2:00

and they all realize they're better off

2:02

working together. And they seal the deal

2:04

with what else? A new theme park

2:06

to be built within the confines of

2:08

the Reedy Creek Improvement District. You might

2:10

know it as Disney World. It's kind

2:12

of a beautiful thing. In fact, it

2:15

is indeed. ["The Circle of

2:17

Life"] On

2:24

the show today. And by the way, in

2:26

that last analogy, is DeSantis Pumbaa or

2:28

Timon? I'm trying to think. Some

2:31

vestiges of each. Anyway, we speak

2:33

of a race for Congress that

2:35

is close and is nasty. But

2:37

first, Glenn McDonald is a streaming

2:39

music pioneer who helped engineer

2:42

and program the algorithm that powers Spotify

2:44

and chooses the song that you hear

2:46

next. Yeah, it's that guy. He's out

2:48

with a new book. You have not

2:51

yet heard your favorite song, How Streaming

2:53

Changes Music, Glenn McDonald, up next. ["How

2:56

Streaming Changes Music"] As

3:04

a radio professional, I love a good

3:06

sound effect. Here's one. And it also

3:08

inspires a Pavlovian response. To me, it

3:11

says, Shopify, that is the sound of

3:13

Shopify doing its job. Because

3:15

we know creating retail experiences is

3:17

really tough, especially with

3:19

multiple stores, teams of staff, fulfillment

3:22

centers, separate workflows. It is a

3:24

lot if you've ever been in

3:26

e-commerce, trying to get in e-commerce.

3:28

We're intimidated out of e-commerce. You

3:30

know this. But then

3:32

come Shopify point of sale and

3:35

you could do it without complexity.

3:37

If this existed for hundreds of

3:39

years, maybe even more, the headache

3:42

of commerce would have been so

3:44

much easier, so much less of

3:46

a headache. This is the kind of miracle

3:48

that just hums along pretty quietly in the

3:50

background. I mean, it gives you amazing data

3:52

and reports that you could act on, but

3:55

it just takes things off your plate

3:57

so you could concentrate on your actual.

6:00

like the first three letters and hard, B-I-N-G-E,

6:03

as in how you'll want to

6:05

catch up on all the episodes,

6:07

on Apple Podcasts, Spotify, or wherever

6:09

you listen to podcasts. I've

6:16

interviewed many musicians and magicians on the

6:18

show, magicians figurative, magicians, well, I'm not

6:21

gonna say literal, but people who claim

6:23

their job is to be magicians and

6:25

they're good at it. I

6:27

don't know if I've ever interviewed an alchemist,

6:29

but I'm going to now break

6:32

that trend. Spotify's former data

6:34

alchemist, Glenn McDonald, is here.

6:38

He is the author of the new

6:40

book, "'You Have Not Yet Heard Your

6:42

Favorite Song," and he's going to talk

6:44

about the digital wizardry that he was

6:46

in charge of for a company you

6:48

may have heard of. And in fact,

6:50

you may be listening to us now

6:52

on Spotify. Glenn, welcome to the gist.

6:54

Thank you. When they said,

6:57

you're going to be our data alchemist, you immediately

6:59

said, oh, I know what you're talking about? Well,

7:02

it went the other way. At

7:05

the Echo Nest before we were acquired

7:07

by Spotify, I had a boring title.

7:09

It was Principal Engineer, and

7:12

I'd get interviewed about things and they'd say, what's

7:14

your title? And I'd say Principal Engineer, which

7:17

was just a level. But

7:19

then the story the next day would say,

7:21

the Echo Nest's Principal Engineer, and

7:24

because the two founders are both engineers too,

7:26

it was really embarrassing for me because they

7:28

were definitely more principal than I

7:31

was. So I started

7:33

calling myself a data alchemist. At least we'd

7:35

get rid of the confusion. And Jim

7:38

Luchese, who was the CEO of the Echo

7:40

Nest, loved making people live with their own

7:42

jokes forever. So he heard that

7:44

and was like, all right, that's your title, you're stuck

7:46

with it. So alchemy is

7:48

creating a new substance out of

7:50

an old one. What was your

7:52

main task? They said, we want

7:54

you to what? Be able to

7:56

suggest more music, more genres

7:58

of music. that our users didn't even know

8:01

they'd like, but then you get them to

8:03

like it. That was a thing. I

8:05

mean, I was at the, the equinest when

8:07

it was acquired became the personalization

8:10

division at Spotify. So

8:12

I worked on things for personalization, but also

8:14

in a lot of sort of categorization, music

8:18

knowledge, things that were helpful

8:20

in understanding what your taste was or

8:22

understanding how the music interacted with your

8:25

taste to build personalization on top of.

