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Speaker 1: It feels like we all have whiplash from the policy

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Speaker 1: changes that are happening in the United States of America right.

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Speaker 2: Now, right right. The rent is high, groceries are high.

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Speaker 2: You want to play sixty five dollars to make a

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Speaker 2: turkey and cheese sandwich.

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Speaker 1: Wow, that's no condiments. People are being laid off. Jobs

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Speaker 1: are hard to come by. We even had a listener

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Speaker 1: right in and ask us. They say, hey, and Dope

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Speaker 1: Labs cover the current state of the economy and the

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Speaker 1: possibility for the future. Hey, you know what that means.

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Speaker 1: Your wish is our command. Friend. I'm TT and I'm Zakiyah,

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Speaker 1: and this is Dope Labs. Welcome to Dope Labs, a

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Speaker 1: weekly podcast that mixes hardcore science with pop culture and

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Speaker 1: a healthy dose of friendship.

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Speaker 2: This week, we're breaking down the vital signs of the

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Speaker 2: US economy, zooming in on the stem and life sciences world,

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Speaker 2: asking an economists how we got here and what comes next.

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Speaker 1: Let's get into the recitation.

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Speaker 2: I know that the economy is a big word, okay,

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Speaker 2: and it feels unpredictable and like something that my mind

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Speaker 2: can't fully wrap itself around, Like the economy is how

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Speaker 2: much groceries, cout how much fundings universities get, and there

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Speaker 2: are so many different lists that you have to consider

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Speaker 2: when you're talking about the economy. Yes, no, yes, and

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Speaker 2: even within that, like how does the labor market fit

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Speaker 2: into that? Because the jobs numbers are swinging And I

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Speaker 2: don't know about you, but when I submit a report,

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Speaker 2: it's supposed to be done no revisions, but they're coming

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Speaker 2: back with revisions months later, and that.

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Speaker 1: Feels confusing to me.

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Speaker 2: Right, they're saying, oh, psych, there's actually a million less

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Speaker 2: jobs than we say.

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Speaker 1: And we only said nine hundred thousand.

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Speaker 2: There's negative jobs. There's negative jobs, and it feels like

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Speaker 2: with jobs that stem jobs, they're being really hard too.

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Speaker 1: Yeah, I just know that I'm tired. And it feels

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Speaker 1: like everyone is anxious, Like the conversation about the economy

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Speaker 1: is showing up. You're like, ah, yes, I like a

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Speaker 1: macha and they're like, yeah, but the economy, like it's

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Speaker 1: showing up everywhere.

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Speaker 2: Macha in this economy. Yeah yeah, I don't know.

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Speaker 1: I'm making my macha home. That's me talking to myself

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Speaker 1: in the kitchen.

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Speaker 2: So what do we want to know?

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Speaker 1: Well, I want to know how economists are actually measuring

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Speaker 1: this stuff like the economy, and is the labor market

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Speaker 1: included in that? Is a labor market measured separately? Like

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Speaker 1: what's happening?

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Speaker 2: And why are the job numbers swinging so wildly?

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Speaker 1: You know what I mean? Like a million jobs? Yeah,

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Speaker 1: that's a lot of job That doesn't feel like a

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Speaker 1: rounding error. No, that feels like somebody was asleep at

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Speaker 1: the keyboard, just held down to zero exact. And what's

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Speaker 1: been the ripple effects of the cuts to federal research

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Speaker 1: funding that we saw at the top of the year.

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Speaker 2: Is that what.

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Speaker 1: We're seeing now with the stem job landscape?

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Speaker 2: Right? And what about AI You know that's a dirty

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Speaker 2: word for some folks, But how is that changing the

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Speaker 2: job landscape? I thought it was going to be like

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Speaker 2: a boom, so I'm interested in that. And then where

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Speaker 2: does immigration fit into all of this because there's been

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Speaker 2: a lot of rhetoric online m hm hm. And how

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Speaker 2: can we I guess, students, workers, everybody that is involved

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Speaker 2: in the economy adapt.

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Speaker 1: Yeah, how do we get some stability? I want them

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Speaker 1: to stop shaking the table.

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Speaker 2: To answer these questions, We're talking to Daryl West from

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Speaker 2: the Brookings Institution, which is a Washington, DC based think tank.

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Speaker 2: They do research on a wide variety of public policy topics,

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Speaker 2: and prior to that, Daryl was a professor of political

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Speaker 2: science and public policy at Brown University.

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Speaker 1: So, Daryl, before we jump into science funding, I think

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Speaker 1: it's important for us to make sure that we're all

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Speaker 1: on the same page because people are throwing terms around

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Speaker 1: like the economy and the labor market, and these mean

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Speaker 1: different things to people depending on who you ask. And

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Speaker 1: so when an economist says the economy, what exactly is

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Speaker 1: included in that picture? Like what are those markers?

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Speaker 3: Those are all the economic activities that take place in

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Speaker 3: our country. So that includes unemployment, is certainly one of

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Speaker 3: the big indicators, inflation rate, gross domestic product output, all

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Speaker 3: the subsectors that make up the economy healthcare, education, transportation, technology,

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Speaker 3: and the like. So the term economy really encapsulates all

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Speaker 3: of the activities paid or some unpaid, that take place.

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Speaker 2: That's great, and I mean that makes economy sound just

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Speaker 2: as big as we feel like it is because it's

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Speaker 2: always a hot button topic. It's what is on the

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Speaker 2: tip of everyone's tongue these days. And we've seen some

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Speaker 2: really big swings in the jobs numbers with the most

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Speaker 2: recent furlough to cuts for government jobs and cuts and

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Speaker 2: research and just the job market just really being a

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Speaker 2: tough place right now. And sometimes it feels like the

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Speaker 2: economy is cooling and other times it feels like there's

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Speaker 2: record job growth. Can you help us understand what drives

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Speaker 2: those shifts and what the job numbers really tells us

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Speaker 2: about the health of our economy.

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Speaker 3: The economy does seem to be slowing down overall. When

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Speaker 3: you look at unemployment, it is rising. Certainly, the tariff

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Speaker 3: policies of President Trump has created a lot of uncertainty

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Speaker 3: in the business community. When business leaders are cautious, they

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Speaker 3: tend to pull back on hiring. So the unemployment rate

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Speaker 3: is probably the basic indicator that most people follow, but

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Speaker 3: it's an aggregate number, so there's a lot of noise

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Speaker 3: and activity that takes place below that number. Different types

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Speaker 3: of people in the population have different unemployment levels. People

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Speaker 3: look at the overall participation in the job market. Technically,

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Speaker 3: the unemployment rate just measures of the percentage of those

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Speaker 3: people who are looking for jobs. How many people are unemployed,

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Speaker 3: So the employment aspect can mask different things that are

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Speaker 3: going on, like if the economy is really bad. People

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Speaker 3: get discouraged from looking, and so they quit looking. Technically,

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Speaker 3: they no longer are part of the unemployment rate at

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Speaker 3: that point, because the unemployment rate just focuses on those

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Speaker 3: who are looking who are not able to find a job.

