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Speaker 1: From UFOs to psychic powers and government conspiracies. History is

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Speaker 1: riddled with unexplained events. You can turn back now or

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Speaker 1: learn the stuff they don't want you to know. A

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Speaker 1: production of iHeartRadio.

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Speaker 2: Hello, welcome back to the show. My name is Matt,

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Speaker 2: my name is Noah.

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Speaker 3: They call me Ben. We're joined as always with our

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Speaker 3: super producer Dylan Chicago pal Fagan. Most importantly, you are you.

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Speaker 3: You are here. That makes this the stuff they don't

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Speaker 3: want you to know.

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Speaker 4: Okay, can you really have done? Had Thin Crest Pizza

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Speaker 4: and Chicago. I bet it's really good. I bet it's

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Speaker 4: still really excellent.

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Speaker 3: Yeah, sure, Yeah. Who doesn't love a pizza? Bad people?

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Speaker 3: Bad people don't love a pizza? hEDS and Neighbors. It's

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Speaker 3: officially twenty twenty six. As you're tuning in with us,

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Speaker 3: we're so excited that you're here and we are coming

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Speaker 3: in hot and ready with something we first addressed on

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Speaker 3: Strange News a while back. Brain drain. You guys, remember

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Speaker 3: the concept brain drain does.

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Speaker 4: Sound like a bit of a space alien sucking your

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Speaker 4: brain goo out of your skull situation.

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Speaker 2: It is like it, except with policy.

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Speaker 3: Yeah, it does. It does conjure these images of ravenous

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Speaker 3: aliens right cracking open graniums like little Pharaoh Racero's Yeah, fronation,

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Speaker 3: I love it.

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Speaker 4: I'm gonna go with yours. I think you might be

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Speaker 4: the right one, Ben on the right side of history.

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Speaker 3: There as as we'll see. Uh guys. Brain drain is

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Speaker 3: a very real concern. It dates back to ancient times.

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Speaker 3: It only becomes more important in the modern day. And

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Speaker 3: tonight's episode we started asking ourselves ever since we talked

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Speaker 3: about this on Strange News, what exactly is brain train

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Speaker 3: and why, pray tell, are so many people concerned about

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Speaker 3: it right now in the United States?

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Speaker 4: Why? Indeed?

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Speaker 2: Because science good, science good.

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Speaker 4: Yeah. At the end of the episode, we got to

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Speaker 4: have them scientists, and they apparently are going elsewhere.

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Speaker 3: Here are the facts, all right. Not to be confused

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Speaker 3: with brain.

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Speaker 4: Rot six seven due use that correctly.

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Speaker 3: Everybody is using it correctly, because it doesn't really mean

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Speaker 3: anything cool. Brain's raining is describing this phenomena where highly

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Speaker 3: educated or highly skilled individuals move from one place to

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Speaker 3: another on mass It could be one geographical place, or

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Speaker 3: it could be moving from one industry to another, like

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Speaker 3: if you are if you are one of the top

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Speaker 3: boffins in the world of what's something people don't do anymore,

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Speaker 3: in the world of recreational lithium, and recreational lithium is

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Speaker 3: no longer a legal thing to give to children. Then

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Speaker 3: you get into some other part of pharmaceutical so well.

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Speaker 4: You know, it's interesting, it's not quite the same. But

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Speaker 4: I think a part a version of this that we

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Speaker 4: experience here in Georgia, uh is the brain drain that

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Speaker 4: is the kind of migration of the film industry, you know,

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Speaker 4: out of Hollywood and out of Los Angeles and into

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Speaker 4: our fair metropolis of Atlanta. And you hear people in

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Speaker 4: LA talking about that all the time as something that's

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Speaker 4: really wrecking their industry. Obviously it's a boon for us,

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Speaker 4: but there are various reasons that this kind of brain

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Speaker 4: drink can happen, and in our situation, it seems largely

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Speaker 4: based around financial incentives, you know, government subsidies and things

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Speaker 4: like that that places like LA just can't seem to

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Speaker 4: figure out how to compete.

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Speaker 3: I love that example.