8:28

Yeah. So one of the, one of

8:30

the things that your website has and

8:32

people can still check out this fantastic

8:36

project, it's everynoise.com and

8:38

it used a lot of Spotify data, but

8:40

you no longer have access to that, but

8:43

it's essentially a map. It's

8:45

a lot of things, but one of the

8:47

things it does, it's a taxonomy of musical

8:50

genres. Now that's interesting

8:52

and it's also available as a

8:54

hoodie. So you can have, you

8:56

know, Latin tech tech house and

8:58

techno Argentinica and bass

9:01

trap and Polish metal core and

9:03

Czech reggae and Ecuadorian alternative rock

9:05

and Ghanaian gospel and German worship

9:08

music. Are you going to list

9:10

all 6,000 of them? I'm

9:13

just scrolling down the list and just

9:15

calling out what, what catches my eye.

9:17

And this isn't even curated, you know,

9:19

there are music and classic Tunisian pop,

9:21

right? Because we hate the modern Tunisian

9:23

pop. We got to go with classic

9:25

Tunisian pop. Some of us do. Yeah.

9:28

You can have those all represented on a

9:30

sprawling map or hoodie, but other

9:33

than curiosity and the

9:35

old Linnaeus type

9:38

task of trying to order the

9:41

world, what's the value of that?

9:44

I mean, I think about genres as communities.

9:47

So to me, the goal

9:49

of the music service

9:51

ought to be connecting people to

9:53

their communities. Some of

9:56

those communities are audiences. Some

9:58

of them are artists communities. Most of

10:00

them are some combination of

10:02

those, but the project and the reason why there's

10:04

so many of them was find

10:07

and try to represent all the communities

10:09

in the world, both show them back

10:11

to themselves, collate their

10:13

collective knowledge, and then use

10:16

it so they or other tourists

10:18

wandering into classic Tunisian

10:20

pop from the nearby

10:23

realms of theremin music could

10:27

try to make sense of like, what is this thing? Does

10:29

it have a name? And if I like it, can I

10:31

hear more of it? So classic

10:33

Tunisian pop actually relies on theremin more

10:36

than other kind of pop music. So

10:39

the map, a bunch of

10:41

dimensions, the map is

10:43

just two of those dimensions. Top

10:45

to bottom is mechanical to

10:48

organic and left to

10:50

right is sonically dense to sort of

10:53

spare and bouncy. And

10:56

a lot of things that don't sound

10:58

totally like each other holistically

11:00

are at similar places on

11:02

those two axes. Right. So

11:05

if you go into each one of those, then

11:07

under the little cloud of artists, there's a map

11:10

of the nearby genres and that's a

11:13

sort of more dimension version

11:16

of just the things that are

11:18

more closely related using more variables.

11:21

And then if you really want to

11:23

amuse yourself, you scroll down further, there's

11:25

a map of the opposite side of

11:28

the genre universe. I

11:30

could just spend days like looking up music

11:33

that I like and then looking at the

11:35

opposites and going, yeah, that's the opposite. It's

11:38

very satisfying. Give me

11:40

a couple opposites that we might not

11:42

think of as opposites. Oh,

11:44

you should really, it's much more interesting to

11:46

do it for yourself. If you go to

11:48

genres on every noise.com and scroll down and

11:50

look at the

11:53

dark one, the second map, and

11:56

you'll see that, you know, whatever you like,

11:58

the opposite is, it's probably probably like

12:00

Norwegian children's music or

12:03

Christian EDM or something. And

12:06

I find that, oh, here's a good one. This

12:08

isn't the opposite. These are two closely related ones.

12:11

Death Industrial, and then just a

12:13

couple of steps away, Bagpipe. And

12:16

I'm thinking to myself, those two, the

12:18

people who play them must find no

12:20

overlap. But when you think about it,

12:23

there is that like droning, I don't

12:25

wanna insult the Bagpipe or the Death

12:27

Industrial scene, but there is a constant

12:29

drone to both of them, is there

12:31

not? Yeah. They probably have different colors.

12:33

The colors are also data. So

12:37

that's a little visual cue that when things

12:39

are next to each other with different colors,

12:41

they have some differences. And

12:43

the same way, if you look

12:45

at patterns of colors across the

12:47

map, you can find some things

12:49

that are spread out in their

12:51

density or their electric acousticness, but

12:53

share a certain ambience, like chill

12:57

things, like there's an ambient

12:59

glassiness that can be done in

13:01

dance music or it can be done

13:04

in experimental. So tell

13:06

me about the idea of genre.

