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Speaker 1: Welcome, Welcome, Welcome back to the Bob left Fess Podcast.

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Speaker 1: My guest today is writer, musician, investor Roger macum. Roger,

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Speaker 1: it is so good to be here with you, Bob. Okay,

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Speaker 1: so Roger, how are you coping with the COVID nineteen era, So, Bob,

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Speaker 1: After a two weeks where I was really trying to

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Speaker 1: figure out which way was up, I decided to adopt

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Speaker 1: a full zen program, and I am now one with

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Speaker 1: the quarantine and it's really working for me. Okay, let's

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Speaker 1: go a little bit deeper. You're one with the quarantine.

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Speaker 1: Do you leave your domicile almost never. I'm lucky to

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Speaker 1: live in a semi rural area where I can go

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Speaker 1: for walks and get out without going near anyone else,

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Speaker 1: and that is pretty much where I am. I'm really

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Speaker 1: lucky because where we live, one of my bandmates chose

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Speaker 1: to shelter with us, and so we have been able

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Speaker 1: to play music every day, and we do a live

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Speaker 1: stream that's on our websites, on Facebook, on Twitter, and

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Speaker 1: YouTube every single day and that has made the whole experience.

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Speaker 1: It's given it a focus that's really been for me

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Speaker 1: at least wild change from three and a half years

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Speaker 1: of activism where I was on the road seven days

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Speaker 1: a week and you know, banging my head against a

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Speaker 1: wall trying to protect democracy from internet platforms. So let's

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Speaker 1: go back to the band. Why don't you uh tell

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Speaker 1: give us the U r L for those who are

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Speaker 1: unfamiliar to so they can live stream. So everybody should

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Speaker 1: understand that when I was in high school, I was

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Speaker 1: in a really really sorry When I was in college,

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Speaker 1: I was in a really cool band, but the lead

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Speaker 1: songwriter in the band didn't want to go for it,

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Speaker 1: and so I was one of these people who was

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Speaker 1: like completely left at the altar and felt crushed about it.

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Speaker 1: And I went and got a real job because I

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Speaker 1: had what was a ridiculous amount of student loans for

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Speaker 1: that period, and I felt like I couldn't afford to

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Speaker 1: take a risk starting from scratch, but I always wanted

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Speaker 1: to play, so I kept playing you know, happy hours

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Speaker 1: and small band things all the way through. And then

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Speaker 1: about twenty years ago, I decided that I had gotten

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Speaker 1: far enough in my day job career that I could

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Speaker 1: afford to try to get serious and convert the industry

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Speaker 1: group I was in from a garage band into something

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Speaker 1: real and then it evolved into a full time band

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Speaker 1: called Moon Else. Uh T Bone. Burnett put us together,

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Speaker 1: recorded the first album, and the notion was he'd just

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Speaker 1: done Oh Brother Ware Art Thou and it was a

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Speaker 1: huge hit, and so he was going to do a

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Speaker 1: series of albums of Americano music in different styles. So

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Speaker 1: the notion was reinterpreting them, and he did three at

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Speaker 1: the same time. We were supposed to take the sound

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Speaker 1: of the Hate Ashbury and reinterpret it, and then he

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Speaker 1: got h Elvis Costello to do kind of I think

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Speaker 1: a New York folk thing, but what he really got

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Speaker 1: was Alison Krauss and Robert Plant to do Raising Sand,

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Speaker 1: which of course became huge, and we and Elvis were

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Speaker 1: completely forgotten in the mix. I mean, we got the

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Speaker 1: album done in all, but you know, Raising Sand sucked

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Speaker 1: all the oxygen out of the room, and that forced

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Speaker 1: Moon Else, which at the time included Jack Cassidy from

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Speaker 1: the Jefferson Airplane, included Geez Smith, included people who have

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Speaker 1: been part of the Grateful Dead extended family. That band

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Speaker 1: essentially had to focus on finding another way to get attention,

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Speaker 1: and beginning in two thousand and eight, we focused on

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Speaker 1: Facebook and Twitter, So we did the first live shows

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Speaker 1: on on Twitter, and then we did we we figured

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Speaker 1: out how to use Facebook to build an audience, and

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Speaker 1: we got the hundreds of thousands of people with ridiculously

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Speaker 1: high levels of engagement as the band gradually figured out

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Speaker 1: what it's, what its thing was, and you know, we've

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Speaker 1: been at it now thirteen years and now we're called

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Speaker 1: Full Moon Eilis because last summer we added Lester Chambers

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Speaker 1: and his son Dylan from the Chambers Brothers and the

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Speaker 1: Tea Sisters, who are three sisters who sing tight harmony

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Speaker 1: to what was basically a hippie band. You know. So

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Speaker 1: we were really good instrumentally and our vocals were We're

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Speaker 1: good enough but not great. Now we've added these unbelievable

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Speaker 1: vocals and we've just recorded new album and we were

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Speaker 1: about to begin our first tour of theaters, right it

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Speaker 1: was supposed to start basically March one, and you know,

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Speaker 1: we had like I want to say, seventy shows set

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Speaker 1: up for this year, two thirds of the theaters, and

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Speaker 1: it was going to be really excited because Full Moon Elis,

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Speaker 1: you know, the notion of bringing back the Chambers Brothers

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Speaker 1: psychedelic gospel and the fantastic harmonies of the Tea Sisters

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Speaker 1: on top of what we were doing. People were really

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Speaker 1: groo it on him, and of course, just like everybody else,

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Speaker 1: you know, we got shut down and uh, we've missed

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Speaker 1: all but one show from our and but we have

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Speaker 1: this album ready to go, and so we're going to

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Speaker 1: just try to launch an album. And if you go

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Speaker 1: to moon Alis dot com you can get the first

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Speaker 1: two songs, which include a new version of Time Has

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Speaker 1: Come Today with Lester now at age eight, on the

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Speaker 1: lead vocal as he was on the original and h

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Speaker 1: T sister song called Wo Wo that it's just it's

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Speaker 1: really hot and you can check those out if you like,

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Speaker 1: but it's you know, we're just like everybody else. So

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Speaker 1: we've we've resorted to pushing the technology really hard and

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Speaker 1: seeing what you can do with live streaming with multiple

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Speaker 1: locations and you know, we haven't solved the latency problem,

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Speaker 1: so we can't all play at the same time, but

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Speaker 1: we've been able to have all of us on screen

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Speaker 1: at the same time using a thing that's better than zoom,

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Speaker 1: and uh, with people playing from all locations but not together. Okay,

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Speaker 1: you know, this brings us to the question if you know,

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Speaker 1: the music business at large, recording end of it is

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Speaker 1: sort of solved with streaming not deeply affected by COVID nineteen,

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Speaker 1: but the touring business has been brought down to zero.

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Speaker 1: Do you have any insights on how you would address

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Speaker 1: this problem that may be able to move it forward.

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Speaker 1: I mean, Bob, we have spent our time doing almost nothing,

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Speaker 1: but so you know, we, like a million other people,

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Speaker 1: had the idea of how about driving movie theaters? Right,

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Speaker 1: and so we studied the economics, we started talking to

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Speaker 1: people who own theaters. Now do we begin doing this

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Speaker 1: some other more ago? And uh, you know, the problem

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Speaker 1: is the experience for the fans, right, I mean, you know,

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Speaker 1: the audio would be really imperfect. You can't get that

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Speaker 1: many people into them. The production costs are pretty high,

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Speaker 1: and so is it doable? Absolutely? Uh? Is it gonna

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Speaker 1: be hard? Yes? And you know the question of when

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Speaker 1: comes back? I think it's really super difficult because, let's

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Speaker 1: face it, we've mostly been hearing wishful thinking out of Washington.

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Speaker 1: And you know, as somebody made a professional career in

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Speaker 1: the daytime studying technology and studying economics, and you know,

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Speaker 1: I pretty good at reading the news and The thing

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Speaker 1: that really concerns me is that, you know, one, we

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Speaker 1: have no leadership in the country, and so our response

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Speaker 1: to this literally couldn't have been worse. And yet there's

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Speaker 1: no solution on the horizon. I mean, it might take

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Speaker 1: multiple years to get a vaccine that works in enough

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Speaker 1: supply to actually protect the country. So we're stuck for

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Speaker 1: a while. And what does that mean for live music?

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Speaker 1: I mean, we're going to have to find new models

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Speaker 1: because until then, when people get close together, there's a

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Speaker 1: really high risk of getting sick. And in my mind,

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Speaker 1: folks who are older, and our audience includes a lot

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Speaker 1: of you know, older folks, they're going to be really

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Speaker 1: hesitant about what they do. And uh, we we haven't

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Speaker 1: got that figured out yet, but we're going to keep

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Speaker 1: trying until we do. Okay, let's segue to the COVID

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Speaker 1: nineteen And it's important because the wind ever, the facts

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Speaker 1: don't really change, but the spin does. That we're recording

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Speaker 1: this Thursday, May fourteenth, Starting today, we wave a magic

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Speaker 1: wand you're in charge. What should we be doing in

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Speaker 1: the US or maybe worldwide to fight COVID nineteen. Well,

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Speaker 1: in my mind, the United States as biggest failing right

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Speaker 1: now is that we don't cooperate with the rest of

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Speaker 1: the world about anything. So we dropped out of the

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Speaker 1: International Confederation to develop a vaccine that is insane. So

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Speaker 1: on day one, I would get back into that and

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Speaker 1: I would go to everyone around the world and I

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Speaker 1: both listened to what they've learned, and I would adopt it.

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Speaker 1: Our problem was we spend two months in a form

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Speaker 1: of quarantine which slowed the spread of the disease without

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Speaker 1: actually shrinking it. So every other country went to a

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Speaker 1: more harsh form of quarantine. Well, let's let's just go back.

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Speaker 1: We stopped the spread, but we didn't shrink that. Please

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Speaker 1: amplify that from my audience. So essentially, the way to

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Speaker 1: think about this is if you look at New Zealand,

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Speaker 1: or you look at Taiwan, or you look at South Korea,

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Speaker 1: they implemented measures immediately, they tested immediately, they went to

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Speaker 1: social distancing immediately before there was widespread infection, and the

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Speaker 1: result of that behavior was that they stopped the thing

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Speaker 1: from spreading and made it possible to resume economic activity

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Speaker 1: after a couple of months. In our case, we waited

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Speaker 1: for almost two months after the first case before we

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Speaker 1: did anything significant. And then when we implemented our quarantine,

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Speaker 1: we did it in such a way that it was

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Speaker 1: already too late in the Northeast, and we didn't think

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Speaker 1: about elements of our economy like meat packing facilities, like

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Speaker 1: retirement homes, prisons where people are tightly packed and where

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Speaker 1: the normal behavior did not have public health standards that

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Speaker 1: would be resistant to a communicable disease like COVID. And

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Speaker 1: so the result is we are still having outbreaks at

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Speaker 1: exactly the time we're trying to reopen the economy. So,

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Speaker 1: you know, they talked about this rate of infection called

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Speaker 1: are not and you want to get that thing significantly

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Speaker 1: below one in order to get the actual spread of

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Speaker 1: the disease. Now that's how many people one person infects

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Speaker 1: can In fact, right, we started out I think around three,

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Speaker 1: you know, now we're down to just slightly over one.

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Speaker 1: And the result is we're sort of stable with twenty

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Speaker 1: to of thousand people a day being diagnosed and between

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Speaker 1: fifteen hundred a day dying. Well I'm sorry, but you

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Speaker 1: can do the man. I mean, you know, if you're

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Speaker 1: going to have let's say an average of two thousand

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Speaker 1: people a day dying, that's sixty people a month, right,

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Speaker 1: So that's bigger than Vietnam every single month. And you

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Speaker 1: know that means that by this time next year, if

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Speaker 1: it persists, of this time next year, you literally have

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Speaker 1: more people dead in a year than died in the

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Speaker 1: Second World War. And so that's not a solution, right.

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Speaker 1: We have to find a way to get the numbers

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Speaker 1: so that you know they're like everybody else, which is

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Speaker 1: to say that there are some days you have next

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Speaker 1: to no new infections and nobody dying, and we haven't

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Speaker 1: done any of the things to do that are testing

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Speaker 1: is woefully inadequate. We started so late that we missed

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Speaker 1: the window when this level of testing would have made

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Speaker 1: a difference. Now we need the testing to be five

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Speaker 1: times is great to produce the same effect that this

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Speaker 1: part would have done if we've done it three months ago.

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Speaker 1: And so I find all of that obviously alarming, because Bob,

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Speaker 1: you and I are not spring chickens, right, we are

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Speaker 1: in the portion of the population that needs to be

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Speaker 1: super careful, and many of our favorite people in the

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Speaker 1: music business are also, and obviously to the extent that

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Speaker 1: anybody has had any past health history, you know, if

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Speaker 1: you've ever had hypertension or heart disease or lung disease,

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Speaker 1: or you're a smoker or overweight or whatever. I mean,

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Speaker 1: those things just make it a lot more dangerous if

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Speaker 1: you've and god forbid, you've ever had cancer. And so

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Speaker 1: you know, to me, we've had a massive failure of

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Speaker 1: you know, public health administration in this country and there's

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Speaker 1: no sign of fixing that until best case, January of

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Speaker 1: next year, right, which is like, wow, you know that's

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Speaker 1: just okay, Just so I know what would happen theoretically

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Speaker 1: on January one next year. It wouldn't be January. Fe

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Speaker 1: be January right when you change presidents. Okay, but let's

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Speaker 1: I don't I don't want to make this false equivalences.

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Speaker 1: But since we the pass is locked in stone, if

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Speaker 1: hypothetically you were in charge today, what would you do?

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Speaker 1: So the first thing that I would do is that

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Speaker 1: I would I would simply there there too two paths.

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Speaker 1: I would take, one relative the economy and one relative

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Speaker 1: to the to the the coronavirus. And keep in mind,

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Speaker 1: I'm just a citizen. I have a professional analyst, so

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Speaker 1: I have Oh yeah, but the reason you have a

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Speaker 1: long history in tech, and just like with many people

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Speaker 1: saying about climate crisis, climate control in there there depending

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Speaker 1: on tech solutions. So your viewpoint is important. So to

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Speaker 1: be clear, I do not I think the tech industry

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Speaker 1: is grossly overstated what it can do on this. Relative

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Speaker 1: to the pandemic. We have got to find a way

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Speaker 1: to increase the testing by a factor of five, like immediately.

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Speaker 1: And we need to culturally and this notion that the

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Speaker 1: pandemic is part of the culture wars, this notion that

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Speaker 1: somehow people's liberty is being infringed upon because we're asking

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Speaker 1: them not to kill grandmother, grandfather or someone else in

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Speaker 1: their household. That I mean, we have you know, the

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Speaker 1: first thing I do is try to bridge that gap

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Speaker 1: politically and because we have to work together on this.

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Speaker 1: This is this is a situation where the country is

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Speaker 1: threatened in a way it has potentially never been threatened

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Speaker 1: in its homeland, certainly not since the Civil War. And

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Speaker 1: you know, we have to start doing the right thing.

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Speaker 1: But on the economy, I think it's really simple. Trump

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Speaker 1: has focused all of his energy on protecting his friends,

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Speaker 1: basically billionaires, large corporations, and that is insane. We have

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Speaker 1: got to have focused the energy on the people who

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Speaker 1: work in our economy and on the small businesses on

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Speaker 1: which it depends. And you know the thing that I

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Speaker 1: would do is I would I would sit there relative

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Speaker 1: to Congress and go here is the deal. Okay, we

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Speaker 1: need to have something that guarantees an income to every

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Speaker 1: single American for the duration of this crisis, and it

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Speaker 1: should be uncontestable, and we need to have billionaires paying

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Speaker 1: their share. From a taxpoint of view. You need to

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Speaker 1: have corporations recognizing that they're not going to be allowed

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Speaker 1: to use the pandemic as an excuse to harm employees

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Speaker 1: or to harm customers. And you know, the reality is

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Speaker 1: we're paying a price here because for forty years we

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Speaker 1: deregulated our economy in a way that shifted all the

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Speaker 1: power and most of the wealth to a tiny fraction

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Speaker 1: of the population. And you know, ideas that worked pretty

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Speaker 1: well in the eighties became a disaster by two thousand

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Speaker 1: and a train wreck. Recently, and my very strong opinion,

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Speaker 1: having spent a career looking at this stuff, is that

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Speaker 1: our economy right now looks like an authoritarian regime. You

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Speaker 1: have a small number of monopolies that dominate every industry,

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Speaker 1: and that contributed to magnifying the damage to the pandemic.

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Speaker 1: If you look at it, we had been firing employees

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Speaker 1: and shifting production of low cost things outside the US

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Speaker 1: for forty years, to the point where today you cannot

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Speaker 1: make cotton swaps in order to do a test. Right.

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Speaker 1: We've lost the ability to things that are absolutely essential

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Speaker 1: to the economy because we were so focused on optimizing

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Speaker 1: shareholder value in the short run, and our supply chains

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Speaker 1: are really fragile. Our health care system is a train wreck.

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Speaker 1: It is not designed for any kind of public health disaster.

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Speaker 1: In fact, the entire economy has no margin for everything

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Speaker 1: is so efficient that any disruption at all breaks. And

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Speaker 1: that is what's going on. That is why they are

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Speaker 1: thirty three million people that are explicitly unemployed. But the

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Speaker 1: reality is it's probably much much bigger than that. And

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Speaker 1: you know, you look at this and you just go.

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Speaker 1: The thing that I would be all over on day

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Speaker 1: one is a new new deal that we've got to

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Speaker 1: get out there and recognize that all of the people

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Speaker 1: that live in this country deserve to be treated better.

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Speaker 1: And so I would follow that up. For example, is

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Speaker 1: I mean I would reverse everything Trump has ever done

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Speaker 1: on immigration, and I would absolutely recognize that the people

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Speaker 1: whose jobs are on the front line. So these are

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Speaker 1: the people who work in healthcare, the people who work

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Speaker 1: in retail point of sale, particularly like grocery stores and pharmacies,

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Speaker 1: the people who work in u meat packing and other

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Speaker 1: food supply things. Those are essential abs, we say, but

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Speaker 1: we treat them like they're not, and that's insane. These

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Speaker 1: jobs need to be paid better. In fact, we need

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Speaker 1: to look at the whole ecounty. We need to recognize

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Speaker 1: that part of the reason we're here is that we

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Speaker 1: cripple public education, right, and so are are too many

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Speaker 1: people in our population have lost critical thinking and they

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Speaker 1: can't see facts as facts. They can't appreciate why expertise

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Speaker 1: really matters. And so I would love, you know, to

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Speaker 1: use the current environment to reset the whole economy and

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Speaker 1: to sit there and say, look, our goal should be

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Speaker 1: to get back to you know, we hold these truths

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Speaker 1: to be self evident. You know, everybody's created equal, right,

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Speaker 1: I want to form a more perfect union, and you

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Speaker 1: really want people to be able to pursue their lives

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Speaker 1: without fear. And you sit there and you look at

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Speaker 1: that poor situation where a jogger in Georgia is hunted

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Speaker 1: down and killed in broad daylight. And you said, you

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Speaker 1: see these guys in Michigan, armed to the teeth with

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Speaker 1: heavy weaponry, who are claiming that somehow their rights are

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Speaker 1: being infringed. I'm going the whole world is upside down.

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Speaker 1: It is backwards. And if you know, if you made

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Speaker 1: me president for a day, my goal would be to

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Speaker 1: try to remind people that we actually have shared interests,

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Speaker 1: that we you know, this notion that each one of

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Speaker 1: us is an independent like Marlborough man and not depend

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Speaker 1: on anybody else. I mean, that's ridiculous, and you can

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Speaker 1: see that in this pandemic. Okay, let's before we let's

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Speaker 1: just step focused on the other half for a second

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Speaker 1: before we leave it behind. How should we be fighting

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Speaker 1: COVID nineteen irrelevant of the economic effects. So here's the thing.

