuff.

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Speaker 1: He was literally like trying to solve a problem like

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Speaker 1: how do you deal with real estate in Manhattan? How

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Speaker 1: do you how do you keep programmers happy in a

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Speaker 1: world where you know, back then, hard as it is

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Speaker 1: to believe, programmers were treated sort of like dirt. They

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Speaker 1: were like this guy in the back, We're going to

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Speaker 1: get him a computer and lock him in the dark

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Speaker 1: and exactly right, and throw caffeine at him. And uh

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Speaker 1: and now you know, you think, well, I mean, there's

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Speaker 1: probably no more spoiled workers in the world in terms

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Speaker 1: of like the free massages and the trades of candy.

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Speaker 1: And you mentioned that Google lifted the idea of all

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Speaker 1: the free food. Yeah, this and this is one of

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Speaker 1: those things where like things become urban legend, and so

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Speaker 1: it's hard to separate fact from fiction. But what I've

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Speaker 1: heard so one thing that is, you know, definitely true

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Speaker 1: is fault Creek was one of the first companies to

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Speaker 1: do the like let's really spoil our coders and our

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Speaker 1: technical workers. And it was everything from great free lunches

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Speaker 1: to UM. One of the things I still spend a

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Speaker 1: lot of time working on completely end to end healthcare.

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Speaker 1: Nobody on our team pays anything for healthcare UM. In fact,

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Speaker 1: we have people who have been at the company a

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Speaker 1: long time or they came right out of school. They

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Speaker 1: didn't know what in network out of network means because

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Speaker 1: they never had to deal with it the network. And

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Speaker 1: I was like, that's great, Like that's what we want

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Speaker 1: people to feel. And then one of those things was

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Speaker 1: really great free catered lunches. In retrospect, I think some

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Speaker 1: of this was the company was always like downtown Manhattan,

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Speaker 1: and especially back then, you know, just post nine eleven,

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Speaker 1: there wasn't There wasn't like good restaurants there, you know.

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Speaker 1: You know it also, especially if you're working late, like

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Speaker 1: five pm, it would just shut down that neighborhood would

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Speaker 1: just be dead a so how do you get food

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Speaker 1: down to So they had caterers, right, and they had

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Speaker 1: caterers come in many employees. So now the company were

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Speaker 1: about forty it's it's still pretty small. It's it's kind

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Speaker 1: of going up and down in size because um over

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Speaker 1: the years, like they co created stack Overflow and they

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Speaker 1: created Trello, and as those products grow, they get pretty

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Speaker 1: big and then they would spin them out. You know,

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Speaker 1: Trello spun out a couple of years ago and sold

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Speaker 1: to it last back in January for let let me

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Speaker 1: reel you back into the blog is sphere and talk

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Speaker 1: about one of my favorite subjects, which is um uh

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Speaker 1: public a blog post of yours called Don't Read the

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Speaker 1: Comments Now. I wrote Bailout Nation on the blog. I

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Speaker 1: would put up a few hundred words and I would

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Speaker 1: get feedback and have you seen this story and look

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Speaker 1: at this link and the readers the community was astonishing.

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Speaker 1: And then tragedy of the comments that just gets overrun

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Speaker 1: with the spammers and trolls, and it became so time

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Speaker 1: consuming to stay on top of comments that finally I

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Speaker 1: had to just grip my teeth and rip the band

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Speaker 1: aid off in close conscience, and I was not happy

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Speaker 1: about doing it, but it just became this giant time suck.

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Speaker 1: What is the problem? And by the way, that's true

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Speaker 1: on my columns at the Washington Post and Bloomberg as well.

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Speaker 1: It's like, if you want to say something, go someplace.

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Speaker 1: Here's a link to Twitter, Here's a link to Facebook,

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Speaker 1: where hopefully you aren't doing this anonymously, and you could

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Speaker 1: be called out because eventually I could subpoena Twitter and

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Speaker 1: find out who you are if you say something. Although

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Speaker 1: Twitter has been done a good job of protecting people's nanimity,

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Speaker 1: they've done at protecting on a non amenmity yet but

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Speaker 1: but not abuse at all. Right, they're just in fact.

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Speaker 1: In fact, my argument as to why Twitter stock prices

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Speaker 1: has been in the crap all this time is they

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Speaker 1: have not created an encouraging communally totally agree. So there's

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Speaker 1: a couple things I would sort of break out here.

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Speaker 1: You know. The first is, um, I get to watch

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Speaker 1: people creating the first comment systems on the internet. You know,

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Speaker 1: there was a time when you couldn't actually comment on

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Speaker 1: a web page and so um. The interestingly, the challenge

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Speaker 1: then was what are people can type in this box

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Speaker 1: at all. Are they can even understand that you can

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Speaker 1: leave a comment and will show up on the page,

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Speaker 1: and that's the thing you can do. So they were

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Speaker 1: hyper optimized for at any cost. We just want to

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Speaker 1: put we don't want to put any barriers to somebody

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Speaker 1: typing in this box and leave and comment. Um. Of

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Speaker 1: course that pretty quickly became well, we made it really

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Speaker 1: really easy, and now there's no barriers and there's no

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Speaker 1: standard and what you know, I wish we had understood

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Speaker 1: the time. And I will say this, this is something

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Speaker 1: I personally didn't get for a long time. Was you

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Speaker 1: make a real community by introducing a set of rules

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Speaker 1: that everybody understands. This is true in the physical world.

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Speaker 1: We get it very intuitively. If you go to a

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Speaker 1: park and it's got the you know, you can't be

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Speaker 1: throwing your ball around here because you're gonna hit these

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Speaker 1: little kids that are over here, or there's a dog running.

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Speaker 1: You gotta keep your dog inside the fence. Whatever the

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Speaker 1: rules are. It makes the place work for everybody, and

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Speaker 1: it doesn't have to be honors. It doesn't have to

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Speaker 1: be a burden. We needn't do any of that in

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Speaker 1: creating these online systems, and in fact, a lot of

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Speaker 1: the people, and this is something it wasn't as much me,

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Speaker 1: but people that I saw that were creating other tools

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Speaker 1: that made the systems for commenting and feedback online were

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Speaker 1: total zealots about the fact there shouldn't be any rules.

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Speaker 1: It should be wild West all the time. And you

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Speaker 1: know wild West is basically well, if you have wild

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Speaker 1: West and there's no cops, guess who runs the shell

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Speaker 1: the outlaws. And in fact, when when I was I

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Speaker 1: went through a two step process. The first step was saying,

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Speaker 1: all right, we're gonna do moderated comments and and in

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Speaker 1: order to I'm gonna set up some rules which I'm

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Speaker 1: not going to share, so you're not gonna know, you

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Speaker 1: won't be able to gain the system just for just

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Speaker 1: just to get past step one. And then step two

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Speaker 1: is no ad hominem attacks, no no false no fake

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Speaker 1: news like it. It's amazing that one simple sentence of

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Speaker 1: nonsense can undercut this conversation deep deeply researched, intelligently debated

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Speaker 1: um and I want back and forth. I wanted debate,

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Speaker 1: but what I didn't want was just people derailing things

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Speaker 1: with nonsense. So we've had Trump talk about fake news.

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Speaker 1: Fake news, some of which is confirmation bias and tribalism,

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Speaker 1: and some of which is just people purposefully trying to Yeah. Yeah,

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Speaker 1: And there's there's a couple of guides online which I've

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Speaker 1: posted on the blog as a see. It's it's the

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Speaker 1: guide to disrupting Social Forums. They're they're actually out there

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Speaker 1: and they're out of the CIA Black Book to how

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Speaker 1: to go disrupt society. Right, it's misinformation as a tactic.

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Speaker 1: And so there's there's an interesting thing here where we

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Speaker 1: we've had this escalation. So first we had, um, you

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Speaker 1: know what, the Internet always had ordinary trolls, right, just

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Speaker 1: people saying like I don't because I can hide behind

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Speaker 1: my anonymity or relative nanimity, I can be transgressive in

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Speaker 1: this way where I'm just being the person who's like,

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Speaker 1: you know, ruining things for people, but but in a

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Speaker 1: way that I think they think it's entertaining. Um, And

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Speaker 1: that's sort of like it's annoying, but it's not a

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Speaker 1: big deal, and if you can ban them, that's fine.

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Speaker 1: The evolution of that into organized communities that are trying

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Speaker 1: to undermine other communities or undermine individual people who are

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Speaker 1: trying to communicate by misinformation, by personal attacks, by threats,

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Speaker 1: by all that sort of these tactics. I think people

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Speaker 1: don't understand that these have gotten very organized and very instructure.

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Speaker 1: As you said, there are guides to how to do it,

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Speaker 1: and so they say, well, why don't you just ignore

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Speaker 1: it if you don't you know, get y yeah, yeah, total.

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Speaker 1: I mean, whether whether it's you know, the game or

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Speaker 1: Gate or or or the men's rights activists, like, there

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Speaker 1: are a lot of communities that we're doing this online.

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Speaker 1: And and the interesting thing about this is one they

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Speaker 1: learned from each other. They've been evolving this over ten

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Speaker 1: or fifteen years. Uh, they are very organized, but they

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Speaker 1: organized in places that people aren't watching. So they're happening

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Speaker 1: on you know, some screw chan. I mean, there's the

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Speaker 1: ones that people know, but there's also just private channels.

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Speaker 1: You know, they can text each other like anybody else.

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Speaker 1: Like they're they're not you know, they're very technically literate.

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Speaker 1: And so what happens is people who are not sophisticating

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Speaker 1: these things think, well, okay, look, if this person is

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Speaker 1: being a jerk to online, why don't you just not

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Speaker 1: go on Twitter? Or why don't you just not you know,

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Speaker 1: don't worry about a delete or comment and kind of thing.

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Speaker 1: And it's like, well, the difference is when you have

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Speaker 1: people organizing trying to undermine a specific community, Um, just

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Speaker 1: ignoring it doesn't make it go away. And the the

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Speaker 1: the social costs of for example, saying just get off

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Speaker 1: of social media or don't go on Twitter, don't go whenever,

428
00:20:51,720 --> 00:20:53,800
Speaker 1: it's like, well, that's you know, if I work in media,

429
00:20:53,840 --> 00:20:55,720
Speaker 1: I work in publisher and work in tech. It's a

430
00:20:55,720 --> 00:20:57,720
Speaker 1: business tool. I need that. I need to have a

431
00:20:57,720 --> 00:21:01,480
Speaker 1: presence there. Translate the digital version of that into meat space.

432
00:21:01,520 --> 00:21:03,919
Speaker 1: It's sort of like saying don't go to the town square,

433
00:21:04,520 --> 00:21:06,680
Speaker 1: don't don't go to the school, don't go to the theater,

434
00:21:06,960 --> 00:21:09,520
Speaker 1: and it's it's a ridiculous exactly right. Then you take like,

435
00:21:09,600 --> 00:21:11,520
Speaker 1: you know, YouTube comments. I think they're getting a little better,

436
00:21:11,560 --> 00:21:14,240
Speaker 1: but notoriously terrible. And if you said I'm gonna go

437
00:21:14,280 --> 00:21:17,560
Speaker 1: to Google's lobby in Mountain View and I'm going to

438
00:21:17,640 --> 00:21:20,040
Speaker 1: start shouting epithets at people, They're not gonna be like,

439
00:21:20,040 --> 00:21:22,080
Speaker 1: have a seat, have some of our free lash. They're

440
00:21:22,080 --> 00:21:24,400
Speaker 1: gonna be like, no, you gotta stop doing that. We're

441
00:21:24,400 --> 00:21:27,560
Speaker 1: gonna kick you out my My explanation of it was,

442
00:21:27,600 --> 00:21:29,399
Speaker 1: if you have a cocktail party, a you get to

443
00:21:29,440 --> 00:21:32,720
Speaker 1: invite who comes and be someone starts flipping over tables,

444
00:21:32,720 --> 00:21:35,240
Speaker 1: you get to throw them out. It's not like well,

445
00:21:35,280 --> 00:21:38,280
Speaker 1: the thing that makes me incensed about this is that

446
00:21:38,359 --> 00:21:42,159
Speaker 1: they scream First Amendment. And my response is always, nothing

447
00:21:42,280 --> 00:21:45,520
Speaker 1: is stopping you from going and starting your own blog

448
00:21:46,160 --> 00:21:48,760
Speaker 1: and laboriously building it other than the fact that you're

449
00:21:48,880 --> 00:21:52,399
Speaker 1: lazy untalented. Other than yeah, I mean the other thing

450
00:21:52,400 --> 00:21:54,360
Speaker 1: to feel free. They don't want to do that. They're

451
00:21:54,400 --> 00:21:57,360
Speaker 1: not trying to create some coy're trying to destroy something exactly.

452
00:21:57,480 --> 00:21:59,600
Speaker 1: And I think that that there's a really there's a

453
00:21:59,600 --> 00:22:03,720
Speaker 1: tough lunge where um, you know, you can express yourself

454
00:22:03,760 --> 00:22:07,359
Speaker 1: however you want. You're not entitled to destroy my platform

455
00:22:07,440 --> 00:22:10,239
Speaker 1: and my community and my back and forth. Yea, and

456
00:22:10,240 --> 00:22:13,200
Speaker 1: and and and It's an interesting thing because there's also we,

457
00:22:14,119 --> 00:22:16,960
Speaker 1: I think especially technical people, have this desire to say,

458
00:22:16,960 --> 00:22:19,359
Speaker 1: I want one set of rules that applies to everybody,

459
00:22:19,480 --> 00:22:20,960
Speaker 1: and I want this one set of you know, this

460
00:22:21,040 --> 00:22:23,280
Speaker 1: behavior is always bad if you do this, if if

461
00:22:23,359 --> 00:22:27,240
Speaker 1: then exactly exactly exactly. Binary logic like the stuff that

462
00:22:27,000 --> 00:22:29,800
Speaker 1: that doesn't always work, and and it ignores the realities

463
00:22:29,840 --> 00:22:32,919
Speaker 1: of societies, which which is that people have different positions, roles, power,

464
00:22:33,320 --> 00:22:35,320
Speaker 1: all these things shape of dynamics. And the example I

465
00:22:35,320 --> 00:22:38,240
Speaker 1: else give is the sort of like the classic, you know,

466
00:22:38,359 --> 00:22:40,800
Speaker 1: one of the worst things that people do to threaten

467
00:22:40,880 --> 00:22:42,840
Speaker 1: people who are on the margins, who are vulnerable or

468
00:22:43,000 --> 00:22:45,720
Speaker 1: ideas that are unpopular. You know, they're gonna, we're gonna

469
00:22:45,760 --> 00:22:48,119
Speaker 1: expose you. We're gonna, we're gonna you know what they

470
00:22:48,160 --> 00:22:49,720
Speaker 1: called docking, and we're going to publish your home address.

471
00:22:49,760 --> 00:22:50,840
Speaker 1: I mean, have had this happen to me? You know,

472
00:22:51,080 --> 00:22:53,880
Speaker 1: the gamer gets published my home address. Don't you have

473
00:22:53,960 --> 00:22:57,040
Speaker 1: your phone number on your do? I thought that was insane,

474
00:22:57,359 --> 00:22:59,200
Speaker 1: you know. So there's an interesting thing where part of

475
00:22:59,240 --> 00:23:01,040
Speaker 1: it is about reclaim aiming like I'm going to control

476
00:23:01,119 --> 00:23:04,239
Speaker 1: this stuff and what's out there. Um, some of it

477
00:23:04,320 --> 00:23:07,800
Speaker 1: is I do I want to show people of good intent.

478
00:23:07,880 --> 00:23:11,159
Speaker 1: I am accessible, I'm not trying to hide sometimes, I'm

479
00:23:11,160 --> 00:23:13,520
Speaker 1: not trying to be you know, wall myself off from

480
00:23:13,560 --> 00:23:15,159
Speaker 1: because I do think most people are good and do

481
00:23:15,200 --> 00:23:17,560
Speaker 1: want to engage with ideas and want to be thoughtful.

482
00:23:18,000 --> 00:23:20,640
Speaker 1: And so that's something that's just signaling like I'm open

483
00:23:20,680 --> 00:23:24,280
Speaker 1: to that. Then there's this other part, which is so

484
00:23:24,280 --> 00:23:26,879
Speaker 1: there's a behavior where like if somebody is like legitimately

485
00:23:26,920 --> 00:23:30,199
Speaker 1: vulnerable and they are keeping themselves anonymous or pseudonymous in

486
00:23:30,280 --> 00:23:33,240
Speaker 1: order to to keep themselves safe, and you out them,

487
00:23:33,280 --> 00:23:36,800
Speaker 1: that's a real danger. On the other hand, if you say,

488
00:23:37,000 --> 00:23:40,320
Speaker 1: the person who did this transgressive thing, this dangerous thing,

489
00:23:40,359 --> 00:23:43,639
Speaker 1: who posted this threat, I'm gonna identify them, that is

490
00:23:43,640 --> 00:23:46,720
Speaker 1: actually protecting people. Right. So the exact same activity I'm

491
00:23:46,720 --> 00:23:49,120
Speaker 1: gonna identify this person who's trying to hide can be

492
00:23:49,160 --> 00:23:51,320
Speaker 1: both very good or very bad. It can be very

493
00:23:51,400 --> 00:23:53,680
Speaker 1: much a positive that helps society, or can be very

494
00:23:53,680 --> 00:23:57,560
Speaker 1: negative because you're making somebody vulnerable. And so the logic

495
00:23:58,040 --> 00:24:00,520
Speaker 1: of what I think a lot of programmers tend towards,

496
00:24:00,600 --> 00:24:02,240
Speaker 1: like if you do this rule, you're bad. If you

497
00:24:02,280 --> 00:24:04,520
Speaker 1: follow this, if you break this rule, you're bad. It

498
00:24:04,560 --> 00:24:08,240
Speaker 1: ignores power, ignores the dynamics of society, and that's why

499
00:24:08,320 --> 00:24:11,840
Speaker 1: we keep bumping into what seemed like really obvious screw

500
00:24:11,960 --> 00:24:13,920
Speaker 1: ups in tech where we're like, how come we can't

501
00:24:13,920 --> 00:24:15,639
Speaker 1: make a civil place. It's like, you're not going to

502
00:24:15,720 --> 00:24:18,240
Speaker 1: be able to regulate human behavior with a single binary

503
00:24:18,240 --> 00:24:22,120
Speaker 1: set of rules. Let's talk a little bit about diversity

504
00:24:22,240 --> 00:24:26,080
Speaker 1: and inclusion. This is all over the You were way

505
00:24:26,119 --> 00:24:28,719
Speaker 1: way ahead of the curve on this. We have the

506
00:24:28,760 --> 00:24:32,520
Speaker 1: CEO of Uber being forced out. We have a number

507
00:24:32,560 --> 00:24:36,680
Speaker 1: of vcs having to step down either from the boards

508
00:24:36,680 --> 00:24:39,960
Speaker 1: that they serve on or from their own companies. Uh.