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Speaker 1: Wait a minute, Wow, how do they That is mind

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Speaker 1: blowing for me? Is it after thirty days you drop off?

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Speaker 3: Like?

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Speaker 1: What's the cutoff?

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Speaker 3: Well, this is the reason why the unemployment rate can

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Speaker 3: mask a lot of other things that are going on.

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Speaker 3: Like right now, the official unemployment rate in the United

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Speaker 3: States is about four and a half percent, which doesn't

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Speaker 3: sound very high by historic standards. It's actually at the

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Speaker 3: lower end in terms of the employment figures. But there

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Speaker 3: are people who are called discouraged workers, people who want

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Speaker 3: to work, maybe have tried for a little while, have

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Speaker 3: not been able to find a job. They get discouraged

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Speaker 3: and they quit looking. Therefore they drop out of the

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Speaker 3: unemployment rate. They are still there, they still do not

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Speaker 3: have a job. So sometimes the economy is worse than

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Speaker 3: the economic numbers would actually suggest, and I think that

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Speaker 3: is likely to be the case right now. There are

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Speaker 3: probably people who would like to have a job. They

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Speaker 3: perhaps have gotten discouraged because they've been looking and not

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Speaker 3: able to find anything. A lot of the big companies

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Speaker 3: have announced layoffs in a recent months, so I think

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Speaker 3: it's one of the reasons why you can have a

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Speaker 3: relatively low unemployment rate, but yet the economy still is

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Speaker 3: not doing very well and people feel poorly about the

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Speaker 3: national economy.

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Speaker 2: But I'm curious how that's tracked. How do they track

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Speaker 2: when somebody has disengaged from looking for a job.

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Speaker 3: There are both public surveys and surveys of businesses that

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Speaker 3: track a variety of economic indicators. With businesses, they're asking

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Speaker 3: people about their hiring rates each month. There are surveys

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Speaker 3: that go out to a large number of businesses that

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Speaker 3: you know, ask a series of questions. Now, of course,

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Speaker 3: the problem right now is with the government shutdown, those

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Speaker 3: surveys actually are not taking place, and so many of

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Speaker 3: the economic indicators that we typically follow are at least

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Speaker 3: a month out of date because the people who would

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Speaker 3: collect that information have been furloughed. They're not working, they're

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Speaker 3: not collecting the survey information. So we're actually flying a

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Speaker 3: bit blind as a result of the government shutdown, And

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Speaker 3: obviously the longer that shutdown continues, the more of a

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Speaker 3: problem that creates because you know, business leaders have to

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Speaker 3: make decisions. They want the best and most up to

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Speaker 3: date information. We're not getting that right now, So the

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Speaker 3: government shutdown creates a lot of problems in terms of

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Speaker 3: collecting economic data.

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Speaker 1: That makes a lot of sense. Now, I want to

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Speaker 1: go back a little bit too, before the government shut down,

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Speaker 1: when we saw the reporting of numbers of this many

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Speaker 1: jobs being available, then the switch to like, no, it

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Speaker 1: wasn't there aren't these many jobs available. And you've helped

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Speaker 1: us understand economy and all these different factors for the economy.

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Speaker 1: But when we talk about like labor market, I've been

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Speaker 1: hearing reports that say, like the labor market is tight

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Speaker 1: or is soft, and I'm like, what does that mean?

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Speaker 1: In plane talk? And then what's going into determining that.

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Speaker 3: One of the things that creates the greatest difficulty for

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Speaker 3: people who even follow these statistics is the Bureau of

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Speaker 3: Labor Statistics is the part of the government that collects

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Speaker 3: all this information, and so on a monthly basis, they

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Speaker 3: do these surveys and then once a month they put

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Speaker 3: out the unemployment rate. But then a lot of times,

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Speaker 3: since the data are based on surveys of businesses, the

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Speaker 3: preliminary number can be revised in the following month because

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Speaker 3: more businesses have responded with any survey that you're sending,

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Speaker 3: Like there are a bunch of people who respond right away,

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Speaker 3: and then there are other people who respond two weeks later,

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Speaker 3: three weeks later, or four weeks later. So the beer

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Speaker 3: of labor statistics will revise the numbers, and in recent

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Speaker 3: months sometimes the revisions have actually been really big in

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Speaker 3: either direction. Either they can make the economy look better

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Speaker 3: or worse based on that revision. This is upsetting to

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Speaker 3: people like Trump used that as an argument that the

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Speaker 3: numbers are unreliable, that the people who work there are biased,

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Speaker 3: they're trying to make him look bad by reporting bad

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Speaker 3: numbers for the economy. That actually is not the case.

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Speaker 3: You know, these are professional economists who are compiling the data.

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Speaker 3: But when you have big revisions each month, it does

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Speaker 3: make people wonder, like, why are there so many revisions,

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Speaker 3: Why aren't the numbers more consistent and more reliable?

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Speaker 2: And I feel like those numbers will also contribute to

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Speaker 2: what you were saying when someone gets fatigued with applying

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Speaker 2: for jobs, because if you realize there's actually a million

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Speaker 2: less jobs, available. I would imagine that that might end

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Speaker 2: up fluctuating that number as well. Like Takia was saying

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Speaker 2: at the very beginning, I look a lot at the

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Speaker 2: research funding and things like that, and means a key

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Speaker 2: have a lot of conversations about this because you know,

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Speaker 2: we both have doctorates, we both benefited from research funding.

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Speaker 2: And when the federal government cut back on research funding,

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Speaker 2: can you talk about the ripple effects that that has

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Speaker 2: on the broader economy, Because some people when they hear

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Speaker 2: these things, they're like, Okay, who cares, so you won't

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Speaker 2: be able to test that frog or whatever, But we

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Speaker 2: know it's bigger than that.

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Speaker 3: Now, you're exactly right, that's a very good question. I mean,

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Speaker 3: when the government over the last year has cut back

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Speaker 3: on research funding, especially money that was going to universities,

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Speaker 3: it's actually been devastating. Like there are a lot of

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Speaker 3: young people and a lot of professors who depend on

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Speaker 3: that money for their research. As soon as the money

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Speaker 3: either slowed or got eliminated, me a lot of universities

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Speaker 3: had to lay off people. You know, this would be

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Speaker 3: devastating for a young person starting out in the field

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Speaker 3: of science, engineering, math, or otherwise. Like they were counting

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Speaker 3: on a certain level of support for their graduate studies

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Speaker 3: and the money basically got yanked. So that would be

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Speaker 3: devastating for those individuals. But you're also right, there's a

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Speaker 3: broader issue, like beyond those individuals, you know, the impact

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Speaker 3: on the academics who were assuming that funding was going

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Speaker 3: to come through. The economic impact for entire communities can

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Speaker 3: actually be quite substantial. In many cities across the United States,

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Speaker 3: two of the big drivers are what we call eds

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Speaker 3: and mets, educational institutions and all the medical and health

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Speaker 3: related institutions. The whole hospital establishment, the healthcare community, the

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Speaker 3: doctors like that generates a lot of jobs. And what

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Speaker 3: the administration has done has disrupted both the educational communities

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Speaker 3: and the healthcare establishment, and so devastating for many cities.