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Speaker 1: I'm no doctor, but I can tell you about the

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Speaker 1: tech part. Everything that you've heard it about contact tracing

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Speaker 1: using smartphones is nonsense. Everything you've heard about using surveillance

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Speaker 1: is nonsense. And here are the problems. So this notion

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Speaker 1: that a smartphone can be used to create automatic automated

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Speaker 1: contact tracing fails. For the following reasons. The core technology

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Speaker 1: and the smartphone that you would use to figure out

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Speaker 1: whether you got close to people who had symptoms or

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Speaker 1: people who actually were infected with COVID is bluetooth. And

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Speaker 1: the problem for this application with bluetooth is that while

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Speaker 1: it can get you within roughly six ft, it doesn't

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Speaker 1: recognize walls, So you can be within six ft of

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Speaker 1: somebody but nowhere near them relative to the disease. Because

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Speaker 1: there's a wall between you and the way the systems

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Speaker 1: are set up, it's very hard for them to keep

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Speaker 1: track of how long you are close to somebody. Right,

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Speaker 1: That's what Apple and Google are trying to create. They're

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Speaker 1: trying to create something that would would fix that. But

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Speaker 1: the fundamental problem is you're going to get massive numbers

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Speaker 1: of false positives, and that's going to require a ridiculous

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Speaker 1: level of processing. Because with a country of three and

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Speaker 1: thirty million people, if you get you know, if half

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Speaker 1: the things you get are false positives or two thirds

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Speaker 1: of the ones you get are false positives, that number

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Speaker 1: would be staggering. But it's going to be more like,

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Speaker 1: are gonna be false positives? And so let's assue for

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Speaker 1: by some miracle, just say to be inherently in the

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Speaker 1: way the phones are designed. This is an unsolvable problem,

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Speaker 1: or could Google and Apple come up with a solution

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Speaker 1: to this issue. Even enough time, you can come up

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Speaker 1: with a problem. But with the time constraints were under,

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Speaker 1: you're not going to get there fast enough, which is

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Speaker 1: a big reason why Google and Apple are radically narrowing

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Speaker 1: the scope of what they're trying to do. So the

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Speaker 1: second piece of the problem is artificial intelligence, which is

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Speaker 1: certainly artificial but not intelligence. The current state of artificial

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Speaker 1: intelligence is so grossly oversold that it will not help

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Speaker 1: you to solve the false positives problem. In fact, if

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Speaker 1: you look at it, all these people claiming that they

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Speaker 1: can create these uh heat based cameras to identify people

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Speaker 1: are sick. That is all utter nonsense, okay. And all

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Speaker 1: these people who say, well, I can look at a

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Speaker 1: picture of you and identify whether you have COVID or not.

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Speaker 1: I mean that is I don't know what language we

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Speaker 1: can use here, but that you can use any language

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Speaker 1: you choose. Bullshit. Okay, it is just not So doesn't

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Speaker 1: mean you can't get there eventually, but the current state

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Speaker 1: of the technology, it was not designed for that, and

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Speaker 1: so it's not going to get you there quickly. So

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Speaker 1: here's the thing that I believe really matters. When I

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Speaker 1: look at the tech industry my big problem and I've

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Speaker 1: spent you know, I've been there since night teen two, right,

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Speaker 1: so from when the Space program was the most important thing,

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Speaker 1: before PCs were the dominant stuff. So I've watched the

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Speaker 1: whole thing and I've had a front row seat. And

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Speaker 1: technology has so much promise, but the industry is out

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Speaker 1: of control and it fundamentally it it's driven by this

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Speaker 1: passion to take advantage of the weakest elements of human

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Speaker 1: psychology because the technology allot should do that. That's what's

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Speaker 1: wrong with YouTube and Facebook and is just just before

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Speaker 1: we go because now we're going down a very deep avenue.

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Speaker 1: But let me let me just fine. Fine, So they've

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Speaker 1: got that thing, but the other part, the enterprise products

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Speaker 1: all they're eliminating jobs. And I say, COVID is a

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Speaker 1: perfect opportunity to fix that problem. Because contact tracing is

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Speaker 1: actually best done by human beings enabled and empowered by

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Speaker 1: a small amount of automation. So the thing that Apple

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Speaker 1: and Google can do is, you know, empower a huge number,

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Speaker 1: you know, hundreds of thousands, maybe even millions of people

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Speaker 1: who are physically going and meeting people who have symptoms

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Speaker 1: and doing that contact tracing. It would have been so

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Speaker 1: much easier to do this when you're dealing with hundreds

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Speaker 1: or low thousands of infected patients. But here we are

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Speaker 1: in a million and a half. And so you know

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Speaker 1: you've got this problem that the contract tracing thing, the

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Speaker 1: scale of it is simply staggering. But here's the good news.

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Speaker 1: We have tens of millions of unemployed people and here's

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Speaker 1: an opportunity to put them all to work and to

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Speaker 1: use technology to enhance that. So the big piece I

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Speaker 1: would give our listeners to think about relative to technology today,

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Speaker 1: and COVID provides the perfect case in point, is that

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Speaker 1: we should not trust the technology can solve all our problems.

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Speaker 1: It's not a silver bol and we first certain should

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Speaker 1: not believe the promises given by the people who run

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Speaker 1: tech companies. There. They aren't all horrible people, but they

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Speaker 1: are relentlessly optimistic and the culture of the industry is

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Speaker 1: not what it needs to be. Tech is today where

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Speaker 1: the chemicals industry was in nineteen sixty when they spewed

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Speaker 1: toxic fumes into the air. When they poured mercury into

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Speaker 1: fresh water, when they left mine residue on the side

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Speaker 1: of the hill. They were profitable because they were destroying

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Speaker 1: the economy and the sorry. They were destroying the environment

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Speaker 1: and public health. The tech industry, the profits of Google

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Speaker 1: and Facebook are grossly overstated because they're destroying democracy, public health,

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Speaker 1: privacy in the economy. And so I look at this

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Speaker 1: and I go, COVID is the moment. This is the

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Speaker 1: pivot where we can sit there and go. Tech is

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Speaker 1: so important that like chemicals in nineteen sixty, like pharmaceuticals

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Speaker 1: in nineteen o six when we passed the Pure Food

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Speaker 1: and Drug Act, and just like the building trades after

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Speaker 1: the Chicago fire, when we realized we really needed to

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Speaker 1: make the people who build houses responsible for what they built.

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Speaker 1: That that you have to make tech accountable. And this

433
00:26:06,200 --> 00:26:08,840
Speaker 1: is a great opportunity to do that because we all

434
00:26:08,880 --> 00:26:11,320
Speaker 1: know how important it is in our lives. And the

435
00:26:11,359 --> 00:26:14,960
Speaker 1: future of tech could be so bright and it can

436
00:26:15,040 --> 00:26:18,520
Speaker 1: be so constructive. But if he keeps doing what it's

437
00:26:18,560 --> 00:26:21,000
Speaker 1: doing now, I mean, I look at Amazon. I'm so

438
00:26:21,119 --> 00:26:24,679
Speaker 1: frustrated because Jeff Bezos said he's going to take the

439
00:26:24,720 --> 00:26:26,960
Speaker 1: four billion dollars of profits he would otherwise make in

440
00:26:27,000 --> 00:26:29,480
Speaker 1: the Jeune quarter. He's going to push him all into

441
00:26:29,520 --> 00:26:32,000
Speaker 1: COVID stuff. And my question what's he going to put

442
00:26:32,000 --> 00:26:34,800
Speaker 1: it into. Is he going to proctect his employees. Is

443
00:26:34,880 --> 00:26:37,360
Speaker 1: he going to change the work rules in the warehouses

444
00:26:37,760 --> 00:26:41,120
Speaker 1: so that it's healthier to work in an Amazon warehouse?

445
00:26:41,560 --> 00:26:44,600
Speaker 1: Is he going to pay his people more? Because if

446
00:26:44,640 --> 00:26:47,560
Speaker 1: he was going to do all those things, that would

447
00:26:47,560 --> 00:26:50,280
Speaker 1: be huge. What I fear is that he's going to

448
00:26:50,359 --> 00:26:52,399
Speaker 1: spend a ton of money on computer solutions that he

449
00:26:52,440 --> 00:26:55,720
Speaker 1: can then sell to governments, and he's going to still

450
00:26:55,760 --> 00:26:58,680
Speaker 1: treat the employees really badly. And if that's true, that

451
00:26:58,720 --> 00:27:03,400
Speaker 1: will be a missed opportunity, completely tragic. Okay, we're segueing

452
00:27:03,440 --> 00:27:05,920
Speaker 1: into a whole thing in terms of if we know

453
00:27:06,680 --> 00:27:08,960
Speaker 1: that tech is not going to solve the problem, and

454
00:27:09,000 --> 00:27:13,600
Speaker 1: assuming there's no vaccine on the immediate horion horizon, you're saying,

455
00:27:13,600 --> 00:27:16,280
Speaker 1: put the unemployed people to work to do contact tracing

456
00:27:16,760 --> 00:27:20,600
Speaker 1: very slowly. How would you close down the spread of

457
00:27:20,600 --> 00:27:24,359
Speaker 1: the virus? Or maybe you don't. I don't know, Bob,

458
00:27:24,400 --> 00:27:26,160
Speaker 1: I wish I knew the answer to that. The one

459
00:27:26,200 --> 00:27:29,480
Speaker 1: thing I do know is that there is a silver

460
00:27:29,600 --> 00:27:33,879
Speaker 1: line with this whole thing. If you and I stay

461
00:27:33,880 --> 00:27:39,160
Speaker 1: physically isolated, we can come through this thing. Right. We're

462
00:27:39,160 --> 00:27:41,159
Speaker 1: in a position where you can do your job. I

463
00:27:41,160 --> 00:27:44,680
Speaker 1: can do my job in an isolated way. And that's

464
00:27:44,680 --> 00:27:49,199
Speaker 1: a lucky thing, right, because otherwise we're in h the

465
00:27:49,280 --> 00:27:52,719
Speaker 1: peer group of those with the greatest risk. Anybody in

466
00:27:52,720 --> 00:27:57,160
Speaker 1: that situation who has that opportunity is blessed. My core

467
00:27:57,280 --> 00:27:59,520
Speaker 1: question is what do you do about the people who

468
00:27:59,560 --> 00:28:02,359
Speaker 1: can't or to do that, whose jobs do not allow

469
00:28:02,440 --> 00:28:07,760
Speaker 1: them to be isolated, who's lack of political power this

470
00:28:08,320 --> 00:28:11,280
Speaker 1: means they have no protection, and so my focus is

471
00:28:11,320 --> 00:28:14,840
Speaker 1: on those people. And I would simply note that Amazon

472
00:28:14,920 --> 00:28:18,919
Speaker 1: employees have begun to push back, and not just the

473
00:28:18,960 --> 00:28:21,880
Speaker 1: people in the warehouses, right, Even salaried people who work

474
00:28:21,880 --> 00:28:24,960
Speaker 1: in headquarters have had some pushback, and I think that's

475
00:28:25,000 --> 00:28:28,800
Speaker 1: really excited. Citing teachers, We've had more teacher strikes in

476
00:28:28,800 --> 00:28:30,720
Speaker 1: the last two years that I think the prior twenty

477
00:28:30,800 --> 00:28:36,240
Speaker 1: put together. It's you know, it's time to have work

478
00:28:36,320 --> 00:28:41,280
Speaker 1: action everywhere in the economy. People in healthcare, people who

479
00:28:41,320 --> 00:28:44,080
Speaker 1: work in meat packing plans, people who work in prisons.

480
00:28:45,640 --> 00:28:49,400
Speaker 1: They have way more power than they realize, and it's

481
00:28:49,960 --> 00:28:52,720
Speaker 1: incumbent on all of us to help them. You know,

482
00:28:52,760 --> 00:28:55,800
Speaker 1: there were days when people didn't buy from Facebook, didn't

483
00:28:55,840 --> 00:28:59,360
Speaker 1: buy from instat cart to protest against their labor practices.

484
00:28:59,680 --> 00:29:01,280
Speaker 1: We need to have more of that kind of stuff.

485
00:29:01,320 --> 00:29:05,400
Speaker 1: We need to if if we always take the convenient path,

486
00:29:06,200 --> 00:29:08,640
Speaker 1: the country's gonna just keep going right off the Cliffic's

487
00:29:08,800 --> 00:29:11,840
Speaker 1: going off now, Okay, now, Naomi Klein wrote a whole

488
00:29:11,880 --> 00:29:15,520
Speaker 1: book called The Shock Doctrine talking about these big moments

489
00:29:15,680 --> 00:29:19,840
Speaker 1: in national history, and then they basically say, the powers

490
00:29:19,880 --> 00:29:23,040
Speaker 1: that be, the government and the corporations ram through things

491
00:29:23,160 --> 00:29:26,000
Speaker 1: to their advantage. You're delineating a lot of things that

492
00:29:26,000 --> 00:29:29,600
Speaker 1: would benefit the public. How do we make sure that

493
00:29:30,280 --> 00:29:33,120
Speaker 1: this crisis does benefit the public as opposed to the

494
00:29:33,280 --> 00:29:38,160
Speaker 1: fat cats. So at the moment, we're doing a terrible

495
00:29:38,240 --> 00:29:43,400
Speaker 1: job of that, right because Trump's whole stick is he

496
00:29:43,560 --> 00:29:46,120
Speaker 1: has the people he supports, and he really doesn't care

497
00:29:46,160 --> 00:29:53,480
Speaker 1: about anybody else. And the Democrats in Congress have moderated

498
00:29:53,600 --> 00:29:58,480
Speaker 1: some of his worst instincts, but because of McConnell in

499
00:29:58,560 --> 00:30:02,800
Speaker 1: the Senate, they have of not being able to do

500
00:30:03,120 --> 00:30:08,200
Speaker 1: what needs doing, and that I find incredibly distressing. And

501
00:30:09,080 --> 00:30:20,240
Speaker 1: if the pandemic gives Trump the ability two manipulate the

502
00:30:20,320 --> 00:30:27,800
Speaker 1: presidential election or two implement voter suppression techniques that are

503
00:30:27,840 --> 00:30:33,840
Speaker 1: as effective as the ones that we're employed in, you know,

504
00:30:34,080 --> 00:30:37,320
Speaker 1: we're going to have to work really hard to get

505
00:30:37,400 --> 00:30:41,240
Speaker 1: past this. I mean, job one has to be ending

506
00:30:41,320 --> 00:30:46,280
Speaker 1: the Trump presidency, and that there is I mean, the

507
00:30:46,520 --> 00:30:52,160
Speaker 1: fastest development of a vaccine in history, I believe was

508
00:30:52,280 --> 00:30:54,560
Speaker 1: the for the months and I think it took four years.

509
00:30:56,000 --> 00:30:58,680
Speaker 1: And my understanding is that it's not uncommon for a

510
00:30:58,760 --> 00:31:01,520
Speaker 1: vaccine to take twenty so more. I mean, AIDS has

511
00:31:01,600 --> 00:31:04,280
Speaker 1: been thirty years and we still don't have one. Uh.

512
00:31:04,840 --> 00:31:09,560
Speaker 1: And so I'm looking at this and just saying we're

513
00:31:09,600 --> 00:31:11,880
Speaker 1: going to be living with this for a while, and

514
00:31:12,040 --> 00:31:18,120
Speaker 1: it is essential that we followed naomi clients brilliant observations

515
00:31:18,160 --> 00:31:21,120
Speaker 1: about these moments and not waste this opportunity to get

516
00:31:21,160 --> 00:31:23,400
Speaker 1: it right. So I would look at everybody and say,

517
00:31:23,560 --> 00:31:27,280
Speaker 1: our job is not to go back to what the

518
00:31:27,360 --> 00:31:31,280
Speaker 1: world was before, because the world before actually sucked for

519
00:31:31,440 --> 00:31:37,160
Speaker 1: most people, right it massive income inequality, really unfair labor practices,

520
00:31:37,520 --> 00:31:44,120
Speaker 1: incredibly predatory business practices by large companies and our goal

521
00:31:44,240 --> 00:31:47,520
Speaker 1: should be to move forward to something much better. And

522
00:31:48,160 --> 00:31:50,360
Speaker 1: you know, I say this as somebody who's I spent

523
00:31:50,480 --> 00:31:52,920
Speaker 1: my whole life as a capitalist, But the truth is,

524
00:31:53,000 --> 00:31:55,160
Speaker 1: we haven't had capitalism in this country for at least

525
00:31:55,200 --> 00:31:58,640
Speaker 1: a decade because the world is dominated by monopolies. And

526
00:31:58,720 --> 00:32:04,240
Speaker 1: if you think back history, monopoly is associated with monarchy,

527
00:32:04,640 --> 00:32:08,960
Speaker 1: with authoritarianism because it creates balance it's easy to control

528
00:32:09,040 --> 00:32:14,760
Speaker 1: for an authoritarian whereas capitalism and democracy are really tightly aligned.

529
00:32:15,560 --> 00:32:19,200
Speaker 1: And I believe that the United States is a failed

530
00:32:19,360 --> 00:32:22,880
Speaker 1: democracy in many dimensions. And you can argue about how

531
00:32:23,000 --> 00:32:29,280
Speaker 1: far down the failure uh spectrum the country is, but

532
00:32:29,600 --> 00:32:33,000
Speaker 1: it's in my mind. You know, you've had to presidential

533
00:32:33,080 --> 00:32:36,920
Speaker 1: elections in the last twenty years where the loser of

534
00:32:36,960 --> 00:32:42,360
Speaker 1: the popular vote became president and that is clearly not

535
00:32:43,000 --> 00:32:53,440
Speaker 1: an outcome that is consistent with any normal view of democracy. Okay,

536
00:32:53,480 --> 00:32:55,760
Speaker 1: so let's talk about politics for a second, because it

537
00:32:55,880 --> 00:33:02,360
Speaker 1: leads into another topic. Uh In, Bernie Sanders gave Hillary

538
00:33:02,400 --> 00:33:07,000
Speaker 1: Clinton a real run for her money in the primaries.

539
00:33:07,440 --> 00:33:10,959
Speaker 1: We had Bernie Sanders on the left, we had Elizabeth

540
00:33:11,040 --> 00:33:14,720
Speaker 1: Warren on the left. Needles to say the ultimate nominee

541
00:33:14,760 --> 00:33:18,320
Speaker 1: at this point in time is Joe Biden. My personal

542
00:33:18,400 --> 00:33:22,880
Speaker 1: analysis is that once it appeared that Bernie Sanders was

543
00:33:22,960 --> 00:33:26,240
Speaker 1: going to be the nominee, the d n C and

544
00:33:26,400 --> 00:33:31,760
Speaker 1: the media, ie the New York Times primarily conspired to

545
00:33:31,920 --> 00:33:37,160
Speaker 1: make sure that didn't happen. So my questions are secondarily

546
00:33:37,760 --> 00:33:43,160
Speaker 1: how important is the media too? Can a candidate of

547
00:33:43,840 --> 00:33:48,920
Speaker 1: a what is seen as left today be successful? And see?