509
00:24:40,000 --> 00:24:45,119
Speaker 1: It looks like the broke culture in Silicon Valley is

510
00:24:45,800 --> 00:24:49,119
Speaker 1: coming to an end. UH, tell us a little bit

511
00:24:49,160 --> 00:24:53,320
Speaker 1: about your perspective on diversity and inclusion in the world

512
00:24:53,320 --> 00:24:56,120
Speaker 1: of technology. So there's definitely a moment of reckoning going

513
00:24:56,160 --> 00:24:58,680
Speaker 1: on right now. And for me, ten years ago, I

514
00:24:58,720 --> 00:25:00,520
Speaker 1: was just I had been in Silicon Value a couple

515
00:25:00,560 --> 00:25:02,600
Speaker 1: of years. Um, even though I've been in tech twenty years,

516
00:25:02,600 --> 00:25:05,400
Speaker 1: I've spent a couple of years. Because you're really uh

517
00:25:06,359 --> 00:25:08,320
Speaker 1: in New York. Yeah, yeah, so you when did you?

518
00:25:08,359 --> 00:25:09,960
Speaker 1: Were you here when we were they were doing six

519
00:25:09,960 --> 00:25:12,160
Speaker 1: apart and the company was growing. And I went out

520
00:25:12,359 --> 00:25:15,159
Speaker 1: to uh San Francisco in two thousand four and I

521
00:25:15,160 --> 00:25:19,000
Speaker 1: was there until two thousand seven. And really one of

522
00:25:19,040 --> 00:25:21,800
Speaker 1: the drivers for me of sort of being done with

523
00:25:21,880 --> 00:25:24,199
Speaker 1: being in Silicon Valley and being in San Francisco was

524
00:25:24,840 --> 00:25:28,520
Speaker 1: it felt so homogeneous and and yeah, it just you know, well,

525
00:25:28,720 --> 00:25:30,160
Speaker 1: I think I've been spoiled. I've been in New York.

526
00:25:30,200 --> 00:25:34,080
Speaker 1: I had worked in media publishing, where you are there's

527
00:25:34,119 --> 00:25:35,840
Speaker 1: so many and you know, and I had people that,

528
00:25:36,080 --> 00:25:38,320
Speaker 1: you know, there were friends that were outside of tech

529
00:25:38,359 --> 00:25:40,040
Speaker 1: and they were in other just ones that they could

530
00:25:40,040 --> 00:25:41,840
Speaker 1: be in fashion, they can be media, they can be

531
00:25:41,920 --> 00:25:44,520
Speaker 1: in in finance, whatever it was. And you just get

532
00:25:44,520 --> 00:25:47,440
Speaker 1: a different view of the world. And it was astonishing

533
00:25:47,440 --> 00:25:48,960
Speaker 1: to me. It's like, with all the problems that you know,

534
00:25:49,040 --> 00:25:52,040
Speaker 1: say the entertainment industry had, there was still much more

535
00:25:52,080 --> 00:25:56,000
Speaker 1: inclusive and much more diverse. And so to go into

536
00:25:56,200 --> 00:25:59,560
Speaker 1: conference rooms, boardrooms, meeting rooms in Silicon Valley and look

537
00:25:59,600 --> 00:26:02,120
Speaker 1: around and be like, essentially, this is just a bunch

538
00:26:02,119 --> 00:26:05,960
Speaker 1: of white and Asian guys and that doesn't count as diversity,

539
00:26:06,160 --> 00:26:08,080
Speaker 1: you know. Well, and it's interesting because it's it's it's

540
00:26:08,080 --> 00:26:12,399
Speaker 1: particularly complicated being Asian American, where we're overrepresented and you know,

541
00:26:12,480 --> 00:26:14,520
Speaker 1: like we over index were two percent of the population.

542
00:26:14,560 --> 00:26:18,119
Speaker 1: And yet you look at just Indian American you know,

543
00:26:18,359 --> 00:26:20,920
Speaker 1: people in tech, the CEO of Google, CEO of Microsoft,

544
00:26:21,000 --> 00:26:23,719
Speaker 1: CEO of Adobe, these are all Indian guys, it's like,

545
00:26:23,720 --> 00:26:27,000
Speaker 1: we're doing fine. And yet you know, like I said,

546
00:26:27,000 --> 00:26:30,680
Speaker 1: being in media, publishing, entertainment, I was like, I know

547
00:26:31,000 --> 00:26:33,080
Speaker 1: that there are black and Latino folks in California. You

548
00:26:33,119 --> 00:26:35,520
Speaker 1: can't tell me they're not there. And yet you go

549
00:26:35,560 --> 00:26:38,000
Speaker 1: to these offices and it wasn't just technical staff, it

550
00:26:38,119 --> 00:26:42,720
Speaker 1: was the legal staff, the marketing staff that you know, everything,

551
00:26:42,840 --> 00:26:45,720
Speaker 1: every one of these roles. The representation was way out

552
00:26:45,720 --> 00:26:48,520
Speaker 1: of whack to a point where you couldn't ignore it anymore.

553
00:26:48,680 --> 00:26:51,040
Speaker 1: The number that was in in one of your columns,

554
00:26:51,560 --> 00:26:58,920
Speaker 1: California's Hispanic population is uh the average percentage of employees

555
00:26:59,000 --> 00:27:01,879
Speaker 1: and tech companies head quartered there is less than five percent.

556
00:27:02,480 --> 00:27:05,960
Speaker 1: Google is three And if you look at the industry

557
00:27:06,040 --> 00:27:09,119
Speaker 1: average for women, it's only a third of employees and

558
00:27:09,200 --> 00:27:12,520
Speaker 1: women when more than half of the population of women, right,

559
00:27:12,640 --> 00:27:14,720
Speaker 1: and so so there's just this proportionality where you like,

560
00:27:14,840 --> 00:27:16,960
Speaker 1: at a certain point you can say, Okay, it's not

561
00:27:17,160 --> 00:27:20,840
Speaker 1: exactly match, of course not, but if you try, if

562
00:27:20,840 --> 00:27:23,480
Speaker 1: you take you said, well, we we looked at the

563
00:27:23,520 --> 00:27:25,840
Speaker 1: population and we could only find three percent of our

564
00:27:25,840 --> 00:27:28,159
Speaker 1: staff that could meet our requirements. I don't buy I

565
00:27:28,240 --> 00:27:30,040
Speaker 1: just don't buy it. Just the math doesn't add up.

566
00:27:30,080 --> 00:27:32,479
Speaker 1: Now that the pushback to that is, hey, you know

567
00:27:32,720 --> 00:27:37,960
Speaker 1: you mentioned India, huge technical training, engineering, mathematics science, UH,

568
00:27:38,080 --> 00:27:42,080
Speaker 1: Indian Institute of Technology, go down the list, just tremendous. UH.

569
00:27:42,119 --> 00:27:44,359
Speaker 1: And my other favorite stat is half of the C

570
00:27:44,560 --> 00:27:48,680
Speaker 1: suite and Silicon Valley are immigrants. So there's clearly some

571
00:27:48,800 --> 00:27:52,359
Speaker 1: recognition of meritocracy, at least in fear that's the ideal.

572
00:27:52,400 --> 00:27:54,360
Speaker 1: And I mean, I could not be more pro immigrant.

573
00:27:54,440 --> 00:27:56,919
Speaker 1: My parents are immigrants. They're here because you know, you know,

574
00:27:57,080 --> 00:27:59,920
Speaker 1: they were willing to do the work and get educated

575
00:28:00,000 --> 00:28:02,920
Speaker 1: and and and you know, I'm incredibly proud to be

576
00:28:03,320 --> 00:28:05,560
Speaker 1: in that you know, of that descent and in that tradition.

577
00:28:06,119 --> 00:28:08,840
Speaker 1: That being said, you look at the costs for paying

578
00:28:08,880 --> 00:28:10,960
Speaker 1: for an H one B, for paying for the lawyers

579
00:28:10,960 --> 00:28:12,560
Speaker 1: to bring somebody over here, for paying for all these

580
00:28:12,560 --> 00:28:14,960
Speaker 1: things to bring those workers over here is a huge

581
00:28:15,000 --> 00:28:18,520
Speaker 1: investment for these companies, huge And for the same amount

582
00:28:18,560 --> 00:28:21,240
Speaker 1: of money, you could train workers here and they're not

583
00:28:21,600 --> 00:28:24,359
Speaker 1: and you could train people from the underrepresented communities. So

584
00:28:24,440 --> 00:28:27,920
Speaker 1: what's the thinking that's a sure thing and training them

585
00:28:28,000 --> 00:28:29,720
Speaker 1: is a risk? You know, well, I think there's a

586
00:28:29,720 --> 00:28:31,720
Speaker 1: lot of factors. I think one of them is, you know,

587
00:28:31,840 --> 00:28:35,080
Speaker 1: h one B workers can never organize or really complain

588
00:28:35,240 --> 00:28:38,080
Speaker 1: because if you you know, essentially, if you get too

589
00:28:38,160 --> 00:28:41,240
Speaker 1: up at you lose your job, you get deported, and

590
00:28:41,240 --> 00:28:43,200
Speaker 1: then you're not sending money back to your family, to

591
00:28:43,240 --> 00:28:45,320
Speaker 1: your village or whatever else. So the amount of leverage

592
00:28:45,360 --> 00:28:49,000
Speaker 1: they have over these workers is incredible. UM. I have

593
00:28:49,120 --> 00:28:51,320
Speaker 1: to think that's a factor, you know, you look at

594
00:28:51,360 --> 00:28:54,160
Speaker 1: particularly in the case of like there was UM this

595
00:28:54,280 --> 00:28:58,120
Speaker 1: collusion orchestrated by Steve Jobs and and and Eric Google

596
00:28:58,240 --> 00:29:01,800
Speaker 1: Apple for you of the biggest techn companies, everybody exceptally

597
00:29:01,880 --> 00:29:05,600
Speaker 1: essentially except for Facebook, UM colluded against their own workers

598
00:29:05,880 --> 00:29:07,760
Speaker 1: right to depress their wages by saying we're not going

599
00:29:07,840 --> 00:29:11,440
Speaker 1: to poach each other's workers and UM, which is still

600
00:29:11,640 --> 00:29:15,320
Speaker 1: astonishing to me. And if there was almost no ramification,

601
00:29:15,360 --> 00:29:17,280
Speaker 1: this is an amazing thing. Is the workers Like there

602
00:29:17,320 --> 00:29:19,640
Speaker 1: was a sort of obligatory lawsuit. I think it was

603
00:29:19,680 --> 00:29:21,480
Speaker 1: for eight billion dollars or something. They settled it for

604
00:29:21,520 --> 00:29:26,400
Speaker 1: a tiny pittance that which and you know the people

605
00:29:26,440 --> 00:29:28,280
Speaker 1: at Apple who went through this. I talked to people

606
00:29:28,320 --> 00:29:29,680
Speaker 1: that work there and they were like, yeah, I still

607
00:29:29,720 --> 00:29:31,400
Speaker 1: just really love and Revere, Steve, and I'm like, the

608
00:29:31,480 --> 00:29:34,000
Speaker 1: guy took money out of your kids college funds and

609
00:29:34,040 --> 00:29:36,120
Speaker 1: you're like, it seems like a nice guy. Like what

610
00:29:36,200 --> 00:29:38,440
Speaker 1: would you have to do for you to be like,

611
00:29:38,480 --> 00:29:40,480
Speaker 1: I'm not gonna, you know, fall along with this. You'd

612
00:29:40,520 --> 00:29:43,840
Speaker 1: have to remove the headphone jack from that is a

613
00:29:43,880 --> 00:29:47,080
Speaker 1: bridge too far, right, That's the line. And what you realize,

614
00:29:47,160 --> 00:29:49,920
Speaker 1: what you realize is, you know, when there's that reverence

615
00:29:49,960 --> 00:29:51,479
Speaker 1: to they're like, who am I to complaint? I am

616
00:29:51,520 --> 00:29:53,640
Speaker 1: getting a good salary, I am being paid well. And

617
00:29:53,640 --> 00:29:55,560
Speaker 1: what they don't see is common cause with those H

618
00:29:55,560 --> 00:29:58,320
Speaker 1: one B workers or common cause with the you know

619
00:29:58,360 --> 00:30:01,800
Speaker 1: the contractors, I say contractors and quotes who are providing

620
00:30:01,800 --> 00:30:05,840
Speaker 1: the meals, driving the shuttles to the office and giving

621
00:30:05,840 --> 00:30:08,120
Speaker 1: them a free massages. All those things are presented as

622
00:30:08,160 --> 00:30:09,760
Speaker 1: perks or you get free lunch, you get these things

623
00:30:09,800 --> 00:30:12,440
Speaker 1: like therese are people are workers and they never get

624
00:30:12,480 --> 00:30:15,400
Speaker 1: equity in these companies. And so we realize that there's

625
00:30:15,440 --> 00:30:18,040
Speaker 1: this sort of you know, this class system built in

626
00:30:18,240 --> 00:30:20,800
Speaker 1: that um and I'm just a big believer in like,

627
00:30:20,840 --> 00:30:23,160
Speaker 1: you got to treat your people well and they certainly

628
00:30:23,200 --> 00:30:25,280
Speaker 1: have the money to do it, and they didn't need

629
00:30:25,360 --> 00:30:27,240
Speaker 1: to nickel and dime their workers they did. That's kind

630
00:30:27,240 --> 00:30:29,120
Speaker 1: of odds because there was no reason they have more

631
00:30:29,160 --> 00:30:32,040
Speaker 1: cash than all these companies and more cash I have

632
00:30:32,120 --> 00:30:34,280
Speaker 1: to point out that the only reason Facebook did not

633
00:30:34,400 --> 00:30:37,360
Speaker 1: participate in it is a they were too young for

634
00:30:37,600 --> 00:30:40,480
Speaker 1: that deal was originally made, and be they were busy

635
00:30:40,560 --> 00:30:43,880
Speaker 1: rating Google for some of their favorite engineers. So as

636
00:30:43,880 --> 00:30:46,239
Speaker 1: well as Apple. Let's talk a little bit about what

637
00:30:46,240 --> 00:30:50,040
Speaker 1: fog Creek is doing before we have you repair Twitter.

638
00:30:50,600 --> 00:30:53,080
Speaker 1: Tell me what tell us about glitch and some of

639
00:30:53,120 --> 00:30:56,440
Speaker 1: the other products. Creek Creek is a very storied company,

640
00:30:56,480 --> 00:30:59,280
Speaker 1: has been around seventeen years. Brilliant co founders Joe Spoilsky,

641
00:30:59,400 --> 00:31:01,920
Speaker 1: Michael Prior and what they always wanted to build one

642
00:31:02,000 --> 00:31:04,239
Speaker 1: a great place for like people who want to make

643
00:31:04,280 --> 00:31:06,680
Speaker 1: the most interesting technology to come work. And it's been

644
00:31:06,680 --> 00:31:09,320
Speaker 1: a very influential company that has spun out. They co

645
00:31:09,440 --> 00:31:12,040
Speaker 1: created stack overflow, which is a community that pretty much

646
00:31:12,040 --> 00:31:14,280
Speaker 1: every code in the world uses to answer the questions

647
00:31:14,280 --> 00:31:18,280
Speaker 1: about programming. Did that eventually become like a white labeled

648
00:31:18,360 --> 00:31:19,960
Speaker 1: version where if you want to set up your own

649
00:31:19,960 --> 00:31:22,760
Speaker 1: internal Q and a UM you you can do that. Yeah,

650
00:31:22,800 --> 00:31:25,120
Speaker 1: for sure a sacriflow has has an enterprise product for that.

651
00:31:25,160 --> 00:31:26,480
Speaker 1: I'm I'm just on the board of Stacks, so I

652
00:31:26,480 --> 00:31:28,480
Speaker 1: get to see a lot of what they're doing. And

653
00:31:28,480 --> 00:31:30,120
Speaker 1: and the bigger thing to me is you have this

654
00:31:30,160 --> 00:31:33,160
Speaker 1: community where tens of millions of coders around the world

655
00:31:33,560 --> 00:31:36,600
Speaker 1: come and answer each other's questions in this really collaborative way.

656
00:31:37,240 --> 00:31:42,560
Speaker 1: Um and and interestingly, it's a very you know, reassuring, nurturing,

657
00:31:42,560 --> 00:31:47,200
Speaker 1: supportive environment. People really get answers right away, problems or

658
00:31:47,480 --> 00:31:49,920
Speaker 1: no and you know, like I think historically the one

659
00:31:49,960 --> 00:31:52,240
Speaker 1: of the biggest challenges was they weren't probably friendly enough

660
00:31:52,240 --> 00:31:53,840
Speaker 1: to newbies because they were like, you have to phrase

661
00:31:53,880 --> 00:31:55,360
Speaker 1: your question the right way and it has to be

662
00:31:55,440 --> 00:31:57,560
Speaker 1: you know, exactly right. I think that's starting to ease

663
00:31:57,640 --> 00:31:59,040
Speaker 1: up a little bit, is the sort of you know,

664
00:31:59,080 --> 00:32:01,320
Speaker 1: the community evolves in being more welcoming. But the key

665
00:32:01,360 --> 00:32:04,560
Speaker 1: thing is there's never been wide scale harassment. There's never

666
00:32:04,640 --> 00:32:06,400
Speaker 1: really wide scale abuse. And that's what the site that

667
00:32:06,520 --> 00:32:09,000
Speaker 1: is probably in the top forty websites in the world

668
00:32:09,040 --> 00:32:11,120
Speaker 1: in terms of traffic. So it's possible to make a

669
00:32:11,160 --> 00:32:13,920
Speaker 1: large site that works well. So so Stack was co

670
00:32:14,040 --> 00:32:15,959
Speaker 1: created with the Jeff Atwood and his team, and that's

671
00:32:15,960 --> 00:32:18,200
Speaker 1: spun out. It's an independent company. H They made a

672
00:32:18,240 --> 00:32:20,719
Speaker 1: project management tool, Trelloh, which lots of people use. It's

673
00:32:20,760 --> 00:32:23,520
Speaker 1: really popular, and that spun out and last thing about that.