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Speaker 3: They have counted on the economic growth and the jobs

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Speaker 3: generated by these types of institutions, and in the last

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Speaker 3: six months they can no longer count on that money.

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Speaker 3: Even when there are being court rulings demanding that the

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Speaker 3: federal government resume the funding, it's not clear that the

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Speaker 3: administration has followed up to the degree that judges have required.

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Speaker 1: Daryl, I want to share with you a letter that

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Speaker 1: we received from a Dope Labs listener, and they wrote

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Speaker 1: this to us in August and as part of why

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Speaker 1: we're talking to you, and I'd love to just hear

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Speaker 1: your reaction or what you think based on what they said.

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Speaker 1: They said, Hi, Dope Labs. I think a podcast episode

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Speaker 1: focusing on today's science job market would be a great idea.

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Speaker 1: I've spent over seven years working in the farharmaceutical industry,

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Speaker 1: but after being laid off from a major biotech company,

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Speaker 1: I've found it incredibly difficult to secure a new role.

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Speaker 1: I've seen many others share similar struggles in online communities

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Speaker 1: like Reddit, and it's discouraging to realize how widespread this

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Speaker 1: has become. So many of us have dedicated our careers

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Speaker 1: and lives to advancing science, yet with the way things

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Speaker 1: are now, it can feel like this work is no

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Speaker 1: longer appreciated or valued. Covering this topic could remind people

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Speaker 1: why it is worth staying the course in their studies

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Speaker 1: or in careers in science and give them hope to

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Speaker 1: keep moving forward. And I won't share their name, but

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Speaker 1: I'm curious your response to this, and I don't know

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Speaker 1: if you can give that type of recommendation, but if

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Speaker 1: you have any kind of forecasting. Should people be following

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Speaker 1: these careers, Should they pursue this with the way things

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Speaker 1: look now?

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Speaker 3: Well, first of all, I feel for that person. That

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Speaker 3: person is not unique. I know there are many examples

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Speaker 3: of other people who have had exactly the same experience

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Speaker 3: over the last year. Some do to cut back and

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Speaker 3: government funding, some do to as in this case, companies

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Speaker 3: just laying off individuals. You know, we've all seen the

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Speaker 3: stories about AI starting to affect a number of different industries.

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Speaker 3: AI is doing more and more sophisticated tasks, including in

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Speaker 3: the research area. AI can do things that gradu students

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Speaker 3: and faculty used to do on their own. So the

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Speaker 3: combination of all these things has been very destabilizing, and

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Speaker 3: I do worry what it's going to mean for the

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Speaker 3: future in the United States, because you know, what actually

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Speaker 3: has made America great has been the innovation economy, our

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Speaker 3: scientific establishment. Like this is the reason so many foreign

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Speaker 3: students want to come to the United States because they

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Speaker 3: know America has the best universities in the world, and

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Speaker 3: a lot of these people come here they'd like to stay.

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Speaker 3: Some of them end up starting their own companies. So

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Speaker 3: they're a vital part of what is propelled American prosperity

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Speaker 3: the creation of jobs and the fact that the United

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Speaker 3: States has been very innovative in a lot of different areas.

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Speaker 3: So to the extent that the we're cutting back in

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Speaker 3: that area, either through research funding or if big pharmaceutical

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Speaker 3: companies are laying off people, or if immigration policies are

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Speaker 3: making it very difficult for foreign students who get educated

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Speaker 3: here and would like to stay but they're no longer

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Speaker 3: able to do that, all of that is going to

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Speaker 3: have a very detrimental effect on our future economy. Like

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Speaker 3: people seem to think we can do all these things

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Speaker 3: and everything else is going to stay the same, and

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Speaker 3: that is just simply not the case. Without all of

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Speaker 3: the ingredients that drive the innovation economy, we're not going

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Speaker 3: to have the same level of economic prosperity in the

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Speaker 3: future that we have had over the last couple of decades.

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Speaker 2: Yes, and I know that you often talk about the

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Speaker 2: future of work and so, like Zekia was saying, folks

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Speaker 2: that are post docs in the life science, is post

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Speaker 2: docs technicians even undergrads thinking about research careers. I feel

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Speaker 2: like we're going to see a decrease in the amount

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Speaker 2: of folks interested in it, and I think that that

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Speaker 2: is overall just a bad situation for the country. I

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Speaker 2: do want to touch on something that you brought up

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Speaker 2: just now. I would love to hear more about how

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Speaker 2: AI is affecting the job market.

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Speaker 3: This has been the big topic in recent months. I mean,

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Speaker 3: there have been lots of headlines where companies have announced

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Speaker 3: layoffs and the companies themselves are saying one of the

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Speaker 3: reasons they're getting rid of humans is AI is doing

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Speaker 3: the work that these humans used to do. For example,

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Speaker 3: software coding development, all these things have been in very

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Speaker 3: hot demand for a number of years. It turns out

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Speaker 3: AI can actually do that stuff pretty well, and so

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Speaker 3: some of these companies have said, you know, these are

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Speaker 3: tech companies, forty percent of their layoffs have been due

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Speaker 3: to AI being able to do the jobs that these

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Speaker 3: humans used to do. So I think it is creating

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Speaker 3: a problem in the entire STEM field, and it's not

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Speaker 3: just in the computer area. Like a lot of what

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Speaker 3: happens in the knowledge sector is basic research, and basic

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Speaker 3: research consists of a variety of different things. It's like

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Speaker 3: doing a literature review to find out what's going on

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Speaker 3: in the field, collecting data, analyzing, data, interpreting the data,

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Speaker 3: writing reports, having summaries of what comes out of various studies.

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Speaker 3: It turns out AI can actually do many of those things,

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Speaker 3: and so the implications of the rise of AI for

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Speaker 3: the entire knowledge sector, I think are actually quite serious,

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Speaker 3: and so we need to think about how we build

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Speaker 3: the next generation of scientific talent in a world that

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Speaker 3: increasingly is being driven by AI. You don't want robots

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Speaker 3: and AI to be doing all the jobs and humans

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Speaker 3: having no role in it. Like, that's not a good

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Speaker 3: rest of for creative solutions coming out of the future.