13:08

Is genre a necessity? It's certainly

13:10

not a science. It's a bit

13:12

of an art to figure out

13:14

what's inside a genre. And

13:16

you can always debate everything, but what are

13:18

some of the, you had to, this is

13:20

part of your job, to come up with

13:22

genres and see which genres are

13:25

close to the other ones. What were some of

13:27

the rules of defining a genre that you live

13:30

by? Yeah, I didn't

13:32

begin with a clear sense of

13:34

even that I needed a set of rules. We

13:37

just had like a list of, like, well, these are,

13:39

people always talk about these. Like rock,

13:41

jazz, like you can list, you

13:43

can list 12 probably if you're anybody. And

13:45

then if you're really like stubborn, you can probably

13:47

list 100. And

13:51

as we worked on it, what

13:53

I realized was basically genres are

13:56

communities. Some

13:58

of them are literal communities. of

14:00

artists. I think this was most clear to me

14:02

when I was thinking about punk, because

14:04

I grew up with punk as a new

14:06

thing in the late seventies.

14:09

And so I know the bands that

14:11

were the punk bands and

14:13

my kid is 17

14:16

now and trying

14:18

to explain to them why

14:20

the damned or

14:23

the stranglers are

14:26

a punk band when their idea of

14:28

punk is, you know, a post green

14:30

day. Yeah. Good Charlotte.

14:32

Yeah. Right. It's like,

14:35

it's very, like they don't sound, it doesn't sound

14:37

the same. Um, and the,

14:39

but the truth is punk, the original,

14:41

you know, UK version of punk, it

14:44

was a literal community. Like it was, it

14:46

was people who knew each other. Sometimes they hated each

14:48

other. They were playing at the same clubs.

14:50

You know, they shared the same promoters.

14:52

It was a scene of

14:55

people and of an audience.

14:58

And what I suddenly realized was that's

15:00

basically true of everything.

15:02

Like that's the way to think about

15:05

the way the world organizes

15:08

its attachment to music is it's,

15:11

it's tribal, it's communal. And

15:13

yes, yes. And it's aesthetic often,

15:16

right? It's not about chord progression

15:19

or types of instruments.

15:22

It's about vibe, if

15:24

not vibraphones. Yeah. And, and,

15:26

well, or, or sometimes it is about

15:28

instruments. Like the ration, the, there's

15:30

a, there's a section in the book where I talk

15:33

about the numbers of kinds of genres, but you have

15:35

genres that are historical genres

15:37

that are instrumental. Like you said, bagpipe

15:40

that's and theremin, like

15:42

those are, those are communities around a

15:44

particular instrument. Um, sometimes

15:46

the instruments are so off putting to other musicians.

15:49

They have to go off and form their own

15:51

communities. What's happened with the viola? Yeah.

15:54

And, uh, but like vegan straight

15:56

edge, is a genre based like

15:58

around a lyrical. agenda

16:00

and a sound. And

16:04

they're violin bowls, bows can't use horse hair. But

16:06

sorry to interrupt, go ahead. Oh, yes. Vegan

16:08

violin, that would be a, that one's

16:10

not on the list yet, but yeah. And

16:15

that was the crucial insight to being

16:17

able to make sense of these things.

16:19

And data is if you can find

16:21

the people that like a thing, then

16:24

you can find out what else they like. And

16:26

it, or it goes the other way. If you can find

16:28

a bunch of bands that do a thing

16:31

and you can find the people that listen to

16:33

them all together, then you can

16:35

find the audience. So some

16:37

of the, sometimes the exercise went one

16:39

way and sometimes it went the other, but it

16:42

always ended up with those two things linked. You

16:44

have a bunch of music, you have people, and

16:47

you have some rationale for what they

16:49

mean, but sometimes the people are the

16:51

rationale. Yeah, were there some,

16:53

did you find that there were some genres or

16:56

groups that were conspicuously

16:58

resistant to this? Like

17:00

you would think fans of the B-52s

17:02

would like, I don't know, other things

17:05

in the post-punk genre, but they just

17:07

don't like Gang of Four for whatever.