674
00:32:23,760 --> 00:32:26,760
Speaker 1: So there's this track record of making these wildly successful products.

675
00:32:27,440 --> 00:32:31,040
Speaker 1: And you know, I they approached me about taking over

676
00:32:31,080 --> 00:32:32,960
Speaker 1: the CEO last year and I said, well, you know

677
00:32:33,000 --> 00:32:35,480
Speaker 1: what's what's coming down the pipe. And I saw what

678
00:32:35,720 --> 00:32:38,320
Speaker 1: became Glitch that we launched earlier this year, and I

679
00:32:38,400 --> 00:32:40,320
Speaker 1: was just blown away. I think it's one of the

680
00:32:40,360 --> 00:32:43,600
Speaker 1: most revolutionary products I've seen in my life, like in

681
00:32:43,600 --> 00:32:48,800
Speaker 1: my whole co text. And so what glitches is very simply,

682
00:32:48,840 --> 00:32:51,040
Speaker 1: it's a it's a programming environment where you can go

683
00:32:51,080 --> 00:32:53,840
Speaker 1: and write code. Um and there's a couple of things

684
00:32:53,880 --> 00:32:56,440
Speaker 1: that does that nobody has done before. The first is

685
00:32:56,640 --> 00:32:59,800
Speaker 1: as you type, it's automatically taking the code you're writing,

686
00:32:59,800 --> 00:33:02,240
Speaker 1: the that you're creating and publishing it live to the web.

687
00:33:03,000 --> 00:33:05,800
Speaker 1: That sounds trivial, but that's you know, you take entire

688
00:33:05,840 --> 00:33:10,840
Speaker 1: businesses like Amazon's web services hosting business or Hiroku, which

689
00:33:11,000 --> 00:33:13,720
Speaker 1: is sort of beloved by coders, and the whole process

690
00:33:13,720 --> 00:33:16,120
Speaker 1: of getting an app live onto the web is really hard.

691
00:33:16,160 --> 00:33:19,120
Speaker 1: It's become very complicated. To do it completely automatically in

692
00:33:19,160 --> 00:33:22,160
Speaker 1: the background is a radical change. So is this an app?

693
00:33:22,200 --> 00:33:24,000
Speaker 1: When when we talk about apps, I think about the

694
00:33:24,000 --> 00:33:26,240
Speaker 1: app store in the Android stores right now web app

695
00:33:26,280 --> 00:33:27,840
Speaker 1: So this is things that you go to in your browsers.

696
00:33:27,840 --> 00:33:29,120
Speaker 1: So if you want to make a little, you know,

697
00:33:29,400 --> 00:33:31,520
Speaker 1: a simple app for your business, you're gonna make an

698
00:33:31,520 --> 00:33:33,400
Speaker 1: expensing app for your your team to use, or you

699
00:33:33,520 --> 00:33:35,240
Speaker 1: make it to do list app or something like that.

700
00:33:35,480 --> 00:33:37,520
Speaker 1: It can be as complicated as you want. But the

701
00:33:37,520 --> 00:33:39,360
Speaker 1: problem is that process of like even if you know

702
00:33:39,440 --> 00:33:41,360
Speaker 1: how to write the code and you've built that whole

703
00:33:41,360 --> 00:33:44,840
Speaker 1: thing yourself, just getting it onto the web was a

704
00:33:44,880 --> 00:33:46,920
Speaker 1: lot of work and it was just a pain. So

705
00:33:46,960 --> 00:33:48,760
Speaker 1: we took all that away and that was step one.

706
00:33:49,240 --> 00:33:52,160
Speaker 1: Step two was your entire coding environment. Everything just lives

707
00:33:52,160 --> 00:33:53,920
Speaker 1: in the browser. And that's easier for the same reason

708
00:33:53,920 --> 00:33:56,080
Speaker 1: that like you'd like to use Gmail instead of having

709
00:33:56,360 --> 00:33:58,640
Speaker 1: a mail app on your on your computers, like it's

710
00:33:58,680 --> 00:34:01,400
Speaker 1: just there, whatever computer log into all my stuff is there.

711
00:34:02,240 --> 00:34:05,880
Speaker 1: Those alone were a big leap forward. The biggest things

712
00:34:05,880 --> 00:34:07,479
Speaker 1: that happened the two things that sort of came out

713
00:34:07,480 --> 00:34:10,279
Speaker 1: earliest year was the first is we made almost an

714
00:34:10,280 --> 00:34:12,440
Speaker 1: app store, a catalog of all the different apps people

715
00:34:12,440 --> 00:34:14,760
Speaker 1: have built, and you can remix any of them. So

716
00:34:14,760 --> 00:34:16,440
Speaker 1: I say, somebody already made it to do list app

717
00:34:16,480 --> 00:34:17,759
Speaker 1: and you say, well that's nice, but I want to

718
00:34:17,800 --> 00:34:19,880
Speaker 1: be blue instead of green. You go in there, you

719
00:34:20,000 --> 00:34:22,080
Speaker 1: edit it. That's instantly, years you can remix it, do

720
00:34:22,080 --> 00:34:23,840
Speaker 1: whatever you want to with it. So it's really the

721
00:34:23,880 --> 00:34:25,719
Speaker 1: power the promise of open source that we've had for

722
00:34:25,760 --> 00:34:28,520
Speaker 1: many years. And then the thing that blew my mind

723
00:34:28,560 --> 00:34:31,319
Speaker 1: when I saw the team had built it was you

724
00:34:31,360 --> 00:34:33,720
Speaker 1: can edit this code in real time with other people.

725
00:34:34,120 --> 00:34:36,000
Speaker 1: So like Google Docs. I was about to say, that

726
00:34:36,080 --> 00:34:38,880
Speaker 1: makes me think of Google Docs, but for application exactly

727
00:34:39,719 --> 00:34:43,279
Speaker 1: applications that's exactly it. So nobody has made that kind

728
00:34:43,320 --> 00:34:47,640
Speaker 1: of powerful real programming environment that that is multiplayer. What's

729
00:34:47,680 --> 00:34:49,760
Speaker 1: the business model on this? You're selling it to enterprise.

730
00:34:49,840 --> 00:34:52,399
Speaker 1: There's there's a couple parts to it. Um. The first

731
00:34:52,400 --> 00:34:55,600
Speaker 1: thing we're doing is um incidental to the fact that

732
00:34:55,640 --> 00:34:57,560
Speaker 1: you can code at the same time as other people,

733
00:34:57,840 --> 00:35:00,320
Speaker 1: which is an incredible learning tool, teaching tool because you

734
00:35:00,320 --> 00:35:02,399
Speaker 1: can help people. So right now, all of the big

735
00:35:02,400 --> 00:35:05,680
Speaker 1: companies have what they call their APIs Application Programming Interface,

736
00:35:05,719 --> 00:35:07,800
Speaker 1: and this is the way that you build services on

737
00:35:07,920 --> 00:35:10,840
Speaker 1: top of Stripe for payments, or Twilio for messages, or

738
00:35:11,280 --> 00:35:15,080
Speaker 1: um Twitter for sending messages obviously and um but it's

739
00:35:15,080 --> 00:35:17,399
Speaker 1: really hard for them to get developers to try out

740
00:35:17,400 --> 00:35:19,400
Speaker 1: their tools. So if you say, we have a new

741
00:35:19,440 --> 00:35:21,680
Speaker 1: developer platform and we want people to use it. For example,

742
00:35:21,840 --> 00:35:24,560
Speaker 1: Amazon has skills for the Alexa, you want to make

743
00:35:24,600 --> 00:35:27,120
Speaker 1: new commands that work there. Where Slack has bots in

744
00:35:27,160 --> 00:35:29,920
Speaker 1: their messaging app. They're desperate to be just added a

745
00:35:29,960 --> 00:35:34,480
Speaker 1: whole bunch of slack bots and the birthdays and it's

746
00:35:34,520 --> 00:35:36,239
Speaker 1: just really interesting. Now you see that and you're like, wow,

747
00:35:36,280 --> 00:35:38,120
Speaker 1: I wish it would talk to this other system we're using,

748
00:35:38,719 --> 00:35:41,000
Speaker 1: Like I can never do that, that's too hard. The

749
00:35:41,120 --> 00:35:44,520
Speaker 1: process with glitch now is we've got a sample slack

750
00:35:44,600 --> 00:35:46,560
Speaker 1: bot for you. You go and your remix it. You

751
00:35:46,640 --> 00:35:48,400
Speaker 1: change the part that just works for your system to

752
00:35:48,400 --> 00:35:50,600
Speaker 1: be exactly what you wanted to be, and it's instantly

753
00:35:50,680 --> 00:35:52,880
Speaker 1: up and running. So we take the time to develop

754
00:35:52,920 --> 00:35:56,160
Speaker 1: a slack bot or Alexa skill from uh days or

755
00:35:56,239 --> 00:35:59,640
Speaker 1: hours in two minutes, and that is something that's a

756
00:35:59,719 --> 00:36:02,000
Speaker 1: normal value. All these companies of shots platforms, so they

757
00:36:02,120 --> 00:36:04,399
Speaker 1: want to use it um and be able to pay

758
00:36:04,480 --> 00:36:05,880
Speaker 1: to do a couple of different things. The key one

759
00:36:05,920 --> 00:36:08,520
Speaker 1: is supporting developers creating these things. So right now, if

760
00:36:08,520 --> 00:36:10,640
Speaker 1: you're like, I want to build on you know, Alexa's

761
00:36:10,920 --> 00:36:13,600
Speaker 1: skill set from Amazon, so it's Amazon buying this or

762
00:36:13,800 --> 00:36:17,160
Speaker 1: or Twitter buying this, not necessarily an enterprise company to

763
00:36:17,760 --> 00:36:21,800
Speaker 1: create their own unique Everybody's desperate to make things easier

764
00:36:21,840 --> 00:36:24,359
Speaker 1: for developers because developers are so in demand and it's

765
00:36:24,400 --> 00:36:26,120
Speaker 1: so rare to get them and pay attention to your platform.

766
00:36:26,160 --> 00:36:28,080
Speaker 1: And I look at it. There's a search tool called

767
00:36:28,120 --> 00:36:30,000
Speaker 1: Algolia that I just love. It was one of those

768
00:36:30,239 --> 00:36:33,080
Speaker 1: searchers really hard to do well, Like, I'm not Google,

769
00:36:33,120 --> 00:36:34,880
Speaker 1: I'm not going to figure this thing out. I had

770
00:36:34,920 --> 00:36:37,600
Speaker 1: always been interested in trying it, and I thought I

771
00:36:37,760 --> 00:36:40,200
Speaker 1: have if I could tie that search feature into my app,

772
00:36:40,239 --> 00:36:42,640
Speaker 1: would be really useful. And I was like, but you know,

773
00:36:42,680 --> 00:36:44,480
Speaker 1: I'm running a company. I'm busy. I don't have time

774
00:36:44,520 --> 00:36:45,800
Speaker 1: to learn all this stuff. Even if I got a

775
00:36:45,840 --> 00:36:48,920
Speaker 1: little bit of coding skills. Now I can go remix

776
00:36:48,960 --> 00:36:51,800
Speaker 1: an example out from Algolia that already has search working.

777
00:36:52,440 --> 00:36:54,000
Speaker 1: Just plug in the parts that I want to into

778
00:36:54,040 --> 00:36:55,880
Speaker 1: my own app and be up and running instantly. That

779
00:36:56,080 --> 00:36:58,160
Speaker 1: was something where I was like, it took it from

780
00:36:58,440 --> 00:36:59,800
Speaker 1: it would be cool to try this out. I have

781
00:36:59,880 --> 00:37:02,600
Speaker 1: this intent of learning this programming skill into I can

782
00:37:02,680 --> 00:37:05,560
Speaker 1: deploy it instantly. And the biggest thing I see is

783
00:37:05,920 --> 00:37:08,680
Speaker 1: the coders who we show it too, like their eyes

784
00:37:08,760 --> 00:37:10,560
Speaker 1: light up, like it looks like Christmas morning for them,

785
00:37:10,600 --> 00:37:12,560
Speaker 1: And I'm like, that is a really good sign that

786
00:37:12,640 --> 00:37:15,040
Speaker 1: we were on something something big with glitch. So that

787
00:37:15,160 --> 00:37:18,919
Speaker 1: sounds really fascinating. You you mentioned Twitter earlier. Let's let's

788
00:37:18,960 --> 00:37:23,279
Speaker 1: talk about what you would do to fix Twitter. I've

789
00:37:23,320 --> 00:37:26,640
Speaker 1: been amazed that they while there have been a series

790
00:37:26,680 --> 00:37:30,200
Speaker 1: of updates and they continue to improve the interface and

791
00:37:30,320 --> 00:37:34,120
Speaker 1: some of the general behaviors, the broader concept behind the community,

792
00:37:34,360 --> 00:37:36,960
Speaker 1: they just can't seem to wrap their their heads around.

793
00:37:37,040 --> 00:37:39,719
Speaker 1: It's a hard thing. And I do have a lot

794
00:37:39,800 --> 00:37:41,680
Speaker 1: of empathy for the team. I do think they're trying,

795
00:37:41,840 --> 00:37:44,320
Speaker 1: but I think, you know, it was so long for

796
00:37:44,400 --> 00:37:46,920
Speaker 1: them to turn the ship around to really addressing a

797
00:37:47,000 --> 00:37:49,000
Speaker 1: lot of the issues that that's the question. Believe in it.

798
00:37:49,200 --> 00:37:51,200
Speaker 1: Why why did it take so long? For them to

799
00:37:51,360 --> 00:37:54,480
Speaker 1: notice that they had a giant harassment problem. You know,

800
00:37:54,640 --> 00:37:57,080
Speaker 1: I think there's a there's a lot of reasons for that.

801
00:37:57,280 --> 00:38:01,839
Speaker 1: I am one of the key issues is um who

802
00:38:01,920 --> 00:38:04,360
Speaker 1: feels the pain? Right? So we talked about the inclusion

803
00:38:04,360 --> 00:38:07,560
Speaker 1: in diversity issue and tech and you know, Twitter is

804
00:38:07,640 --> 00:38:09,480
Speaker 1: like most of the tech companies, it doesn't have a

805
00:38:09,560 --> 00:38:12,280
Speaker 1: lot of people from you know, black and Latino communities,

806
00:38:12,320 --> 00:38:14,560
Speaker 1: doesn't have as many women. And guess who gets targeted

807
00:38:14,600 --> 00:38:18,560
Speaker 1: by the majority of harassment online. See, I haven't let

808
00:38:18,640 --> 00:38:20,440
Speaker 1: me stop you there, because as a white dude in

809
00:38:20,440 --> 00:38:25,040
Speaker 1: New York City, perhaps I'm not experiencing the same thing. However,

810
00:38:25,360 --> 00:38:28,399
Speaker 1: and I'm kind of thick skinned. I'm more annoyed by

811
00:38:28,480 --> 00:38:34,279
Speaker 1: the failed logical deduction people calling me ugly. But what

812
00:38:34,440 --> 00:38:38,120
Speaker 1: I I'm amazed at is and I'm I'm I'm seeing

813
00:38:38,680 --> 00:38:43,920
Speaker 1: all this harassment mostly on a partisan basis, name calling

814
00:38:44,000 --> 00:38:48,759
Speaker 1: and stupidity, just craziness, which I think discourages knew you. Oh,

815
00:38:48,800 --> 00:38:52,359
Speaker 1: I don't want to go ye absolutely, And so it's

816
00:38:52,400 --> 00:38:56,160
Speaker 1: a little moderate in Facebook because people have to use

817
00:38:56,520 --> 00:38:59,480
Speaker 1: theoretically are using their real names or otherwise I have

818
00:38:59,520 --> 00:39:01,480
Speaker 1: to go through hope process of creating a fake name.

819
00:39:01,560 --> 00:39:04,120
Speaker 1: And I know people certainly do that, but but there's

820
00:39:04,160 --> 00:39:07,319
Speaker 1: some barriers, right, it's harder to do. So what would

821
00:39:07,360 --> 00:39:10,080
Speaker 1: you do to fix fixed Twitter? Yeah, there are a

822
00:39:10,080 --> 00:39:12,320
Speaker 1: couple of things. I actually wrote a piece back in

823
00:39:12,960 --> 00:39:16,600
Speaker 1: January one Jack Dorsey asked, I guess the whole internet, like,

824
00:39:16,880 --> 00:39:18,960
Speaker 1: how would you how would you fix Twitter? And there

825
00:39:19,000 --> 00:39:21,000
Speaker 1: were a couple of things I wrote in there, and um,

826
00:39:21,360 --> 00:39:24,719
Speaker 1: the more cogent ones. One of them which was, um,

827
00:39:26,400 --> 00:39:28,239
Speaker 1: show people you know how to update the service and

828
00:39:28,320 --> 00:39:31,440
Speaker 1: update the apps. Just the ability to iterate and introduce

829
00:39:31,520 --> 00:39:34,400
Speaker 1: new things would introduce a lot of trust into the platform.