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Speaker 1: But then I'm curious, what is it then? Right then,

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Speaker 1: what does it look like to be a scientist prepared

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Speaker 1: for work in the future. What does it look like

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Speaker 1: to adapt and be ready to respond to these changes?

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Speaker 3: Well, there certainly are jobs that are going to be lost,

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Speaker 3: and we're already seeing that. But the good news is

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Speaker 3: there actually are new kinds of jobs that are being created,

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Speaker 3: So this is kind of the optimistic side of all this.

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Speaker 3: In the data area, people who have really good data

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Speaker 3: analysis skills are still in hot demand, particularly those who

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Speaker 3: are skilled at working with very large data sets, data

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Speaker 3: sets that may number in the hundreds of thousands or

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Speaker 3: even millions of records associated with them, So that's an

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Speaker 3: important skill, and the digital economy is just creating so

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Speaker 3: much data. Anybody who has data skills like cleaning data sets,

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Speaker 3: analyzing information, interpreting information, I think still be an important thing.

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Speaker 3: There are other types of new jobs where companies and

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Speaker 3: organizations are trying to integrate AI into their operations and

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Speaker 3: improve their administrative processing, their financial management. Like there's a

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Speaker 3: wide variety of things, but it actually is not such

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Speaker 3: a simple matter just to add AI to your organization

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Speaker 3: and expect people to be able to figure it out.

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Speaker 3: So they're going to mean new jobs that I would

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Speaker 3: describe as something like management, innovation, organizational dynamics, kind of

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Speaker 3: figuring out how AI works in the ways that organizations

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Speaker 3: particularly need, Like to really automate functions, you have to

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Speaker 3: break down every administrative task into its component parts, and

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Speaker 3: even the simple thing like paying a bill, there may

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Speaker 3: be like five six or seven steps involved with that,

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Speaker 3: and so the process of automation means taking a look

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Speaker 3: at each of those those five six or seven steps,

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Speaker 3: figuring out how to automate that, how to link that

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Speaker 3: sequence of activities, and then how to integrate all that

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Speaker 3: so you actually get the right answer. At the end

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Speaker 3: of that, there are going to be jobs for people

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Speaker 3: who actually know how to do that. So that will

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Speaker 3: involve scientists who understand AI, people who understand organizations, and

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Speaker 3: then people who are used to dealing with human beings

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Speaker 3: that can actually sit down with you or I and

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Speaker 3: explain you know, this is how we're integrating AI into

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Speaker 3: our operations. So there are going to be a bunch

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Speaker 3: of new types of jobs that are being created. If

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Speaker 3: you look at the types of job ads that organizations

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Speaker 3: are starting to put out now, there are job listings

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Speaker 3: that have the strangest titles like jobs I've never heard of.

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Speaker 3: But yet these organizations are understanding that as technology gets

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Speaker 3: integrated into their operations, they need new types of people

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Speaker 3: who have different types of skills. So there will be

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Speaker 3: lots of new opportunities. But the key thing is making

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Speaker 3: sure people have the training that will qualify them for

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Speaker 3: those new types of jobs.

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Speaker 2: And that means changing the perspective that a lot of

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Speaker 2: folks in higher education have on AI, because I think

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Speaker 2: in the beginning it was like, Oh, all these students,

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Speaker 2: they're just cheaters, they're using AI for everything. But I

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Speaker 2: think we're past that now, and now we have to

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Speaker 2: start teaching them how to use it to their benefit.

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Speaker 2: Just like when Google hit the scene and everybody felt

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Speaker 2: like there was just all this information at your fingertips,

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Speaker 2: no one had to think about anything. But now we've

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Speaker 2: learned how to use it in better ways, even though

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Speaker 2: some people's Google searches are very different from the rest

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Speaker 2: of the population. We've talked about a lot of the

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Speaker 2: tough things going on with the economy, but I am

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Speaker 2: interested from your perspective at Brookings, how you would describe

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Speaker 2: the overall state of the US economy right now, but

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Speaker 2: then also what you would do or how you would

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Speaker 2: fix our economy, Like, because you know, people are we

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Speaker 2: just had an election, the exit pole, they're saying that

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Speaker 2: the economy was the most important thing for folks. What

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Speaker 2: are the steps that were needed in order to course correct.

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Speaker 3: I mean, the biggest word I hear when I talk

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Speaker 3: to people about the economy, including people in the business community,

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Speaker 3: is uncertainty. Like I think the thing that has really

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Speaker 3: screwed up our economy this year is there's so much

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Speaker 3: policy generated uncertainty. So you have the whole tariff situation,

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Speaker 3: like most businesses in America involve some importing of foreign goods.

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Speaker 3: They may assemble an item in the United States. They

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Speaker 3: may rely on a service here, but somewhere along the way,

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Speaker 3: there's something happening abroad that needs to come here to

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Speaker 3: help them do what they need to do. With Trump's

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Speaker 3: tariffs problems, it seems like every other week he changes

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Speaker 3: the tariff rate on China or India or Brazil or Argentina,

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Speaker 3: and so these countries like their heads are spinning, and

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Speaker 3: then the business people who are having to make decisions

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Speaker 3: when they don't know what their supply chain looks like

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Speaker 3: is just completely problematic. The same thing is true in

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Speaker 3: terms of immigration, Like the United States economy depends on immigrants.

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Speaker 3: Immigrants are doing a large percentage of the job in agriculture,

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Speaker 3: the hotel industry, restaurants, construction. I mean, you can kind

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Speaker 3: of go down a very long list of sectors. Immigrants

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Speaker 3: are doing a lot of work in those areas. We've

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Speaker 3: all seen the raids that are taking place in a

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Speaker 3: number of major cities across the country that's completely disrupted

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Speaker 3: the immigrant portion of the market. That creates enormous problems

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Speaker 3: for the business communities. So if you ask me, how

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Speaker 3: do we make the American economy better? It's like our

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Speaker 3: policy has to become more consistent. Our leaders have to

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Speaker 3: adopt policies that actually make sense given the way our

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Speaker 3: economy operates. Like, you know, you can kind of have

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Speaker 3: in your head this mythical notion that only native born

438
00:25:03,720 --> 00:25:08,080
Speaker 3: Americans are going to get the jobs in America, and

439
00:25:08,440 --> 00:25:12,120
Speaker 3: that's a complete fantasy. Like, our economy doesn't operate that way.