17:09

And I'm just pulling some examples out

17:11

of my head. From

17:13

a sort of data perspective, you can

17:15

think of genres as neighborhoods in artists

17:17

similarity space and the

17:19

mechanisms that we

17:21

used to extrapolate. All those genres are,

17:24

a human has decided this is gonna be on

17:26

the list, this is what we're gonna call it,

17:29

and these are some artists that define what we

17:31

mean by it. But in

17:33

most of the cases, then

17:36

we used algorithms to extrapolate. So we didn't

17:38

have to manually tag every artist in the

17:40

world. So it's like, well, if what you

17:42

mean by classic rock is Leonard Skinner, Creedence

17:45

Clearwater, Vible, and The Who, then

17:47

here are the other 180 bands that

17:51

are also share an audience and

17:53

style with those bands. And here's

17:55

where that cloud sort of turns

17:59

marginal. It doesn't go on.

18:04

But that meant you could look at

18:06

artists and their list of similar artists

18:08

and see how coherent are

18:11

these. Because yes, there's some metal bands where

18:14

all their fans listen to 100 other

18:16

metal bands that sound exactly like them. And

18:19

the B-52s are a good example. There aren't

18:21

100 other bands that sound exactly like the B-52s. And

18:26

it's the same thing with Damned and the Strangers.

18:28

Those were punk bands that are fans like to

18:30

other punk music. The other punk music mostly didn't

18:32

sound like those bands. But

18:35

the audience and the artists

18:37

all knew that they went together. Yeah.

18:40

So I want to ask you a little bit more

18:42

about genre and then we'll get into your

18:44

techniques. But this is from a great book

18:46

called To Anyone Who Ever Asks.

18:48

And it's about a very obscure

18:50

musician named Connie Converse. It's by Howard Fishman.

18:53

I don't know if you know her or

18:55

the book, but she's really interesting. I know

18:57

of the book. I haven't read it. Yeah.

19:00

And Connie Converse is really interesting because

19:02

what genre does she belong to?

19:04

And Fishman writes, what

19:06

makes some American roots music country

19:09

as opposed to blues or

19:11

gospel or folk? Rodgers and

19:13

Carters record songs that had the artist

19:15

been black would have been labeled blues

19:18

or race music. Both

19:20

act similarly recorded gospel and

19:22

spiritual numbers that were also

19:24

called country or sometimes hillbilly.

19:26

Similarly blues artists like the Mississippi Sheikhs

19:28

or Mississippi John Hurt recorded some of

19:31

the same songs that the Rodgers and

19:33

the Carters did often in similar or

19:35

might be called country musical manner, also

19:37

known as blue notes. And then they

19:39

notes that Jimmy Rodgers even recorded a

19:42

track with Louis Armstrong and asked what

19:44

makes blue Yodel model number nine a

19:47

country song and not a blues

19:49

song. Okay. Great questions. Luckily

19:51

he offers an answer. The answer

19:53

is the recording industry. The

19:56

industry codified and promoted the musical

19:58

genre system to make it easier

20:00

to sell records, grouping artists into

20:02

oversimplified categories that customers could easily

20:05

understand, turn them into flavors and

20:07

brands, flattening and sterilizing much of

20:10

the previously bold idiosyncratic music that

20:12

was made and recorded in the

20:14

United States. Okay, I understand you

20:17

probably understand his critique. On the

20:19

other hand, you know, there's

20:21

a Dewey Decimal system in the library, and

20:23

we could argue if this is this should

20:25

be categorized as 791.4 or 794.2.

20:30

We need some form of organization, but

20:32

what do you think of his critique?

20:35

Is the record industry to blame for

20:37

flattening and over sterilizing? Oh,

20:39

sure. I mean, that definitely happens.

20:43

I think corporations in general do a

20:46

lot of enthusiastic flattening of culture

20:48

because it makes business easier

20:50

to run. I mean, the

20:54

interesting, like, if you turn

20:56

that around, what is the right answer for

20:58

what distinguishes like country

21:01

music from hip hop? Like what is the right

21:03

answer to was Old Town Road a country song?

21:06

And interestingly, the way Billboard

21:08

used to do these things

21:12

back when, like you said, at one point

21:14

they had a race music chart. They

21:17

assembled those charts by polling different

21:19

radio stations in different record stores. And

21:24

then, you know, in the modern era, they no

21:26

longer do that. There's one big set of statistics

21:28

and the current billboard genre charts are

21:31

basically you just take the main chart

21:33

and you cross out anything that isn't whatever genre

21:36

you're in. So the top of the country chart

21:38

is whatever the most popular thing is that counts

21:41

in their methodology as

21:43

country. But I think

21:45

the spirit of that and the way it

21:47

used to work is the country

21:49

audience decides what's country. And

21:52

I was still at Spotify when Old Town Road was big,

21:54

so I could actually do this. I could look and see,

21:57

all right, the people who are listening to Old Town Road.