830
00:39:34,440 --> 00:39:37,040
Speaker 1: Because they hadn't shipped any features, they hadn't updated anything,

831
00:39:37,280 --> 00:39:39,360
Speaker 1: so you can make whatever proclamations you want to about

832
00:39:39,360 --> 00:39:42,440
Speaker 1: we're fixing abuse, for fixing harrassment, we're adding better features

833
00:39:42,560 --> 00:39:45,160
Speaker 1: or filtering or whatever, and people don't believe it because like, well,

834
00:39:45,200 --> 00:39:47,239
Speaker 1: the thing hasn't changed at all in a long time,

835
00:39:47,680 --> 00:39:49,560
Speaker 1: you know. And in fact, they were killing off things

836
00:39:49,640 --> 00:39:52,120
Speaker 1: like vine that was really great and creative and interesting

837
00:39:52,200 --> 00:39:55,680
Speaker 1: and didn't have harassment problem. And and you know, she said, okay,

838
00:39:55,680 --> 00:39:57,719
Speaker 1: well these these things that make you feel good, and

839
00:39:57,800 --> 00:40:00,279
Speaker 1: those are getting killed and the things that are making

840
00:40:00,280 --> 00:40:02,480
Speaker 1: me feel terrible. You're you're you know, doubling down on

841
00:40:02,920 --> 00:40:04,480
Speaker 1: So what I think they've gotten better at that they've

842
00:40:04,520 --> 00:40:06,520
Speaker 1: sort of started shipping more too, is to sort of

843
00:40:07,160 --> 00:40:09,880
Speaker 1: be really clear about a harassment policy. So instead of

844
00:40:09,920 --> 00:40:12,080
Speaker 1: these nebulous, vague rules like we have to see like

845
00:40:12,160 --> 00:40:16,160
Speaker 1: this person who's very obviously transgressing, being abusive and horrible

846
00:40:16,200 --> 00:40:19,160
Speaker 1: to people, Um, we got to see their account gets suspended.

847
00:40:19,840 --> 00:40:21,640
Speaker 1: That that happened not too long ago. I forgot his

848
00:40:21,760 --> 00:40:30,280
Speaker 1: name is a fairly milos Yanna Pulosolis, right, notorious troll

849
00:40:30,560 --> 00:40:34,480
Speaker 1: and harasser. And he finally again you have to go

850
00:40:34,719 --> 00:40:38,920
Speaker 1: so far, so repeatedly before your account. Is not not

851
00:40:39,080 --> 00:40:41,880
Speaker 1: just that that he transgressed so frequently, so often that

852
00:40:42,000 --> 00:40:44,319
Speaker 1: he was openly explicit about the fact he was trying

853
00:40:44,360 --> 00:40:46,640
Speaker 1: to harass people, right, you know, and like these are

854
00:40:46,640 --> 00:40:50,600
Speaker 1: the things where it's like this is a um, but

855
00:40:50,719 --> 00:40:53,359
Speaker 1: the fact that he stands out as as someone who's

856
00:40:53,440 --> 00:40:56,960
Speaker 1: banned and there isn't. First of all, there's a boatload

857
00:40:57,040 --> 00:41:00,040
Speaker 1: of bots just insane anounza. I assume half might it

858
00:41:00,120 --> 00:41:03,200
Speaker 1: or followers or software al goes and then on top

859
00:41:03,239 --> 00:41:05,640
Speaker 1: of that, it seems that there are some people that

860
00:41:05,760 --> 00:41:09,520
Speaker 1: are just you know, calls to violence and just all

861
00:41:09,600 --> 00:41:12,960
Speaker 1: sorts of like how do they tolerate this? I think

862
00:41:13,000 --> 00:41:14,360
Speaker 1: one of the things it's easy to lose track of

863
00:41:14,400 --> 00:41:16,920
Speaker 1: outside of Silicon Valley is how extreme they are about

864
00:41:17,000 --> 00:41:20,359
Speaker 1: some of some parts of libertarianism around these views. Right,

865
00:41:20,400 --> 00:41:23,480
Speaker 1: so they're very like everything is free speech, everything is

866
00:41:23,480 --> 00:41:25,640
Speaker 1: fair you know, fair game to put no one saying

867
00:41:25,719 --> 00:41:28,160
Speaker 1: you you can't do this. But we're a private company,

868
00:41:28,800 --> 00:41:31,239
Speaker 1: this is our product, and you could go do this

869
00:41:31,320 --> 00:41:34,640
Speaker 1: house free. You're free to be obnoxious and offense of

870
00:41:34,719 --> 00:41:38,239
Speaker 1: wherever you want, just not in our private community. Well,

871
00:41:38,280 --> 00:41:40,000
Speaker 1: the interesting thing, I think there's a couple of parts

872
00:41:40,040 --> 00:41:42,200
Speaker 1: they sort of ignore, one of which is, you know,

873
00:41:42,440 --> 00:41:44,680
Speaker 1: the argument there's often the argument that technically it's too

874
00:41:44,719 --> 00:41:46,880
Speaker 1: hard to limit these things. They say, well listen, and

875
00:41:46,920 --> 00:41:49,200
Speaker 1: I say listen, you know, go ahead and upload a

876
00:41:49,200 --> 00:41:52,719
Speaker 1: Beyonce MP MP three. Quickly they can detect that. So

877
00:41:52,800 --> 00:41:55,920
Speaker 1: like the tech is there, Right, it's not harder to

878
00:41:56,040 --> 00:42:00,319
Speaker 1: detect you know, a sound signature and a song than

879
00:42:00,400 --> 00:42:03,200
Speaker 1: it is text. Right, this is a racial epic. A

880
00:42:03,280 --> 00:42:07,520
Speaker 1: key phrases. Here's I mean especially in the machine learning

881
00:42:07,600 --> 00:42:10,239
Speaker 1: is making leaps and bounds in advancements like that can

882
00:42:10,280 --> 00:42:12,120
Speaker 1: be something where you can get better at a I

883
00:42:12,160 --> 00:42:13,960
Speaker 1: should really be all over And I think that is

884
00:42:14,080 --> 00:42:16,160
Speaker 1: starting to seep into Twitter a little bit. They're getting

885
00:42:16,160 --> 00:42:18,440
Speaker 1: a little bit better at hiding and flagging things. Um.

886
00:42:18,600 --> 00:42:20,200
Speaker 1: And it's hard to say, but that's part of this.

887
00:42:20,280 --> 00:42:22,680
Speaker 1: They need to communicate clearly about it. The The other

888
00:42:22,800 --> 00:42:25,920
Speaker 1: part is, um, you know, we always talk about the

889
00:42:25,920 --> 00:42:28,160
Speaker 1: free speech for the people who are harassing and abusing,

890
00:42:28,280 --> 00:42:31,200
Speaker 1: but what they do is they chase off vulnerable voices,

891
00:42:31,239 --> 00:42:32,759
Speaker 1: and what about the free speech and the people who

892
00:42:32,800 --> 00:42:36,360
Speaker 1: are exactly And I see this where like you know,

893
00:42:36,480 --> 00:42:39,839
Speaker 1: I have extremely thick skin. I am a loudmouth all

894
00:42:39,880 --> 00:42:42,279
Speaker 1: the time, so like I'm I'm pretty hard to shut up.

895
00:42:42,800 --> 00:42:44,880
Speaker 1: There are times when you get to the worst of them,

896
00:42:45,120 --> 00:42:48,320
Speaker 1: you know, a mob of people coming after you and

897
00:42:48,480 --> 00:42:51,759
Speaker 1: they're you know, targeting you, your friends, your family, your coworkers,

898
00:42:52,360 --> 00:42:54,279
Speaker 1: and you just say enough, I'm gonna put this away.

899
00:42:54,360 --> 00:42:55,960
Speaker 1: And like, if I can go through that with all

900
00:42:56,440 --> 00:42:58,680
Speaker 1: as fortunate and privilege as I am, with as much

901
00:42:58,719 --> 00:43:00,759
Speaker 1: of a network as I have to be able to

902
00:43:00,800 --> 00:43:03,799
Speaker 1: be like, sometimes it's too much. People who aren't as

903
00:43:03,880 --> 00:43:06,040
Speaker 1: lucky as I am and don't have that support network

904
00:43:06,080 --> 00:43:09,360
Speaker 1: behind them can easily be hounded out off of this network.

905
00:43:09,480 --> 00:43:11,600
Speaker 1: And it's like their speech matters too. And I care

906
00:43:11,640 --> 00:43:14,960
Speaker 1: a lot more about the people who are targeted, you know,

907
00:43:15,600 --> 00:43:17,680
Speaker 1: fairly for harassment. I care a lot more about their

908
00:43:17,719 --> 00:43:19,960
Speaker 1: free speech than the people who are saying horrible things

909
00:43:20,000 --> 00:43:22,760
Speaker 1: to them. We have been speaking to a Neil Dash

910
00:43:23,080 --> 00:43:27,440
Speaker 1: of fog Creek Software. If you enjoy this conversation, be

911
00:43:27,520 --> 00:43:30,320
Speaker 1: sure and stick around for the podcast extras, where we

912
00:43:30,480 --> 00:43:33,799
Speaker 1: keep the tape running and continue to discuss all things technology.

913
00:43:34,400 --> 00:43:37,680
Speaker 1: Be sure to check out my daily column on Bloomberg

914
00:43:37,880 --> 00:43:42,440
Speaker 1: View dot com. We love your comments, feedback and suggestions

915
00:43:43,120 --> 00:43:46,839
Speaker 1: right to us at m IB podcast at Bloomberg dot net.

916
00:43:47,360 --> 00:43:50,319
Speaker 1: You can follow me on Twitter at rid Holts. I'm

917
00:43:50,400 --> 00:43:53,400
Speaker 1: Barry rid Holts. You're listening to Masters in Business on

918
00:43:53,480 --> 00:44:08,920
Speaker 1: Bloomberg Radio. Welcome to the podcast, and Neil, thank you

919
00:44:09,040 --> 00:44:11,000
Speaker 1: for doing this and appreciate you being for so so

920
00:44:11,200 --> 00:44:14,160
Speaker 1: generous with your time. Happy to be here. We we

921
00:44:14,280 --> 00:44:19,080
Speaker 1: were talking during the during the break about the blocking

922
00:44:19,280 --> 00:44:23,600
Speaker 1: problem on on Twitter, and you mentioned the service Twitter

923
00:44:23,680 --> 00:44:26,680
Speaker 1: has its own service for importing and exporting lists of blocks,

924
00:44:26,719 --> 00:44:28,960
Speaker 1: but it's not very well integrated. There is a site

925
00:44:28,960 --> 00:44:32,480
Speaker 1: called block together that actually a bunch of activists made

926
00:44:32,520 --> 00:44:35,160
Speaker 1: that gives you the tools to share a block list

927
00:44:35,239 --> 00:44:38,279
Speaker 1: with your friends and or to subscribe to theirs and

928
00:44:38,600 --> 00:44:40,120
Speaker 1: uh and it's really handy because then you don't have

929
00:44:40,160 --> 00:44:42,200
Speaker 1: to individually block a whole community of people that are

930
00:44:42,239 --> 00:44:44,800
Speaker 1: trying to troll a harass. So if you're looking to

931
00:44:45,480 --> 00:44:50,040
Speaker 1: so I break the world into three categories of people

932
00:44:50,600 --> 00:44:54,160
Speaker 1: and we'll we'll keep this relatively PG. But there are

933
00:44:54,200 --> 00:44:57,680
Speaker 1: the folks who are just simply misinformed. And I've learned

934
00:44:58,400 --> 00:45:02,320
Speaker 1: if you give somebody a fact that challenges their misunderstanding,

935
00:45:02,400 --> 00:45:06,200
Speaker 1: it doesn't doesn't help them. So what I always do

936
00:45:06,280 --> 00:45:10,560
Speaker 1: with that group of people is you should find data

937
00:45:10,680 --> 00:45:15,800
Speaker 1: source for the bls and if you could, if you

938
00:45:16,000 --> 00:45:19,160
Speaker 1: can prove to me that what you're you're saying is correct,

939
00:45:19,239 --> 00:45:21,680
Speaker 1: I'll write a column on it and either all because

940
00:45:21,719 --> 00:45:23,800
Speaker 1: if they follow me, I could d M them and

941
00:45:23,880 --> 00:45:26,360
Speaker 1: then subsequently delete the d M so they can't harangue

942
00:45:26,400 --> 00:45:29,719
Speaker 1: me on direct message, and I'll give them a not

943
00:45:29,840 --> 00:45:32,880
Speaker 1: so much a homework assignment. But if you really believe

944
00:45:33,440 --> 00:45:38,000
Speaker 1: this steaming pile and nonsense you've shared. I'm not asking

945
00:45:38,000 --> 00:45:42,239
Speaker 1: you to create a persuasive argument, just sending your data source. Right.

946
00:45:42,719 --> 00:45:46,560
Speaker 1: So so that's a that's the sort of gentle nudge.

947
00:45:47,280 --> 00:45:50,880
Speaker 1: The next level of people who are just kind of

948
00:45:51,160 --> 00:45:55,480
Speaker 1: ideologically broken. And what I mean by that is no

949
00:45:55,760 --> 00:46:01,439
Speaker 1: concept of of beyond not having any data, any data

950
00:46:01,480 --> 00:46:06,640
Speaker 1: that contradicts their beliefs, their ideology, just pure cognitive dissonance, right,

951
00:46:07,120 --> 00:46:09,400
Speaker 1: and and for them but not but not venal, but

952
00:46:09,480 --> 00:46:15,839
Speaker 1: not vicious, just philosophically askew on top of not being

953
00:46:15,920 --> 00:46:20,680
Speaker 1: evidence based. And so now you know, I really because

954
00:46:20,719 --> 00:46:22,920
Speaker 1: I start, I'll look at something and I'll go down

955
00:46:22,960 --> 00:46:25,279
Speaker 1: the rabbit hole and it's like, oh, okay, I know

956
00:46:25,440 --> 00:46:28,719
Speaker 1: this is you know, old roads lead to bright Bard

957
00:46:28,800 --> 00:46:31,400
Speaker 1: and Drudge in a bunch of And there's some versions

958
00:46:31,440 --> 00:46:33,560
Speaker 1: of that on the left as well. Some of the

959
00:46:33,760 --> 00:46:38,160
Speaker 1: early um, I'm trying to remember the sites Salon could

960
00:46:38,160 --> 00:46:40,160
Speaker 1: be a little over the top. And then there's another

961
00:46:40,239 --> 00:46:42,560
Speaker 1: one on the left. And I mean, I think they

962
00:46:42,600 --> 00:46:46,640
Speaker 1: can be wrong or exaggerated, but they very seldom inspire

963
00:46:46,680 --> 00:46:49,400
Speaker 1: a mob to go target people, that's for sure. But

964
00:46:50,080 --> 00:46:53,440
Speaker 1: as somebody who works in finance. I can't afford to

965
00:46:53,520 --> 00:46:57,720
Speaker 1: have a stream of dead, bad memes and misinformation and myths.

966
00:46:57,960 --> 00:46:59,719
Speaker 1: So I just want to cut so those people get

967
00:46:59,800 --> 00:47:04,000
Speaker 1: me did But the aggressive like I'm wrong and I'm

968
00:47:04,040 --> 00:47:07,400
Speaker 1: gonna be aggressive about it, um and obnoxious about it

969
00:47:07,440 --> 00:47:10,200
Speaker 1: and offensive about it. I'm sorry those folks have to

970
00:47:10,280 --> 00:47:13,680
Speaker 1: be blocked. I didn't know block together even existed. My

971
00:47:13,840 --> 00:47:17,560
Speaker 1: only concern is how do I not So I've noticed

972
00:47:17,640 --> 00:47:21,279
Speaker 1: some crazy Trumpers lately. Right at one point in time,

973
00:47:21,320 --> 00:47:23,839
Speaker 1: it was other crazies. But I don't mean people who

974
00:47:23,880 --> 00:47:26,400
Speaker 1: are pro Trump or anti Trump. I have friends in

975
00:47:26,440 --> 00:47:29,640
Speaker 1: the Trump administration. Anthony Scamucci is a buddy of mine.

976
00:47:29,920 --> 00:47:34,120
Speaker 1: We've had very civil debates about Trump. Someone in my

977
00:47:34,200 --> 00:47:36,600
Speaker 1: office as a Trump supporter. She and I have had

978
00:47:37,080 --> 00:47:43,920
Speaker 1: very rational adult discussions that online just do something tribal

979
00:47:44,040 --> 00:47:48,120
Speaker 1: and partisan that people lose their mind. So, and I'll

980
00:47:48,120 --> 00:47:51,600
Speaker 1: give you a perfect example. This weekend, I discovered that

981
00:47:51,800 --> 00:47:56,040
Speaker 1: Jenna Jamison, the former adult film star, is kind of

982
00:47:56,200 --> 00:48:01,920
Speaker 1: like a wild just listen there. There is some extreme

983
00:48:01,960 --> 00:48:05,200
Speaker 1: behavior in her history. So but I never expected that

984
00:48:05,320 --> 00:48:10,839
Speaker 1: to tip into wild ideological and it was just kind

985
00:48:10,880 --> 00:48:14,120
Speaker 1: of random that I found she's amplified white supremacists. I mean,

986
00:48:14,160 --> 00:48:18,759
Speaker 1: there's Yeah, it's a sort of surprising, you know, I think, Um, so,

987
00:48:18,920 --> 00:48:22,160
Speaker 1: how do you how do you block the people that

988
00:48:22,480 --> 00:48:25,200
Speaker 1: you want to block, yet at the same time not

989
00:48:25,520 --> 00:48:29,600
Speaker 1: block so so I can't say it on the radio,

990
00:48:29,719 --> 00:48:34,000
Speaker 1: but there was a science thing about something happening in

991
00:48:34,080 --> 00:48:37,279
Speaker 1: one of the guests, giants in outer space, about a

992
00:48:37,360 --> 00:48:40,960
Speaker 1: subsequent probe. I won't even go there, and she just retweeted,

993
00:48:41,000 --> 00:48:44,080
Speaker 1: at least buy me dinner first. And I just found

994
00:48:44,120 --> 00:48:47,279
Speaker 1: that hilarious that I was looking for something science and

995
00:48:48,239 --> 00:48:52,920
Speaker 1: phil plate uh does does a bad astronomy exactly? And

996
00:48:53,239 --> 00:48:55,239
Speaker 1: from that led to this, led to that, So I

997
00:48:55,320 --> 00:48:57,640
Speaker 1: don't want to The beauty of the web is the

998
00:48:57,840 --> 00:49:01,600
Speaker 1: random serendipity. Yeah, absolutely, So how do you block people

999
00:49:01,880 --> 00:49:07,680
Speaker 1: on a list like um blocked together and not lose

1000
00:49:07,800 --> 00:49:10,560
Speaker 1: that random? You know what I want? They're going to

1001
00:49:10,600 --> 00:49:12,720
Speaker 1: be some false positives, but that already happens, an email