548
00:33:49,680 --> 00:33:52,640
Speaker 1: Are though those the people we should be running and

549
00:33:52,880 --> 00:33:56,600
Speaker 1: would they be embraced? So, Bob, I am so much

550
00:33:56,640 --> 00:33:59,520
Speaker 1: more close to politics in this country than I would

551
00:33:59,560 --> 00:34:02,480
Speaker 1: have been before I became an activist. You know, when

552
00:34:02,520 --> 00:34:08,759
Speaker 1: I started my campaign in basically the end of to

553
00:34:09,480 --> 00:34:12,160
Speaker 1: it really early to make the world aware of what

554
00:34:12,400 --> 00:34:16,239
Speaker 1: happened in the election, how Facebook and Instagram in particular,

555
00:34:16,680 --> 00:34:22,680
Speaker 1: and Twitter and YouTube were manipulated to distort the outcome

556
00:34:22,760 --> 00:34:25,919
Speaker 1: of our presidential election. And I tried to warn people

557
00:34:25,920 --> 00:34:29,239
Speaker 1: to prevent that from happening again. And what wound up

558
00:34:29,280 --> 00:34:31,360
Speaker 1: happening is I spent a huge amount of time in Washington.

559
00:34:31,360 --> 00:34:35,240
Speaker 1: I got to know a ton of people and learned

560
00:34:35,280 --> 00:34:38,080
Speaker 1: a lot about how our process works when it's working well,

561
00:34:38,520 --> 00:34:41,200
Speaker 1: and what its failure modes are, so my read of

562
00:34:41,320 --> 00:34:45,520
Speaker 1: what happened this time is very different from yours, not

563
00:34:45,760 --> 00:34:48,160
Speaker 1: that in the end it matters either way, but let

564
00:34:48,239 --> 00:34:51,120
Speaker 1: me just suggest an alternative hypothesis which I think actually

565
00:34:51,160 --> 00:34:56,760
Speaker 1: explains the facts slightly better. Uh. And So the first

566
00:34:57,080 --> 00:35:00,920
Speaker 1: signal that I had there was something wrong with Facebook

567
00:35:01,239 --> 00:35:05,480
Speaker 1: and democracy occurred in January when I saw a hate

568
00:35:05,520 --> 00:35:10,600
Speaker 1: speech from Facebook groups that were notionally associated with Bernie Sanders,

569
00:35:11,360 --> 00:35:14,960
Speaker 1: and they were hate speech against Clinton. And what struck

570
00:35:15,080 --> 00:35:20,640
Speaker 1: me was how rapidly these memes were spreading, and how

571
00:35:20,719 --> 00:35:23,920
Speaker 1: many of my friends were spreading them, and how you

572
00:35:24,000 --> 00:35:27,320
Speaker 1: went from one person to a dozen people in a

573
00:35:27,360 --> 00:35:30,520
Speaker 1: matter of days, which suggested somebody was spending money to

574
00:35:30,600 --> 00:35:32,640
Speaker 1: get my friends into these groups. And I don't know that,

575
00:35:32,719 --> 00:35:36,000
Speaker 1: I can't prove that that was true. But it turned

576
00:35:36,040 --> 00:35:40,520
Speaker 1: out there was a a group of people outside the

577
00:35:40,560 --> 00:35:45,200
Speaker 1: Sanders campaign but tightly affiliated with them, who were really

578
00:35:45,360 --> 00:35:49,680
Speaker 1: clever in their use of Facebook and Instagram and Twitter,

579
00:35:50,360 --> 00:35:58,080
Speaker 1: and who essentially supported that campaign really aggressively against Hillary Clinton.

580
00:35:59,280 --> 00:36:01,239
Speaker 1: Now it turns out what really pushed me over the

581
00:36:01,320 --> 00:36:04,719
Speaker 1: edge in was breggsit because that was the first time

582
00:36:04,719 --> 00:36:07,239
Speaker 1: I realized, oh, my God, the ad tools at Facebook.

583
00:36:07,600 --> 00:36:09,360
Speaker 1: The same thing that you know you can use to

584
00:36:09,440 --> 00:36:12,759
Speaker 1: sell records or tickets to a concert could be used

585
00:36:12,800 --> 00:36:16,160
Speaker 1: to destroy the outcome of the general election of major country.

586
00:36:16,200 --> 00:36:18,359
Speaker 1: I mean, that was like, that scared the crap out

587
00:36:18,360 --> 00:36:20,160
Speaker 1: of me. And so you know, when I went to

588
00:36:20,360 --> 00:36:24,640
Speaker 1: Zuckerberg and Sandberg in October, it was because I was

589
00:36:24,760 --> 00:36:28,480
Speaker 1: convinced that the business model, the algorithms, and the culture

590
00:36:28,480 --> 00:36:33,480
Speaker 1: of Facebook, we're allowing bad guys too harm innocent people

591
00:36:33,560 --> 00:36:36,759
Speaker 1: into harm democracy. So I set out to inform the

592
00:36:36,840 --> 00:36:39,239
Speaker 1: world and prevent that from happening again. And what was

593
00:36:39,440 --> 00:36:46,239
Speaker 1: tragic about was that the exact same forces that we

594
00:36:46,280 --> 00:36:50,600
Speaker 1: saw in We're back in size and had a huge impact.

595
00:36:51,360 --> 00:36:56,920
Speaker 1: And the the thing that really was so frustrating for

596
00:36:57,000 --> 00:37:02,080
Speaker 1: me was that pull people in the press, they acknowledged

597
00:37:02,120 --> 00:37:04,480
Speaker 1: there's a real primary, and they acknowledge there is what

598
00:37:04,719 --> 00:37:07,120
Speaker 1: is called a donor primary, where you know, it's about

599
00:37:07,160 --> 00:37:09,480
Speaker 1: whose money can you get? Right, And the thing that

600
00:37:09,760 --> 00:37:12,680
Speaker 1: that Bernie and had Warren did so well is to

601
00:37:12,800 --> 00:37:17,719
Speaker 1: convert fundraising from a batcat thing to a masses of

602
00:37:17,800 --> 00:37:22,840
Speaker 1: people thing using social media. Now, that same Bernie Sanders

603
00:37:22,920 --> 00:37:28,959
Speaker 1: group that did the UH Facebook stuff in never went away,

604
00:37:30,080 --> 00:37:33,240
Speaker 1: and they got really good and they built up their network.

605
00:37:33,320 --> 00:37:38,000
Speaker 1: They had, I want to say, something like Facebook pages,

606
00:37:38,920 --> 00:37:43,480
Speaker 1: and they were amplified by roughly four hundred Facebook groups

607
00:37:43,520 --> 00:37:46,319
Speaker 1: which would have in many cases thousands of people in them.

608
00:37:47,440 --> 00:37:50,919
Speaker 1: And they were all in for Bernie and a big

609
00:37:51,040 --> 00:37:54,279
Speaker 1: part of their effort, and I worked with researchers at

610
00:37:54,280 --> 00:37:58,440
Speaker 1: George Washington University. Uh was the beginning in the summer

611
00:37:58,440 --> 00:38:01,080
Speaker 1: of nineteen they decided to clear the field for Bernie,

612
00:38:01,320 --> 00:38:06,320
Speaker 1: and they made very quick work of Senator Harris and

613
00:38:06,440 --> 00:38:10,240
Speaker 1: then turned their sights on Warren and beginning in October,

614
00:38:10,360 --> 00:38:14,240
Speaker 1: focused on the one issue where Warren's position was identical

615
00:38:14,320 --> 00:38:18,200
Speaker 1: to Sanders and somehow made people think there was something

616
00:38:18,239 --> 00:38:20,760
Speaker 1: wrong with Warren. Right issue was becoming the front runner,

617
00:38:21,440 --> 00:38:24,080
Speaker 1: and they were amazingly effective at getting it. We're talking

618
00:38:24,080 --> 00:38:28,719
Speaker 1: about healthcare, Yes, Medicare for all. So the point was

619
00:38:29,040 --> 00:38:32,320
Speaker 1: where they were really affected was getting the breath to

620
00:38:32,480 --> 00:38:36,640
Speaker 1: position Warren as somehow with a dangerous position without saying

621
00:38:36,640 --> 00:38:40,360
Speaker 1: the same about about Burnie. The key thing is there's

622
00:38:40,560 --> 00:38:44,320
Speaker 1: nothing in American law that makes this illegal. Okay, this

623
00:38:44,560 --> 00:38:48,160
Speaker 1: is hardball politics. It's how the game is played. It

624
00:38:48,320 --> 00:38:53,520
Speaker 1: was amazingly successful, and I was with the folks at

625
00:38:53,560 --> 00:38:56,080
Speaker 1: George Wasshing University try to call attention to fact that hey,

626
00:38:56,200 --> 00:38:57,960
Speaker 1: this is going on, we should at least be talking

627
00:38:57,960 --> 00:39:01,000
Speaker 1: about is this the right way to conduct to Democratic primary?

628
00:39:01,960 --> 00:39:06,000
Speaker 1: So they cleared the field because I think the Sanders

629
00:39:06,080 --> 00:39:09,239
Speaker 1: people correctly thought that Warren was the biggest threat and

630
00:39:09,320 --> 00:39:11,520
Speaker 1: Harris was the second biggest threat. I think they thought

631
00:39:11,560 --> 00:39:14,200
Speaker 1: Biden would just peter out. Now, my perception of what

632
00:39:14,320 --> 00:39:16,200
Speaker 1: happened is not that the d n C did anything.

633
00:39:16,200 --> 00:39:19,319
Speaker 1: In fact, my impression of the DNC is honest to god,

634
00:39:20,239 --> 00:39:22,400
Speaker 1: I'm amazed they can get dressed in the morning because

635
00:39:23,000 --> 00:39:25,960
Speaker 1: I watched them. You know, we tried to get them

636
00:39:26,000 --> 00:39:29,480
Speaker 1: to pay attention to disinformation a couple of years ago,

637
00:39:29,719 --> 00:39:32,120
Speaker 1: and they just had no interest. Their focus was making

638
00:39:32,160 --> 00:39:35,920
Speaker 1: sure they were not embarrassed by a hack again. And

639
00:39:36,400 --> 00:39:39,239
Speaker 1: uh so, I literally don't think they could possibly have

640
00:39:39,320 --> 00:39:41,520
Speaker 1: tilted this divide. I think what happened was that the

641
00:39:41,680 --> 00:39:47,000
Speaker 1: most important constituency in the Democratic Party, black people, particularly

642
00:39:47,040 --> 00:39:51,440
Speaker 1: black women, decided that all that mattered was beating Trump.

643
00:39:52,120 --> 00:39:53,960
Speaker 1: They would deal with a guy who was hopeless in

644
00:39:54,040 --> 00:39:55,800
Speaker 1: every other respect as long as it could be Trump.

645
00:39:56,040 --> 00:39:58,920
Speaker 1: And the guy who had consistently the best numbers against

646
00:39:58,960 --> 00:40:02,440
Speaker 1: Trump was Biden, and they knew him well from the

647
00:40:02,520 --> 00:40:05,719
Speaker 1: Obama administration, and they decided in South Carolina they're going

648
00:40:05,800 --> 00:40:08,560
Speaker 1: to go there, and that just tipped the whole damn thing.

649
00:40:08,880 --> 00:40:11,480
Speaker 1: I think the d n C was every bit as surprised.

650
00:40:11,800 --> 00:40:15,640
Speaker 1: In fact, people I know around that thing express complete

651
00:40:15,680 --> 00:40:18,560
Speaker 1: and utter shock by what happened. Because if you look

652
00:40:18,600 --> 00:40:21,200
Speaker 1: at I mean remember the movie, the Peter Sellers movie

653
00:40:21,280 --> 00:40:25,080
Speaker 1: being there. Sure, well, I look at Biden, I'm going

654
00:40:25,239 --> 00:40:29,560
Speaker 1: that's Chauncey Gardner. I mean, you know, I look at Biden.

655
00:40:29,640 --> 00:40:32,200
Speaker 1: I just go. You gotta be kidding. Now. The one

656
00:40:32,280 --> 00:40:34,160
Speaker 1: good thing is the guy's a weather vane, right, So

657
00:40:34,280 --> 00:40:37,960
Speaker 1: I'm really hopeful that Warren and Harris are going to

658
00:40:38,000 --> 00:40:43,680
Speaker 1: play a really big role in his administration. Stacy Abrams, Right, Uh,

659
00:40:44,160 --> 00:40:47,600
Speaker 1: But the first thing, you should gotta get him elected.

660
00:40:47,880 --> 00:40:52,440
Speaker 1: And you know, as much as you know he's not

661
00:40:52,640 --> 00:40:57,200
Speaker 1: my guy, you know what, I want to go forward,

662
00:40:57,280 --> 00:41:01,160
Speaker 1: not backward, right, But it's really essentially getting elected. He's

663
00:41:01,160 --> 00:41:04,319
Speaker 1: the guy we have, right, And to me, the great

664
00:41:04,400 --> 00:41:09,680
Speaker 1: tragedy is that the d n C organized what was

665
00:41:09,800 --> 00:41:15,280
Speaker 1: demonstrably a ridiculously bad primary process for picking a candidate,

666
00:41:16,360 --> 00:41:19,440
Speaker 1: and in the end it was decided on cosmetic stuff

667
00:41:20,719 --> 00:41:23,880
Speaker 1: as opposed to like who would be well prepared. I mean,

668
00:41:23,920 --> 00:41:25,960
Speaker 1: can you imagine how different the thing might have been

669
00:41:26,120 --> 00:41:30,440
Speaker 1: if the pandemic has started three months earlier, right, Because

670
00:41:30,640 --> 00:41:35,080
Speaker 1: in that context, Warren probably would have emerged differently than

671
00:41:35,200 --> 00:41:40,040
Speaker 1: she did, because I mean, she looks like the kind

672
00:41:40,120 --> 00:41:42,319
Speaker 1: of people who have been successful around the world, right.

673
00:41:42,320 --> 00:41:44,840
Speaker 1: I mean, if you look at it, whether it's Germany

674
00:41:45,120 --> 00:41:48,080
Speaker 1: or New Zealand or any of those other countries in

675
00:41:48,160 --> 00:41:53,600
Speaker 1: Europe that have women prime ministers, there is this incredible

676
00:41:53,680 --> 00:41:55,839
Speaker 1: thing that the you know, I want to say, eight

677
00:41:55,920 --> 00:41:58,240
Speaker 1: of the ten countries they are most successful in finding

678
00:41:58,280 --> 00:42:02,840
Speaker 1: the pandemic have a minutes their chief executive. And that's

679
00:42:04,000 --> 00:42:06,719
Speaker 1: I don't think that's a fluke, right, And you know,

680
00:42:07,239 --> 00:42:10,560
Speaker 1: women technocrats in politics have a really good track record,

681
00:42:11,719 --> 00:42:14,320
Speaker 1: and you know, but we're not going to get to

682
00:42:14,400 --> 00:42:16,200
Speaker 1: run that experiment right where we are where we are,

683
00:42:16,280 --> 00:42:18,840
Speaker 1: so we we got to play with the horse we've got. Okay,

684
00:42:19,080 --> 00:42:22,000
Speaker 1: before we get back to the political thing, uh, talking

685
00:42:22,040 --> 00:42:27,479
Speaker 1: about income, inequality, etcetera, globalization has gotten a bad name.

686
00:42:27,640 --> 00:42:32,759
Speaker 1: My viewpoint would be that globalization is inevitable. It's just

687
00:42:32,840 --> 00:42:34,840
Speaker 1: that they left out the people who would be screwed

688
00:42:34,960 --> 00:42:38,319
Speaker 1: by globalization. What's your viewpoint on that? So I am

689
00:42:38,480 --> 00:42:41,279
Speaker 1: totally with you, and if you don't mind, I'm going

690
00:42:41,320 --> 00:42:44,759
Speaker 1: to go past where you are, okay. So I love

691
00:42:44,840 --> 00:42:50,719
Speaker 1: globalization because it's a peacemaking phenomenon that when you have

692
00:42:51,200 --> 00:42:56,000
Speaker 1: interlocking economies, it's really hard to go to war. And

693
00:42:57,320 --> 00:43:02,880
Speaker 1: the flaws of globalization really can be reduced to the

694
00:43:03,080 --> 00:43:06,360
Speaker 1: ancillary choices that were made with it. So if you

695
00:43:06,480 --> 00:43:09,520
Speaker 1: think about the fact that we allowed the tax law

696
00:43:10,840 --> 00:43:20,640
Speaker 1: to be used to encourage outsourcing of manufacturing to other countries,

697
00:43:21,200 --> 00:43:25,799
Speaker 1: which caused whole communities to disappear in the United States

698
00:43:25,880 --> 00:43:31,840
Speaker 1: economically whole basically whole states. And if you think about

699
00:43:32,360 --> 00:43:39,160
Speaker 1: the choices we've made relative to optimizing our globalization strategy

700
00:43:39,200 --> 00:43:41,960
Speaker 1: to ensure that there would be a hundred thousand different

701
00:43:42,000 --> 00:43:45,279
Speaker 1: products at Walmart at the lowest possible price. There are

702
00:43:45,440 --> 00:43:48,200
Speaker 1: lots of ways you could have optimized the strategy, but

703
00:43:48,360 --> 00:43:50,640
Speaker 1: we basically say we're going to optimize in a way

704
00:43:50,719 --> 00:43:54,080
Speaker 1: that you know goes to all this Huxley, We're gonna

705
00:43:54,080 --> 00:43:58,719
Speaker 1: give people the soma of consumerism. People can take away

706
00:43:58,719 --> 00:44:02,520
Speaker 1: their job. And it's like, if that is those things

707
00:44:02,600 --> 00:44:08,080
Speaker 1: are not linked, those are choices. And we have a

708
00:44:08,239 --> 00:44:12,120
Speaker 1: thing that started really well, went way off the tracks

709
00:44:12,280 --> 00:44:17,520
Speaker 1: because we forgot something about capitalism that really matters, which is,

710
00:44:17,560 --> 00:44:21,280
Speaker 1: for capitalism the work, someone has to set the rules

711
00:44:21,320 --> 00:44:24,800
Speaker 1: and enforce them, and traditionally that's the federal government. And

712
00:44:25,040 --> 00:44:27,400
Speaker 1: Reagan comes in says the government is the problem. And

713
00:44:27,480 --> 00:44:32,600
Speaker 1: the Republicans set about making government ineffective. And it took

714
00:44:32,640 --> 00:44:35,319
Speaker 1: them forty years, but they succeeded to the point where

715
00:44:35,400 --> 00:44:39,640
Speaker 1: today government does not have the ability to meet the

716
00:44:39,840 --> 00:44:43,439
Speaker 1: needs that people incidently expect from it. And exactly the moment,

717
00:44:44,160 --> 00:44:46,480
Speaker 1: the technology is creating a new set of needs for

718
00:44:46,520 --> 00:44:48,320
Speaker 1: which the government does not have the budget or the

719
00:44:48,400 --> 00:44:54,160
Speaker 1: skills to provide support. And we have got to break

720
00:44:54,520 --> 00:44:59,000
Speaker 1: the back of the libertarian philosophy that there is nothing

721
00:44:59,120 --> 00:45:02,320
Speaker 1: useful the government does, because if you're looking at it

722
00:45:02,480 --> 00:45:10,279
Speaker 1: right now, the absence of a thoughtful government response all

723
00:45:10,360 --> 00:45:14,880
Speaker 1: by itself explains why the United States has the worst

724
00:45:14,960 --> 00:45:19,680
Speaker 1: outcome from COVID in the entire world. Okay, you know,

725
00:45:20,000 --> 00:45:23,440
Speaker 1: in the news right now. Moving into the social media

726
00:45:23,480 --> 00:45:31,239
Speaker 1: sphere is the whole plandemic documentary okay, which doesn't seem

727
00:45:31,320 --> 00:45:33,719
Speaker 1: to be able to be killed in terms of video,

728
00:45:33,840 --> 00:45:37,360
Speaker 1: keeps popping up. Give us your viewpoint on that. So

729
00:45:37,800 --> 00:45:41,040
Speaker 1: the first piece, let me just remind our audience how

730
00:45:41,600 --> 00:45:46,719
Speaker 1: the business model of YouTube, Facebook, Instagram, and in a

731
00:45:46,800 --> 00:45:52,719
Speaker 1: slightly different way Twitter work. These sites are all dependent

732
00:45:52,920 --> 00:45:58,680
Speaker 1: on our attention. They sell ants. They're only twenty four

733
00:45:58,719 --> 00:46:00,520
Speaker 1: hours in a day. They need keep as much of

734
00:46:00,520 --> 00:46:07,239
Speaker 1: our attention as possible. For YouTube, Facebook, and Instagram, they

735
00:46:08,000 --> 00:46:11,439
Speaker 1: have used surveillance what Shoshana zoo Boff at Harvard calls

736
00:46:11,480 --> 00:46:17,400
Speaker 1: surveillance capitalism. Two. Build a dossier on every single person

737
00:46:17,560 --> 00:46:23,000
Speaker 1: that is, for all intents and purposes, a data voodoo

738
00:46:23,040 --> 00:46:26,120
Speaker 1: doll that is a complete representation of our digital lives,

739
00:46:26,480 --> 00:46:28,440
Speaker 1: every touch point, not just the things you have on

740
00:46:28,560 --> 00:46:31,640
Speaker 1: Facebook and Google, but every time you use a credit card,

741
00:46:31,719 --> 00:46:34,000
Speaker 1: every time you travel, every time you use your phone,

742
00:46:34,040 --> 00:46:36,480
Speaker 1: every time you move with the phone in your position.