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Speaker 2: Though, Oh yeah, fantastic example. And in today's case, we

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Speaker 2: are talking about, as we said, these highly skilled scientific minds,

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Speaker 2: highly intelligent people who are very much interested in pushing

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Speaker 2: the boundaries of the field that they're interested in. Right, So,

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Speaker 2: for that stuff, you generally need money for research, and

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Speaker 2: in many cases grants from a government or an institution

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Speaker 2: that then gets money from governments. Usually, So, why in

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Speaker 2: the heck are people leaving right now?

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Speaker 3: Well, historically brain drain has This has been fascinating me

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Speaker 3: ever since bringing up on strange news. Historically, brain drain

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Speaker 3: is caused by the opposite of some of the things

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Speaker 3: we just mentioned, political instability, economic hardship, war, human rights issues,

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Speaker 3: or just the appeal of better opportunities, better options somewhere else.

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Speaker 3: It can occur on local, regional, global levels. And this

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Speaker 3: this stands out to us, folks. If you have spent

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Speaker 3: a lot of time in some parts of rural America,

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Speaker 3: you have likely encountered brain drain and its consequences firsthand,

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Speaker 3: even if you never heard the term. You know, where,

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Speaker 3: like manufacturing dries up and all the technically skilled employees

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Speaker 3: who worked at that assembly line or worked at that

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Speaker 3: factory have to scramble for options, and often without a

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Speaker 3: lot of lead time. They may find a job in

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Speaker 3: a related industry, or may even start a new career

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Speaker 3: that doesn't require moving that's the ideal case.

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Speaker 4: We certainly saw a lot of that around the housing crisis,

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Speaker 4: the collapse you know, of the housing industry, when a

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Speaker 4: lot of related fields and whole towns that you know,

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Speaker 4: were built around making things products, fabrics, whatever, carpet, whatever

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Speaker 4: it might be, building materials, and then when that market

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Speaker 4: kind of dried up, you started to see here in

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Speaker 4: Georgia a lot of communities scrambling to figure out what

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Speaker 4: to do in place of that industry that had more

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Speaker 4: or less disappeared. And that was when you really started

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Speaker 4: seeing the kind of this situation where a lot of

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Speaker 4: these private prisons were coming in and capitalizing on these

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Speaker 4: sort of ghosts downs that had become that because of

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Speaker 4: exactly what you're talking with.

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Speaker 3: Oh yeah, man, More often than not, these individuals who

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Speaker 3: get the rug pulled out from beneath them have to

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Speaker 3: look beyond their community for survival. So if you can

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Speaker 3: afford it, you're probably gonna move your family somewhere else.

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Speaker 3: This can have real serious consequences for the local economy,

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Speaker 3: especially when it occurs at scale. Unfortunately, as we know,

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Speaker 3: as I think a lot of people have recognized a

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Speaker 3: lot of times of family cannot move due to financial

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Speaker 3: concerns or medical concerns or familial concerns that can also

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Speaker 3: be bad for the local economy. It's real, Kobeashi Maru,

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Speaker 3: because now if you are the local economy, you don't

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Speaker 3: have people moving away, but you have an influx of

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Speaker 3: people who are underemployed or straight up unemployed, and that

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Speaker 3: puts unprecedented strain on support services. It's tough either way

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Speaker 3: you look at it. We also see brain drain in

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Speaker 3: support services. Guys. We know a lot of folks throughout

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Speaker 3: rural America and communities here in the United States where

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Speaker 3: people are hours away from a doctor now because hospitals

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Speaker 3: and medical centers close their doors and shout out to

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Speaker 3: the one doctor in that small town who stay behind

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Speaker 3: because they wanted to fulfill the hippocratic oath and to

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Speaker 3: help people. Now, they're overworked, they're probably underpaid. They're probably

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Speaker 3: considering leaving as well and finding an area with more opportunities,

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Speaker 3: a more prosperous place.

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Speaker 2: Yeah, and that's tough, right, because you're talking about people

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Speaker 2: with highly trained individuals with medical expertise that have to

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Speaker 2: make that hard choice of continuing their career right rather

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Speaker 2: than actually helping people in a place that really do

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Speaker 2: need help. You can't make the money there to support

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Speaker 2: yourself and your family because of you know, whatever aspirations

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Speaker 2: you've got, because of the standards of the pay for

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Speaker 2: you know, people in the medical industry here in the

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Speaker 2: United States, the only place that has that weird private

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Speaker 2: healthcare thing instituted, you know, which means doctors can make

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Speaker 2: a craft ton of money if you play the game right,

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Speaker 2: and only if you play the game, which requires you

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Speaker 2: to be in a place that has a lot of

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Speaker 2: patients and has a hospital slash medical infrastructure that.