440
00:25:12,400 --> 00:25:16,679
Speaker 3: Businesses don't operate that way. So the administration is trying

441
00:25:16,680 --> 00:25:19,720
Speaker 3: to force a model of the economy on the country

442
00:25:20,200 --> 00:25:24,720
Speaker 3: that is just completely unrealistic. So fixing the economy involves

443
00:25:24,920 --> 00:25:28,080
Speaker 3: kind of removing all of the things that are actually

444
00:25:28,160 --> 00:25:32,960
Speaker 3: disrupting the market, creating uncertainty, paralyzing business leaders, leading them

445
00:25:33,000 --> 00:25:35,840
Speaker 3: not to invest, and they end up not hiring people

446
00:25:35,880 --> 00:25:37,720
Speaker 3: because they don't know what the environment is going to be.

447
00:25:37,920 --> 00:25:40,320
Speaker 3: That's completely problematic. We need to fix that.

448
00:25:40,720 --> 00:25:43,040
Speaker 1: I think that is so so true, Darryl. You just

449
00:25:43,080 --> 00:25:46,280
Speaker 1: really snapped. It helped us understand all of these things

450
00:25:46,280 --> 00:25:48,600
Speaker 1: that are happening. And it feels like you're saying, hey,

451
00:25:48,720 --> 00:25:51,119
Speaker 1: look at the data, look at how this system works.

452
00:25:51,160 --> 00:25:53,639
Speaker 1: Before we start tinkering and I would love for you

453
00:25:53,680 --> 00:25:55,720
Speaker 1: to kind of talk about, especially because we started out

454
00:25:55,920 --> 00:25:58,400
Speaker 1: in the STEM area, if you were able to talk

455
00:25:58,400 --> 00:26:01,919
Speaker 1: to us about like how immigrant populations contribute to our

456
00:26:01,960 --> 00:26:05,199
Speaker 1: STEM economy and workforce so people have an understand of that,

457
00:26:05,240 --> 00:26:08,560
Speaker 1: and then broader how we can see immigrant labor in

458
00:26:08,600 --> 00:26:09,119
Speaker 1: our market.

459
00:26:09,560 --> 00:26:14,080
Speaker 3: Immigrants have been a vital part of the whole technology

460
00:26:14,240 --> 00:26:18,480
Speaker 3: sector for many years. Like I'm sure you recall from

461
00:26:18,520 --> 00:26:21,359
Speaker 3: your own experiences in graduate school, like when you go

462
00:26:21,440 --> 00:26:26,480
Speaker 3: into the graduate programs of any leading university in any

463
00:26:26,520 --> 00:26:30,199
Speaker 3: of the STEM fields science, technology, engineering, or math, a

464
00:26:30,280 --> 00:26:32,800
Speaker 3: majority of the students and sometimes it's two thirds or

465
00:26:32,840 --> 00:26:36,960
Speaker 3: three quarters actually coming from abroad. Immigrants have been a

466
00:26:37,080 --> 00:26:40,200
Speaker 3: very important part of the STEM field because the data

467
00:26:40,240 --> 00:26:44,680
Speaker 3: suggests data born Americans have not gone into these fields,

468
00:26:45,080 --> 00:26:47,600
Speaker 3: or they've gone in, or they've gotten discouraged and they've

469
00:26:47,840 --> 00:26:49,720
Speaker 3: dropped out. I mean, there are lots of different things

470
00:26:49,920 --> 00:26:53,080
Speaker 3: that are going on there, and so it's hard to

471
00:26:53,160 --> 00:26:59,280
Speaker 3: know how our technology innovation is going to continue in

472
00:26:59,320 --> 00:27:04,439
Speaker 3: the future without some involvement from immigrants. They have a

473
00:27:04,440 --> 00:27:08,760
Speaker 3: lot of technical expertise. There's tremendous talent all around the world,

474
00:27:09,400 --> 00:27:15,560
Speaker 3: and companies have relied on that for several decades right now,

475
00:27:15,760 --> 00:27:19,760
Speaker 3: so clearly we need immigration reform. We need kind of

476
00:27:19,800 --> 00:27:23,040
Speaker 3: a more standardized way for people who want to come

477
00:27:23,080 --> 00:27:26,600
Speaker 3: to America to actually do that. Right now, it's kind

478
00:27:26,600 --> 00:27:30,440
Speaker 3: of a free for all because the last major immigration

479
00:27:30,560 --> 00:27:33,480
Speaker 3: reform was in the nineteen eighties, So I mean we're

480
00:27:33,520 --> 00:27:36,399
Speaker 3: talking about like almost forty years ago, and the world

481
00:27:36,400 --> 00:27:39,119
Speaker 3: has just changed so much in that time. Our policies

482
00:27:39,160 --> 00:27:41,879
Speaker 3: have not kept up with the changes that are taking place.

483
00:27:42,440 --> 00:27:45,760
Speaker 1: Is that the trend like before nineteen eighty If.

484
00:27:45,680 --> 00:27:50,879
Speaker 3: You look historically, immigration reform generally takes place once every

485
00:27:51,480 --> 00:27:54,760
Speaker 3: twenty years, thirty years, or forty years. I mean, it's

486
00:27:54,760 --> 00:27:57,160
Speaker 3: a difficult subject, Like there are lots of different things

487
00:27:57,240 --> 00:28:01,159
Speaker 3: that are going on. People have complicated feelings about immigrants

488
00:28:01,200 --> 00:28:03,640
Speaker 3: and what it means to be an American, so it's

489
00:28:03,680 --> 00:28:06,239
Speaker 3: hard for our political system to deal with that, and

490
00:28:06,320 --> 00:28:10,320
Speaker 3: typically only once a generation or once every other generation

491
00:28:10,520 --> 00:28:13,800
Speaker 3: there's an opportunity that comes along, people are able to

492
00:28:13,840 --> 00:28:16,639
Speaker 3: pass some reform, but most of the time we're in

493
00:28:16,680 --> 00:28:20,399
Speaker 3: the same situation we are now, which is the system

494
00:28:20,480 --> 00:28:23,760
Speaker 3: is completely screwed up. Everybody recognizes it's screwed up. But

495
00:28:23,880 --> 00:28:26,480
Speaker 3: yet we can't muster the political will to actually fix it.

496
00:28:40,520 --> 00:28:44,120
Speaker 2: So for the folks that are listening that are saying, yes,

497
00:28:44,880 --> 00:28:49,400
Speaker 2: doctor Wes, you are so wise, this is exactly what

498
00:28:49,560 --> 00:28:51,320
Speaker 2: is going wrong. These are the things that we need

499
00:28:51,400 --> 00:28:54,640
Speaker 2: to know. But I am just one person, and I

500
00:28:54,680 --> 00:28:57,680
Speaker 2: am not an economist. What advice would you give to

501
00:28:57,720 --> 00:29:00,600
Speaker 2: folks about impacts that they can have with their local

502
00:29:00,640 --> 00:29:04,240
Speaker 2: government that can help them on a smaller scale, but

503
00:29:04,280 --> 00:29:07,880
Speaker 2: then has ripple effects that could reach across the country.