743
00:46:36,680 --> 00:46:39,279
Speaker 1: They know everything. They know what you do minute by

744
00:46:39,320 --> 00:46:41,120
Speaker 1: minute the whole day. They know where you are, who

745
00:46:41,160 --> 00:46:46,640
Speaker 1: you're with. They use that in order to identify content.

746
00:46:47,239 --> 00:46:52,880
Speaker 1: It will activate your emotions. Well, guess what. For most people,

747
00:46:53,239 --> 00:46:59,200
Speaker 1: the surest way engage people emotional is to appeal to

748
00:46:59,320 --> 00:47:03,040
Speaker 1: flight or fight. Right, it's you can't help, but survivally,

749
00:47:03,080 --> 00:47:05,280
Speaker 1: you have to react. Even if you don't like the content,

750
00:47:05,480 --> 00:47:07,560
Speaker 1: you still have to pay attention. It's the same reason

751
00:47:07,600 --> 00:47:12,239
Speaker 1: why you have rubber necking when there's an accident. So

752
00:47:12,400 --> 00:47:17,040
Speaker 1: what kind of content does that? Hate speech, disinformation, and

753
00:47:17,120 --> 00:47:22,799
Speaker 1: conspiracy theories. So an algorithm that is designed to maximize

754
00:47:22,840 --> 00:47:27,280
Speaker 1: attention will, over the course of time, wind up promoting

755
00:47:27,360 --> 00:47:31,200
Speaker 1: hate speech, disinformation, conspiracy theories far more than other kinds

756
00:47:31,239 --> 00:47:38,600
Speaker 1: of content. So conclusion number one, YouTube, Facebook, Instagram. Their

757
00:47:38,680 --> 00:47:42,400
Speaker 1: business is hate speech, disinformation, and conspiracy theories. And so

758
00:47:42,560 --> 00:47:45,680
Speaker 1: when something comes along and you look at their reaction,

759
00:47:46,760 --> 00:47:52,200
Speaker 1: their basic reaction is first order responses, Oh, it's free speech,

760
00:47:52,239 --> 00:47:55,440
Speaker 1: We're not going to interfere. If the pressure doesn't go away,

761
00:47:55,920 --> 00:47:58,799
Speaker 1: they go, well, we have this tool so people can

762
00:47:58,880 --> 00:48:01,840
Speaker 1: report it, and you know, if enough people report it

763
00:48:01,880 --> 00:48:06,279
Speaker 1: will do something. Then the third level response is, uh, oh,

764
00:48:06,640 --> 00:48:10,239
Speaker 1: I'm sorry, but that doesn't violate our terms of service. Yes,

765
00:48:10,320 --> 00:48:13,160
Speaker 1: it's objectional, what doesn't If it still won't go away,

766
00:48:13,640 --> 00:48:17,239
Speaker 1: they will eventually remove either the piece of content or

767
00:48:17,320 --> 00:48:20,440
Speaker 1: the person who put it up. So they got rid

768
00:48:20,480 --> 00:48:23,840
Speaker 1: of Alex Jones. Why did they do that because the

769
00:48:23,960 --> 00:48:28,040
Speaker 1: pressure was really huge, and even though Alex Jones was gigantic,

770
00:48:28,719 --> 00:48:31,680
Speaker 1: he was a tiny fraction of all the hate speech, disinformation,

771
00:48:31,800 --> 00:48:34,560
Speaker 1: conspiracy theories on those platforms and they were able to

772
00:48:34,640 --> 00:48:37,080
Speaker 1: protect all the rest of it for a period of

773
00:48:37,120 --> 00:48:40,120
Speaker 1: time by getting rid of him. So they take down plandemic,

774
00:48:40,239 --> 00:48:44,280
Speaker 1: But what do they not do. They do not eliminate

775
00:48:44,320 --> 00:48:48,080
Speaker 1: the ability of someone to advertise and share the link

776
00:48:48,160 --> 00:48:51,040
Speaker 1: to plandemic in an ad, and they do nothing to

777
00:48:51,120 --> 00:48:55,719
Speaker 1: prevent it from being spread inside groups on Facebook, so

778
00:48:56,080 --> 00:48:58,680
Speaker 1: you wind up having people promoting it in places and

779
00:48:58,800 --> 00:49:03,319
Speaker 1: other people just sharing it inside groups. So it's they

780
00:49:03,400 --> 00:49:06,319
Speaker 1: don't actually want to get rid of it because that's

781
00:49:06,400 --> 00:49:08,839
Speaker 1: the thing that drives their business. This is the same

782
00:49:08,960 --> 00:49:14,960
Speaker 1: basis on which Google, Facebook as corporations, and Twitter have

783
00:49:15,239 --> 00:49:20,799
Speaker 1: had two standards, one for real people and the other

784
00:49:20,880 --> 00:49:25,480
Speaker 1: for people who are conservatives right. Twitter famously said they

785
00:49:25,640 --> 00:49:30,879
Speaker 1: couldn't eliminate white supremacy hate speech because doing so would

786
00:49:30,920 --> 00:49:35,200
Speaker 1: require them to shut down a bunch of Republicans. They

787
00:49:35,320 --> 00:49:38,960
Speaker 1: obviously do not enforce their terms of service on Trump

788
00:49:39,200 --> 00:49:44,719
Speaker 1: for anything. And Facebook has done the most amazing thing.

789
00:49:45,320 --> 00:49:51,959
Speaker 1: A reporter named Judd Lego discovered that Trump was advertising

790
00:49:52,400 --> 00:49:56,440
Speaker 1: with blatant falsehoods that violated the Facebook terms of service.

791
00:49:57,680 --> 00:50:00,160
Speaker 1: He calls them on it, and so what did Facebook do?

792
00:50:01,320 --> 00:50:06,839
Speaker 1: They change their terms of service last summer and now

793
00:50:07,000 --> 00:50:11,600
Speaker 1: it's okay to lie in a political act. Now I

794
00:50:11,800 --> 00:50:16,319
Speaker 1: look at all these things and I just go why.

795
00:50:17,080 --> 00:50:22,319
Speaker 1: And here's the thing. There are three billion people who

796
00:50:22,480 --> 00:50:27,400
Speaker 1: actively use Facebook products. Roughly similar number actively use Google products,

797
00:50:27,880 --> 00:50:32,000
Speaker 1: so have almost half the worlds population. They're more than

798
00:50:32,040 --> 00:50:36,759
Speaker 1: twice as big as any country. Neither Google nor Facebook

799
00:50:37,400 --> 00:50:41,680
Speaker 1: acknowledges responsibility to any country. They're bigger than any country.

800
00:50:41,719 --> 00:50:45,600
Speaker 1: They go, but you can't regulate us. And yet they

801
00:50:45,640 --> 00:50:48,120
Speaker 1: do have a problem. They don't have armies and they

802
00:50:48,160 --> 00:50:51,759
Speaker 1: don't control currencies, so they lack the two things that

803
00:50:52,600 --> 00:50:57,640
Speaker 1: sovereign nations have. So they have to cooperate to sub degree.

804
00:50:58,640 --> 00:51:03,760
Speaker 1: They will always aligned with power. There's a famous story

805
00:51:04,080 --> 00:51:07,960
Speaker 1: about how Twitter in particular and Facebook also we're used

806
00:51:08,040 --> 00:51:10,720
Speaker 1: during the Arab Spring to help get those people together.

807
00:51:11,040 --> 00:51:13,200
Speaker 1: How they were used to help organize the Women's Arch,

808
00:51:13,600 --> 00:51:15,680
Speaker 1: how they were used to help them organize the March

809
00:51:15,760 --> 00:51:19,000
Speaker 1: for Our Lives, how they were used in Black Lives Matter.

810
00:51:19,680 --> 00:51:22,320
Speaker 1: The part of the story that people don't focus on

811
00:51:22,440 --> 00:51:26,760
Speaker 1: it closely is that these companies aligned with the powerful,

812
00:51:27,000 --> 00:51:30,239
Speaker 1: such that when something like the Arab Spring or the

813
00:51:30,320 --> 00:51:33,279
Speaker 1: March for Our Lives of the Women's March happens, the

814
00:51:33,440 --> 00:51:37,400
Speaker 1: people on the other side, particularly authoritarians, can use the

815
00:51:37,480 --> 00:51:42,640
Speaker 1: exact same technology to replect, to suppress any kind of resistance,

816
00:51:43,320 --> 00:51:46,080
Speaker 1: and Facebook in particular has been a huge enabler of

817
00:51:46,120 --> 00:51:49,520
Speaker 1: that in countries like Myan mar in countries like Cambodia

818
00:51:50,400 --> 00:51:59,319
Speaker 1: and the Philippines, where you know, the authoritarians have inflicted

819
00:51:59,400 --> 00:52:04,919
Speaker 1: great harm on innocent people. So what drives me insane, Bob,

820
00:52:05,360 --> 00:52:09,160
Speaker 1: is this week's big stories. Facebook has something called the

821
00:52:09,400 --> 00:52:13,719
Speaker 1: Oversight Board, and in theory, it's going to police. It's

822
00:52:13,760 --> 00:52:17,920
Speaker 1: academics and journalists who are going to police hate speech,

823
00:52:18,000 --> 00:52:22,200
Speaker 1: disinformation and conspiracy theories. And I'm pulling my hair up

824
00:52:22,280 --> 00:52:24,719
Speaker 1: because people are trying to debate whether the people on

825
00:52:24,840 --> 00:52:27,840
Speaker 1: this board are the right people. And I'm going to

826
00:52:27,880 --> 00:52:34,759
Speaker 1: hang out people. This entire discussion is ridiculous. The oversight

827
00:52:34,840 --> 00:52:39,680
Speaker 1: board requires human moderation. Humans look at the content. It

828
00:52:39,880 --> 00:52:42,480
Speaker 1: fails for two reasons, and our audience will get one

829
00:52:42,520 --> 00:52:46,480
Speaker 1: of them instantly. One of them is latency. There's a

830
00:52:46,719 --> 00:52:50,520
Speaker 1: lag between when something gets put up and when a

831
00:52:50,680 --> 00:52:53,120
Speaker 1: human can review it and agree and take it down.

832
00:52:53,520 --> 00:52:56,440
Speaker 1: During that lag is when all the harm takes place, right,

833
00:52:56,560 --> 00:52:59,799
Speaker 1: because when the thing gets put out, the damage is instantaneous.

834
00:53:00,400 --> 00:53:04,640
Speaker 1: So what Facebook uses was what I call algorithmic amplification.

835
00:53:04,800 --> 00:53:07,760
Speaker 1: It blows this thing out to literally three billion people,

836
00:53:08,640 --> 00:53:13,840
Speaker 1: and there's nothing you can do with human moderation to

837
00:53:13,960 --> 00:53:16,320
Speaker 1: keep pace with that. So the other problem is the

838
00:53:16,400 --> 00:53:20,280
Speaker 1: problems scale right that you know you're gonna have forty

839
00:53:20,400 --> 00:53:23,759
Speaker 1: moderators patrolling a thing with billions of posts a day.

840
00:53:24,120 --> 00:53:27,200
Speaker 1: I mean, that's hopeless. And so what we need to

841
00:53:27,280 --> 00:53:31,319
Speaker 1: do is to stop pretending like Facebook is seriously trying

842
00:53:31,320 --> 00:53:34,480
Speaker 1: to solve any of these problems. If they want to

843
00:53:34,560 --> 00:53:36,560
Speaker 1: do that, they wouldn't be treating Trump the way they

844
00:53:36,600 --> 00:53:41,600
Speaker 1: are in the selection. They wouldn't be you know, they

845
00:53:41,640 --> 00:53:45,640
Speaker 1: wouldn't be aligning themselves so tightly. They'd be sitting there saying,

846
00:53:45,640 --> 00:53:47,800
Speaker 1: wait a minute, when this is done, we have to

847
00:53:47,880 --> 00:53:50,879
Speaker 1: live somewhere. Employees have to live somewhere. Do they want

848
00:53:50,920 --> 00:53:56,040
Speaker 1: to live in an authoritarian country? I mean that it's

849
00:53:56,280 --> 00:53:58,560
Speaker 1: to my mind, that's what's wrong with all of this

850
00:53:58,680 --> 00:54:03,640
Speaker 1: stuff right now. Because these companies are so big, they

851
00:54:03,760 --> 00:54:07,399
Speaker 1: have to align with power, and they are inherently authoritarian

852
00:54:07,480 --> 00:54:10,480
Speaker 1: in their own decision. Right because the founders of Google,

853
00:54:10,719 --> 00:54:14,880
Speaker 1: the founder of Facebook have absolute control over those platforms, right,

854
00:54:15,239 --> 00:54:21,560
Speaker 1: shareholders have no voice. And so in that situation, authoritarians

855
00:54:21,600 --> 00:54:24,280
Speaker 1: are going to align with authoritarians and just make them comfortable.

856
00:54:24,960 --> 00:54:29,120
Speaker 1: And I'm sitting I've spent three and a half years

857
00:54:29,160 --> 00:54:32,960
Speaker 1: trying to go, hey, hello, we got a huge problem here.

858
00:54:33,000 --> 00:54:35,560
Speaker 1: We gotta do something about it. And you know, I'm

859
00:54:35,600 --> 00:54:37,880
Speaker 1: not some dude who just walked in off the street.

860
00:54:39,000 --> 00:54:42,160
Speaker 1: I spent thirty eight years in Silicon Valley. I was

861
00:54:42,560 --> 00:54:45,280
Speaker 1: at Kleiner Perkins when they made the first investment in Amazon,

862
00:54:45,320 --> 00:54:48,239
Speaker 1: when they made the first investment in Google. You know,

863
00:54:48,320 --> 00:54:50,719
Speaker 1: I was one of the early advisors from Mark zucker

864
00:54:50,760 --> 00:54:53,400
Speaker 1: Bergen and Cheryl Sandberg. I mean, I saw all this stuff,

865
00:54:53,960 --> 00:54:56,880
Speaker 1: and look, I'm not the perfect messenger, duh. You can

866
00:54:56,920 --> 00:55:00,640
Speaker 1: tell because it didn't want But I did my because

867
00:55:01,840 --> 00:55:03,200
Speaker 1: and I took three and a half years of my

868
00:55:03,280 --> 00:55:05,440
Speaker 1: life to do nothing else because I thought it was

869
00:55:05,560 --> 00:55:09,239
Speaker 1: that important. And here we are. Now. The good news

870
00:55:09,360 --> 00:55:12,399
Speaker 1: is the cavalry sort of has arrived because a lot

871
00:55:12,480 --> 00:55:14,600
Speaker 1: of people who really know way more about how this

872
00:55:14,640 --> 00:55:16,960
Speaker 1: stuff works than I do have come into the game.

873
00:55:17,000 --> 00:55:20,279
Speaker 1: You know, Shoshana Zooboff is an amazing person. Becca Lewis

874
00:55:20,360 --> 00:55:23,560
Speaker 1: relative to white supremacy at Stanford. You know, the list goes.

875
00:55:23,840 --> 00:55:28,239
Speaker 1: You know, there's Joe Donovan who does disinformation, and I

876
00:55:28,320 --> 00:55:30,600
Speaker 1: mean there's just tons of people who have come in now,

877
00:55:30,680 --> 00:55:33,560
Speaker 1: and so the real experts are in the game and

878
00:55:33,640 --> 00:55:37,319
Speaker 1: that makes me feel like we got a shot. But man,

879
00:55:37,400 --> 00:55:39,839
Speaker 1: we got a lot of work to do. But okay, well,

880
00:55:39,920 --> 00:55:42,759
Speaker 1: we know, like any business, there's outside and inside, and

881
00:55:42,840 --> 00:55:45,840
Speaker 1: you have had the privilege, unlike these researchers, to literally

882
00:55:45,960 --> 00:55:48,719
Speaker 1: be on the inside. So let's start with Zuckerberg and

883
00:55:49,080 --> 00:55:53,120
Speaker 1: Cheryl Sandberg. Since you were an early investor and an advisor,

884
00:55:54,160 --> 00:55:59,440
Speaker 1: do they understand the problem you're obviously, especially someone like Zuckerberg.

885
00:55:59,480 --> 00:56:02,520
Speaker 1: A lot of these tech people, uh I will say,

886
00:56:02,520 --> 00:56:08,240
Speaker 1: are not fully rounded people. Okay, where you're thirty years older, etcetera.

887
00:56:08,600 --> 00:56:13,480
Speaker 1: Do they literally understand the issues. So I think the

888
00:56:13,680 --> 00:56:17,600
Speaker 1: challenge here, Bob, is that the founders of Google and

889
00:56:17,719 --> 00:56:24,200
Speaker 1: Facebook have a different philosophy. So I'll start with Mark

890
00:56:24,360 --> 00:56:29,320
Speaker 1: at Facebook. Mark believes that bringing together the whole world

891
00:56:29,800 --> 00:56:33,239
Speaker 1: onto one network that he controls is the single most

892
00:56:33,280 --> 00:56:35,960
Speaker 1: important thing any human being can do, and that it's

893
00:56:36,040 --> 00:56:39,680
Speaker 1: a much better idea than the United States of America,

894
00:56:39,920 --> 00:56:46,240
Speaker 1: or France or Italy. And he believes that haven't gotten

895
00:56:46,320 --> 00:56:49,880
Speaker 1: this far, we should let him finish the job. The

896
00:56:50,000 --> 00:56:58,640
Speaker 1: founders of Google believe that if they can gather all

897
00:56:58,719 --> 00:57:01,680
Speaker 1: the data in the world, they can make everything a

898
00:57:01,800 --> 00:57:05,839
Speaker 1: million times more efficient. So one thing that both Mark

899
00:57:06,000 --> 00:57:11,000
Speaker 1: and Larry and Surrogey share is the engineering philosophy that

900
00:57:11,120 --> 00:57:16,080
Speaker 1: efficiency is the value that you want to optimize for, which,

901
00:57:16,160 --> 00:57:19,160
Speaker 1: by the way, if you're making a motor, that's obviously true.