22:00

Are they country fans? Are they hip-hop

22:02

fans? And that, to

22:04

me, is more interesting. Like, let the

22:06

people decide. But if

22:08

the people can't find the song, and

22:12

maybe they wouldn't if it was

22:14

buried in the wrong chart or

22:16

ignored by the gatekeepers of a

22:18

genre, then the people can't decide,

22:21

right? Yeah, it's true. It's

22:24

a circular problem to introduce things. So,

22:27

you know, there might be a great

22:29

hip-hop song buried on a black metal record

22:31

somewhere, and the hip-hop fans are never going

22:34

to find it. But Old Town

22:36

Road was a case where, yep, they knew

22:38

about it. Like, everybody knew that was happening.

22:40

So you could see, and you

22:42

could do it proportional. So you could

22:44

see that it was

22:47

getting heard, like it was getting

22:49

introduced to country audiences, but it was not

22:51

getting traction in country audiences as much as

22:53

it was getting traction in

22:55

hip-hop and pop audiences. How

22:58

far can you go in accurately

23:00

mapping a genre and recommending

23:02

songs that sound like this with just

23:05

the empirical data that you could load

23:07

into a computer before you let humans

23:10

say if it works or didn't work

23:12

or makes sense or doesn't make sense

23:14

to them? Not very far. I mean,

23:16

we involved humans at all parts of

23:19

the process. I mean, you

23:22

can do a little. They're like clustering

23:24

techniques that, it's

23:26

all humans, because all the data is people

23:28

listening. So they don't think

23:31

of themselves as coding

23:33

or categorizing, but when

23:35

you listen in a non-random way, like you have

23:37

tastes and so you listen to something,

23:42

you are the data that's fueling the system,

23:44

which is part of why I

23:46

think there should

23:48

be a lot more transparency and a

23:50

lot more flexibility in the tools because

23:53

they only exist because people

23:55

listen and share their

23:57

listening with streaming services. And

24:00

so it's kind of their data. The

24:02

data is the world's data. And

24:06

we, the people working on

24:08

trying to make sense of it, owe it back to

24:10

the people who created it. I

24:14

know you write about, for instance, there are

24:16

mistakes that just the computers make. It

24:19

didn't understand banjo as something other

24:21

than singing. So it

24:23

was categorizing all these bluegrass

24:25

records as classical records.

24:28

It's instrumental. Instrument. Yeah,

24:30

vocal. No, vocal. Right. The thing was it

24:33

didn't know what banjo was, so it thought it was a voice. So

24:35

are there other things that I guess you could train

24:38

a computer after a while, but you need a human

24:40

to say, what the hell are you talking about? Yeah.

24:42

I mean, most of the interesting things are

24:46

computer processes as tools for

24:49

amplifying human effort or

24:51

refining human insight. So all

24:54

those genres began with a person saying this

24:56

is a genre, and all the

24:59

algorithms behind them began with me running

25:02

a lot of comparisons and

25:04

being like, all right, this is supposed to be

25:06

German hip hop. And I got

25:09

a list. Is it hip hop? Is it

25:11

German? Or is it wandering

25:13

off into Poland? It's

25:17

so funny that you mentioned German hip hop.

25:19

I was just listening to this song

25:22

that has gone extremely viral about a

25:24

woman named Barbara who has a rutabaga

25:26

and a barber and barbarians.

25:29

And it's this great hip hop German song.

25:31

And then I started, I'm not going to

25:33

say getting into German hip hop, but start

25:36

listening to German hip hop. And I said

25:38

to myself, I wish I were a better

25:40

or more eclectic person so I could actually

25:42

give this more of a chance. But you

25:45

know what got in the way? It wasn't

25:47

anything other than the actual German language. And

25:49

if they were just saying nonsense words in

25:51

English, I think I could abide it. But

25:53

it was listening to these words that were

25:56

just constantly creating such cognitive dissonance that

25:58

thus ended my experience. with German

26:00

hip-hop. And there's

26:03

a book, I mean there's a chapter in

26:05

the book about this, about listening to hip-hop

26:08

and other languages. And when

26:10

I started writing it, I was like, I

26:13

want to explain how people can do this,

26:15

how they can become people who appreciate hip-hop

26:18

and other languages. And as I was

26:20

writing it, I realized, I don't have any

26:23

idea. Like, I can't, I have no way to

26:25

tell you how to do that. All

26:27

I can do is tell you why it's

26:30

rewarding if you can get yourself there.