1002
00:49:12,760 --> 00:49:14,759
Speaker 1: that already happens, and everything, right, I mean, but you

1003
00:49:14,800 --> 00:49:17,120
Speaker 1: can at least check your seat. But yeah, but it's

1004
00:49:17,120 --> 00:49:18,560
Speaker 1: the same thing like if you really I mean, you

1005
00:49:18,640 --> 00:49:21,560
Speaker 1: know somebody exactly, you can just go and and bet

1006
00:49:21,600 --> 00:49:23,120
Speaker 1: it like if you're like I really want to see

1007
00:49:23,120 --> 00:49:24,480
Speaker 1: this tweet, but I have this person blocked, you just

1008
00:49:24,520 --> 00:49:27,360
Speaker 1: do unblock them. There's nothing to that. I think what

1009
00:49:27,719 --> 00:49:29,560
Speaker 1: is key is like being able to use the service

1010
00:49:29,600 --> 00:49:32,680
Speaker 1: where like it's not it's not some huge barrier, right

1011
00:49:32,719 --> 00:49:34,520
Speaker 1: if you block somebody, they can still see your tweets

1012
00:49:34,520 --> 00:49:37,600
Speaker 1: if they want, they just don't. Yeah, absolutely, So it's

1013
00:49:37,640 --> 00:49:40,879
Speaker 1: not like this is some impermeable barrier. All it's doing

1014
00:49:40,960 --> 00:49:44,520
Speaker 1: is making it harder for a mob of harassers to

1015
00:49:44,640 --> 00:49:47,160
Speaker 1: target you. And that's really useful. Like for me, it's

1016
00:49:47,160 --> 00:49:50,440
Speaker 1: like like if I'm like whatever, out with my kid

1017
00:49:50,560 --> 00:49:52,320
Speaker 1: and you know, we're doing fun stuff on the weekend,

1018
00:49:52,719 --> 00:49:54,680
Speaker 1: and it happens to be the moment when like a

1019
00:49:54,760 --> 00:49:56,800
Speaker 1: mob of white supremacist is a decided they want to

1020
00:49:56,840 --> 00:49:59,000
Speaker 1: come after me for something I wrote. And the thing

1021
00:49:59,120 --> 00:50:00,919
Speaker 1: is like, they'll go back through your history. It could

1022
00:50:00,920 --> 00:50:03,680
Speaker 1: be something I wrote years ago. Um, and I'm getting

1023
00:50:03,760 --> 00:50:06,120
Speaker 1: notifications on my phone while I'm out with my kid

1024
00:50:06,320 --> 00:50:08,359
Speaker 1: and I'm like, yeah, exactly. I like, I don't want

1025
00:50:08,400 --> 00:50:10,520
Speaker 1: to be distracted by this. If I can just go

1026
00:50:10,760 --> 00:50:13,040
Speaker 1: and find somebody who's already got a good block list,

1027
00:50:13,480 --> 00:50:15,000
Speaker 1: and just share it and be like, Okay, good, I've

1028
00:50:15,040 --> 00:50:17,600
Speaker 1: been able to sort of cut this off. That's it's

1029
00:50:17,640 --> 00:50:19,600
Speaker 1: a no brainer. Like why can you search for a

1030
00:50:19,680 --> 00:50:24,040
Speaker 1: blocklist by a specific it's block list with this person

1031
00:50:24,120 --> 00:50:26,120
Speaker 1: and then I'll share it's just a person. Yeah, so

1032
00:50:26,200 --> 00:50:28,160
Speaker 1: you go by like an individual Twitter user who you

1033
00:50:28,239 --> 00:50:29,800
Speaker 1: trust and use, you know what I mean? The opposite,

1034
00:50:29,840 --> 00:50:33,319
Speaker 1: I want to block Jimmy Dean and then who else

1035
00:50:33,440 --> 00:50:35,560
Speaker 1: is blocked? I don't think so, And part like they've

1036
00:50:35,600 --> 00:50:37,600
Speaker 1: been very thoughtful about it where they don't they don't

1037
00:50:37,680 --> 00:50:40,080
Speaker 1: encourage sort of willy nilly blocking, Like it's really about

1038
00:50:40,160 --> 00:50:42,239
Speaker 1: sort of sharing with the community and doing and and

1039
00:50:42,360 --> 00:50:44,440
Speaker 1: and people having human judgment involved in it. And so

1040
00:50:44,480 --> 00:50:46,960
Speaker 1: I think that's really good. And you can um and

1041
00:50:47,040 --> 00:50:48,960
Speaker 1: you can also go and search for like people that

1042
00:50:49,120 --> 00:50:51,800
Speaker 1: you UM follow who do have lists, and so like

1043
00:50:51,920 --> 00:50:54,040
Speaker 1: those things are very handy. I think Twitter is gonna

1044
00:50:54,040 --> 00:50:56,719
Speaker 1: involve their tools too. But the key is that, like, um,

1045
00:50:57,360 --> 00:51:02,720
Speaker 1: there's a there's a really valid use to blocking people

1046
00:51:03,239 --> 00:51:05,440
Speaker 1: that we learned from Again, like I almost think digital

1047
00:51:06,000 --> 00:51:08,680
Speaker 1: communities need to learn from physical communities, right, And there's

1048
00:51:08,680 --> 00:51:10,520
Speaker 1: a reason why we sort of say, like you can't

1049
00:51:10,560 --> 00:51:12,479
Speaker 1: come into this coffee shop if you're going to shout

1050
00:51:12,560 --> 00:51:14,760
Speaker 1: at people, and you can't you come into this lobby

1051
00:51:14,800 --> 00:51:18,000
Speaker 1: if you're gonna be acting this way, and a crowd theater,

1052
00:51:19,280 --> 00:51:22,600
Speaker 1: and so being able to have analogous tools for sort

1053
00:51:22,600 --> 00:51:26,080
Speaker 1: of just limiting really really anti social behavior. I think

1054
00:51:26,080 --> 00:51:27,719
Speaker 1: it's really useful, and I'm glad that, like the tools

1055
00:51:27,719 --> 00:51:29,359
Speaker 1: are starting to evolve. I think it's a shame they're

1056
00:51:29,360 --> 00:51:33,000
Speaker 1: happening by like activists self funding themselves, building as opposed

1057
00:51:33,000 --> 00:51:35,680
Speaker 1: to the platforms building in. So are we just going

1058
00:51:35,760 --> 00:51:41,040
Speaker 1: to end up with ideologically opposed left blocks and right

1059
00:51:41,120 --> 00:51:44,520
Speaker 1: blocks or is it really is the unifying factor anti

1060
00:51:44,600 --> 00:51:46,680
Speaker 1: social behavior? I think it's a social behavior. There are

1061
00:51:46,719 --> 00:51:48,400
Speaker 1: people that do that, of course, that are like ignore

1062
00:51:48,400 --> 00:51:51,000
Speaker 1: anybody who disagrees with them politically, but they were already

1063
00:51:51,080 --> 00:51:52,880
Speaker 1: doing that, Like they don't need software to do that

1064
00:51:52,880 --> 00:51:54,360
Speaker 1: if you're the kind of person they can't deal with

1065
00:51:54,880 --> 00:51:58,480
Speaker 1: dissenting ideas. The block was not the issue. The interesting

1066
00:51:58,520 --> 00:52:00,799
Speaker 1: thing that's happening rhetorically now where I'm like, I don't

1067
00:52:00,840 --> 00:52:03,920
Speaker 1: want to interact with for example, like white supremacists online,

1068
00:52:05,320 --> 00:52:08,000
Speaker 1: go figure right and they'll come back to me. And

1069
00:52:08,120 --> 00:52:11,560
Speaker 1: be like, oh, you can't handle political dissentsion sake. I

1070
00:52:11,640 --> 00:52:15,600
Speaker 1: love the expression snowflake, yeah, because it's all massive projection

1071
00:52:15,640 --> 00:52:20,279
Speaker 1: because to the slightest challenge and and and and I'm

1072
00:52:20,320 --> 00:52:22,960
Speaker 1: just like, you know what, Like I like, I'm tough

1073
00:52:23,000 --> 00:52:25,239
Speaker 1: as nails. I have no question about that. Like I

1074
00:52:25,320 --> 00:52:26,759
Speaker 1: know what I've been through, and I know you know

1075
00:52:26,800 --> 00:52:29,399
Speaker 1: what I'm able to do. I'm just like, why would

1076
00:52:29,400 --> 00:52:31,520
Speaker 1: I want to deal with you? This is like, this

1077
00:52:31,640 --> 00:52:33,800
Speaker 1: is an elective thing. It's about me having good judgment

1078
00:52:33,880 --> 00:52:36,759
Speaker 1: and discernment where I'm like, you're you're a person who

1079
00:52:36,800 --> 00:52:40,440
Speaker 1: acts obnoxious online all day? Why would I put like,

1080
00:52:40,719 --> 00:52:43,360
Speaker 1: I'm not that's that's not the idea. I'm working to engagement.

1081
00:52:43,440 --> 00:52:45,279
Speaker 1: Like if you think that the only way that your

1082
00:52:45,320 --> 00:52:48,040
Speaker 1: ideas can be representing in culture is by you acting

1083
00:52:48,080 --> 00:52:50,480
Speaker 1: like a monster all day lighting it on fire, and

1084
00:52:52,320 --> 00:52:55,120
Speaker 1: yours probably aren't that good, you know. And it's like,

1085
00:52:55,480 --> 00:52:57,799
Speaker 1: it's not that I'm not intellectually curious. I know, I am.

1086
00:52:57,840 --> 00:53:01,240
Speaker 1: I'm very interested in having my options challenge and learning

1087
00:53:01,280 --> 00:53:04,160
Speaker 1: things like I am very much like I love that

1088
00:53:04,280 --> 00:53:06,439
Speaker 1: idea of like I had to change my mind because

1089
00:53:06,480 --> 00:53:08,040
Speaker 1: I was wrong about the way I thought about this thing,

1090
00:53:08,120 --> 00:53:11,120
Speaker 1: Like I love that feeling. Uh, it doesn't come from

1091
00:53:11,200 --> 00:53:14,759
Speaker 1: somebody saying, like why streaming epithets exactly, Like why the

1092
00:53:14,840 --> 00:53:17,800
Speaker 1: fact that, like my family is multiracial is wrong? Like

1093
00:53:17,880 --> 00:53:20,000
Speaker 1: that is never going to be the thing that I'm like, Wow,

1094
00:53:20,040 --> 00:53:21,279
Speaker 1: I've seen the light. You know, we used to have

1095
00:53:21,440 --> 00:53:23,480
Speaker 1: laws against that sort of stuff that's in the good

1096
00:53:23,520 --> 00:53:26,759
Speaker 1: old days. It's uh, it's it's amazing. You know, when

1097
00:53:26,800 --> 00:53:30,600
Speaker 1: I get the requests through a colleague, Hey, you block

1098
00:53:30,719 --> 00:53:35,080
Speaker 1: so and so so. Now the processes, I'll go look

1099
00:53:35,120 --> 00:53:38,000
Speaker 1: at their not only their tweet stream, but their tweets

1100
00:53:38,040 --> 00:53:40,120
Speaker 1: and replies because I want to see how they're interacting.

1101
00:53:40,200 --> 00:53:42,400
Speaker 1: That's right. And I say to people, listen, life is

1102
00:53:42,480 --> 00:53:47,120
Speaker 1: too short. You're not a good person. There's eight billion people,

1103
00:53:47,640 --> 00:53:50,520
Speaker 1: most of whom are half decent and well intentioned. Some

1104
00:53:50,719 --> 00:53:54,920
Speaker 1: may be misguided. But I don't need venal jerks and

1105
00:53:55,280 --> 00:53:57,520
Speaker 1: nobody needs no Life is too short, and I got

1106
00:53:57,560 --> 00:53:59,400
Speaker 1: too much left to learn to spend my fighting with

1107
00:53:59,440 --> 00:54:01,799
Speaker 1: the strangers really wants to fight more than they want

1108
00:54:01,800 --> 00:54:03,520
Speaker 1: to learn. Right, That's right. You know. One of the

1109
00:54:03,560 --> 00:54:06,880
Speaker 1: beauties of of going to law school is mood court.

1110
00:54:07,320 --> 00:54:09,960
Speaker 1: And the best part about mood court is you have

1111
00:54:10,160 --> 00:54:13,200
Speaker 1: to be able to switch hats and argue either side

1112
00:54:13,280 --> 00:54:17,239
Speaker 1: of any litigation. Literally mid case, you could be all

1113
00:54:17,320 --> 00:54:21,200
Speaker 1: right now. So I've always taken that as a as

1114
00:54:21,239 --> 00:54:25,399
Speaker 1: a sign of intellectual openness. Having the ability to see

1115
00:54:25,440 --> 00:54:27,160
Speaker 1: all sides of an issue, of a problem, what have

1116
00:54:27,320 --> 00:54:33,920
Speaker 1: you prevent you from, uh turning your your opponents into

1117
00:54:34,400 --> 00:54:41,359
Speaker 1: a sub human It keeps the discussion rational because Hey,

1118
00:54:41,520 --> 00:54:44,319
Speaker 1: things that are really really at least in court, things

1119
00:54:44,400 --> 00:54:47,680
Speaker 1: that are really one sided, those cases settle. But where

1120
00:54:47,680 --> 00:54:51,279
Speaker 1: there's a legitimate debate, let's have the debate. And unfortunately

1121
00:54:51,360 --> 00:54:55,080
Speaker 1: too many people uh just can't imagine the other side

1122
00:54:55,239 --> 00:54:57,560
Speaker 1: of the discussion. And that's amazing. Yeah, and I'm very

1123
00:54:57,640 --> 00:54:59,960
Speaker 1: you know, my my mother's families all lawyers, and I'm

1124
00:55:00,040 --> 00:55:04,040
Speaker 1: sort of you know Rais Well, you know, it's interesting

1125
00:55:04,120 --> 00:55:08,800
Speaker 1: they were both um somewhere criminal defense lawyers and and

1126
00:55:08,880 --> 00:55:11,880
Speaker 1: then um, my great grandfather was involved in the Indian

1127
00:55:11,920 --> 00:55:14,040
Speaker 1: independence movement. He marked with FANDI and was sort of

1128
00:55:14,200 --> 00:55:19,440
Speaker 1: very involved in civil rights and social justice about you

1129
00:55:19,520 --> 00:55:21,799
Speaker 1: know what's interesting is they had a printing press at

1130
00:55:21,840 --> 00:55:24,440
Speaker 1: the house, and so there is a tradition of like

1131
00:55:24,520 --> 00:55:30,520
Speaker 1: how do you use your own you know platform exact idea? Right, Yeah,

1132
00:55:30,600 --> 00:55:32,480
Speaker 1: so you know a century ago, that was cutting edge

1133
00:55:32,520 --> 00:55:35,239
Speaker 1: technology to be able to have in a rural, very

1134
00:55:35,320 --> 00:55:37,719
Speaker 1: very poor part of India. And so yeah, I think

1135
00:55:37,760 --> 00:55:40,800
Speaker 1: there is this idea of how do you debate ideas

1136
00:55:41,040 --> 00:55:43,799
Speaker 1: using cutting edge platforms to get your ideas out there

1137
00:55:44,280 --> 00:55:47,120
Speaker 1: and advancing the cause of social justice. And I think

1138
00:55:47,160 --> 00:55:49,520
Speaker 1: those are things that you know, you don't think about

1139
00:55:49,520 --> 00:55:51,320
Speaker 1: consciously as a kid, but they sort of seep in

1140
00:55:51,600 --> 00:55:54,080
Speaker 1: into your mind. And and so there was always a

1141
00:55:54,120 --> 00:55:56,239
Speaker 1: healthy debate about how to how to do these things.

1142
00:55:56,280 --> 00:55:58,719
Speaker 1: I mean, you know, like especially you look at this

1143
00:55:58,880 --> 00:56:01,279
Speaker 1: is still true today. Civil rights movements always have these

1144
00:56:01,400 --> 00:56:04,360
Speaker 1: big schisms within them of like how how radical do

1145
00:56:04,440 --> 00:56:05,880
Speaker 1: we want to be? And what's the right way to

1146
00:56:05,960 --> 00:56:08,240
Speaker 1: approach this? And you know, do we change the system

1147
00:56:08,320 --> 00:56:10,480
Speaker 1: from the inside or do we you know, try to

1148
00:56:10,640 --> 00:56:12,880
Speaker 1: tear it down from the outside. And those kinds of debates.

1149
00:56:13,200 --> 00:56:15,839
Speaker 1: I think those are fascinating and timeless debates. And I'm

1150
00:56:15,840 --> 00:56:18,080
Speaker 1: always happy to engage in those. The people who are

1151
00:56:18,160 --> 00:56:21,520
Speaker 1: like I want to personally, you know, hurt you or

1152
00:56:21,760 --> 00:56:24,800
Speaker 1: or or I want to attack you, and and and

1153
00:56:25,239 --> 00:56:26,640
Speaker 1: that's the only way to vance my ideas. I'm like,

1154
00:56:26,880 --> 00:56:29,120
Speaker 1: that's never it's never going to be the thing that

1155
00:56:29,360 --> 00:56:31,319
Speaker 1: that persuades me or that makes me see the light.

1156
00:56:31,680 --> 00:56:34,720
Speaker 1: And it certainly doesn't indicate much confidence in that person's

1157
00:56:34,760 --> 00:56:37,080
Speaker 1: argument anyway. You know, I've gone back and looked at

1158
00:56:37,160 --> 00:56:40,279
Speaker 1: some old blog posts that I could see are out

1159
00:56:40,360 --> 00:56:43,000
Speaker 1: of frustration where I don't want to say I just

1160
00:56:43,160 --> 00:56:47,000
Speaker 1: called other people idiots, but I would look at their

1161
00:56:47,080 --> 00:56:51,280
Speaker 1: position and first try and take it apart, and somewhere

1162
00:56:51,280 --> 00:56:53,120
Speaker 1: in the middle was a little bit of name calling

1163
00:56:53,160 --> 00:56:55,560
Speaker 1: would be in and then you catch yourself and move

1164
00:56:55,640 --> 00:56:59,640
Speaker 1: away from it. How have you you, more than any

1165
00:56:59,719 --> 00:57:03,279
Speaker 1: person and I know, have been at the vanguard of

1166
00:57:03,560 --> 00:57:07,640
Speaker 1: of seeing the arc of the blogosphere change over time.