902
00:57:19,400 --> 00:57:22,400
Speaker 1: If you're making a small piece of software, great, But

903
00:57:22,480 --> 00:57:28,280
Speaker 1: when you're applying it to a country, then you have

904
00:57:28,480 --> 00:57:32,120
Speaker 1: to ask the question, is efficiency consistent with the values

905
00:57:32,160 --> 00:57:35,600
Speaker 1: of that country? And I would simply observe that Western

906
00:57:35,720 --> 00:57:41,360
Speaker 1: democracies we're valued. We're sorry, We're established on the principles

907
00:57:41,480 --> 00:57:48,600
Speaker 1: of the Enlightenment. Specifically, two things, free will, self determination,

908
00:57:48,680 --> 00:57:52,360
Speaker 1: and another word for that, and the other one is democracy.

909
00:57:52,880 --> 00:57:58,160
Speaker 1: Now think about it. Self determination is inherently inefficient. You

910
00:57:58,280 --> 00:58:00,480
Speaker 1: decide what you're going to wear today, You decide what

911
00:58:00,520 --> 00:58:02,640
Speaker 1: you're gonna eat today, You decide where you're gonna go.

912
00:58:03,320 --> 00:58:06,480
Speaker 1: I make my own choices. If everybody does that, you know,

913
00:58:07,000 --> 00:58:09,680
Speaker 1: that's immensely inefficient. Would be so much more efficient if

914
00:58:09,720 --> 00:58:12,600
Speaker 1: everybody wore the same clothes, if everybody ate the same things, right,

915
00:58:12,640 --> 00:58:14,480
Speaker 1: you just be able to optimize everything a lot better.

916
00:58:17,400 --> 00:58:20,440
Speaker 1: And you think about democracy, You go, whoa democracy is

917
00:58:20,520 --> 00:58:25,640
Speaker 1: all about forcing compromise, right, be so much better if

918
00:58:25,640 --> 00:58:27,120
Speaker 1: you could just sit there and go, these are the rules.

919
00:58:27,120 --> 00:58:30,520
Speaker 1: Everybody has to obey them. And the thing happened last week.

920
00:58:31,000 --> 00:58:37,480
Speaker 1: It was an amazing step for our side in that battle.

921
00:58:37,880 --> 00:58:44,680
Speaker 1: Google has been following the a path of developing products

922
00:58:45,000 --> 00:58:48,200
Speaker 1: that's a little bit like the Apollo program to go

923
00:58:48,240 --> 00:58:50,760
Speaker 1: to the Moon, where you know, you broke down each

924
00:58:50,800 --> 00:58:52,520
Speaker 1: of the steps necessary to go to the moon, and

925
00:58:52,640 --> 00:58:55,480
Speaker 1: Gemini and Apollo had to do each one, advancing to

926
00:58:55,600 --> 00:58:59,160
Speaker 1: the next only after they've successfully accomplished going to Earth orbit.

927
00:58:59,640 --> 00:59:02,560
Speaker 1: Rande of Alot Earth orbit spacewalk and Earth orbit, go

928
00:59:02,680 --> 00:59:06,200
Speaker 1: to the Moon, go around it, do a rendezvous, and

929
00:59:06,640 --> 00:59:09,360
Speaker 1: lunar orbit to a spacewalk in lunar orbit, then you

930
00:59:09,400 --> 00:59:11,360
Speaker 1: go down to the Moon without landing, and then finally

931
00:59:11,360 --> 00:59:13,360
Speaker 1: you go to the Moon. So they've been building up

932
00:59:13,400 --> 00:59:16,840
Speaker 1: towards something they call smart cities. They have an alphabet

933
00:59:16,920 --> 00:59:20,160
Speaker 1: division called Sidewalk Collapse. They just going to impose this

934
00:59:20,360 --> 00:59:24,800
Speaker 1: notion of efficiency on the city and they have been

935
00:59:25,000 --> 00:59:27,120
Speaker 1: for the last few years trying to do the very

936
00:59:27,280 --> 00:59:32,520
Speaker 1: first moon landing, if you will, in Toronto and something

937
00:59:32,560 --> 00:59:35,000
Speaker 1: called water Front Toronto. There was going to be a

938
00:59:35,040 --> 00:59:37,760
Speaker 1: development where they were going to essentially take over control

939
00:59:37,840 --> 00:59:41,120
Speaker 1: of all the city services and make everything really efficient

940
00:59:41,200 --> 00:59:45,520
Speaker 1: through a combination of surveillance and them controlling the information streams.

941
00:59:46,120 --> 00:59:48,080
Speaker 1: And they sold this thing to the city on the

942
00:59:48,120 --> 00:59:51,120
Speaker 1: basis of, Hey, we're going to finance this massive development

943
00:59:52,560 --> 00:59:54,000
Speaker 1: and we're going to give you some great data for

944
00:59:54,080 --> 00:59:57,840
Speaker 1: running the city. And for a long time they didn't

945
00:59:57,880 --> 01:00:01,840
Speaker 1: talk about what the gotchas were. And I played a

946
01:00:02,000 --> 01:00:05,480
Speaker 1: very small role in the campaign to expose those gotches,

947
01:00:05,760 --> 01:00:10,480
Speaker 1: and they were things like, oh, if there's a problem,

948
01:00:10,560 --> 01:00:13,360
Speaker 1: you complained to the city government. But the city government

949
01:00:13,360 --> 01:00:15,600
Speaker 1: can actually fix the problem because Google has total control.

950
01:00:16,560 --> 01:00:17,880
Speaker 1: Google is going to own a lot of the land,

951
01:00:17,920 --> 01:00:19,000
Speaker 1: so they're gonna make a lot of money on the

952
01:00:19,080 --> 01:00:21,479
Speaker 1: real estate. Maybe that was a fair deal, but they're

953
01:00:21,480 --> 01:00:24,000
Speaker 1: also going to own all the data, and they were

954
01:00:24,080 --> 01:00:26,040
Speaker 1: going to be able to take any data they wanted

955
01:00:26,800 --> 01:00:31,000
Speaker 1: and you could not push back on it. Well, I

956
01:00:31,040 --> 01:00:35,240
Speaker 1: mean that's way past that's past the matrix, right, I mean,

957
01:00:35,360 --> 01:00:40,080
Speaker 1: that's really creepy stuff. They were forced to withdraw their

958
01:00:40,480 --> 01:00:45,880
Speaker 1: bid last week because of a tsunami of opposition, but

959
01:00:46,040 --> 01:00:49,680
Speaker 1: the day before they started a new thing because Governor

960
01:00:49,760 --> 01:00:54,680
Speaker 1: Cuomo New York appointed Eric Schmidt to help redesign public

961
01:00:54,840 --> 01:00:57,400
Speaker 1: education in New York. And it's like, I just want

962
01:00:57,440 --> 01:01:00,520
Speaker 1: to sit there and go, you have got be kidding.

963
01:01:01,440 --> 01:01:05,640
Speaker 1: I mean, this is insane. And you know it's when

964
01:01:05,720 --> 01:01:08,920
Speaker 1: you look at this thing. Technology could be used to

965
01:01:09,160 --> 01:01:15,080
Speaker 1: empower people, to give them greater rights of self determination,

966
01:01:15,560 --> 01:01:20,040
Speaker 1: to give a better form of democracy, and instead it's

967
01:01:20,080 --> 01:01:23,800
Speaker 1: being used to exploit all the weak elements in our society,

968
01:01:23,840 --> 01:01:27,920
Speaker 1: all the weak elements in our psychology. And it doesn't

969
01:01:28,000 --> 01:01:29,800
Speaker 1: have to be that way. That is a choice, that

970
01:01:29,920 --> 01:01:34,680
Speaker 1: is a that is a sociopathy that has become endemic

971
01:01:34,760 --> 01:01:37,520
Speaker 1: and silicon volley over the past decade, and you see

972
01:01:37,560 --> 01:01:41,960
Speaker 1: it in things like Uber and Airbnb and we Work

973
01:01:42,400 --> 01:01:49,520
Speaker 1: and Palenteer and now more recently with Banjo and clear

974
01:01:49,600 --> 01:01:54,040
Speaker 1: View AI. The people who are basically using surveillance, stealing

975
01:01:54,080 --> 01:01:56,360
Speaker 1: your right you know, your photos and all that, and

976
01:01:56,520 --> 01:02:02,080
Speaker 1: using it in really creepy ways and going it doesn't

977
01:02:02,120 --> 01:02:05,280
Speaker 1: have to be this one. This is a choice. And

978
01:02:05,480 --> 01:02:08,520
Speaker 1: our job is to use the pandemic to force change.

979
01:02:09,360 --> 01:02:14,000
Speaker 1: And you know, we gotta take our little victories like Toronto,

980
01:02:14,960 --> 01:02:19,280
Speaker 1: but we somebody needs to send out the governor of

981
01:02:19,320 --> 01:02:22,880
Speaker 1: New York and go. Billionaires are not going to be

982
01:02:23,080 --> 01:02:27,120
Speaker 1: our path out of this. They are the problem. Expecting

983
01:02:27,160 --> 01:02:31,040
Speaker 1: Bloomberg and Gates and and Eric Schmidt to suddenly become

984
01:02:32,240 --> 01:02:36,880
Speaker 1: committed two super high taxes on the rich and bringing

985
01:02:36,960 --> 01:02:46,800
Speaker 1: up the rest. That does not seem like a good back. Okay,

986
01:02:47,120 --> 01:02:50,240
Speaker 1: let's talk. And I'm really talking about the reality more.

987
01:02:50,480 --> 01:02:54,880
Speaker 1: Most of the political debate to what degree was Russia

988
01:02:55,080 --> 01:02:59,560
Speaker 1: and their disinformation employed on social media to affect the

989
01:02:59,640 --> 01:03:02,880
Speaker 1: outcome them in Brexit and to affect election outcomes in

990
01:03:02,880 --> 01:03:07,280
Speaker 1: the US. So the thing that we've focused a lot

991
01:03:07,400 --> 01:03:09,880
Speaker 1: on Russia. We had a Muller report here, there was

992
01:03:10,280 --> 01:03:15,840
Speaker 1: analysis in the United Kingdom. Their impact was huge and

993
01:03:15,920 --> 01:03:19,560
Speaker 1: in the United States. My hypothesis, and I can't prove

994
01:03:19,680 --> 01:03:22,560
Speaker 1: this because I'm not connected in that world well enough

995
01:03:22,600 --> 01:03:26,520
Speaker 1: to have real data, but my hypothesis is that without

996
01:03:26,600 --> 01:03:31,400
Speaker 1: the Russians, Trump could never get nominated. That essentially, they

997
01:03:31,600 --> 01:03:36,200
Speaker 1: had spent from to the beginning of sixteen millions of

998
01:03:36,280 --> 01:03:39,640
Speaker 1: dollars sewing discent in America over a set of issues

999
01:03:39,840 --> 01:03:46,880
Speaker 1: like white supremacy, like guns, like anti vax where they

1000
01:03:47,640 --> 01:03:50,640
Speaker 1: were trying to divide Americans, and Trump just picked up

1001
01:03:50,680 --> 01:03:54,200
Speaker 1: all their themes and the other whatever was sixteen Republicans

1002
01:03:54,440 --> 01:03:57,960
Speaker 1: were running on conventional Republican things, and so he ignited

1003
01:03:58,040 --> 01:04:03,520
Speaker 1: a you know, a populist wave that got him nominated.

1004
01:04:06,600 --> 01:04:09,360
Speaker 1: A similar thing happened in the United Kingdom and the

1005
01:04:09,440 --> 01:04:11,760
Speaker 1: run up to Brexit. But the piece that people have

1006
01:04:11,920 --> 01:04:15,560
Speaker 1: not focused on enough here is the role that the

1007
01:04:15,720 --> 01:04:20,160
Speaker 1: campaigns themselves played. Thanks to something called Cambridge Analytic, we

1008
01:04:20,360 --> 01:04:27,760
Speaker 1: know that that the Leave EU campaign for Brexit used

1009
01:04:27,800 --> 01:04:36,200
Speaker 1: Facebook data two essentially distort people's understanding of what Brexit

1010
01:04:36,320 --> 01:04:39,400
Speaker 1: was about. And to tilt the skills in their favor.

1011
01:04:40,000 --> 01:04:42,760
Speaker 1: The thing people have not focused on enough is how

1012
01:04:42,880 --> 01:04:47,200
Speaker 1: that same data was used by the Trump campaign, with

1013
01:04:47,520 --> 01:04:54,360
Speaker 1: Facebook employees as the active agents of doing it two

1014
01:04:55,720 --> 01:05:00,600
Speaker 1: suppress the votes of suburban white women, p people of color,

1015
01:05:00,960 --> 01:05:05,040
Speaker 1: and idealistic young people in a set of states, ten

1016
01:05:05,160 --> 01:05:11,040
Speaker 1: states in particular, as well as to essentially activate emotionally

1017
01:05:11,160 --> 01:05:14,880
Speaker 1: and increased turnout of people already like Trump. It didn't

1018
01:05:15,000 --> 01:05:19,000
Speaker 1: move one vote from Clinton to Trump, but that wasn't

1019
01:05:19,000 --> 01:05:21,000
Speaker 1: the goal. The goal was to suppress people who might

1020
01:05:21,120 --> 01:05:25,120
Speaker 1: vote for clone and engage everybody else. And it clearly

1021
01:05:25,200 --> 01:05:29,200
Speaker 1: worked because if you look at this, particularly, people of

1022
01:05:29,280 --> 01:05:34,600
Speaker 1: color and young people did not turn out in the

1023
01:05:34,680 --> 01:05:37,800
Speaker 1: way the models suggested they should, and the numbers are

1024
01:05:37,880 --> 01:05:41,000
Speaker 1: particularly telling of the states that Trump needed to win. Now,

1025
01:05:41,080 --> 01:05:44,320
Speaker 1: the Russian hack of the Democratic National Committee and the

1026
01:05:44,400 --> 01:05:48,240
Speaker 1: Russian hack of the Democratic Congressional Campaign Committee may also

1027
01:05:48,280 --> 01:05:51,200
Speaker 1: have figured. No one has ever actually told us how

1028
01:05:51,320 --> 01:05:53,520
Speaker 1: that data was used, but it meant they had the

1029
01:05:53,600 --> 01:05:58,440
Speaker 1: complete Clinton campaign playbook and the Democratic playbook and every

1030
01:05:58,480 --> 01:06:02,000
Speaker 1: congressional district, and they focused in particular intense states and

1031
01:06:02,040 --> 01:06:04,640
Speaker 1: a set of congressional districts where the data said that

1032
01:06:04,680 --> 01:06:08,000
Speaker 1: they could win, and they turned a ridiculous percentage of

1033
01:06:08,040 --> 01:06:13,840
Speaker 1: them and won the election thanks to seventy votes distributed

1034
01:06:13,880 --> 01:06:16,440
Speaker 1: over three states. So I look at this and go

1035
01:06:16,760 --> 01:06:22,400
Speaker 1: The Russian thing was absolutely essential, But so was Wiki leaks.

1036
01:06:23,040 --> 01:06:26,160
Speaker 1: So was the New York Times, which both promoted her

1037
01:06:26,240 --> 01:06:30,040
Speaker 1: emails as a giant story and didn't report on Trump

1038
01:06:30,080 --> 01:06:33,520
Speaker 1: being investigated by the FBI a few weeks before the election.

1039
01:06:33,880 --> 01:06:37,320
Speaker 1: So was Coomey. But I think in the file analysis,

1040
01:06:37,440 --> 01:06:40,880
Speaker 1: the voter suppression done by the Trump campaign, the highly

1041
01:06:40,920 --> 01:06:46,760
Speaker 1: targeted voter suppression, was decisive because you know, Jill Stein,

1042
01:06:47,840 --> 01:06:51,400
Speaker 1: her votes alone were enough to determine the outcome in Wisconsin.

1043
01:06:52,400 --> 01:06:55,000
Speaker 1: And you know, they're like ten things that had to

1044
01:06:55,080 --> 01:06:57,480
Speaker 1: happen for Trump to win it. He got all ten. Okay,

1045
01:06:57,560 --> 01:07:02,280
Speaker 1: So let's talk about today, um, in terms of media.

1046
01:07:02,960 --> 01:07:05,680
Speaker 1: One thing we know about the Internet, it was it

1047
01:07:05,800 --> 01:07:12,440
Speaker 1: allowed other stories to come out now. But we have

1048
01:07:12,720 --> 01:07:16,920
Speaker 1: these giant, powerful media operations, and if we were to

1049
01:07:17,040 --> 01:07:19,080
Speaker 1: go on right now, and I do it multiple times

1050
01:07:19,240 --> 01:07:23,360
Speaker 1: a day, the stories featured on the Fox News website

1051
01:07:23,480 --> 01:07:27,560
Speaker 1: are completely different from the stories featured in the WAPO.

1052
01:07:27,720 --> 01:07:30,960
Speaker 1: In the New York Times. Do we throw our hands

1053
01:07:31,080 --> 01:07:33,600
Speaker 1: up in the air. Is there any way to get

1054
01:07:33,720 --> 01:07:37,200
Speaker 1: the populace to agree on facts, especially in a world

1055
01:07:37,240 --> 01:07:41,960
Speaker 1: where facts are fungible. So, Bob, one of the things

1056
01:07:42,040 --> 01:07:46,560
Speaker 1: that's driving crazy is that we didn't learn from so

1057
01:07:48,280 --> 01:07:51,440
Speaker 1: major media. And here I would put all of the networks,

1058
01:07:52,880 --> 01:07:58,800
Speaker 1: plus the New York Times, Politico, ax eos uh and

1059
01:07:59,120 --> 01:08:04,720
Speaker 1: some parts of the Watch Shi Post have all essentially

1060
01:08:04,840 --> 01:08:08,560
Speaker 1: behaved as though Trump is normal and as though we're

1061
01:08:08,640 --> 01:08:15,320
Speaker 1: having a normal political process. Now, if you ask stuff,

1062
01:08:15,360 --> 01:08:18,400
Speaker 1: why would they do that? Well, it's really obvious. I mean,

1063
01:08:18,640 --> 01:08:23,599
Speaker 1: the guy who runs CNN talked about Trump and said, look,

1064
01:08:23,640 --> 01:08:25,160
Speaker 1: he may not be good for America, but he's great

1065
01:08:25,200 --> 01:08:33,200
Speaker 1: for CNN. And that's the problem. The incentives of journalism today, Look,

1066
01:08:33,720 --> 01:08:39,120
Speaker 1: I mean, they're just there. They drive them to normalize Trump.

1067
01:08:39,840 --> 01:08:43,080
Speaker 1: And the New York Times had what more new subscriptions

1068
01:08:43,479 --> 01:08:47,000
Speaker 1: this past quarter, more digital subscriptions rather up to four million,

1069
01:08:47,479 --> 01:08:50,120
Speaker 1: but they had like half a million in one quarter exactly,

1070
01:08:50,479 --> 01:08:52,720
Speaker 1: which is like greater than the sum of like all

1071
01:08:52,840 --> 01:08:56,320
Speaker 1: subscriptions to like local newspapers side of New York and

1072
01:08:56,400 --> 01:09:02,840
Speaker 1: d c uh. I mean, it's insane. Right, and the

1073
01:09:03,240 --> 01:09:07,240
Speaker 1: journalism is now dominated by Twitter, so everything, you know,

1074
01:09:07,360 --> 01:09:09,479
Speaker 1: the way they find their stories, the way that they

1075
01:09:09,560 --> 01:09:12,400
Speaker 1: decide what's important is all about what trends on Twitter,

1076
01:09:13,720 --> 01:09:16,800
Speaker 1: and that's really easily gained. And the right has been

1077
01:09:16,880 --> 01:09:24,200
Speaker 1: brilliant a gameing and clearly the willingness of Fox two

1078
01:09:25,680 --> 01:09:30,560
Speaker 1: act as an amplifier of the far right, irrespective of

1079
01:09:30,760 --> 01:09:36,080
Speaker 1: the danger to public health and society, is magnified this

1080
01:09:36,280 --> 01:09:40,439
Speaker 1: and made it intractable. But we have to also note

1081
01:09:41,120 --> 01:09:46,920
Speaker 1: that the hollowing out of newspapers by Google and Facebook,

1082
01:09:46,960 --> 01:09:52,479
Speaker 1: by essentially taking away whatever economics they still had, has

1083
01:09:52,520 --> 01:09:57,240
Speaker 1: been horrific. It's been you know, the the role that

1084
01:09:57,360 --> 01:10:02,120
Speaker 1: Facebook and Google and Twitter have had and in undermining

1085
01:10:02,160 --> 01:10:05,800
Speaker 1: the economics of these things is something we have to

1086
01:10:05,880 --> 01:10:08,400
Speaker 1: pay attention to. Now. I've spent the last couple of

1087
01:10:08,520 --> 01:10:13,320
Speaker 1: years quietly trying to build an idea for redesigning the

1088
01:10:13,479 --> 01:10:16,960
Speaker 1: economics of local news, really all news, but starting with

1089
01:10:17,080 --> 01:10:22,040
Speaker 1: local news. And technology plays a really huge role in that.