504
00:29:08,080 --> 00:29:10,840
Speaker 3: Well, the thing that I tell young people when I'm

505
00:29:10,880 --> 00:29:14,800
Speaker 3: talking to them is, given all the changes that are

506
00:29:14,800 --> 00:29:19,600
Speaker 3: taking place in the economy, the workforce, technology, and everything else,

507
00:29:20,440 --> 00:29:22,800
Speaker 3: they're going to need to be devoted to what we

508
00:29:22,920 --> 00:29:26,760
Speaker 3: call lifelong learning. Like when I was growing up, the

509
00:29:26,800 --> 00:29:29,080
Speaker 3: model was you kind of invest in education up through

510
00:29:29,120 --> 00:29:32,360
Speaker 3: about age twenty five, and then after that you don't

511
00:29:32,360 --> 00:29:34,280
Speaker 3: really have to worry too much. Like you may learn

512
00:29:34,320 --> 00:29:37,800
Speaker 3: some things on the job, but both of you are

513
00:29:38,040 --> 00:29:40,680
Speaker 3: much younger. You're going to face a world where you're

514
00:29:40,680 --> 00:29:44,560
Speaker 3: going to have to upgrade your job skills at ages thirty, forty, fifty,

515
00:29:44,600 --> 00:29:48,240
Speaker 3: and sixty literally throughout your adult lifetimes. Everybody else is

516
00:29:48,280 --> 00:29:49,840
Speaker 3: going to have to do the same thing because the

517
00:29:49,920 --> 00:29:53,400
Speaker 3: job market is changing. Old jobs are disappearing, new jobs

518
00:29:53,400 --> 00:29:56,160
Speaker 3: are being created. People are going to have to adapt

519
00:29:56,200 --> 00:29:59,640
Speaker 3: to an era of change. You may be trained in

520
00:29:59,720 --> 00:30:02,960
Speaker 3: one field, you may end up having to develop skills

521
00:30:03,000 --> 00:30:07,040
Speaker 3: that put you in a different area. And so people

522
00:30:07,160 --> 00:30:10,520
Speaker 3: regularly are going to have to take adult education classes

523
00:30:10,880 --> 00:30:15,520
Speaker 3: avail themselves of professional development opportunities. Like everybody is just

524
00:30:15,560 --> 00:30:17,880
Speaker 3: going to have to learn new skills throughout the rest

525
00:30:17,880 --> 00:30:21,360
Speaker 3: of their life. Now, at one level, that's actually not bad.

526
00:30:21,600 --> 00:30:24,080
Speaker 3: As an educator, I like the fact people have to

527
00:30:24,120 --> 00:30:28,239
Speaker 3: constantly educate themselves, But there is a societal question of

528
00:30:28,280 --> 00:30:31,400
Speaker 3: who pays for this, Like you know, for elementary school,

529
00:30:31,480 --> 00:30:34,080
Speaker 3: for high school, and for college. We as a society

530
00:30:34,120 --> 00:30:38,200
Speaker 3: have always said this is important, we will help finance education.

531
00:30:38,680 --> 00:30:42,800
Speaker 3: We've never actually made that commitment for adult education or

532
00:30:42,880 --> 00:30:46,200
Speaker 3: professional development. So right now, when people have to upgrade

533
00:30:46,200 --> 00:30:49,600
Speaker 3: their job skills, generally they have to pay for it themselves.

534
00:30:49,840 --> 00:30:53,040
Speaker 3: We as a society need to understand that's actually an

535
00:30:53,080 --> 00:30:56,160
Speaker 3: important part of our economy now. We need to provide

536
00:30:56,160 --> 00:30:59,440
Speaker 3: that kind of assistance. The worst case scenario is people

537
00:30:59,520 --> 00:31:03,000
Speaker 3: just being up behind, not having the skills not qualifying

538
00:31:03,040 --> 00:31:04,760
Speaker 3: for any of the new jobs that are being created,

539
00:31:05,000 --> 00:31:07,760
Speaker 3: and we end up with a permitted underclass. Ah.

540
00:31:08,400 --> 00:31:11,600
Speaker 1: So basically we need night school vouchers. Say it's time

541
00:31:11,640 --> 00:31:13,520
Speaker 1: for everybody to go back to school. You get a

542
00:31:13,560 --> 00:31:16,520
Speaker 1: voucher every five to ten years, take some new classes.

543
00:31:16,960 --> 00:31:22,080
Speaker 1: I think that is really a great response to our

544
00:31:22,200 --> 00:31:25,960
Speaker 1: changing market. But it seems like everything on our car

545
00:31:26,000 --> 00:31:28,120
Speaker 1: of the economy and the United States, all the lights

546
00:31:28,160 --> 00:31:29,960
Speaker 1: are on. Everything needs to be checked. We need to

547
00:31:30,000 --> 00:31:33,360
Speaker 1: all change, we need break fluid flush. If you were

548
00:31:33,520 --> 00:31:37,080
Speaker 1: the orchestrator of this, what goes first? What has the

549
00:31:37,120 --> 00:31:38,760
Speaker 1: biggest ripple effect in your mind?

550
00:31:39,000 --> 00:31:40,880
Speaker 3: I mean, the first thing that needs to happen is

551
00:31:40,920 --> 00:31:44,480
Speaker 3: we need to be talking about these issues of workforce changes,

552
00:31:44,800 --> 00:31:48,360
Speaker 3: how technology is changing the nature of the skills that

553
00:31:48,480 --> 00:31:51,080
Speaker 3: people need. I mean, you know, we just had the

554
00:31:51,240 --> 00:31:55,520
Speaker 3: off year elections. There's virtually no discussion of this in

555
00:31:55,600 --> 00:31:59,040
Speaker 3: any of the major races that are taking place. So

556
00:31:59,280 --> 00:32:01,080
Speaker 3: the first thing that had to happen is we need

557
00:32:01,120 --> 00:32:03,640
Speaker 3: to start talking about this. We need to understand things

558
00:32:03,640 --> 00:32:07,120
Speaker 3: are changing fast that we need to help people deal

559
00:32:07,160 --> 00:32:09,880
Speaker 3: with the changes that are taking place, and that will

560
00:32:09,920 --> 00:32:14,560
Speaker 3: involve public policy changes. Like one hundred years ago, when

561
00:32:14,560 --> 00:32:18,480
Speaker 3: the United States moved from an agrarian to an industrial economy,

562
00:32:18,920 --> 00:32:22,800
Speaker 3: we actually made a number of policy changes designed to

563
00:32:22,880 --> 00:32:26,760
Speaker 3: help people with that transition. Today, we're moving from an

564
00:32:26,760 --> 00:32:31,200
Speaker 3: industrial to a digital economy that is equally fundamental to

565
00:32:31,240 --> 00:32:35,080
Speaker 3: what we experienced with industrialization. We need a bunch of

566
00:32:35,080 --> 00:32:38,960
Speaker 3: new policies to address different aspects of it, like who

567
00:32:39,000 --> 00:32:43,000
Speaker 3: pays for adult education, how do we get people the

568
00:32:43,040 --> 00:32:46,080
Speaker 3: skills that they're going to need for these new jobs.