26:33

Like, that's the best test. Like,

26:36

if you can appreciate hip-hop in other

26:39

languages, you basically, that's

26:41

your past to understand, to

26:43

appreciate anything. Because it's,

26:45

you know, instrumental music, it's easier, because

26:48

there's, like you said, there's no cognitive dissonance. But

26:50

if you can confront the cognitive dissonance and get

26:52

through it, and

26:55

it was Turkish hip-hop, for me, which

26:58

interestingly, mostly arose in Germany,

27:01

that really

27:03

broke through. And I'm like, I have no

27:05

idea. I don't pretend to know even what,

27:07

like, I mean, I can guess

27:10

at what Turkish hip-hop is about, but

27:12

I could be totally wrong. It

27:15

doesn't matter. There's like a rhythm to it.

27:17

I'm not even, like, I wasn't even that

27:20

interested in Turkey. I'm interested in

27:22

many things, but like, it wasn't the top of my list. But

27:24

Turkish hip-hop, I'm like, this is great. This

27:28

rhythm is great. I'll

27:30

just imagine what they're saying, or maybe I won't.

27:33

I'm just like listening without imagining.

27:35

And that was sort of neat when it

27:37

clicked over for me. I'm like, all

27:40

right, it doesn't matter what they're saying to me.

27:42

It matters to them. I'm okay with

27:44

that. And therefore I can

27:46

listen to everything. And that

27:48

is Glenn McDonald, streaming music genius, author of

27:50

the new book, You Have Not Yet Heard

27:52

Your Favorite Song, How Streaming Changes Music, Pesca

27:54

Plus listeners. We'll get to hear my final

27:56

question for Glenn during our interview. Interview in

27:58

which he cracks and cries. No, he doesn't

28:01

answer is it just as well as the

28:03

rest of them I will get

28:05

him to tell us how

28:07

to make Spotify suggest more

28:09

exciting and surprising songs Pesca

28:12

plus listeners will hear that answer. We're

28:14

not trying to hold you hostage But

28:17

if you want to support the show and

28:19

get a bit more content each week just

28:21

a bit more It's a whole interview you

28:24

heard. This is a whole interview. What would

28:26

be the mathematical equation plus? Pesca

28:28

plus go to subscribe Mike

28:30

Pesca comm and sign up

28:43

And now the spiel in this

28:45

election year few incumbents have been losing

28:47

primaries We have one or possibly

28:49

have one Bob good of Virginia Does

28:52

trail by a few hundred votes in

28:54

the Republican primary there? He may

28:56

go on the Democratic side there was

28:58

the trend of a couple years ago

29:01

of progressives unseating more centrist Legislators

29:03

that has calmed down the question is

29:05

has it reversed? Well in

29:07

New York early voting is open

29:09

for the Tuesday primary and one

29:11

progressive who may lose to a

29:14

more moderate Candidate is Jamal Bowman

29:16

Bowman represents New York 16th congressional

29:18

district almost entirely in Westchester County

29:20

He's a member of the squad

29:22

He's verbally sparred with really sought

29:24

out a chance to yell at

29:26

Marjorie Taylor Greene He broke

29:28

from almost every member of Congress to campaign

29:31

for tick tock remaining in the hands of

29:33

bite dance He was a

29:35

member of the Democratic Socialists of America

29:37

than he wasn't but now he is

29:39

again and claims He never stopped their

29:41

records of dues paying don't rebut that

29:43

but nationally you will be told

29:45

that Jamal Bowman's candidacy

29:47

comes down to one issue

29:50

Israel Bowman is

29:52

against continued US funding to Israel

29:54

his opponent County executive George Latimer

29:56

has received more money from a

29:58

pack the pro-Israel lobbying group than

30:01

anyone this cycle. Here is Bowman

30:03

asked a question about Israel in

30:05

a debate held Tuesday. If

30:07

they're engaged in a military occupation of the

30:09

West Bank, if we have a settlement expansion

30:11

in the neighborhood of 700,000 settlers in the

30:13

West Bank, and

30:16

we have a blockade in Gaza, and if we

30:18

have a situation where 18 human

30:21

rights organizations have referred to Israel as an

30:23

apartheid state, we need to be doing something

30:25

different. And he doesn't want to speak honestly

30:28

about the conditions over there. And again, it

30:30

doesn't acknowledge Palestine. Here is Latimer's response. You

30:32

heard from Jamal about 75 years of occupation.

30:34

That's how he defines the state of Israel

30:37

being in their present location. And you heard

30:39

him use the word apartheid as dealing with

30:41

the Israeli government. So I think he's clearly

30:44

on the record, again, in public. He said

30:46

over the weekend that he viewed it as

30:48

a colonial settler state in one of his

30:50

Breakfast Club YouTube conversations. So I think you

30:53

understand what Jamal Bowman is on this issue.