1090
01:10:22,320 --> 01:10:24,519
Speaker 1: But it requires a different philosophy than one of the

1091
01:10:24,600 --> 01:10:28,240
Speaker 1: people have had. But at the end of the day,

1092
01:10:28,479 --> 01:10:30,639
Speaker 1: when you hear somebody say, I just want to teach

1093
01:10:30,720 --> 01:10:34,519
Speaker 1: everybody news literacy. I'm going to hang on. We've got

1094
01:10:34,640 --> 01:10:37,000
Speaker 1: to be realistic. This is going to take a generation,

1095
01:10:37,120 --> 01:10:40,880
Speaker 1: and it's going to have to start in kindergarten. We

1096
01:10:41,080 --> 01:10:43,960
Speaker 1: have to go back and make public education about teaching

1097
01:10:44,000 --> 01:10:48,040
Speaker 1: people how to think. And we have to have you know,

1098
01:10:48,320 --> 01:10:51,120
Speaker 1: we have to say this stuff matters to us. I

1099
01:10:51,240 --> 01:10:54,520
Speaker 1: just don't see a silver bullet pop. That's the pro problem. Okay,

1100
01:10:55,200 --> 01:10:57,160
Speaker 1: let's just go back. Do you think there's a trend

1101
01:10:57,240 --> 01:11:00,400
Speaker 1: now in Australian and other countries of making Google and

1102
01:11:00,479 --> 01:11:02,519
Speaker 1: other outlets pay for the news. Do you think that

1103
01:11:02,680 --> 01:11:05,680
Speaker 1: is gaining power? I do believe it's gaining power. But

1104
01:11:05,800 --> 01:11:09,280
Speaker 1: the problem is that it doesn't fix the problem. If

1105
01:11:09,320 --> 01:11:12,320
Speaker 1: the incentives of these guys are to promote Trump as

1106
01:11:12,439 --> 01:11:17,639
Speaker 1: normal because he sells lots of subscriptions, then just having

1107
01:11:17,680 --> 01:11:19,880
Speaker 1: a little bit more subscription money isn't going to help.

1108
01:11:20,880 --> 01:11:23,000
Speaker 1: You know, we have that. We have to change the

1109
01:11:23,120 --> 01:11:27,680
Speaker 1: demand side. People have to want facts. I think you're

1110
01:11:27,760 --> 01:11:32,320
Speaker 1: running a really interesting experiment on COVID because every major periodical,

1111
01:11:32,640 --> 01:11:35,559
Speaker 1: all the ones with paywalls, have put their COVID stuff

1112
01:11:35,600 --> 01:11:38,200
Speaker 1: out for free. Their most valuable stuff has been out

1113
01:11:38,240 --> 01:11:40,280
Speaker 1: there for free, and two things have come from that.

1114
01:11:40,800 --> 01:11:42,479
Speaker 1: One is that the people have done that have seen

1115
01:11:42,560 --> 01:11:45,800
Speaker 1: a massive explosion in their subscriptions. So there is a

1116
01:11:45,920 --> 01:11:48,280
Speaker 1: portion of the market willing to pay for it, but

1117
01:11:48,560 --> 01:11:51,920
Speaker 1: that is a very small portion of the market. A

1118
01:11:52,080 --> 01:11:56,479
Speaker 1: far larger number of people have decided that COVID is

1119
01:11:56,520 --> 01:12:01,960
Speaker 1: a part of the culture wars and have therefore resisted fact,

1120
01:12:02,479 --> 01:12:07,160
Speaker 1: they've resisted expertise. They have said, you know, I'm going

1121
01:12:07,200 --> 01:12:10,160
Speaker 1: to bring my gun to the state House in Michigan

1122
01:12:11,320 --> 01:12:14,360
Speaker 1: because I want to get a haircutter. I want to

1123
01:12:14,400 --> 01:12:17,600
Speaker 1: get my nails done. And I'm sitting there going you

1124
01:12:17,720 --> 01:12:20,519
Speaker 1: have got to be kidding me. I mean, that is

1125
01:12:20,640 --> 01:12:25,400
Speaker 1: not a problem solvable by news media in the current model.

1126
01:12:25,800 --> 01:12:28,760
Speaker 1: That's a problem that you have to make a new

1127
01:12:28,840 --> 01:12:32,599
Speaker 1: generation people. And by the way, the way we're handling COVID,

1128
01:12:33,720 --> 01:12:37,160
Speaker 1: there's a really good chance that Darwinian processes are gonna,

1129
01:12:37,920 --> 01:12:44,040
Speaker 1: you know, essentially raise the cost of ignorance to a

1130
01:12:44,240 --> 01:12:47,519
Speaker 1: degree that makes people Okay, well, you know, let's talk

1131
01:12:47,560 --> 01:12:51,280
Speaker 1: about this education. We've been privileged, you and myself uh

1132
01:12:51,400 --> 01:12:54,479
Speaker 1: to have education that focused on analysis. I remember being

1133
01:12:54,560 --> 01:12:57,200
Speaker 1: in my first college course and the guy said, we're

1134
01:12:57,240 --> 01:12:59,439
Speaker 1: never going to discuss the reading in class. If you

1135
01:12:59,479 --> 01:13:01,920
Speaker 1: don't under in the reading, you shouldn't be here. So

1136
01:13:02,160 --> 01:13:04,439
Speaker 1: what is the environment we live in? Certainly with Betsy

1137
01:13:04,560 --> 01:13:09,320
Speaker 1: devas head of education, we have a great number of

1138
01:13:09,400 --> 01:13:14,240
Speaker 1: people moving towards parochial and home schooling. We have money

1139
01:13:14,400 --> 01:13:18,719
Speaker 1: taken from public schools. We have public schools where essentially

1140
01:13:18,840 --> 01:13:22,800
Speaker 1: books and certain thoughts are banned. Then we have what

1141
01:13:23,000 --> 01:13:26,000
Speaker 1: remains of the upper middle class and those above them

1142
01:13:26,560 --> 01:13:29,759
Speaker 1: rigging the system such that they get the best education,

1143
01:13:30,160 --> 01:13:32,479
Speaker 1: whether it be in private school, then allowing them to

1144
01:13:32,560 --> 01:13:35,320
Speaker 1: get in good universities. You know, there are a lot

1145
01:13:35,400 --> 01:13:38,760
Speaker 1: of tentacles here. How do we address this? And the

1146
01:13:38,840 --> 01:13:42,200
Speaker 1: other thing I must say, which goes back to education,

1147
01:13:42,640 --> 01:13:46,760
Speaker 1: to what you were saying earlier about Reagan, etcetera. With

1148
01:13:46,920 --> 01:13:50,719
Speaker 1: the money and the government. As soon as you say

1149
01:13:50,920 --> 01:13:53,360
Speaker 1: because the right is defined debate, we have to spend

1150
01:13:53,439 --> 01:13:58,000
Speaker 1: more money, they immediately tune out. So I think that this,

1151
01:13:58,680 --> 01:14:01,599
Speaker 1: you know, we can date that client in public education

1152
01:14:02,960 --> 01:14:09,759
Speaker 1: probably to the sixties. Right that things like the Civil

1153
01:14:09,920 --> 01:14:14,640
Speaker 1: Rights Act where and the things that followed from it,

1154
01:14:14,760 --> 01:14:24,320
Speaker 1: like bussing, caused a backlash against what I think had

1155
01:14:24,439 --> 01:14:28,599
Speaker 1: been the central premise of publication public education America, which

1156
01:14:28,640 --> 01:14:34,120
Speaker 1: is bringing up you know it basically teaching everyone to

1157
01:14:34,200 --> 01:14:41,880
Speaker 1: be a good citizen. And the opposition two civil rights

1158
01:14:43,040 --> 01:14:52,559
Speaker 1: laws started a pushback, and you know, simultaneously you saw

1159
01:14:52,680 --> 01:14:56,280
Speaker 1: the rise of egypt evangelical Christianity, which is really about

1160
01:14:56,600 --> 01:14:59,479
Speaker 1: you know, creating a version of Christianity that could keep

1161
01:14:59,520 --> 01:15:03,320
Speaker 1: black people prob And you know, I think sadly a

1162
01:15:03,479 --> 01:15:08,160
Speaker 1: lot of these things are basically about white supremacy trying

1163
01:15:08,200 --> 01:15:14,200
Speaker 1: to impose its view on policy and everything that follows it.

1164
01:15:14,320 --> 01:15:17,880
Speaker 1: Whether it's you know, imposing on a woman's right to choose,

1165
01:15:17,920 --> 01:15:22,120
Speaker 1: whether it is about how much money we invest in

1166
01:15:22,400 --> 01:15:26,120
Speaker 1: in public education and what is taught there. Those are

1167
01:15:26,200 --> 01:15:30,040
Speaker 1: all battles that I think stem from this, this underlying

1168
01:15:31,000 --> 01:15:34,200
Speaker 1: desire of a certain group of white people to retain

1169
01:15:34,360 --> 01:15:40,120
Speaker 1: privileges over everyone else, and that you know, after a

1170
01:15:40,360 --> 01:15:44,880
Speaker 1: long period of progress, you know, into the sixties and

1171
01:15:45,000 --> 01:15:48,840
Speaker 1: maybe even into the early seventies, you know, we've been backsliding,

1172
01:15:49,640 --> 01:15:53,840
Speaker 1: and initially very slowly and then much more rapidly. And

1173
01:15:55,120 --> 01:15:58,240
Speaker 1: I mean it's hard to know what the driver of

1174
01:15:58,280 --> 01:16:01,479
Speaker 1: it is, but it's possible that the fact that the

1175
01:16:01,560 --> 01:16:07,280
Speaker 1: country has not faced an existential crisis since the Second

1176
01:16:07,280 --> 01:16:11,000
Speaker 1: World War and depression immediately before it. That you know,

1177
01:16:11,560 --> 01:16:15,720
Speaker 1: those things receding into the background caused people not to

1178
01:16:15,800 --> 01:16:26,880
Speaker 1: appreciate the value of cooperation and promoting fairness for everyone.

1179
01:16:27,520 --> 01:16:31,040
Speaker 1: You know that essentially forgetting that causes to prioritize our

1180
01:16:31,120 --> 01:16:35,440
Speaker 1: individual rights and our infant individual autonomy and our convenience.

1181
01:16:36,080 --> 01:16:38,240
Speaker 1: And you know, this happened at a time when the

1182
01:16:39,160 --> 01:16:42,120
Speaker 1: economy was getting more and more driven by the needs

1183
01:16:42,160 --> 01:16:44,760
Speaker 1: of consumers, and so you went from you know, mass

1184
01:16:44,840 --> 01:16:48,960
Speaker 1: market products to mass customization to everybody needs to have

1185
01:16:49,120 --> 01:16:56,479
Speaker 1: their you know, bespoke items. That whole trend has put

1186
01:16:56,560 --> 01:16:59,719
Speaker 1: us where we are today. And with COVID, it seems

1187
01:16:59,760 --> 01:17:03,599
Speaker 1: to me that you have exactly the kind of issue

1188
01:17:03,640 --> 01:17:06,600
Speaker 1: and you layer climate change on top of that, and

1189
01:17:06,720 --> 01:17:10,120
Speaker 1: you have exactly the kind of issue that threatens everyone

1190
01:17:10,640 --> 01:17:13,120
Speaker 1: and where there's no place to hide. You know, your

1191
01:17:13,160 --> 01:17:15,920
Speaker 1: gated community is not going to protect you against climate change.

1192
01:17:16,320 --> 01:17:20,040
Speaker 1: I mean, I live in California. A wildfire could burn

1193
01:17:20,160 --> 01:17:23,720
Speaker 1: my place down. Probably not today because it's overcast, but

1194
01:17:24,200 --> 01:17:28,160
Speaker 1: you know, at some point this summer, and it doesn't

1195
01:17:28,160 --> 01:17:30,960
Speaker 1: matter where you live in California, wildfires are a huge

1196
01:17:31,200 --> 01:17:33,519
Speaker 1: threat and they are a function of climate change. And

1197
01:17:33,600 --> 01:17:37,920
Speaker 1: it turns out that infectious diseases like COVID are also

1198
01:17:37,960 --> 01:17:40,400
Speaker 1: a function of climate change. And we haven't had an

1199
01:17:40,439 --> 01:17:43,720
Speaker 1: honest conversation by climate change in this country. Well, well, well,

1200
01:17:44,040 --> 01:17:46,800
Speaker 1: how is COVID related to climate change? So as the

1201
01:17:46,880 --> 01:17:52,320
Speaker 1: temperature rises, infectious diseases, uh, just seemed to prosper. And

1202
01:17:54,400 --> 01:17:58,400
Speaker 1: you know, it's like, I mean, climate change is also

1203
01:17:58,439 --> 01:18:01,000
Speaker 1: contributed to the you know, the play of locusts and

1204
01:18:01,520 --> 01:18:05,680
Speaker 1: you know the h crack atla. I mean, it's just

1205
01:18:05,840 --> 01:18:11,400
Speaker 1: like we have gotten ourselves into the psycho where we're

1206
01:18:11,479 --> 01:18:15,720
Speaker 1: so focused on our consumption that we've forgotten to leave

1207
01:18:15,880 --> 01:18:18,439
Speaker 1: something for the next generation. We've forgotten to leave something

1208
01:18:18,520 --> 01:18:22,880
Speaker 1: for our leader years. And you know, again the connections

1209
01:18:22,920 --> 01:18:24,800
Speaker 1: to all these things. They are better people to make

1210
01:18:24,840 --> 01:18:27,640
Speaker 1: those cases than I but those people are out there

1211
01:18:27,720 --> 01:18:30,800
Speaker 1: making them constantly. Well, this brings a connection. You were

1212
01:18:30,840 --> 01:18:33,880
Speaker 1: talking about dedicating three and a half years your life

1213
01:18:34,240 --> 01:18:38,799
Speaker 1: to raising the alarm of the abuse of social media,

1214
01:18:39,000 --> 01:18:42,000
Speaker 1: both by those using the systems and those running the systems.

1215
01:18:42,640 --> 01:18:45,320
Speaker 1: We've been talking about climate change essentially for fifty years.

1216
01:18:45,800 --> 01:18:48,400
Speaker 1: All of a sudden, we have this woman on the spectrum,

1217
01:18:48,479 --> 01:18:51,839
Speaker 1: a girl on the spectrum, Greta Thunberg, and she literally

1218
01:18:52,040 --> 01:18:56,880
Speaker 1: pushes the message much further, showing the power of the individual.

1219
01:18:57,760 --> 01:19:02,560
Speaker 1: Uh are you do you? Are you still optimistic or

1220
01:19:02,680 --> 01:19:05,640
Speaker 1: you worn out with your work? Or have you achieved

1221
01:19:05,800 --> 01:19:08,679
Speaker 1: or is it somebody else who needs to do that? Yes, so, Bob,

1222
01:19:08,960 --> 01:19:13,960
Speaker 1: I look at Greta Tunberg with ah. I mean, you know,

1223
01:19:14,200 --> 01:19:18,000
Speaker 1: she is in many ways for her movement what Martin

1224
01:19:18,080 --> 01:19:24,519
Speaker 1: Luther King was for his And what if if I

1225
01:19:24,640 --> 01:19:27,599
Speaker 1: had a chance to meet Greta, I would say, Greta

1226
01:19:29,680 --> 01:19:35,240
Speaker 1: the biggest barrier to climate change action in Western democracies

1227
01:19:37,200 --> 01:19:44,559
Speaker 1: is the power of the power that internet platforms like YouTube, Facebook, Instagram,

1228
01:19:44,640 --> 01:19:49,799
Speaker 1: and Twitter give to the most angry, dissonant voices in society.

1229
01:19:50,360 --> 01:19:53,720
Speaker 1: That they give disproportionate political power to those people, and

1230
01:19:54,040 --> 01:19:58,320
Speaker 1: they basically prevent action on essential issues like climate change,

1231
01:19:58,520 --> 01:20:07,080
Speaker 1: like vaccination, like COVID. And we need to force changes

1232
01:20:07,120 --> 01:20:09,840
Speaker 1: in the business model. We need to end algorithm amplification,

1233
01:20:10,000 --> 01:20:15,040
Speaker 1: We need to provide better privacy rights, not because those

1234
01:20:15,160 --> 01:20:19,719
Speaker 1: things will uh you know, not to punish Facebook and Google,

1235
01:20:20,040 --> 01:20:24,719
Speaker 1: but simply because we cannot operate as a society under

1236
01:20:24,840 --> 01:20:29,960
Speaker 1: the terms that these guys have created force. And you

1237
01:20:30,080 --> 01:20:32,080
Speaker 1: asked me how I'm doing, and I will tell you.

1238
01:20:33,800 --> 01:20:36,559
Speaker 1: I started this conversation by saying that I am one

1239
01:20:36,680 --> 01:20:42,439
Speaker 1: with the quarantine. I the quarantine for me came along

1240
01:20:42,520 --> 01:20:45,120
Speaker 1: in a moment in time when without realizing it, I

1241
01:20:45,320 --> 01:20:50,720
Speaker 1: really needed to take a rest, and in my head

1242
01:20:50,760 --> 01:20:54,639
Speaker 1: I was already there that you know, I could see

1243
01:20:54,880 --> 01:20:59,120
Speaker 1: that my voice was not as effective as it was

1244
01:20:59,600 --> 01:21:04,160
Speaker 1: your wire going, and then other voices were doing a

1245
01:21:04,240 --> 01:21:06,320
Speaker 1: better job of my work than I was, and so

1246
01:21:06,439 --> 01:21:08,640
Speaker 1: I was thinking, Okay, this is great, But I was

1247
01:21:08,760 --> 01:21:10,880
Speaker 1: also in this routine of just doing it and the

1248
01:21:10,880 --> 01:21:13,320
Speaker 1: where people would call and I would always respond. Now

1249
01:21:13,439 --> 01:21:17,080
Speaker 1: with the quarantine, all that has stopped because other issues

1250
01:21:17,160 --> 01:21:24,400
Speaker 1: are more paramount and people's attention, and I don't know

1251
01:21:24,560 --> 01:21:29,639
Speaker 1: what I'm going to do after quarantine. It's possible focus

1252
01:21:29,720 --> 01:21:33,680
Speaker 1: on the local news thing, because in my career I

1253
01:21:33,760 --> 01:21:35,720
Speaker 1: also was very deeply involved in a lot of news

1254
01:21:35,840 --> 01:21:39,519
Speaker 1: organizations and so and I would involved with things like

1255
01:21:39,600 --> 01:21:45,120
Speaker 1: Wikipedia and AH just a lot of things that that

1256
01:21:45,280 --> 01:21:49,000
Speaker 1: could contribute to making this uh to creating a new

1257
01:21:49,800 --> 01:21:55,360
Speaker 1: ecosystem for for local news and it may be that

1258
01:21:55,400 --> 01:21:57,120
Speaker 1: I wind up just getting stuck back into the same

1259
01:21:57,160 --> 01:22:00,759
Speaker 1: thing I was doing. But I'm going to look around

1260
01:22:00,880 --> 01:22:04,240
Speaker 1: and see what the highest value thing is. Because when

1261
01:22:04,600 --> 01:22:10,760
Speaker 1: Tristan Harris and I first joined forces in early you

1262
01:22:10,800 --> 01:22:13,519
Speaker 1: can count on one hand the number of people were

1263
01:22:13,520 --> 01:22:16,120
Speaker 1: speaking publicly about the issues we were talking about. There

1264
01:22:16,160 --> 01:22:18,439
Speaker 1: are a ton of researchers who were working on the issues,

1265
01:22:18,520 --> 01:22:22,720
Speaker 1: doing great work, but they were buried inside organizations that

1266
01:22:23,000 --> 01:22:25,479
Speaker 1: did not amplify them, and so their voices were not

1267
01:22:25,600 --> 01:22:28,080
Speaker 1: being heard in the right place. And because Tristan and

1268
01:22:28,160 --> 01:22:31,479
Speaker 1: I were coming out of the valley, we had an

1269
01:22:31,560 --> 01:22:35,760
Speaker 1: ability to get access and amplify early on UM. But

1270
01:22:35,960 --> 01:22:39,280
Speaker 1: now those those really great researchers and the people who

1271
01:22:39,280 --> 01:22:42,240
Speaker 1: are the domain experts, they have access to the amplifiers

1272
01:22:42,280 --> 01:22:45,000
Speaker 1: and so UM, it's not as important for me to

1273
01:22:45,080 --> 01:22:48,519
Speaker 1: do that. And thank God, because you know, I need to.