569
00:32:46,120 --> 00:32:49,080
Speaker 3: There's like a variety of different questions that we need

570
00:32:49,120 --> 00:32:51,880
Speaker 3: to be exploring. The thing I worry the most about

571
00:32:52,120 --> 00:32:54,440
Speaker 3: is most of the time we're not even talking about it,

572
00:32:54,520 --> 00:32:57,200
Speaker 3: and so we can't even get to a solution if

573
00:32:57,240 --> 00:32:59,360
Speaker 3: it's not on the agenda for conversation.

574
00:33:00,640 --> 00:33:04,120
Speaker 1: Ah okay, that's the first thing. Give me one more thing.

575
00:33:04,360 --> 00:33:06,040
Speaker 1: What's that After we talk about it.

576
00:33:06,400 --> 00:33:08,240
Speaker 3: After we talk about it, then we actually have to

577
00:33:08,280 --> 00:33:12,000
Speaker 3: talk about real solutions. Your idea of a voucher for

578
00:33:12,480 --> 00:33:16,960
Speaker 3: night classes, like, that's a great idea, Thank you, No,

579
00:33:17,000 --> 00:33:19,760
Speaker 3: it is a really good idea, and it's very practical.

580
00:33:19,840 --> 00:33:24,480
Speaker 3: It's an idea people can understand. Encouraging companies as they're

581
00:33:24,520 --> 00:33:29,640
Speaker 3: laying off people to provide professional development for those people

582
00:33:29,920 --> 00:33:33,320
Speaker 3: so that they can take classes, get certified in a

583
00:33:33,360 --> 00:33:36,560
Speaker 3: new field, like, do whatever they need to do so

584
00:33:36,640 --> 00:33:40,000
Speaker 3: they don't become obsolete job wise. So that would be

585
00:33:40,280 --> 00:33:45,160
Speaker 3: an important development kind of figuring out how you provide

586
00:33:45,440 --> 00:33:51,360
Speaker 3: healthcare and retirement benefits to people who are undergoing economic transitions,

587
00:33:51,760 --> 00:33:54,719
Speaker 3: because one of the things that's unusual about the United

588
00:33:54,720 --> 00:33:59,760
Speaker 3: States is most of our benefits come through the job.

589
00:34:00,560 --> 00:34:03,960
Speaker 3: Like European countries have national health insurance, so if you

590
00:34:04,040 --> 00:34:07,200
Speaker 3: move from one company to another company, you're not losing

591
00:34:07,200 --> 00:34:10,319
Speaker 3: your health insurance. In the United States, if you move

592
00:34:10,360 --> 00:34:13,920
Speaker 3: from one company to another, you may lose health insurance.

593
00:34:14,160 --> 00:34:16,799
Speaker 3: You may end up with a different healthcare provider. Like

594
00:34:16,840 --> 00:34:19,839
Speaker 3: there are all sorts of changes that flow from that

595
00:34:20,000 --> 00:34:23,680
Speaker 3: job change. So it's not just a question of addressing

596
00:34:23,840 --> 00:34:28,200
Speaker 3: employment related things. It's understanding that our health benefits and

597
00:34:28,239 --> 00:34:31,839
Speaker 3: retirement benefits are linked to jobs, and so anything that

598
00:34:31,920 --> 00:34:36,240
Speaker 3: destabilizes the job market also destabilizes healthcare.

599
00:34:37,040 --> 00:34:37,840
Speaker 2: I love that point.

600
00:34:38,080 --> 00:34:39,160
Speaker 1: I love it so true.

601
00:34:39,560 --> 00:34:43,439
Speaker 2: Yes, I'd heard some accounts of folks saying that their

602
00:34:44,400 --> 00:34:47,600
Speaker 2: premiums are going to be increasing by hundreds of dollars,

603
00:34:47,640 --> 00:34:51,360
Speaker 2: almost thousands of dollars, and I just couldn't believe it.

604
00:34:51,400 --> 00:34:56,160
Speaker 2: That is such a big change, and folks don't have that,

605
00:34:56,280 --> 00:34:59,480
Speaker 2: we like people don't have that just lying around, And

606
00:34:59,520 --> 00:35:02,360
Speaker 2: so I don't know what the future is going to

607
00:35:02,360 --> 00:35:05,480
Speaker 2: look like when it comes to healthcare. I'm nervous for

608
00:35:05,520 --> 00:35:08,840
Speaker 2: a lot of folks, and it feels like there's a

609
00:35:08,880 --> 00:35:12,680
Speaker 2: lot of things swirling around like right now that are

610
00:35:12,760 --> 00:35:16,560
Speaker 2: creating like a perfect storm for a lot of turmoil.

611
00:35:17,640 --> 00:35:20,600
Speaker 2: Is there a glimmer of hope that people can cling to.

612
00:35:20,719 --> 00:35:23,200
Speaker 2: We just had the like I said, we had the midterms,

613
00:35:23,600 --> 00:35:27,160
Speaker 2: and we see that there are some shifts happening. But

614
00:35:27,440 --> 00:35:30,600
Speaker 2: is there something that we don't see that you feel like,

615
00:35:30,760 --> 00:35:33,960
Speaker 2: is Okay, we have this thing, this one thing that's

616
00:35:34,000 --> 00:35:37,360
Speaker 2: going right, and this is what can help us begin

617
00:35:37,480 --> 00:35:40,360
Speaker 2: to start talking about things and then putting things into practice.

618
00:35:40,360 --> 00:35:43,200
Speaker 3: Like you said, well, the candidates who actually talked about

619
00:35:43,239 --> 00:35:47,440
Speaker 3: these affordability issues, talked about the changing nature of the

620
00:35:47,480 --> 00:35:50,600
Speaker 3: workforce and then are trying to figure out how to

621
00:35:50,960 --> 00:35:56,080
Speaker 3: maintain healthcare benefits for people undergoing job transitions actually did

622
00:35:56,160 --> 00:36:01,160
Speaker 3: very well, and so I personally found that very encouraging.

623
00:36:01,200 --> 00:36:03,919
Speaker 3: In the sense that many of the policy issues that

624
00:36:04,000 --> 00:36:07,880
Speaker 3: I worry about it is now starting to percolate with people.