30:55

You understand what George Latimer's on this issue.

30:58

Now, I don't actually think that

31:00

Israel or the war in Gaza is the

31:03

number one or two or three issue for

31:05

voters. Every poll backs that up. Top

31:08

issues include the economy and

31:10

housing. It is on housing

31:12

that I began researching Latimer's

31:14

record. As an only US

31:16

official, Bowman has some

31:18

votes, but he doesn't really have a

31:20

record of actually building housing. County executive

31:22

comes closer to that issue directly. So

31:25

Westchester has a pretty poor

31:28

history of housing and desegregation.

31:30

There was a consent decree

31:33

in which the Department of Justice

31:35

had to monitor the county, and

31:37

they did so for over a

31:40

decade. They had to monitor municipalities

31:42

therein because fair housing

31:44

was not allowed. Latimer

31:47

defeated his Republican predecessor, Rob Asterino,

31:49

who thumped his nose at compliance

31:51

and dug in his heels, denying

31:53

that there was a housing problem.

31:56

But Latimer was on board with

31:58

trying to... to do something about

32:00

the issue. It's a hard issue.

32:02

Westchester needs 12,000 more affordable units.

32:07

It is a wealthy New York

32:09

suburb. Housing is very expensive. Developers

32:11

have to have their arms twisted

32:13

or given incentives to do something

32:15

other than maximize profits down the

32:17

line. Towns, and often the

32:20

very whitest towns in Westchester, don't allow

32:22

apartments to be built. They say it's

32:24

for density or aesthetics or neighborhood history.

32:27

And there may be some elements to

32:30

that or not, but the result is

32:32

a dire lack of affordable housing. So

32:34

Latimer pushed, cajoled, sometimes dug in his

32:36

heels, sometimes opted to receive millions for

32:39

a sewer system overhaul without forcing the

32:41

affordable housing issue as a condition of

32:43

getting that sewer system money. These are

32:45

all the choices that you have to

32:48

make to get things done as a

32:50

county executive. And I'll read the results

32:52

of a 2021 headline in

32:56

the Rockland slash Westchester Journal News.

32:59

Federal Monitor Westchester substantially

33:02

met its obligations in

33:04

housing case. The case

33:06

dated back to 2009, eight

33:08

years before Latimer took office, as I

33:11

said. But once he did, well, I'll

33:13

read from the DOJ's assessment. In the

33:15

time since the Monitor's last assessment, the

33:17

county has elected a new executive, George

33:20

Latimer. As a general matter, under the

33:22

leadership of Mr. Latimer, the county has

33:24

demonstrated a renewed commitment to satisfying its

33:27

obligations under the settlement. I have been

33:29

encouraged by the good faith efforts

33:31

of the Latimer administration. Elsewhere, the

33:34

Monitor writes, the Latimer administration's decision

33:36

to commission such an assessment, this

33:38

was a fair housing guide in

33:40

2018, despite having

33:42

no legal obligation to do so, is

33:45

a powerful indicator of the

33:48

county's good faith and genuine

33:50

commitment to furthering fair housing.

33:52

Bottom line, building affordable

33:54

housing is hard, demand

33:56

perpetually outstrips supply, but

33:58

George Latimer, Latimer was good

34:01

on the affordable housing issue. The

34:04

department of justice, the Joe Biden

34:06

department of justice, by the time

34:08

it signed off and its decree

34:10

said so. Now I only

34:12

know of his record so in

34:14

depth because today I read a

34:16

piece in Jacobin, the socialist magazine,

34:18

criticizing Latimer for his housing policies.

34:20

The article's tactic was to quote

34:22

the advocates who want to push

34:24

Latimer and the county even further,

34:27

but also to leave out the

34:29

context that runs against this advocacy,

34:31

to leave out any counter considerations

34:33

or to leave out facts that

34:35

run against the narrative. The article,

34:37

for instance, claims that under Latimer,

34:39

the county failed to meet the

34:41

minimum requirement of building 750 affordable units.

34:45

It says, quote, by almost

34:47

every metric, Latimer's administration

34:50

fell short of meeting even

34:52

the bare minimum requirement of

34:54

the desegregation order. Except

34:56

it did build 750 units more so. Here's

35:00

from the Westchester record, which is not

35:02

one of those publications that only seeks

35:04

to portray one side of this story.