1274
01:22:49,080 --> 01:22:52,120
Speaker 1: I need a break. I need to. I mean, this

1275
01:22:52,320 --> 01:22:54,479
Speaker 1: was gonna be the year Bob. I was already there,

1276
01:22:54,520 --> 01:22:56,920
Speaker 1: because this was the year we had this amazing album, right,

1277
01:22:57,360 --> 01:23:01,400
Speaker 1: and we were gonna be playing theaters, right, and I

1278
01:23:01,640 --> 01:23:05,160
Speaker 1: was going to be, you know, playing guitar behind Lester

1279
01:23:05,320 --> 01:23:08,200
Speaker 1: Chambers playing guitar behind Dylan Chambers playing guitar and the

1280
01:23:08,280 --> 01:23:11,560
Speaker 1: Tea Sisters to audiences that were just totally grooving on it.

1281
01:23:12,000 --> 01:23:14,640
Speaker 1: And you know, we had this review, this thing that

1282
01:23:14,920 --> 01:23:22,920
Speaker 1: took you through this this microcosm of you know, what

1283
01:23:24,360 --> 01:23:29,720
Speaker 1: the psychedelic music experience delivered back in the day, uh,

1284
01:23:30,040 --> 01:23:33,640
Speaker 1: in a way that was freshened up. And you know,

1285
01:23:34,560 --> 01:23:36,120
Speaker 1: I really want to do that. Now I can't do

1286
01:23:36,240 --> 01:23:38,600
Speaker 1: that at all, right, and so you know it's like,

1287
01:23:38,760 --> 01:23:40,120
Speaker 1: what are we gonna do? I mean, we're gonna put

1288
01:23:40,120 --> 01:23:41,720
Speaker 1: out this album, right, and we put two songs. You

1289
01:23:41,760 --> 01:23:43,439
Speaker 1: go to mons dot com. You can check out two

1290
01:23:43,439 --> 01:23:45,719
Speaker 1: of the songs, and we're gonna put out one every

1291
01:23:45,760 --> 01:23:48,040
Speaker 1: two weeks and then hopefully about a month from now,

1292
01:23:48,080 --> 01:23:49,599
Speaker 1: we'll put out the whole album. But I mean, how

1293
01:23:49,640 --> 01:23:51,400
Speaker 1: are you people even gonna find it? I have no idea.

1294
01:23:51,600 --> 01:23:53,599
Speaker 1: We're probably gonna give all the money to charity. We're

1295
01:23:53,600 --> 01:23:58,120
Speaker 1: trying to pick which one because it's like the country

1296
01:23:58,200 --> 01:24:03,200
Speaker 1: is broken, and the numbers and music for an album

1297
01:24:03,280 --> 01:24:04,920
Speaker 1: for a band like ours are not great enough to

1298
01:24:05,080 --> 01:24:09,080
Speaker 1: justify us keeping the money. But to Second Harvest or

1299
01:24:09,720 --> 01:24:17,400
Speaker 1: you know, Sweet Relief for two. You know, artists Rescue

1300
01:24:17,560 --> 01:24:20,320
Speaker 1: or one of those organizations helping people in our world,

1301
01:24:21,040 --> 01:24:23,760
Speaker 1: it might really matter. And you famously got together with

1302
01:24:23,920 --> 01:24:28,080
Speaker 1: Bono formed Elevation and Partners. But in our previous discussions

1303
01:24:28,120 --> 01:24:31,400
Speaker 1: you said your first aligned with Bono because you wanted

1304
01:24:31,439 --> 01:24:35,200
Speaker 1: to change some of the infrastructure of the music business. Ultimately,

1305
01:24:35,280 --> 01:24:38,840
Speaker 1: people were not receptive. Since you're still in the music

1306
01:24:39,000 --> 01:24:44,480
Speaker 1: business and it's now twenty years past the initial turmoil,

1307
01:24:45,400 --> 01:24:47,800
Speaker 1: how do you feel about the status today? The other

1308
01:24:47,920 --> 01:24:49,920
Speaker 1: thing of being, of course, people who are younger than

1309
01:24:50,000 --> 01:24:53,760
Speaker 1: us don't understand. They say, yeah, classic rock. But in

1310
01:24:53,880 --> 01:24:55,800
Speaker 1: the sixties and seventies, if you wanted to know what

1311
01:24:55,920 --> 01:24:58,880
Speaker 1: was going on, you listen to a record, and because

1312
01:24:59,000 --> 01:25:02,360
Speaker 1: there wasn't this in committee quality, if you were a

1313
01:25:02,479 --> 01:25:05,000
Speaker 1: musician who was very successful, you as rich as anybody

1314
01:25:05,040 --> 01:25:08,320
Speaker 1: in America and people knew your name. The only person

1315
01:25:08,439 --> 01:25:11,200
Speaker 1: with that kind of mind here today is Trump. Even

1316
01:25:11,240 --> 01:25:14,040
Speaker 1: though the media is saying everybody knows Drake, everybody knows

1317
01:25:14,080 --> 01:25:17,240
Speaker 1: Taylors with that is not true. So what's your general

1318
01:25:17,320 --> 01:25:20,680
Speaker 1: assessment of the music business today. Well, to me, the

1319
01:25:20,760 --> 01:25:25,360
Speaker 1: most profound thing is that the industry has acclimated itself

1320
01:25:25,520 --> 01:25:30,960
Speaker 1: to streaming. You know, everything has renormalized. You know, nobody

1321
01:25:31,080 --> 01:25:35,439
Speaker 1: spends the well. Very few people are still having the

1322
01:25:35,600 --> 01:25:41,320
Speaker 1: argument about the fairness of the economics of streaming. I mean, honestly,

1323
01:25:41,720 --> 01:25:43,479
Speaker 1: I look at it and I just go, you have

1324
01:25:43,720 --> 01:25:47,200
Speaker 1: got to be kidding me. But again, nobody's listening to me.

1325
01:25:47,280 --> 01:25:50,280
Speaker 1: They weren't listening to us eighteen years ago when we

1326
01:25:50,760 --> 01:25:54,599
Speaker 1: came in with another idea. Um. You know what's really

1327
01:25:54,640 --> 01:25:56,840
Speaker 1: weird is the industry is still dominated by the same

1328
01:25:56,880 --> 01:26:01,080
Speaker 1: executives were there then, and the same artists who are

1329
01:26:01,120 --> 01:26:04,080
Speaker 1: the biggest grossing live acts are still the biggest grossing

1330
01:26:04,160 --> 01:26:07,240
Speaker 1: live acts. So it's like the generation that you and

1331
01:26:07,320 --> 01:26:10,640
Speaker 1: I grew up and still dominates the economics of the

1332
01:26:10,840 --> 01:26:15,439
Speaker 1: live business and the industry in some ways is just

1333
01:26:15,560 --> 01:26:20,000
Speaker 1: gonna sunset out with the people that they grew up with, right,

1334
01:26:20,320 --> 01:26:24,840
Speaker 1: And there's still a new artist thing that's on streaming, right,

1335
01:26:24,880 --> 01:26:26,760
Speaker 1: which is where the hip hop guys are happening, and

1336
01:26:26,880 --> 01:26:30,799
Speaker 1: where uh, you know, all of the pop things are happening,

1337
01:26:32,360 --> 01:26:36,200
Speaker 1: And there you've hit a new equilibrium. I don't happen

1338
01:26:36,240 --> 01:26:39,280
Speaker 1: to think it's fair to the artist, and uh, I

1339
01:26:39,360 --> 01:26:41,639
Speaker 1: would like to believe that one of these days I'm

1340
01:26:41,680 --> 01:26:44,040
Speaker 1: going to figure out a way to break that. But

1341
01:26:44,160 --> 01:26:50,400
Speaker 1: the contracts are very ah, very well crafted from the

1342
01:26:50,439 --> 01:26:54,639
Speaker 1: point of view of of labels, and and the truth

1343
01:26:54,840 --> 01:26:58,519
Speaker 1: is that the labels do provide real value for breaking artists.

1344
01:26:58,720 --> 01:27:00,920
Speaker 1: You know, there are people who can do it on

1345
01:27:01,000 --> 01:27:05,000
Speaker 1: their own on YouTube, and but that's still a very

1346
01:27:05,120 --> 01:27:07,640
Speaker 1: very small number. And so when I look at this,

1347
01:27:08,320 --> 01:27:12,799
Speaker 1: the thing that was beautiful about the world I inhabit,

1348
01:27:12,880 --> 01:27:15,200
Speaker 1: which is where people live in the live world, is

1349
01:27:15,320 --> 01:27:24,000
Speaker 1: that the club and small theater environment was really vibrant.

1350
01:27:24,720 --> 01:27:26,799
Speaker 1: There was a lot going on, a lot of venues,

1351
01:27:26,840 --> 01:27:29,519
Speaker 1: a lot of people turning out. Ticket prices weren't high,

1352
01:27:29,640 --> 01:27:33,000
Speaker 1: but they were good enough to keep bands going and

1353
01:27:33,160 --> 01:27:34,840
Speaker 1: to keep people in the business. You know, here in

1354
01:27:34,880 --> 01:27:37,880
Speaker 1: the Bay Area, what Phil Lesh did at Tear Up

1355
01:27:37,880 --> 01:27:42,200
Speaker 1: a Crossroads and Bob Weir did at Sweetwater created an

1356
01:27:42,320 --> 01:27:45,160
Speaker 1: ecosystem for developing new bands that would then make all

1357
01:27:45,200 --> 01:27:47,880
Speaker 1: their money on the road. And I hadn't seen anything

1358
01:27:47,960 --> 01:27:50,760
Speaker 1: like that since you and I were kids. And here

1359
01:27:50,800 --> 01:27:54,599
Speaker 1: in San Francisco, where from basically the early seventies when

1360
01:27:54,680 --> 01:27:58,360
Speaker 1: Journey came up, until these guys started those two clubs,

1361
01:27:59,160 --> 01:28:02,320
Speaker 1: the industry. It was about national acts coming and playing

1362
01:28:02,360 --> 01:28:04,800
Speaker 1: the big vegant venues. The local papers didn't care about

1363
01:28:04,840 --> 01:28:07,840
Speaker 1: local stuff. And it was different than l A in

1364
01:28:07,920 --> 01:28:11,519
Speaker 1: that respect. And you know, you had Bobs s gags

1365
01:28:11,560 --> 01:28:15,360
Speaker 1: doing slims, but that was all by itself. And then

1366
01:28:15,400 --> 01:28:17,600
Speaker 1: all of a sudden, now you have this, this, this

1367
01:28:17,720 --> 01:28:19,840
Speaker 1: whole thing. It was really beautiful. But all of that,

1368
01:28:20,840 --> 01:28:24,680
Speaker 1: all that may be killed off by the pandemic and

1369
01:28:24,720 --> 01:28:26,200
Speaker 1: we're gonna have to do a restart. I mean, the

1370
01:28:26,280 --> 01:28:29,599
Speaker 1: buildings will still be there, but who's going to run?

1371
01:28:30,560 --> 01:28:32,519
Speaker 1: You know, how long is it going to be before

1372
01:28:32,600 --> 01:28:35,920
Speaker 1: people want to be jammed into a tight space. I

1373
01:28:35,960 --> 01:28:38,800
Speaker 1: don't know the answer to those questions. And you know,

1374
01:28:38,920 --> 01:28:42,360
Speaker 1: we were very early on streaming on Moonalysis streamed every

1375
01:28:42,400 --> 01:28:46,760
Speaker 1: show for more than ten years, and uh, you know,

1376
01:28:47,080 --> 01:28:49,920
Speaker 1: but streaming is not the same experience. It's way better

1377
01:28:50,000 --> 01:28:53,760
Speaker 1: than nothing, way way better than nothing, but it's it's

1378
01:28:53,880 --> 01:28:57,360
Speaker 1: nothing like being in a live show. And you know,

1379
01:28:59,280 --> 01:29:01,840
Speaker 1: it may be the best we got for now, you know.

1380
01:29:02,240 --> 01:29:04,040
Speaker 1: I mean, I've been watching a ton of you. I

1381
01:29:04,120 --> 01:29:06,479
Speaker 1: watched Richard Thompson the other day. He was doing something

1382
01:29:06,560 --> 01:29:08,519
Speaker 1: for the Royal Albert Hall from his home and it

1383
01:29:08,640 --> 01:29:10,680
Speaker 1: was like it was beautiful. I love Richie Thompson and

1384
01:29:12,960 --> 01:29:15,000
Speaker 1: he's like three songs in it. He plays a song

1385
01:29:16,040 --> 01:29:17,800
Speaker 1: and he comes to maybe I don't know, four or

1386
01:29:17,840 --> 01:29:21,160
Speaker 1: five measures, and he stops, and I'm going, this is

1387
01:29:21,240 --> 01:29:24,400
Speaker 1: what I love about streaming. You're watching people in the

1388
01:29:24,479 --> 01:29:27,240
Speaker 1: home and it's okay to stop. It doesn't have to

1389
01:29:27,320 --> 01:29:30,439
Speaker 1: be perfect, and it's completely authentic. And Bob, you have

1390
01:29:30,680 --> 01:29:35,320
Speaker 1: been the voice of authenticity from the beginning, right, you

1391
01:29:35,479 --> 01:29:38,680
Speaker 1: are my guru on authenticity. Well, you know, it's your

1392
01:29:38,760 --> 01:29:41,439
Speaker 1: mistakes and your imperfections that make you beautiful, that draw

1393
01:29:41,560 --> 01:29:43,879
Speaker 1: people to you. And my point is you have always

1394
01:29:43,960 --> 01:29:46,599
Speaker 1: been on that and I've always appreciated I think everybody

1395
01:29:46,640 --> 01:29:48,920
Speaker 1: who reached your newsletter and all of us who listened

1396
01:29:48,960 --> 01:29:51,960
Speaker 1: to you. You know, whether we were there before, we're

1397
01:29:52,040 --> 01:29:55,960
Speaker 1: there now, right, And streaming is all about that, right.

1398
01:29:56,439 --> 01:29:59,160
Speaker 1: You know, there's no way to cover the mistakes, there's

1399
01:29:59,280 --> 01:30:02,479
Speaker 1: no you know, you're not able to have a click track,

1400
01:30:02,680 --> 01:30:04,479
Speaker 1: or you probably don't have a click track. You probably

1401
01:30:04,520 --> 01:30:07,439
Speaker 1: don't have all the support. You know. You go and

1402
01:30:07,520 --> 01:30:09,479
Speaker 1: see these great big bands and there's four guys on

1403
01:30:09,600 --> 01:30:11,920
Speaker 1: stage and you just count up a number of instruments

1404
01:30:11,960 --> 01:30:14,400
Speaker 1: that are being played. It's like nine, right, and you go,

1405
01:30:14,840 --> 01:30:18,559
Speaker 1: huh gosh, that's interesting, you know, and you see these things.

1406
01:30:18,560 --> 01:30:21,360
Speaker 1: I mean, you were at the Grammys were Pink did

1407
01:30:21,439 --> 01:30:25,000
Speaker 1: that thing with the act and dropped in the lad

1408
01:30:25,040 --> 01:30:27,120
Speaker 1: and all that, and afterwards she goes, well, that pretty

1409
01:30:27,200 --> 01:30:29,320
Speaker 1: much puts the light to why you need a lip sync?

1410
01:30:29,560 --> 01:30:31,640
Speaker 1: And I'm going, you go, girl, I mean that was

1411
01:30:32,120 --> 01:30:35,200
Speaker 1: that was maybe the single most impressive live thing I've

1412
01:30:35,240 --> 01:30:39,920
Speaker 1: ever seen. Right, We're watching uh Lady Gaga when she learned,

1413
01:30:40,760 --> 01:30:42,880
Speaker 1: you know, she what was the Jazz standards. She'd spent

1414
01:30:42,960 --> 01:30:44,680
Speaker 1: like a year learning how to play before she did

1415
01:30:44,720 --> 01:30:46,880
Speaker 1: I think at a Grammy. I mean, you know, it's like,

1416
01:30:48,280 --> 01:30:52,040
Speaker 1: you see the people for whom this craft really matters, okay,

1417
01:30:52,520 --> 01:30:58,080
Speaker 1: and they have flourished in recent times not because the

1418
01:30:58,200 --> 01:31:01,680
Speaker 1: big dollars in the business supported, but rather because the

1419
01:31:01,800 --> 01:31:07,360
Speaker 1: big dollars in the business create an environment where authenticity

1420
01:31:07,800 --> 01:31:12,120
Speaker 1: and where craft could flourish around the edges. And I

1421
01:31:12,160 --> 01:31:13,880
Speaker 1: mean every once in a while in the mainstream, but

1422
01:31:14,120 --> 01:31:18,000
Speaker 1: always around the edges. And that makes me really happy.

1423
01:31:18,160 --> 01:31:19,840
Speaker 1: I don't know what's going to happen with that. I mean,

1424
01:31:19,880 --> 01:31:23,000
Speaker 1: I'm involved with a lot of local music production. I

1425
01:31:23,080 --> 01:31:25,959
Speaker 1: play a minor role in the Hartley Strictly Bluegrass Festival.

1426
01:31:26,720 --> 01:31:29,320
Speaker 1: I do. I help the city put on a Summer

1427
01:31:29,360 --> 01:31:32,040
Speaker 1: Souls to show every year. Um, you know, I've been

1428
01:31:32,080 --> 01:31:36,960
Speaker 1: involved with a bunch of the local clubs and none

1429
01:31:37,000 --> 01:31:43,479
Speaker 1: of that's happening, right, none of it. And so I

1430
01:31:43,600 --> 01:31:45,400
Speaker 1: don't know how long this lasts. I don't know how

1431
01:31:45,439 --> 01:31:48,160
Speaker 1: long it takes us just to get the opportunity to

1432
01:31:48,280 --> 01:31:52,559
Speaker 1: start again. And who's going to be around and how

1433
01:31:52,640 --> 01:31:54,200
Speaker 1: are the fans going to feel if this goes on

1434
01:31:54,280 --> 01:31:57,360
Speaker 1: two or three years? Right, I don't know. Now, Sarah

1435
01:31:57,520 --> 01:31:59,960
Speaker 1: Ken's your do you know who that is? Everybody needs

1436
01:32:00,160 --> 01:32:04,600
Speaker 1: to get her books. She is brilliant, Okay, right, she

1437
01:32:04,720 --> 01:32:08,000
Speaker 1: just had a presentation and she said two very interesting things.