1167
00:57:07,719 --> 00:57:11,600
Speaker 1: What what have you noticed? Um? How has this evolved?

1168
00:57:12,960 --> 00:57:16,480
Speaker 1: Do you plan on continuing blogging for forever? What? What

1169
00:57:16,840 --> 00:57:19,280
Speaker 1: are your thoughts on? Yeah, you know, I've learned a lot.

1170
00:57:19,320 --> 00:57:22,160
Speaker 1: I think, Um, it is that I definitely see you

1171
00:57:22,200 --> 00:57:25,040
Speaker 1: when I look back at eighteen years of writing now,

1172
00:57:25,800 --> 00:57:30,439
Speaker 1: UM that it is always this sort of ink blot

1173
00:57:30,480 --> 00:57:33,200
Speaker 1: test about where I met in my head. You go

1174
00:57:33,280 --> 00:57:34,880
Speaker 1: back and read it and I can see exactly how

1175
00:57:34,920 --> 00:57:36,240
Speaker 1: I was feeling at the moment, even if I don't

1176
00:57:36,280 --> 00:57:39,360
Speaker 1: remember writing it. Shocking, wo, I was having a bad

1177
00:57:39,400 --> 00:57:41,520
Speaker 1: day that you know, or or wow, I was really

1178
00:57:41,560 --> 00:57:44,320
Speaker 1: in a good mood. And and and you can really

1179
00:57:44,440 --> 00:57:47,160
Speaker 1: read that into you know, the work. I think that

1180
00:57:47,360 --> 00:57:49,920
Speaker 1: that's been really instructive, because like, I don't keep a

1181
00:57:50,120 --> 00:57:52,520
Speaker 1: like a mood journal, and so I could be writing

1182
00:57:52,560 --> 00:57:54,760
Speaker 1: about like whatever a new update to Windows came out

1183
00:57:54,800 --> 00:57:56,200
Speaker 1: when I used to blog about tech a lot, and

1184
00:57:56,200 --> 00:57:59,000
Speaker 1: I could still tell you exactly how I felt, you

1185
00:57:59,080 --> 00:58:00,800
Speaker 1: know what I read. I think that really instructive. I

1186
00:58:00,840 --> 00:58:04,160
Speaker 1: think my attitude about dealing with you know, people being

1187
00:58:04,200 --> 00:58:07,440
Speaker 1: aggressive or hostile online has has changed a lot over

1188
00:58:07,520 --> 00:58:11,840
Speaker 1: the years. I think initially, um, you know, I think

1189
00:58:11,880 --> 00:58:14,880
Speaker 1: your first reaction is like, well, you know, screw you too, buddy,

1190
00:58:14,920 --> 00:58:17,080
Speaker 1: and you can sort of go at them. I think

1191
00:58:17,160 --> 00:58:18,919
Speaker 1: I spent a long time trying to be like I'm

1192
00:58:18,960 --> 00:58:21,480
Speaker 1: just gonna, you know, love you to death and that'll

1193
00:58:21,520 --> 00:58:23,960
Speaker 1: get you to change. And and I had some successes

1194
00:58:24,000 --> 00:58:28,000
Speaker 1: with that. I mean, I have actually seen conversations where

1195
00:58:28,360 --> 00:58:30,560
Speaker 1: I change somebody's mind her they changed my mind, or

1196
00:58:30,560 --> 00:58:33,200
Speaker 1: at least you get them to back down from the

1197
00:58:33,360 --> 00:58:37,840
Speaker 1: sort of over I think people's initial emails, like it

1198
00:58:37,920 --> 00:58:40,640
Speaker 1: would be great if email had like a sixty minute delay,

1199
00:58:41,040 --> 00:58:44,320
Speaker 1: Like you can't respond instantly. So every now and then

1200
00:58:44,480 --> 00:58:48,080
Speaker 1: someone sends an email and if you give them a

1201
00:58:48,200 --> 00:58:53,000
Speaker 1: big friendly hug and say like you're really upset or

1202
00:58:53,320 --> 00:58:56,000
Speaker 1: or hey, I hope you're not missing the key point here,

1203
00:58:56,360 --> 00:58:58,360
Speaker 1: here's my data source. What are you using to reach

1204
00:58:58,440 --> 00:59:02,320
Speaker 1: this conclusion? As often as not or not, especially in

1205
00:59:02,360 --> 00:59:06,440
Speaker 1: the professional community, So my universe's finance. When someone gets

1206
00:59:06,680 --> 00:59:09,480
Speaker 1: it's not even though back down it's like I've gotten Hey,

1207
00:59:09,480 --> 00:59:12,920
Speaker 1: I appreciate your responding. Civilly, I was online like you say, oh,

1208
00:59:13,040 --> 00:59:16,520
Speaker 1: these people are really professional and smart. He was just

1209
00:59:16,760 --> 00:59:19,320
Speaker 1: perturbed at something. Yeah, it's yeah. It could be whatever

1210
00:59:19,440 --> 00:59:21,960
Speaker 1: they you know, they didn't eat lunch that day, or

1211
00:59:22,000 --> 00:59:24,760
Speaker 1: they have something else going on. What what about the

1212
00:59:24,960 --> 00:59:28,880
Speaker 1: change in media? How has the bloggersphere impacted that? In

1213
00:59:28,960 --> 00:59:31,920
Speaker 1: your perspective, it is It's interesting. I was such an

1214
00:59:31,960 --> 00:59:34,920
Speaker 1: idealist about blogging and social media when he came out.

1215
00:59:34,920 --> 00:59:36,480
Speaker 1: I was like, we're gonna give platforms that are going

1216
00:59:36,520 --> 00:59:38,600
Speaker 1: to give voice to people that don't have any other

1217
00:59:38,600 --> 00:59:40,080
Speaker 1: places to share the words, and that was true. That

1218
00:59:40,160 --> 00:59:43,680
Speaker 1: did happen the professional amateurs exactly who are no longer

1219
00:59:43,720 --> 00:59:50,360
Speaker 1: amateurs now they're professional experts, expert professionals, right, And I'm

1220
00:59:50,480 --> 00:59:52,720
Speaker 1: exhibit A. Yeah, and you know I've been very lucky

1221
00:59:52,800 --> 00:59:55,080
Speaker 1: to benefit from that too. And I think that was true.

1222
00:59:55,960 --> 00:59:58,440
Speaker 1: And and we kept saying, you know, the whatever, the

1223
00:59:58,480 --> 01:00:00,760
Speaker 1: mainstream media makes all these mistakes, and now the social

1224
01:00:00,800 --> 01:00:04,920
Speaker 1: media will help correct it. And then we ignored or

1225
01:00:04,960 --> 01:00:08,520
Speaker 1: didn't anticipate the exact opposite, which was the times when

1226
01:00:08,520 --> 01:00:10,800
Speaker 1: mainstream media was exactly right, and people would use social

1227
01:00:10,840 --> 01:00:15,840
Speaker 1: media to spread disinformation. Yeah, and the idea that like, um,

1228
01:00:16,120 --> 01:00:18,840
Speaker 1: the people who didn't have access to get their voice

1229
01:00:18,840 --> 01:00:21,480
Speaker 1: out there, some of them would would not use that

1230
01:00:21,600 --> 01:00:25,880
Speaker 1: power responsibly. We I was such an optimist and idealist

1231
01:00:25,920 --> 01:00:27,840
Speaker 1: of like, wow, if we just give everybody a printing press,

1232
01:00:27,880 --> 01:00:29,840
Speaker 1: all they're going to print is good, thoughtful, true things,

1233
01:00:30,760 --> 01:00:33,000
Speaker 1: and um, you know that's not the case. And it

1234
01:00:33,120 --> 01:00:36,760
Speaker 1: was a a long, slow, painful lesson that I I know,

1235
01:00:36,960 --> 01:00:39,160
Speaker 1: I personally took too long to learn. What's the old

1236
01:00:39,240 --> 01:00:41,640
Speaker 1: quota a law is halfway around the world where the

1237
01:00:41,680 --> 01:00:44,400
Speaker 1: truth is still tying on its boots. Yeah, yeah, and

1238
01:00:45,680 --> 01:00:48,800
Speaker 1: I think that was very naive on my part. And

1239
01:00:49,040 --> 01:00:50,720
Speaker 1: the amazing thing about it is I felt like I

1240
01:00:50,840 --> 01:00:53,240
Speaker 1: was slow to get that lesson and slow to to

1241
01:00:53,360 --> 01:00:55,000
Speaker 1: really build it into my work and the and the

1242
01:00:55,160 --> 01:00:58,200
Speaker 1: tools and the platforms I was creating. And yet I

1243
01:00:58,280 --> 01:01:00,480
Speaker 1: think it still took even longer for the people that

1244
01:01:00,600 --> 01:01:02,920
Speaker 1: made the facebooks and twitters of the world to get

1245
01:01:02,960 --> 01:01:06,320
Speaker 1: that lesson. And not only do they have to recognize that,

1246
01:01:06,400 --> 01:01:10,040
Speaker 1: they have to then recognize that it's an existential threat

1247
01:01:10,120 --> 01:01:13,600
Speaker 1: to their platform and then create the tech to response

1248
01:01:13,600 --> 01:01:16,480
Speaker 1: to it. Well, and I was lucky and that we

1249
01:01:16,560 --> 01:01:19,120
Speaker 1: had built a product when we built blogging tools that

1250
01:01:19,440 --> 01:01:23,440
Speaker 1: people paid for. You paid for right, you know, And so, um,

1251
01:01:23,880 --> 01:01:25,960
Speaker 1: if you wanted to have a voice in a platform,

1252
01:01:26,080 --> 01:01:27,880
Speaker 1: you were going to directly support it and you were

1253
01:01:27,960 --> 01:01:31,760
Speaker 1: head an investment in it. And so we weren't based

1254
01:01:31,800 --> 01:01:34,000
Speaker 1: on attention, We were not based on the ad model,

1255
01:01:34,800 --> 01:01:37,440
Speaker 1: and um, so you didn't have to be outrageous, you

1256
01:01:37,440 --> 01:01:39,240
Speaker 1: didn't have to jump up that scream, you don't have

1257
01:01:39,360 --> 01:01:42,440
Speaker 1: to have clickbait headlines. Well, and you won't believe what

1258
01:01:42,560 --> 01:01:44,760
Speaker 1: slide three, right, But even if you're going to do that,

1259
01:01:44,800 --> 01:01:47,240
Speaker 1: you were incentivized to build your audience on your terms,

1260
01:01:47,800 --> 01:01:50,720
Speaker 1: but not just views at any cost, you know, Patriots

1261
01:01:50,760 --> 01:01:54,280
Speaker 1: in any cost and everybody else basically went with the

1262
01:01:54,280 --> 01:01:58,560
Speaker 1: ad model, and I, you know, I was really adamantly

1263
01:01:58,560 --> 01:02:01,560
Speaker 1: against it, and I do think inc you know, you

1264
01:02:01,640 --> 01:02:03,880
Speaker 1: see the sort of return as subscription models right at

1265
01:02:03,920 --> 01:02:06,320
Speaker 1: the Times New York Times and like everybody, we want

1266
01:02:06,360 --> 01:02:08,760
Speaker 1: you to subscribe and pay for great journalism all these things.

1267
01:02:09,320 --> 01:02:12,520
Speaker 1: This is this reaction to seeing the distorting effect that

1268
01:02:12,600 --> 01:02:15,280
Speaker 1: that the major ad models have on on web media

1269
01:02:16,000 --> 01:02:19,400
Speaker 1: and the facebooks and twitters and and you know instagrams

1270
01:02:19,440 --> 01:02:22,040
Speaker 1: in the world built models that were totally advertising dependent

1271
01:02:22,520 --> 01:02:27,720
Speaker 1: and so get hyper exaggerated into attention getting models. And

1272
01:02:27,800 --> 01:02:31,400
Speaker 1: I think that's something that the publishers didn't understand how

1273
01:02:31,480 --> 01:02:33,919
Speaker 1: much that would skew their business. And it's interesting because

1274
01:02:33,920 --> 01:02:36,000
Speaker 1: in print, you know, there's one of there was more

1275
01:02:36,000 --> 01:02:39,160
Speaker 1: ad dollars to go around two they were indirect models, right,

1276
01:02:39,240 --> 01:02:41,720
Speaker 1: So the fact that you had a ton of classified

1277
01:02:41,760 --> 01:02:44,240
Speaker 1: ads might encourage you to have a real estate section,

1278
01:02:44,640 --> 01:02:48,120
Speaker 1: but it didn't make your news headlines more extreme about

1279
01:02:48,240 --> 01:02:51,480
Speaker 1: politics and about whether and about whatever. Same thing with

1280
01:02:51,520 --> 01:02:53,520
Speaker 1: the automobile, so you can go through each of the

1281
01:02:53,600 --> 01:02:56,040
Speaker 1: major sections of the Sunday New York Times, and they

1282
01:02:56,040 --> 01:02:59,360
Speaker 1: were advertising and so you have the theater section, the

1283
01:02:59,520 --> 01:03:02,960
Speaker 1: arts and Arts and Entertainment section, real estate, automobiles. I

1284
01:03:03,000 --> 01:03:05,160
Speaker 1: don't know if they still have an automobiles. They might,

1285
01:03:05,240 --> 01:03:07,200
Speaker 1: they might have killed off. But even to that example,

1286
01:03:07,280 --> 01:03:10,040
Speaker 1: like the existence of an automobile section was as a

1287
01:03:10,080 --> 01:03:13,560
Speaker 1: sop to advertisers obviously, but it didn't skew the hard

1288
01:03:13,640 --> 01:03:16,600
Speaker 1: news reporting, and so that was okay because you're like, okay, whatever,

1289
01:03:16,640 --> 01:03:18,680
Speaker 1: you gotta pay the bills. Of course you have comics.

1290
01:03:18,720 --> 01:03:20,840
Speaker 1: You don't have comics because like, like, this is an

1291
01:03:20,840 --> 01:03:23,160
Speaker 1: important news for people, Like this makes people read and

1292
01:03:23,200 --> 01:03:25,840
Speaker 1: that gets the circulation up, and that that um, let's

1293
01:03:25,880 --> 01:03:29,200
Speaker 1: just do the hard news work. And the problem is

1294
01:03:29,360 --> 01:03:32,600
Speaker 1: that line goes away in web media. There isn't some like, well,

1295
01:03:32,760 --> 01:03:34,720
Speaker 1: you're gonna come and read the car ads and that's

1296
01:03:34,760 --> 01:03:37,280
Speaker 1: going to support you're reading the hard news. The hard

1297
01:03:37,320 --> 01:03:38,640
Speaker 1: news has to sell on its own, and so it

1298
01:03:38,680 --> 01:03:41,760
Speaker 1: gets more and more distorted and more and more exaggerated

1299
01:03:41,800 --> 01:03:43,560
Speaker 1: in order to get to that attention because you're in

1300
01:03:43,600 --> 01:03:45,440
Speaker 1: this more and more extreme environment. Now that that's a

1301
01:03:45,560 --> 01:03:48,120
Speaker 1: buzz Feed or maybe a vox or something like that,

1302
01:03:48,320 --> 01:03:50,920
Speaker 1: But that shouldn't be The Washington Post, in the New

1303
01:03:51,000 --> 01:03:53,080
Speaker 1: York Times, the Wall Street Journals, all of them. There's

1304
01:03:53,120 --> 01:03:55,520
Speaker 1: no difference between those. Like, yeah, I mean you look

1305
01:03:55,560 --> 01:03:58,320
Speaker 1: at like the best reported stories on buzz feed are

1306
01:03:58,400 --> 01:04:01,000
Speaker 1: not different than the best reported story race on the

1307
01:04:01,080 --> 01:04:04,000
Speaker 1: Times of the Post, like when you do good journalism,

1308
01:04:04,240 --> 01:04:06,960
Speaker 1: like there are but not necessarily the most read stories. No,

1309
01:04:07,120 --> 01:04:10,560
Speaker 1: that's true. And there are more you know, cat pictures

1310
01:04:10,680 --> 01:04:14,000
Speaker 1: or lists that are subsidizing that journalism on the buzz

1311
01:04:14,080 --> 01:04:16,959
Speaker 1: feeds than there are on you know, the other sides.

1312
01:04:17,040 --> 01:04:18,560
Speaker 1: But like that's just a that's just a question of

1313
01:04:18,600 --> 01:04:20,600
Speaker 1: how you subsidize, you know, in the case of the

1314
01:04:20,680 --> 01:04:23,640
Speaker 1: Post of the Times or whatever, they're subsidizing through print

1315
01:04:23,640 --> 01:04:26,720
Speaker 1: subscriptions that are going to go away as that audience

1316
01:04:27,200 --> 01:04:31,560
Speaker 1: ages out. I finally, I finally dropped everything but the

1317
01:04:31,640 --> 01:04:34,200
Speaker 1: weekend edition in New York Times because I would carry

1318
01:04:34,280 --> 01:04:37,200
Speaker 1: through the office carrying home and it would go go

1319
01:04:37,320 --> 01:04:40,320
Speaker 1: into the recycled. Then yeah, and the Wall Street Journal

1320
01:04:40,440 --> 01:04:43,640
Speaker 1: comes to the office, and this way I don't have

1321
01:04:43,720 --> 01:04:45,720
Speaker 1: to take it home. It goes right into the recycled, right,

1322
01:04:46,520 --> 01:04:48,800
Speaker 1: the way the Journal has there, and I think the

1323
01:04:48,920 --> 01:04:52,080
Speaker 1: Times is the same. If you do a digital subscription,

1324
01:04:52,160 --> 01:04:55,680
Speaker 1: the print edition is free. Yeah what what? Well? And

1325
01:04:55,760 --> 01:04:57,560
Speaker 1: this is all about the metrics and the numbers, right,

1326
01:04:57,600 --> 01:04:59,880
Speaker 1: so the advertising exactly. So they want to tell the advertiser,

1327
01:04:59,880 --> 01:05:02,360
Speaker 1: we this many print subscribers, even though all those people

1328
01:05:02,360 --> 01:05:04,840
Speaker 1: are just you know, when does that stop? When does

1329
01:05:04,880 --> 01:05:08,280
Speaker 1: that go next? Ten years? Ten years? No more newspapers? Yeah,

1330
01:05:08,320 --> 01:05:11,080
Speaker 1: I mean you know, for any practical purposes, there will

1331
01:05:11,120 --> 01:05:12,760
Speaker 1: be the same thing with New York or New York

1332
01:05:12,840 --> 01:05:17,520
Speaker 1: or the digital subscription and the digital plus um print

1333
01:05:17,880 --> 01:05:20,640
Speaker 1: are the same price. So your initial reaction is, oh,

1334
01:05:20,720 --> 01:05:22,520
Speaker 1: well this is more for the same price. I'll take that.