625
00:36:08,080 --> 00:36:10,359
Speaker 3: The whole healthcare issue, in the fact that premiums are

626
00:36:10,400 --> 00:36:14,480
Speaker 3: going to go up very dramatically. People now are understanding

627
00:36:14,800 --> 00:36:18,520
Speaker 3: this is not a blue state, red state issue. There

628
00:36:18,560 --> 00:36:23,000
Speaker 3: are a lot of rural, conservative areas where people's healthcare

629
00:36:23,120 --> 00:36:26,520
Speaker 3: costs are rising dramatically. It's not just liberal states, it's

630
00:36:26,560 --> 00:36:29,080
Speaker 3: conservative states that are going to experience the same thing.

631
00:36:29,640 --> 00:36:33,520
Speaker 3: The Medicaid cutbacks that were part of the last congressional

632
00:36:33,520 --> 00:36:35,880
Speaker 3: budget bill. That's going to have a lot of impact

633
00:36:36,160 --> 00:36:40,560
Speaker 3: on rural, southern and conservative estates. So I think there's

634
00:36:40,600 --> 00:36:45,440
Speaker 3: a basis for a coalition to emerge from people whose

635
00:36:45,480 --> 00:36:48,399
Speaker 3: constituents are going to be affected by this. I think

636
00:36:48,400 --> 00:36:51,480
Speaker 3: they're starting to figure that out. They're understanding they need

637
00:36:51,520 --> 00:36:54,600
Speaker 3: to address these issues. The healthcare issue was actually a

638
00:36:54,640 --> 00:36:58,239
Speaker 3: big issue in this week's elections. I'm sure it's going

639
00:36:58,280 --> 00:37:01,279
Speaker 3: to be a big issue in next year's midterm elections.

640
00:37:01,320 --> 00:37:04,600
Speaker 3: So to me, this is a positive sign. People now

641
00:37:04,640 --> 00:37:07,360
Speaker 3: are paying attention to this. They understand it's a problem,

642
00:37:07,520 --> 00:37:09,000
Speaker 3: and people are trying to figure out how can we

643
00:37:09,000 --> 00:37:09,520
Speaker 3: address it.

644
00:37:09,880 --> 00:37:13,040
Speaker 1: Sometimes when things look really gloomy. Yeah, I like to say, oh,

645
00:37:13,080 --> 00:37:15,719
Speaker 1: it looked gloomy in nineteen thirty two, but look how

646
00:37:15,760 --> 00:37:16,560
Speaker 1: we turned it around.

647
00:37:16,680 --> 00:37:16,919
Speaker 2: Right.

648
00:37:16,960 --> 00:37:21,759
Speaker 1: So now, certainly AI wasn't part of the equation. But

649
00:37:21,800 --> 00:37:24,680
Speaker 1: have we seen something that's like this storm that TT

650
00:37:25,000 --> 00:37:25,520
Speaker 1: just mentioned.

651
00:37:25,800 --> 00:37:29,280
Speaker 3: In my lifetime, I would say roughly about once every decade,

652
00:37:29,320 --> 00:37:35,560
Speaker 3: there's been some serious economic problem. Wow, either unemployment, high inflation,

653
00:37:36,640 --> 00:37:42,120
Speaker 3: job dislocations, like things that are really making difficult for people.

654
00:37:42,719 --> 00:37:45,440
Speaker 3: And in some of those time periods, things got so

655
00:37:45,600 --> 00:37:48,279
Speaker 3: bad that it got the attention of politicians and they

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00:37:48,280 --> 00:37:52,040
Speaker 3: actually took effective action to deal with these issues. So

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Speaker 3: my hope is that, you know, we're kind of in

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00:37:54,960 --> 00:37:57,920
Speaker 3: a situation now where technology is making a lot of

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00:37:57,920 --> 00:38:01,640
Speaker 3: these economic issues worse. In the short run, technology is

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00:38:01,640 --> 00:38:06,239
Speaker 3: increasing inequality, but people are now starting to understand that,

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00:38:06,600 --> 00:38:08,919
Speaker 3: they're starting to pinpoint that as a problem, they're starting

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00:38:08,960 --> 00:38:11,600
Speaker 3: to think about the policy measures that we need to

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00:38:11,640 --> 00:38:14,560
Speaker 3: adopt in order to deal with that. So it actually

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Speaker 3: makes me optimisty that even though there's going to be

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00:38:18,360 --> 00:38:21,680
Speaker 3: short term pain, they're definitely going to people who lose

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00:38:21,760 --> 00:38:24,239
Speaker 3: jobs are not able to find them. People who are

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00:38:24,239 --> 00:38:28,880
Speaker 3: losing healthcare benefits, and I don't want to minimize the

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00:38:28,920 --> 00:38:32,120
Speaker 3: reality of that, but I think these issues are now

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00:38:32,200 --> 00:38:35,439
Speaker 3: on the agenda. Political leaders are starting to talk about them,

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00:38:35,560 --> 00:38:38,800
Speaker 3: so there actually is hope in the not too distant future.

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Speaker 2: I like that need too, Doctor West. You were a perfection.

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Speaker 2: You've answered so many questions. I know people are going

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00:38:44,640 --> 00:38:47,719
Speaker 2: to be listening to this episode and really learning a lot,

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Speaker 2: and so we're hoping to contribute to the information that's

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00:38:51,320 --> 00:38:54,040
Speaker 2: out there and make it information that people can understand

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00:38:54,120 --> 00:38:57,759
Speaker 2: and move in their lives accordingly based off of what

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Speaker 2: they've learned from you. So thank you so much for

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Speaker 2: for all of your words and insights.

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Speaker 1: Yes, thank you, Thank you very much.

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Speaker 3: Good a pleasure talking with you.

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Speaker 2: You can find us on X and Instagram at Dope

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Speaker 2: Labs podcast.

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Speaker 1: Tt is on X and Instagram, at d R Underscore

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Speaker 1: t Sho.

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Speaker 2: And you can find Zakiya at z said so.

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Speaker 1: Dope Labs is a production of Lamanada Media. Our supervising

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Speaker 1: producer is Keegan Zimma and our producer is Issara Acevez.

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00:39:33,200 --> 00:39:36,880
Speaker 1: Dope Labs is sound designed, edited and mixed by Jangs Farber,

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00:39:37,600 --> 00:39:41,760
Speaker 1: Lamanada Media's Vice president of Partnerships and production is Jackie Danziger.

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Speaker 1: Executive producer from iHeart Podcast is Katrina Norvil. Marketing lead

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Speaker 1: is Alison Kanter.

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00:39:48,400 --> 00:39:52,640
Speaker 2: Original music composed and produced by Taka Yasuzawa and Alex

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Speaker 2: sugi Ura, with additional music by Elijah Harvey. Dope Labs

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Speaker 2: is executive produced by us T T Show Dia and

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Speaker 2: Zakiah walk Here

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Speaker 3: MHM