1438
01:32:08,479 --> 01:32:10,760
Speaker 1: First thing she said is we're all sitting at home

1439
01:32:10,880 --> 01:32:14,160
Speaker 1: thinking that there's some power somewhere that's gonna take care

1440
01:32:14,200 --> 01:32:17,120
Speaker 1: of this, take care of us, and really it doesn't exist.

1441
01:32:17,720 --> 01:32:22,640
Speaker 1: And she also said she doesn't have hope and we

1442
01:32:22,760 --> 01:32:25,639
Speaker 1: shouldn't have hope. We you know, you do your best

1443
01:32:25,680 --> 01:32:28,160
Speaker 1: to help for your children, You and me don't have children.

1444
01:32:28,600 --> 01:32:32,120
Speaker 1: But my question is do you have hope and how

1445
01:32:32,200 --> 01:32:35,080
Speaker 1: do you view the future for society at larger as

1446
01:32:35,120 --> 01:32:38,680
Speaker 1: opposed to you the individual. So here's the thing. I

1447
01:32:38,920 --> 01:32:46,240
Speaker 1: had massive hope after that it would be possible to

1448
01:32:46,640 --> 01:32:53,160
Speaker 1: educate people the Trump's behavior would be so obviously detrimental

1449
01:32:53,240 --> 01:32:56,720
Speaker 1: to society that that would bring people out of the

1450
01:32:56,960 --> 01:33:00,280
Speaker 1: stupor the soma, if you will, of consumer them and

1451
01:33:00,760 --> 01:33:10,519
Speaker 1: and convenience. When Trump got away with suppressing the Malla report,

1452
01:33:12,720 --> 01:33:20,280
Speaker 1: my hope was reduced. When he got away with the impeachment.

1453
01:33:20,520 --> 01:33:25,640
Speaker 1: My hope was further reduced. When he was successful at

1454
01:33:25,720 --> 01:33:30,160
Speaker 1: making a pandemic into a culture war issue, my hope

1455
01:33:30,240 --> 01:33:36,519
Speaker 1: was reduced even further. I strongly agree with Sarah that

1456
01:33:37,040 --> 01:33:40,840
Speaker 1: hope is the wrong thing to be focused on here.

1457
01:33:41,880 --> 01:33:44,160
Speaker 1: I think it makes more sense to be piste off

1458
01:33:45,720 --> 01:33:47,879
Speaker 1: and to go you know, this is not my America.

1459
01:33:48,120 --> 01:33:50,439
Speaker 1: I'm not putting up with this bullshit one minute longer,

1460
01:33:50,840 --> 01:33:53,040
Speaker 1: and I'm going to do something. Now here's the thing.

1461
01:33:53,479 --> 01:33:55,960
Speaker 1: I can't tell your listeners to do that. I can

1462
01:33:56,040 --> 01:33:58,880
Speaker 1: only tell them what I chose to do. And you know,

1463
01:33:59,200 --> 01:34:03,720
Speaker 1: in the summer of I realized that something I had

1464
01:34:03,760 --> 01:34:08,400
Speaker 1: been involved in was playing a really awful role in

1465
01:34:08,560 --> 01:34:12,400
Speaker 1: undermining democracy. And I didn't really understand it because I've

1466
01:34:12,400 --> 01:34:17,120
Speaker 1: been out of Facebook at that point for h seven years,

1467
01:34:18,479 --> 01:34:20,679
Speaker 1: and so I had to do a lot of studying

1468
01:34:20,800 --> 01:34:23,160
Speaker 1: to get up to speed to figure it out. But

1469
01:34:23,280 --> 01:34:25,519
Speaker 1: by early seventeen it was really obvious to me that,

1470
01:34:26,160 --> 01:34:28,840
Speaker 1: you know, I had to do one or two things,

1471
01:34:28,880 --> 01:34:31,200
Speaker 1: either to say this is somebody else's problem, which is

1472
01:34:31,240 --> 01:34:34,600
Speaker 1: the American way, or I went nope, I played a

1473
01:34:34,680 --> 01:34:36,639
Speaker 1: role in this thing. I'm going to drop everything. I'm

1474
01:34:36,640 --> 01:34:40,200
Speaker 1: going to focus on this because my value system, in

1475
01:34:40,200 --> 01:34:45,080
Speaker 1: the way I was brought up, requires it. And I

1476
01:34:45,160 --> 01:34:47,360
Speaker 1: think each of us reaches that point at a different

1477
01:34:49,160 --> 01:34:52,479
Speaker 1: you know, under different circumstances. I reached mine. You Know,

1478
01:34:54,439 --> 01:34:58,519
Speaker 1: what I am hopeful is that the pandemic will get

1479
01:34:58,880 --> 01:35:03,240
Speaker 1: a majority of America to do that. I took tremendous

1480
01:35:03,360 --> 01:35:08,240
Speaker 1: hope from the mid terms when the very groups most

1481
01:35:08,400 --> 01:35:13,720
Speaker 1: suppressed in turned out in record numbers and delivered the

1482
01:35:13,800 --> 01:35:19,000
Speaker 1: House of Representatives for the Democrats. And my point is,

1483
01:35:19,080 --> 01:35:23,240
Speaker 1: I am hopeful, but I don't prioritize that. I think

1484
01:35:23,320 --> 01:35:26,400
Speaker 1: each of us must do our part. I think this

1485
01:35:26,600 --> 01:35:29,200
Speaker 1: is like a war effort, and we need to suspend

1486
01:35:29,360 --> 01:35:35,439
Speaker 1: our dreams for the duration, right, because whatever path we

1487
01:35:35,560 --> 01:35:39,000
Speaker 1: were on, I mean, if Trump didn't kill it, the

1488
01:35:39,080 --> 01:35:43,639
Speaker 1: pandemic is killing it. So stop focusing on that. Let's

1489
01:35:43,720 --> 01:35:48,840
Speaker 1: focus on things that will, over time make our lives better.

1490
01:35:49,479 --> 01:35:53,280
Speaker 1: Let's look for inspiration to those people who did that

1491
01:35:53,400 --> 01:35:56,160
Speaker 1: in the past. And I get mine from the Civil

1492
01:35:56,240 --> 01:35:59,599
Speaker 1: rights movement. My my mentor in my activism, man named

1493
01:35:59,640 --> 01:36:05,280
Speaker 1: Clarence Clarence Jones. Clarence was Dr King's attorney and speech writer.

1494
01:36:06,200 --> 01:36:09,519
Speaker 1: And Clarence is ninety years old, but he takes a

1495
01:36:09,640 --> 01:36:12,760
Speaker 1: lot of time to teach me how to be an activist.

1496
01:36:13,080 --> 01:36:16,600
Speaker 1: And my parents were bit players and civil rights me

1497
01:36:16,680 --> 01:36:19,000
Speaker 1: when I was a kid, so I already had a

1498
01:36:19,080 --> 01:36:21,640
Speaker 1: great deal of comfort with a lot of the methodology.

1499
01:36:21,760 --> 01:36:25,240
Speaker 1: But you know, I was suddenly I was gonna be

1500
01:36:25,280 --> 01:36:27,200
Speaker 1: out front, right, and I had to learn to where

1501
01:36:27,600 --> 01:36:30,200
Speaker 1: to dress up for every meeting, bring my toothbrush right,

1502
01:36:30,280 --> 01:36:33,519
Speaker 1: do all the things, you know, treat everybody with respect,

1503
01:36:33,720 --> 01:36:36,400
Speaker 1: don't make it personal, right, all the things that they did,

1504
01:36:36,840 --> 01:36:40,800
Speaker 1: you know, to deal with people like Bull Connor. And

1505
01:36:41,520 --> 01:36:44,200
Speaker 1: here's the thing, I'm just one dude, okay, And I'm

1506
01:36:44,320 --> 01:36:47,320
Speaker 1: flawed and I've got limitations, and i haven't been that successful.

1507
01:36:48,400 --> 01:36:52,320
Speaker 1: But what I can tell you is that there you

1508
01:36:52,520 --> 01:36:57,840
Speaker 1: feel better if you're involved. Even when it doesn't work,

1509
01:36:58,320 --> 01:37:02,080
Speaker 1: it's worth doing. It's worth fighting the good fights. And

1510
01:37:02,280 --> 01:37:07,840
Speaker 1: those of us who grew up, you know, with Neil

1511
01:37:07,920 --> 01:37:11,519
Speaker 1: Young singing for Dead in Ohio, right, those of us

1512
01:37:11,600 --> 01:37:15,200
Speaker 1: who grew up with Buffalo Springfield, doesn't there's something happening here.

1513
01:37:16,720 --> 01:37:23,080
Speaker 1: And you know, listening to Paul McCarney to Blackbird right, um,

1514
01:37:24,160 --> 01:37:27,120
Speaker 1: listening to the Chambers brothers tell us time has come today.

1515
01:37:29,720 --> 01:37:33,800
Speaker 1: And I mean everybody's got their list of people who

1516
01:37:33,920 --> 01:37:41,439
Speaker 1: had a call to action. And if not now when

1517
01:37:42,280 --> 01:37:45,120
Speaker 1: I mean seriously, if this doesn't motivate you to get

1518
01:37:45,160 --> 01:37:50,360
Speaker 1: off your ass and and like push back, what will

1519
01:37:50,920 --> 01:37:54,720
Speaker 1: I mean you and I, I mean my wife and I.

1520
01:37:56,120 --> 01:37:59,800
Speaker 1: We like going to demonstrations, right, We like marching. There's

1521
01:38:00,000 --> 01:38:03,240
Speaker 1: something very therapeutic about joining with other people to express

1522
01:38:03,760 --> 01:38:07,719
Speaker 1: political views. Where are the margins now? Right now? Social

1523
01:38:07,800 --> 01:38:11,080
Speaker 1: distancing makes that difficult, But what are the analogs? What

1524
01:38:11,200 --> 01:38:15,240
Speaker 1: are the things that we can do to express our discomfort?

1525
01:38:15,960 --> 01:38:20,519
Speaker 1: Because if we're always going to optimize everything for convenience. Hell,

1526
01:38:21,120 --> 01:38:23,280
Speaker 1: Trump's not our biggest problem. Climate change is going to

1527
01:38:23,400 --> 01:38:25,880
Speaker 1: kill us because convenience is just destroying the account of

1528
01:38:26,000 --> 01:38:29,800
Speaker 1: destroying the environment. And you know, we're going to have

1529
01:38:30,040 --> 01:38:33,760
Speaker 1: to decide that something matters more than our joy in

1530
01:38:33,840 --> 01:38:37,479
Speaker 1: the moment. And you know, here's the thing that was

1531
01:38:37,560 --> 01:38:39,640
Speaker 1: my choice. Everybody gets to make their own. And the

1532
01:38:39,800 --> 01:38:42,880
Speaker 1: thought experiment I asked you to engage in is I'm

1533
01:38:42,920 --> 01:38:46,120
Speaker 1: not asking anybody who's listeners to believe that I know

1534
01:38:46,240 --> 01:38:49,120
Speaker 1: what I'm talking about, but I am asking you to

1535
01:38:49,240 --> 01:38:53,400
Speaker 1: do a thought experiment. Imagine what if what Magna says

1536
01:38:54,240 --> 01:38:58,720
Speaker 1: it's correct, how would I behave differently? Would I do

1537
01:38:59,040 --> 01:39:03,760
Speaker 1: anything different? And if you would, then do that. If

1538
01:39:03,800 --> 01:39:07,680
Speaker 1: you wouldn't, then that's the answer. But you know, I

1539
01:39:10,040 --> 01:39:11,799
Speaker 1: I mean, Bob, one of the things I love about

1540
01:39:11,880 --> 01:39:19,479
Speaker 1: you is that you're you're You're unafraid to put ideas

1541
01:39:19,560 --> 01:39:24,640
Speaker 1: on the table, and when you're wrong, you have a

1542
01:39:24,760 --> 01:39:28,960
Speaker 1: whole newsletter of the feedback, right And you and I

1543
01:39:29,160 --> 01:39:33,800
Speaker 1: had a huge conversation at one point about why your

1544
01:39:33,880 --> 01:39:38,360
Speaker 1: perception than Apple post Steve Jobs was somehow inferior and

1545
01:39:38,520 --> 01:39:41,280
Speaker 1: my view that no, the world was different. You needed

1546
01:39:41,320 --> 01:39:45,719
Speaker 1: a different set of skills, and you know, Apple was different,

1547
01:39:45,800 --> 01:39:47,439
Speaker 1: and there were things you didn't have that you didn't

1548
01:39:47,439 --> 01:39:50,320
Speaker 1: have before, but they weren't it wasn't relevant the way

1549
01:39:50,360 --> 01:39:52,599
Speaker 1: it would have been before. And that oh, by the way,

1550
01:39:53,680 --> 01:39:58,040
Speaker 1: this definition of what counts as innovation or using the

1551
01:39:58,160 --> 01:40:00,920
Speaker 1: wrong metrics that we're looking there. That what Apple has

1552
01:40:01,000 --> 01:40:03,200
Speaker 1: been doing around privacy, what Apple has been doing around

1553
01:40:03,240 --> 01:40:06,479
Speaker 1: payment systems, what Apple has been doing around uh, you know,

1554
01:40:07,400 --> 01:40:10,439
Speaker 1: things like that. Those are forms of innovation that are really,

1555
01:40:10,520 --> 01:40:16,880
Speaker 1: really profound and really important. And so you know, I

1556
01:40:17,040 --> 01:40:20,080
Speaker 1: love you like a brother because there are times when

1557
01:40:20,240 --> 01:40:23,800
Speaker 1: I want to throttle you. And the best part is

1558
01:40:23,880 --> 01:40:27,400
Speaker 1: we can have that conversation and by the way, you

1559
01:40:27,520 --> 01:40:29,760
Speaker 1: straighten me out half the time you're right, and so

1560
01:40:30,080 --> 01:40:32,320
Speaker 1: that's what's cool. Well, the great thing is we can

1561
01:40:32,400 --> 01:40:35,600
Speaker 1: have on an analytical conversation as a result of the

1562
01:40:35,840 --> 01:40:39,840
Speaker 1: era we grew up and in the educations we experienced

1563
01:40:39,920 --> 01:40:43,000
Speaker 1: and achieved and the people we hung with. So you

1564
01:40:43,160 --> 01:40:45,320
Speaker 1: and me, I could go on till the end of

1565
01:40:45,439 --> 01:40:49,000
Speaker 1: time to really addressing the issues, but I think we've

1566
01:40:49,040 --> 01:40:50,800
Speaker 1: come to the end of the feeling we've known. Will

1567
01:40:50,840 --> 01:40:53,400
Speaker 1: certainly check in with you again, you're a great uh

1568
01:40:54,280 --> 01:40:58,280
Speaker 1: temperature taker of what's going on. But Roger, always great

1569
01:40:58,320 --> 01:41:00,120
Speaker 1: to talk you. Thanks so much for your ins and

1570
01:41:00,479 --> 01:41:02,519
Speaker 1: about the one thing that we should also do is

1571
01:41:02,640 --> 01:41:06,360
Speaker 1: we should you should establish a list through your newsletter

1572
01:41:06,760 --> 01:41:10,960
Speaker 1: of artists who need our help, okay, because there are

1573
01:41:11,000 --> 01:41:13,240
Speaker 1: a ton of artists out there who have no financial

1574
01:41:13,280 --> 01:41:14,880
Speaker 1: support right now. There are a ton of people in

1575
01:41:15,920 --> 01:41:19,400
Speaker 1: band crews who are currently unemployed, their stage hands who

1576
01:41:19,439 --> 01:41:22,680
Speaker 1: are unemployed. And we've got to find a way to

1577
01:41:22,840 --> 01:41:25,800
Speaker 1: get way past where music cares goes and you know

1578
01:41:25,880 --> 01:41:28,799
Speaker 1: where a sweet relief well you know, yeah, somebody emailed

1579
01:41:28,800 --> 01:41:33,639
Speaker 1: me they had a benefit in Philadelphia and they raised

1580
01:41:33,640 --> 01:41:36,640
Speaker 1: a hundred grant and they gave out grants of just

1581
01:41:36,760 --> 01:41:40,519
Speaker 1: a couple of grant all these people. This analogizes to

1582
01:41:40,680 --> 01:41:44,920
Speaker 1: the country at large. There's no organization in terms of

1583
01:41:45,000 --> 01:41:47,360
Speaker 1: giving people. It's one thing if you know, someone had

1584
01:41:47,360 --> 01:41:49,360
Speaker 1: a heart attack, they lost their house, but a lot

1585
01:41:49,439 --> 01:41:52,560
Speaker 1: of people they just need to buy food. It's and

1586
01:41:52,680 --> 01:41:54,880
Speaker 1: as I say we're talking earlier, everyone's saying, well, when

1587
01:41:54,880 --> 01:41:56,360
Speaker 1: are we opening? When we opening? And you and me

1588
01:41:56,479 --> 01:41:59,200
Speaker 1: both no, we're not opening soon. No, And we've got

1589
01:41:59,320 --> 01:42:01,400
Speaker 1: to support people and so you know, I've got to

1590
01:42:01,479 --> 01:42:04,040
Speaker 1: deal with my band, my crew, the post artists. It's

1591
01:42:04,040 --> 01:42:05,640
Speaker 1: going to keep them and pay money. This is my

1592
01:42:05,800 --> 01:42:08,519
Speaker 1: opportunity to give back. But there are a lot of

1593
01:42:08,560 --> 01:42:10,400
Speaker 1: other people who need our help and we've got to

1594
01:42:10,439 --> 01:42:12,400
Speaker 1: find a way. And one of the things is, for

1595
01:42:12,520 --> 01:42:15,560
Speaker 1: better worse, your newsletter is one of the has the

1596
01:42:15,760 --> 01:42:19,560
Speaker 1: greatest reach in the music business for the demographic that

1597
01:42:19,600 --> 01:42:21,679
Speaker 1: you and I inhabit, and a lot of folks there

1598
01:42:21,840 --> 01:42:24,160
Speaker 1: and who And I'm just saying, if we keep a list,

1599
01:42:24,240 --> 01:42:26,040
Speaker 1: then people can select the ones that they want to

1600
01:42:26,080 --> 01:42:28,439
Speaker 1: support and help out right. And you know, it's a

1601
01:42:28,800 --> 01:42:31,000
Speaker 1: it's an affinity thing. The great thing about music is

1602
01:42:31,160 --> 01:42:33,759
Speaker 1: you know you can like one artist and not like another.

1603
01:42:34,400 --> 01:42:36,960
Speaker 1: And I think we can use that to help people out. Okay,

1604
01:42:37,160 --> 01:42:40,519
Speaker 1: well that's certainly food for thought. Anyway, Thanks again for

1605
01:42:40,640 --> 01:42:42,840
Speaker 1: doing this, Roger. I love your brother. Take care and

1606
01:42:42,920 --> 01:42:45,400
Speaker 1: stay well, and everybody out there, please stay well. Our

1607
01:42:45,439 --> 01:42:47,760
Speaker 1: first job is to survive this there, that's for sure.

1608
01:42:47,800 --> 01:42:49,519
Speaker 1: Until next time. This is Bob left th