1335
01:05:22,960 --> 01:05:25,640
Speaker 1: Then you have a stack of unread magazines. It's pointless.

1336
01:05:25,720 --> 01:05:27,240
Speaker 1: Well it's like, yeah, unless you're going to the beach

1337
01:05:27,320 --> 01:05:29,320
Speaker 1: or something, you're not you're not looking at that print edition.

1338
01:05:29,360 --> 01:05:30,720
Speaker 1: And I see this all the time with people that

1339
01:05:30,960 --> 01:05:33,600
Speaker 1: like I watched, that have print subscriptions that are saying, Okay,

1340
01:05:33,640 --> 01:05:35,920
Speaker 1: well I found this article, but I'm gonna read it online. Now.

1341
01:05:36,000 --> 01:05:38,400
Speaker 1: I will tell you that when you thumb through a paper,

1342
01:05:38,440 --> 01:05:42,160
Speaker 1: you're gonna find things that you're not going to discovery digital. Yeah,

1343
01:05:42,240 --> 01:05:45,120
Speaker 1: it's other than the ink on your hands and and

1344
01:05:45,280 --> 01:05:48,560
Speaker 1: the fact that you're carrying around. There's there's no question

1345
01:05:48,600 --> 01:05:53,200
Speaker 1: the discovery experience on print media is good, is an

1346
01:05:53,280 --> 01:05:56,160
Speaker 1: interesting and unique thing, and you find stuff you wouldn't

1347
01:05:56,160 --> 01:05:59,280
Speaker 1: find otherwise on digital. But that's also just a design challenge,

1348
01:05:59,560 --> 01:06:01,400
Speaker 1: Like it's not impossible to solve these problems in the

1349
01:06:01,480 --> 01:06:04,040
Speaker 1: digital realm, they just haven't invested in doing so. So

1350
01:06:04,480 --> 01:06:06,920
Speaker 1: one of the things I've noticed in the arc of

1351
01:06:07,200 --> 01:06:11,400
Speaker 1: um of media has been how in the beginning, and

1352
01:06:11,480 --> 01:06:14,640
Speaker 1: I want to call that the mid two thousands, they

1353
01:06:14,760 --> 01:06:20,200
Speaker 1: felt very comfortable lifting anything from print, anything from the

1354
01:06:20,240 --> 01:06:26,080
Speaker 1: blogosphere without attribution, just relentlessly, and and I started the

1355
01:06:26,320 --> 01:06:29,680
Speaker 1: read it here first, here's the blog post from Monday,

1356
01:06:29,760 --> 01:06:31,600
Speaker 1: and oh look, this is what the whole Street General

1357
01:06:31,640 --> 01:06:34,360
Speaker 1: had on Thursday. I would do screenshots side by side. Yeah,

1358
01:06:34,360 --> 01:06:37,000
Speaker 1: I definitely had that with with stuff I read about tech. Right,

1359
01:06:37,040 --> 01:06:38,720
Speaker 1: And then then you send it to the editor and

1360
01:06:38,760 --> 01:06:40,640
Speaker 1: saying I want you to know that I'm going to

1361
01:06:40,760 --> 01:06:43,040
Speaker 1: keep doing this until you're free to call me. I

1362
01:06:43,160 --> 01:06:45,479
Speaker 1: have a professional title where I'm quoted in the media

1363
01:06:45,520 --> 01:06:49,160
Speaker 1: all the time. Don't don't rip this off, and if

1364
01:06:49,200 --> 01:06:51,400
Speaker 1: you do this more blatantly, I'm going to stick the

1365
01:06:51,480 --> 01:06:53,920
Speaker 1: lawyers on UKUS. At a certain point, you cross the

1366
01:06:54,000 --> 01:06:59,520
Speaker 1: line from inspired by two copyright infringement and there was

1367
01:06:59,600 --> 01:07:01,680
Speaker 1: a head. My favorite was a thing I did on

1368
01:07:01,840 --> 01:07:06,280
Speaker 1: terrestrial radio. I'm a big music buff and I just

1369
01:07:06,480 --> 01:07:09,200
Speaker 1: hated what Clear Channel was doing to music. And I

1370
01:07:09,360 --> 01:07:13,360
Speaker 1: didn't right oh three or row four. It was way early.

1371
01:07:13,880 --> 01:07:16,320
Speaker 1: And then I think it was Barons had this front

1372
01:07:16,400 --> 01:07:20,240
Speaker 1: pick cover story losing the signal, and to their credit,

1373
01:07:20,320 --> 01:07:24,080
Speaker 1: they didn't actually steal language, but the structure, and it

1374
01:07:24,200 --> 01:07:26,919
Speaker 1: was like, wait a second, this looks really really didn't

1375
01:07:26,920 --> 01:07:29,960
Speaker 1: even notice it until a friend said, hey, Barons ripped

1376
01:07:30,000 --> 01:07:33,080
Speaker 1: you off? What do you mean? Look at that? It's

1377
01:07:33,200 --> 01:07:34,960
Speaker 1: um And there are a couple of other people I

1378
01:07:35,000 --> 01:07:39,520
Speaker 1: won't mention their names who feel like they can take

1379
01:07:39,640 --> 01:07:43,400
Speaker 1: that and it's so first that was the first phase.

1380
01:07:43,880 --> 01:07:46,440
Speaker 1: The second phase was one the Wall Street Journal in

1381
01:07:46,480 --> 01:07:50,320
Speaker 1: New York Times and other mainstream media started rolling out

1382
01:07:50,760 --> 01:07:54,280
Speaker 1: blogs of their own. Does this have any staying power? What?

1383
01:07:54,440 --> 01:07:57,000
Speaker 1: How do you see the role of a fast, not

1384
01:07:57,200 --> 01:08:00,320
Speaker 1: really very lightly edited, get it out quick gale. How

1385
01:08:00,360 --> 01:08:02,520
Speaker 1: do you see the role of that in mainstream media.

1386
01:08:02,520 --> 01:08:04,200
Speaker 1: I think it depends on the vertical and you know

1387
01:08:04,280 --> 01:08:08,720
Speaker 1: what what space you're covering, and um, how much reporting

1388
01:08:08,800 --> 01:08:12,320
Speaker 1: and and you know the original network sort of fuels it.

1389
01:08:12,800 --> 01:08:15,080
Speaker 1: There are there are great blogs done by mainstream media

1390
01:08:15,080 --> 01:08:17,920
Speaker 1: outlets that are usually written by somebody that has a

1391
01:08:17,960 --> 01:08:21,519
Speaker 1: great voice, that knows the space really well, has their network,

1392
01:08:21,720 --> 01:08:25,599
Speaker 1: and um can turn that into you know, a story

1393
01:08:25,680 --> 01:08:28,240
Speaker 1: really quickly. And I look at like it, Actually it

1394
01:08:28,320 --> 01:08:30,120
Speaker 1: wasn't a blog, but I look at like David Carr

1395
01:08:30,400 --> 01:08:33,120
Speaker 1: what he had done at the Times. Um, boy, I

1396
01:08:33,200 --> 01:08:37,200
Speaker 1: missed that guy. And you know he was very blog

1397
01:08:37,400 --> 01:08:39,439
Speaker 1: like in the way even he wrote his print columns

1398
01:08:40,000 --> 01:08:42,400
Speaker 1: very fast, turn things around new exactly who to call

1399
01:08:42,840 --> 01:08:46,200
Speaker 1: connected the dots really really well. I think that model

1400
01:08:46,280 --> 01:08:51,000
Speaker 1: can work, UM, but very few of the major outlets

1401
01:08:51,080 --> 01:08:53,760
Speaker 1: have a business model for that. You can't hide the

1402
01:08:53,800 --> 01:08:56,360
Speaker 1: blog behind a paywall, because that that ruins its point

1403
01:08:56,400 --> 01:08:58,759
Speaker 1: of linking to stuff. I've had that argument with the Wolster,

1404
01:08:59,160 --> 01:09:01,760
Speaker 1: this discussion with editors of the Wall Street Journal. Hey,

1405
01:09:01,880 --> 01:09:04,360
Speaker 1: why don't you put your blog out ahead of the payaball?

1406
01:09:04,920 --> 01:09:07,519
Speaker 1: But you have to be a registered subscriber to comment,

1407
01:09:07,720 --> 01:09:10,920
Speaker 1: and this way not only that you have actual people

1408
01:09:10,960 --> 01:09:14,960
Speaker 1: who are identifiable and make sense, right, you're inherently raising

1409
01:09:15,000 --> 01:09:17,360
Speaker 1: the quality of discussion. Yeah yeah, and you know so

1410
01:09:17,600 --> 01:09:20,479
Speaker 1: I think the business tensions always arise, and you see

1411
01:09:20,520 --> 01:09:22,599
Speaker 1: that with even sites that create great blogs, they sort

1412
01:09:22,600 --> 01:09:24,519
Speaker 1: of fade out after a while because the company is like,

1413
01:09:24,560 --> 01:09:26,240
Speaker 1: I'm not really behind this, I don't believe in this,

1414
01:09:26,880 --> 01:09:30,680
Speaker 1: um and and I draw that contrast to like organizations

1415
01:09:30,720 --> 01:09:34,000
Speaker 1: that started by blogging, right, so, you know, Gizmoto formerly Gawker,

1416
01:09:34,120 --> 01:09:35,920
Speaker 1: like they're sort of still all in and they still

1417
01:09:35,960 --> 01:09:38,000
Speaker 1: do good work. I mean, I think it's you know,

1418
01:09:38,120 --> 01:09:39,960
Speaker 1: it's always been uneven, but like the good stuff has

1419
01:09:39,960 --> 01:09:43,160
Speaker 1: always been good. You know, BuzzFeed still feels like a blog, um,

1420
01:09:43,479 --> 01:09:45,719
Speaker 1: even though you know, I don't like you can define

1421
01:09:45,760 --> 01:09:48,440
Speaker 1: blog however you want, but like that that that aesthetic,

1422
01:09:48,640 --> 01:09:51,360
Speaker 1: that voice is still there. Can we say the blogosphere

1423
01:09:51,840 --> 01:09:55,880
Speaker 1: is a meritocracy? Or is that overstating Yeah? I think

1424
01:09:55,920 --> 01:09:58,560
Speaker 1: that's overstating it because you still have the same dynamics

1425
01:09:58,600 --> 01:10:00,200
Speaker 1: you have in a lot of media. Would one of

1426
01:10:00,240 --> 01:10:02,559
Speaker 1: which is just simple, like you know, old boys network,

1427
01:10:02,640 --> 01:10:04,760
Speaker 1: like people promote who they know and these kinds of things.

1428
01:10:05,160 --> 01:10:08,160
Speaker 1: I think it's easier to get in. UM. I think

1429
01:10:08,200 --> 01:10:10,800
Speaker 1: you can blog your way to being the voice on

1430
01:10:10,840 --> 01:10:13,400
Speaker 1: a certain topic. Like if you have a certain niche

1431
01:10:13,479 --> 01:10:16,479
Speaker 1: or a certain subject that you are just obsessive about

1432
01:10:16,640 --> 01:10:18,519
Speaker 1: and you go all in on and you just keep

1433
01:10:18,560 --> 01:10:22,320
Speaker 1: bloging about it, you can own that topic or that idea. UM,

1434
01:10:22,439 --> 01:10:24,560
Speaker 1: and that's still true. I think if you're in a

1435
01:10:24,680 --> 01:10:27,040
Speaker 1: popular subject of you know, you know, the sort of

1436
01:10:27,080 --> 01:10:29,599
Speaker 1: like like for me, like a generic tech blog about

1437
01:10:29,640 --> 01:10:33,400
Speaker 1: what's happening in the tech industry, it's really really hard

1438
01:10:33,439 --> 01:10:35,040
Speaker 1: to break out. And that is going to be about

1439
01:10:35,640 --> 01:10:37,519
Speaker 1: do you have the relationships? Do you have somebody who's

1440
01:10:37,520 --> 01:10:40,439
Speaker 1: gonna scratch your back by giving you traffic? Let's jump

1441
01:10:40,560 --> 01:10:43,559
Speaker 1: right into our favorite questions. Tell me something. The most

1442
01:10:43,600 --> 01:10:47,920
Speaker 1: important thing people don't know about your background. UM, A

1443
01:10:48,000 --> 01:10:49,479
Speaker 1: lot of people don't know that I am from a

1444
01:10:49,560 --> 01:10:52,240
Speaker 1: tiny little town in rural Pennsylvania and that we were

1445
01:10:52,360 --> 01:10:57,000
Speaker 1: one of the only uh certainly only Asian families uh

1446
01:10:57,120 --> 01:11:00,360
Speaker 1: and that and that really UM informed out of my

1447
01:11:00,479 --> 01:11:03,400
Speaker 1: view of like having a very different, probably the opposite

1448
01:11:03,439 --> 01:11:06,600
Speaker 1: perspective of living in a big city like Manhattan. Understandable,

1449
01:11:07,160 --> 01:11:10,000
Speaker 1: who are some of your early mentors. Um, I've been

1450
01:11:10,080 --> 01:11:11,600
Speaker 1: very lucky to have a lot of good ones. I

1451
01:11:11,720 --> 01:11:15,200
Speaker 1: had a business partner named Fred Burke, who was my

1452
01:11:15,240 --> 01:11:16,880
Speaker 1: partner in my first company I started the day after

1453
01:11:16,880 --> 01:11:18,920
Speaker 1: I graduated high school, and he taught me a ton

1454
01:11:18,960 --> 01:11:22,160
Speaker 1: about sales and marketing and that was really really instructive.

1455
01:11:23,240 --> 01:11:28,320
Speaker 1: Who most influenced your approach to technology and entrepreneurship? Um,

1456
01:11:28,600 --> 01:11:31,479
Speaker 1: maybe one of the biggest influences is Dan Brocklin, who

1457
01:11:31,600 --> 01:11:37,040
Speaker 1: is the inventor of the spreadsheet and later later it

1458
01:11:37,080 --> 01:11:39,200
Speaker 1: sold it to Lettus and was working with Mr k

1459
01:11:39,280 --> 01:11:41,320
Speaker 1: Port and that team that made one too three. But

1460
01:11:41,520 --> 01:11:45,880
Speaker 1: Dan is one of the more thoughtful, brilliant, creative voices,

1461
01:11:46,120 --> 01:11:48,000
Speaker 1: you know, really undersung as one of the heroes of

1462
01:11:48,040 --> 01:11:51,080
Speaker 1: the tech industry and um super generous with his thoughts

1463
01:11:51,120 --> 01:11:54,000
Speaker 1: and ideas. This is the question that listeners ask all

1464
01:11:54,040 --> 01:11:57,719
Speaker 1: about constantly. This is the most asked question from listeners.

1465
01:11:58,200 --> 01:12:01,720
Speaker 1: What are some of your favorite books? Favorite books? UM,

1466
01:12:03,160 --> 01:12:06,720
Speaker 1: The Powerbroker, Robert Carross, Bio Robert most classic and and

1467
01:12:06,880 --> 01:12:10,360
Speaker 1: and also really teaches systems thinking. Um, so that's one

1468
01:12:10,360 --> 01:12:16,479
Speaker 1: of those that really really jumps out. Um. Uh. David

1469
01:12:16,600 --> 01:12:22,479
Speaker 1: Ritz did a biography of Aretha Franklin. Really and it

1470
01:12:22,720 --> 01:12:25,560
Speaker 1: is it is it's almost a history of America in

1471
01:12:25,760 --> 01:12:28,200
Speaker 1: the form of a biographyavor Wretha Franklin. It is such

1472
01:12:28,240 --> 01:12:34,160
Speaker 1: a brilliant, brilliant David Ritz, Yeah, the biography of Aretha Franklin. Yeah, yeah,

1473
01:12:34,280 --> 01:12:36,840
Speaker 1: see I would have named that respect if Yeah. He

1474
01:12:37,000 --> 01:12:38,800
Speaker 1: I forget what, I forget what the actual titles and

1475
01:12:39,160 --> 01:12:41,080
Speaker 1: they there's a bunch of books about are name of respect,

1476
01:12:41,160 --> 01:12:43,920
Speaker 1: so they didn't go with that name. But it is, um,

1477
01:12:44,560 --> 01:12:46,360
Speaker 1: it is actually one of the best business books that

1478
01:12:46,360 --> 01:12:49,240
Speaker 1: I've read in a long time. Really, Yeah, that's quite fascinating.

1479
01:12:49,280 --> 01:12:54,519
Speaker 1: And give me one more. Oh, um fiction nonfiction technom. Yeah,

1480
01:12:54,640 --> 01:12:58,120
Speaker 1: that's there's so many, it's really it's it's give us

1481
01:12:58,200 --> 01:13:01,200
Speaker 1: ten more. There was actually, um, I'm gonna forget the

1482
01:13:01,280 --> 01:13:02,599
Speaker 1: name of it, there was a book about the creation

1483
01:13:02,640 --> 01:13:06,040
Speaker 1: of the Highline Park here in New York City, um,

1484
01:13:06,160 --> 01:13:08,320
Speaker 1: and how it started as a really a community movement

1485
01:13:08,360 --> 01:13:10,280
Speaker 1: and it became this sort of you know, one of

1486
01:13:10,320 --> 01:13:13,120
Speaker 1: the top landmarks in the city. Now touris to visit.