35:06

This was them in 2021. While

35:10

the settlement called for Westchester to create 750 affordable

35:12

units, far more

35:14

in the pipeline. By December 31st, financing

35:17

was in place for 911 units with

35:20

building permits issued for 853 units. Marketing

35:24

was complete for 798 units and

35:27

739 units were approved for

35:29

occupancy. Let's update to

35:31

today. This is from a February

35:33

report from the County Planning Commissioner

35:35

Blanca Lopez. She said

35:37

that in the six years since the Latimer

35:39

administration took office, more than 1,100 units of

35:41

affordable housing were built

35:44

and fully occupied. In addition, 1,500 units

35:47

are under construction. An additional 530 units

35:49

have obtained their land use and funding

35:51

approvals and an additional 3,200 units are

35:54

either pending approvals or in the planning stages. And

35:57

I get all the critiques of that. I wouldn't

35:59

take that on faith. Blanca Lopez is

36:01

a Latimore appointee, a

36:03

unit in the pipeline, it's not worth that much

36:05

more than a pipe dream, and then you have

36:08

the definition of affordable, which doesn't mean that everyone

36:10

can afford it, not even close in some cases.

36:13

Also, you know, all those numbers, 3,200, even

36:16

the high numbers, don't even get us

36:19

close to halfway to the goal. But

36:21

Latimore, let us be fair,

36:23

he has been at least pretty

36:25

good on affordable housing. If

36:28

I were writing for a socialist magazine, and this

36:30

post got 300,000 likes, I

36:32

could make him look less than good, but

36:35

wouldn't be fair and honest and complete, and

36:37

I would say the public should look deeper.

36:40

In the same way, if I were writing for

36:42

a right-wing publication, I could say, Jamal Bowman is

36:44

a friend of Hamas, but that's unfair.

36:46

People are saying that online, but the

36:48

public should look deeper. The

36:50

Working Families Party, a socialist aligned party

36:53

that's on the ballot in New York,

36:55

is also campaigning for Jamal Bowman, and

36:57

they write against George Latimore on their

36:59

Twitter feed, quote, "'George Latimore

37:02

made it plain.' He

37:04

believes that when black voters turn

37:06

out to the polls, they quote,

37:08

"'Skew results.' In the

37:10

face of voter suppression around the country

37:12

targeting voters of color, Latimore has

37:14

chosen his side. Again, I

37:17

say the public should look deeper." Indeed,

37:20

it is easier than what I

37:22

did today, which is to fact check

37:24

a Jacobin article and subscribe to lowhud.com.

37:27

You could subscribe, too, 25 cents for

37:29

every two months. You could read almost

37:31

all the articles cited that comprise the

37:33

Jacobin article. Don't waste your time, just

37:35

listen to this spiel. But what the

37:37

Working Party's family does in this case

37:39

is they make it really, really easy

37:42

because they have a link to the

37:44

clip from which they draw their conclusion

37:46

that George Latimore believes black voters, quote,

37:48

"'Skew the results.'" Here's that clip. He

37:51

was set up with a question. Why

37:53

did Jamal Bowman win a close

37:55

Democratic primary in 2020? 2020

37:58

is you, as we all know, is very strange here. You

38:00

had COVID and a whole lot of restrictions

38:02

that were in place. And

38:04

everybody, one of the things you may recall

38:06

that Governor Cuomo did was authorize

38:09

an absentee ballot to be sent to

38:11

every single voter. And when you

38:13

do that, people who don't normally vote wind up

38:15

voting in this primary. So you have an abnormally

38:18

high vote total that

38:21

probably skewed results. That is it. And

38:24

I think you hear there the quality of the critique. I

38:27

wish the terms of the debate in this

38:29

race were just Israel. At

38:31

least with Israel, Bowman honestly does want

38:33

the U.S. to end the funding to

38:36

Israel and Latimer honestly doesn't. And there

38:38

are lots of people who agree with

38:40

each of them and honestly understand their

38:43

positions. At least

38:45

with those views, voters can match

38:47

their opinions and their perceptions to

38:49

what the candidates actually think. With

38:51

the rest of it, I don't know what

38:53

to say. Dig deeper. That's

39:01

it for today's show. Corey Warr is the

39:03

producer of The Gist and Joel Patterson is

39:05

the senior producer. Michelle Pesca is in charge

39:08

of special projects for Peachfish Productions. The

39:10

Gist is presented in collaboration with

39:13

Ellipsen's AdvertiseCast for advertising inquiries. Go

39:15

to advertisecast.com/the gist. Um peru, jee

39:17

peru, do peru. And thanks

39:19

for listening.