1487
01:13:13,439 --> 01:13:16,120
Speaker 1: Those guys are actually consulting around the world, people are

1488
01:13:16,120 --> 01:13:18,000
Speaker 1: trying to do similar and they did such a good

1489
01:13:18,040 --> 01:13:20,320
Speaker 1: job of telling story and of even being self critical

1490
01:13:20,800 --> 01:13:24,000
Speaker 1: about the mistakes they made. UM, and for example that

1491
01:13:24,080 --> 01:13:25,920
Speaker 1: the park is not really inclusive enough of the community

1492
01:13:25,960 --> 01:13:28,320
Speaker 1: that that's part of UM. I thought it was just

1493
01:13:28,560 --> 01:13:31,040
Speaker 1: very thoughtful and nuanced and also showed how you can

1494
01:13:31,120 --> 01:13:34,559
Speaker 1: build things that are improbably ambitious and make them happen. Anyway,

1495
01:13:34,640 --> 01:13:36,840
Speaker 1: now now they're talking about trying to create an underground

1496
01:13:36,920 --> 01:13:39,920
Speaker 1: park from it. I don't know if that will really

1497
01:13:39,960 --> 01:13:43,040
Speaker 1: work to the same degree. But listen, no one thought

1498
01:13:43,080 --> 01:13:46,160
Speaker 1: the Highline would work. It's been a home run. UM.

1499
01:13:46,400 --> 01:13:49,120
Speaker 1: Since you've joined tech, tell us about what you think

1500
01:13:49,160 --> 01:13:53,280
Speaker 1: are the most significant changes. UM. You know what I

1501
01:13:53,320 --> 01:13:55,880
Speaker 1: would say these past couple of weeks has been one

1502
01:13:55,920 --> 01:13:59,720
Speaker 1: of the most significant milestones, which is this this wreckling

1503
01:14:00,040 --> 01:14:02,800
Speaker 1: of you know, vcs being pushed out of their own

1504
01:14:02,840 --> 01:14:07,320
Speaker 1: funds on ethical grounds Susan Fowler blog post, which was

1505
01:14:07,360 --> 01:14:09,719
Speaker 1: really powerful, which is amazing because that post was around

1506
01:14:09,760 --> 01:14:12,679
Speaker 1: for months before it seems to have gained any traction. Yeah. Yeah,

1507
01:14:12,760 --> 01:14:14,760
Speaker 1: and and also there were voices before her, right, And

1508
01:14:15,080 --> 01:14:17,120
Speaker 1: you know, I think the fact that just a steady

1509
01:14:17,200 --> 01:14:20,320
Speaker 1: drumbeat of activism worked and that you have things like

1510
01:14:20,479 --> 01:14:22,320
Speaker 1: you know, the CEO of Uber stepping down. I think

1511
01:14:22,400 --> 01:14:25,280
Speaker 1: these are hopefully a moment of reckoning for so many

1512
01:14:25,360 --> 01:14:26,720
Speaker 1: of us that have been talking about the need for

1513
01:14:26,800 --> 01:14:29,960
Speaker 1: tech to be more ethical, more humane, more inclusive, to

1514
01:14:30,040 --> 01:14:33,200
Speaker 1: be able to really point at that having had some impact.

1515
01:14:33,280 --> 01:14:37,120
Speaker 1: And these are not victories, because these are horrible situations

1516
01:14:37,160 --> 01:14:39,639
Speaker 1: that people went through, but it's just the first time

1517
01:14:39,680 --> 01:14:43,280
Speaker 1: that we didn't completely lose after somebody had to endure

1518
01:14:43,400 --> 01:14:47,280
Speaker 1: these kinds of indignities at work. I suspect Travis, who

1519
01:14:47,520 --> 01:14:50,720
Speaker 1: owns fifty one plus percent of the voting stuff, is

1520
01:14:50,760 --> 01:14:54,120
Speaker 1: going to eventually find his way back when he's being

1521
01:14:54,439 --> 01:14:58,000
Speaker 1: you know, re educated and and the kindler, gentler Travis

1522
01:14:58,040 --> 01:15:01,400
Speaker 1: will show up. But you never know. Um. So that's

1523
01:15:01,600 --> 01:15:03,720
Speaker 1: that's the changes that have taken place. What do you

1524
01:15:03,760 --> 01:15:06,839
Speaker 1: think the next major changes are? And it's only technology,

1525
01:15:06,880 --> 01:15:11,840
Speaker 1: it's not a big field that I do think there

1526
01:15:12,040 --> 01:15:14,880
Speaker 1: is um a return to first principles about people being

1527
01:15:14,880 --> 01:15:17,880
Speaker 1: able to create on their own, which is that, you know,

1528
01:15:17,960 --> 01:15:19,320
Speaker 1: the promise of the web was that we were all

1529
01:15:19,360 --> 01:15:20,800
Speaker 1: going to have a voice and we have a place,

1530
01:15:21,280 --> 01:15:23,200
Speaker 1: and that we would be able to publish and create things.

1531
01:15:23,400 --> 01:15:27,160
Speaker 1: And there is such a centralization happening around Facebook, Google,

1532
01:15:27,720 --> 01:15:32,840
Speaker 1: you know, go to those two exactly and about that

1533
01:15:33,000 --> 01:15:36,760
Speaker 1: much of the tech platform development. So what developers are

1534
01:15:36,800 --> 01:15:39,439
Speaker 1: doing outside in the world is I'm doing this for iOS,

1535
01:15:39,520 --> 01:15:41,880
Speaker 1: for for Apple, I'm doing this for Android for Google,

1536
01:15:42,320 --> 01:15:43,760
Speaker 1: and being able to go back and say, well, the

1537
01:15:43,800 --> 01:15:46,439
Speaker 1: web itself is still the bigger platforms. So the biggest

1538
01:15:46,439 --> 01:15:48,840
Speaker 1: platform has ever existed. How do you create for that

1539
01:15:49,040 --> 01:15:51,160
Speaker 1: and support that and express yourself there? And I mean,

1540
01:15:51,520 --> 01:15:53,320
Speaker 1: you know, we have a dog in this fight with

1541
01:15:53,360 --> 01:15:55,840
Speaker 1: glitch where I'm very lucky because developers love it and

1542
01:15:55,880 --> 01:15:58,120
Speaker 1: they're catching on and and really saying like this is

1543
01:15:58,200 --> 01:15:59,920
Speaker 1: one of the things that gives us hope. But I

1544
01:16:00,000 --> 01:16:02,479
Speaker 1: think it's a broader movement, which is um what brought

1545
01:16:02,520 --> 01:16:03,880
Speaker 1: a lot of us to the web in the first place,

1546
01:16:03,920 --> 01:16:05,519
Speaker 1: the idea that we could create something in the world

1547
01:16:05,600 --> 01:16:07,560
Speaker 1: could find it and respond to it and make it

1548
01:16:07,600 --> 01:16:10,800
Speaker 1: a successful So this is a standard question I asked people,

1549
01:16:11,080 --> 01:16:15,719
Speaker 1: but it's especially poignant for you. Tell us about a fail.

1550
01:16:16,000 --> 01:16:18,320
Speaker 1: Tell us about a time you failed and what you

1551
01:16:18,439 --> 01:16:21,000
Speaker 1: learned from the experience. And if people want to know

1552
01:16:21,200 --> 01:16:25,320
Speaker 1: why that is a point in question, just google anal

1553
01:16:25,439 --> 01:16:30,240
Speaker 1: dash and quote fail and you'll understand why. Um, I

1554
01:16:30,360 --> 01:16:34,760
Speaker 1: do think one of the biggest failures was in being

1555
01:16:34,800 --> 01:16:36,559
Speaker 1: part of the community that created the first social media

1556
01:16:36,600 --> 01:16:41,800
Speaker 1: and social networking tools. We were so desperate for and

1557
01:16:41,880 --> 01:16:44,479
Speaker 1: hungry for people to use them and optimize for growth

1558
01:16:45,280 --> 01:16:51,200
Speaker 1: at the expense of making these environments humane and thoughtful

1559
01:16:51,280 --> 01:16:54,320
Speaker 1: for people, and and so there's been a tremendous social

1560
01:16:54,400 --> 01:16:56,760
Speaker 1: costs where Yeah, everybody got connected, and it's great, it's

1561
01:16:56,760 --> 01:16:59,120
Speaker 1: amazing to be able to send messages and media and

1562
01:16:59,200 --> 01:17:03,320
Speaker 1: photos to people instantly anywhere in the world, but it

1563
01:17:03,360 --> 01:17:05,760
Speaker 1: should have also been something that empowered the people, most

1564
01:17:05,840 --> 01:17:09,160
Speaker 1: of the margins, most vulnerable, to be able to advocate

1565
01:17:09,200 --> 01:17:12,320
Speaker 1: for themselves. And and instead, in many ways, we re

1566
01:17:12,600 --> 01:17:17,240
Speaker 1: victimized them. And um that is something that I hope

1567
01:17:17,280 --> 01:17:19,479
Speaker 1: to spend the rest of my career working to fix.

1568
01:17:19,640 --> 01:17:23,439
Speaker 1: To be fair to you guys, that's like third level

1569
01:17:23,520 --> 01:17:25,760
Speaker 1: thinking at the time, it's hey, is anybody going to

1570
01:17:25,880 --> 01:17:30,040
Speaker 1: use these tools? Not the is gonna become widespread, widespread adoption,

1571
01:17:30,200 --> 01:17:34,760
Speaker 1: It'll be enormously successful, so successful that trolls are going

1572
01:17:34,800 --> 01:17:36,880
Speaker 1: to be a problem in the common sense that that

1573
01:17:37,040 --> 01:17:41,400
Speaker 1: was just ends. Yeah, you know, you know, someday there's

1574
01:17:41,400 --> 01:17:43,920
Speaker 1: gonna be a million people on social media, and she

1575
01:17:44,120 --> 01:17:45,560
Speaker 1: was you know, she was founder of our company, and

1576
01:17:45,640 --> 01:17:48,320
Speaker 1: she's like, you idiot, there's gonna be a hundred million people.

1577
01:17:48,600 --> 01:17:50,960
Speaker 1: Of course, then it turns out there's a billion, and so,

1578
01:17:51,280 --> 01:17:55,200
Speaker 1: you know, you would never it would have been absurd

1579
01:17:55,439 --> 01:17:57,400
Speaker 1: if we had said, let's plan for what happens when

1580
01:17:57,400 --> 01:17:59,439
Speaker 1: a billion people show up on these social networks, because

1581
01:17:59,479 --> 01:18:00,960
Speaker 1: people like you're of your mind. There aren't a billion

1582
01:18:01,000 --> 01:18:03,840
Speaker 1: people with computers, right, but there are a billion people

1583
01:18:03,880 --> 01:18:09,000
Speaker 1: with smartphones. It was just so there was no like

1584
01:18:09,080 --> 01:18:12,000
Speaker 1: science fiction that that's exactly right. Um, what do you

1585
01:18:12,080 --> 01:18:15,320
Speaker 1: do to keep mentally? You're physically fit outside of the office,

1586
01:18:15,360 --> 01:18:17,880
Speaker 1: what do you do to relax? I love music. I

1587
01:18:17,920 --> 01:18:21,639
Speaker 1: know you're a music fan. I I still am. I'm

1588
01:18:21,680 --> 01:18:23,960
Speaker 1: sort of notorious for being a big Prince fan even

1589
01:18:24,000 --> 01:18:27,280
Speaker 1: before he passed away. But I love sort of cataloging

1590
01:18:27,479 --> 01:18:29,560
Speaker 1: his work and so he's showing the cultural impact and

1591
01:18:29,640 --> 01:18:32,800
Speaker 1: so it's it's it's a fun hobby because you cross

1592
01:18:32,840 --> 01:18:35,320
Speaker 1: paths with like an improbable cross section of life. Like

1593
01:18:35,400 --> 01:18:38,320
Speaker 1: there are people in politics and media, all these different

1594
01:18:38,320 --> 01:18:40,479
Speaker 1: disciplines that are like, oh, you know whatever, they like

1595
01:18:40,520 --> 01:18:42,320
Speaker 1: the music. It's fun, but also this like, oh, he

1596
01:18:42,439 --> 01:18:44,639
Speaker 1: was a pioneer in tech and did all these sort

1597
01:18:44,640 --> 01:18:46,439
Speaker 1: of interesting cultural things. And then of course just at

1598
01:18:46,479 --> 01:18:48,920
Speaker 1: a human level for me, like, um, one of the

1599
01:18:48,960 --> 01:18:50,599
Speaker 1: best ways to clear my head is I have got

1600
01:18:50,640 --> 01:18:52,320
Speaker 1: a six year old son and will go out and

1601
01:18:52,600 --> 01:18:54,720
Speaker 1: you know, just sort of do something fun. Go to

1602
01:18:54,760 --> 01:18:57,240
Speaker 1: a museum, uh, you know, walk around the neighborhood, take

1603
01:18:57,280 --> 01:19:00,120
Speaker 1: the dog for a walk, and I am now for

1604
01:19:00,600 --> 01:19:03,360
Speaker 1: not reset by spending it just a little bit of

1605
01:19:03,400 --> 01:19:04,840
Speaker 1: time listening to him in his view of the world.

1606
01:19:05,760 --> 01:19:09,160
Speaker 1: That's a lot of fun. If UM, if a millennial

1607
01:19:09,320 --> 01:19:11,160
Speaker 1: came to you, or someone at the beginning of their

1608
01:19:11,240 --> 01:19:14,000
Speaker 1: career came to you and said, hey, I'm interested in

1609
01:19:14,400 --> 01:19:18,360
Speaker 1: going into tech or social community, what sort of advice

1610
01:19:18,520 --> 01:19:22,040
Speaker 1: might you give them? Um? One of the key things is, uh,

1611
01:19:22,520 --> 01:19:26,920
Speaker 1: find this topic about which you are irrationally passionate, like

1612
01:19:27,200 --> 01:19:29,400
Speaker 1: so that it can be as narrow as niche as

1613
01:19:29,439 --> 01:19:31,559
Speaker 1: you want. But if you can be the person who

1614
01:19:31,680 --> 01:19:34,120
Speaker 1: is the one person in the world who is most

1615
01:19:34,160 --> 01:19:36,000
Speaker 1: in love with that idea and knows the most about it,

1616
01:19:36,360 --> 01:19:39,719
Speaker 1: obsesses over it, and really just owns it, Um, there's

1617
01:19:39,760 --> 01:19:42,040
Speaker 1: something there for you like you you can you can

1618
01:19:42,160 --> 01:19:45,200
Speaker 1: really build a whole career around that because you can't

1619
01:19:45,280 --> 01:19:47,400
Speaker 1: win on Like everybody is chasing this one trend and

1620
01:19:47,439 --> 01:19:49,120
Speaker 1: I'm going to be part of it. I think that's

1621
01:19:49,160 --> 01:19:52,760
Speaker 1: really key. I think the other part um, because the

1622
01:19:52,800 --> 01:19:55,560
Speaker 1: tide is starting to turn, particularly in tech, find the

1623
01:19:55,600 --> 01:19:59,960
Speaker 1: people who are most of the margins, least connected, least central,

1624
01:20:00,000 --> 01:20:04,719
Speaker 1: at least privileged in tech and lift them up because

1625
01:20:04,760 --> 01:20:07,000
Speaker 1: people one day will remember it. They'll never forget you

1626
01:20:07,120 --> 01:20:08,760
Speaker 1: did it too. I think that is who is a

1627
01:20:08,760 --> 01:20:11,960
Speaker 1: sentant broadly is the people on on the outside are saying, Okay,

1628
01:20:12,040 --> 01:20:13,880
Speaker 1: I want to be part of this success, that I

1629
01:20:13,960 --> 01:20:16,040
Speaker 1: want to benefit from it. And three it's just the

1630
01:20:16,160 --> 01:20:18,879
Speaker 1: right thing to do. It feels good. And our final question,

1631
01:20:19,600 --> 01:20:22,479
Speaker 1: what is it that you know about technology and social

1632
01:20:22,560 --> 01:20:26,320
Speaker 1: networks today that you wish you knew seventeen or twenty

1633
01:20:26,439 --> 01:20:30,440
Speaker 1: years ago? Um? I wish I had known that technology

1634
01:20:31,479 --> 01:20:33,960
Speaker 1: follows the same rules of human society that the physical

1635
01:20:34,000 --> 01:20:36,519
Speaker 1: world does. In the same way that we architect our

1636
01:20:36,560 --> 01:20:41,920
Speaker 1: buildings and design our communities in our neighborhoods to be safe, comfortable, welcoming,

1637
01:20:42,080 --> 01:20:44,920
Speaker 1: warm places for us to live. We need to put

1638
01:20:44,960 --> 01:20:47,560
Speaker 1: the same thought into designing our digital spaces so that

1639
01:20:47,680 --> 01:20:50,840
Speaker 1: people are welcoming and kind to each other and treat

1640
01:20:50,880 --> 01:20:53,600
Speaker 1: each other well and feel neighborly towards one another. And

1641
01:20:53,800 --> 01:20:56,439
Speaker 1: if we can just repeat a lot of the lessons

1642
01:20:56,520 --> 01:20:59,880
Speaker 1: that the last ten thousand years of civilization have taught us, uh,

1643
01:21:00,120 --> 01:21:02,120
Speaker 1: we can make being online and in our apps a

1644
01:21:02,240 --> 01:21:07,240
Speaker 1: lot more thoughtful and rewarding experience. We have been speaking

1645
01:21:07,360 --> 01:21:11,360
Speaker 1: with Anald Dash he is the CEO of fog Creek Software.

1646
01:21:12,040 --> 01:21:13,720
Speaker 1: Be sure and look up an inch or down an

1647
01:21:13,760 --> 01:21:16,280
Speaker 1: inch on Apple iTunes and you could see any of

1648
01:21:16,320 --> 01:21:20,439
Speaker 1: the other hundred and fifty or so such conversations. We

1649
01:21:20,680 --> 01:21:25,439
Speaker 1: love your feedback, comments and suggestions right to me at

1650
01:21:25,720 --> 01:21:29,439
Speaker 1: m IB podcast at Bloomberg dot net. I would be

1651
01:21:29,560 --> 01:21:32,960
Speaker 1: remiss if I did not thank my audio engineer Charlie Valmer,

1652
01:21:33,439 --> 01:21:37,599
Speaker 1: my head of research Michael bat Nick, and my booker

1653
01:21:37,640 --> 01:21:42,160
Speaker 1: slash producer Taylor Riggs. I'm Barry Ritolts. You're listening to

1654
01:21:42,400 --> 01:21:44,880
Speaker 1: Masters in Business on Bloomberg Radio.