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Speaker 4: Is prosperous and like nothing against people trying to play

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Speaker 4: the game and you know, rise in their career and

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Speaker 4: make more money. But we also know, to the previous

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Speaker 4: examble of the doctor sticking around, there are plenty of

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Speaker 4: people that are highly specialized that it's more they're more

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Speaker 4: in it to do the work, and they're more in

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Speaker 4: it to help people and help communities. Like for example,

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Speaker 4: maybe a lawyer who could very well become a defense attorney,

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Speaker 4: but rather than do that, decides to work protecting you know,

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Speaker 4: tenants from being evicted by corrupt landlords. That's not a

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Speaker 4: higher paying job, but it involves the same degree, and

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Speaker 4: it is a very conscious choice, and we're seeing a

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Speaker 4: mix of that in this situation as well.

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Speaker 3: Absolutely, and don't worry, friends and neighbors, this situation gets

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Speaker 3: worse because you see braid drain is bad for the

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Speaker 3: source region, but it can also be damaging for the

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Speaker 3: destination region. Real Grapes of Wrath with all the Oaks

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Speaker 3: showing up to the Orange far right and you have

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Speaker 3: you have three hundred jobs available, but you have three

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Speaker 3: thousand people who want them right, and they've already moved.

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Speaker 2: Tell me about the Okies.

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Speaker 3: So the Okis is a term we're shouting out the

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Speaker 3: book Grapes of Wrath, which examines the mass migration of

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Speaker 3: people from Oklahoma who were called Oake in a pejorative

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Speaker 3: way by the media of the time.

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Speaker 4: They in California way, it's trying.

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Speaker 3: To work right. Largely largely agrarian communities swept up by

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Speaker 3: the climate disaster in the mid Midwest, lost their farms,

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Speaker 3: lost pretty much everything, and desperately sought to survive by

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Speaker 3: hitching up their tent stakes and as as Grapes of

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Speaker 3: Wrath had it hopping on a jealoppe, which is just

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Speaker 3: a fun word to say. I don't know why. It

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Speaker 3: sounds like a sandwich, but it's a car, all the

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Speaker 3: stuff strapped to.

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Speaker 4: The roof, and you know, their whole family. And I

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Speaker 4: mean a big part of that too, was it was

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Speaker 4: there the corporations of the companies, the larger farms down

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Speaker 4: in California, up in California were capitalizing on this, and

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Speaker 4: they were advertising these jobs and this like, you know,

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Speaker 4: come here, move to California and change your life, bring

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Speaker 4: your family, all are welcome. And it was a lie

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Speaker 4: because there was just not there weren't nearly enough jobs

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Speaker 4: for the amount of people that saw those handbills or

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Speaker 4: advertisements or whatever it might be and uprooted with the

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Speaker 4: hope of changing their lives, only to get there and

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Speaker 4: realize that not only were there not enough jobs, but

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Speaker 4: the jobs that were available were often very difficult and

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Speaker 4: low paying, and they were treated like chattel.

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Speaker 3: Sleeps more or less. Yep. And the destination region, that

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Speaker 3: is what occurs. And to add to that, these folks

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Speaker 3: have gambled everything to get over there and they can't

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Speaker 3: go back, So now it's a problem for the destination region.

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Speaker 3: There's more on that in a moment. But we've got

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Speaker 3: to point this out. I don't know about you, guys,

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Speaker 3: but I was astonished to learn, folks that the phrase

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Speaker 3: brain drain is pretty recent. The etymology traces back to

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Speaker 3: just nineteen sixty three, but the concept is so so old.

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Speaker 3: Brain drain has been around ever since empires started empiring.

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Speaker 2: Yeah, imagine, really, it's talking about getting the best brains right, literally,

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Speaker 2: that the best humans, the best innovators, the best inventors,

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Speaker 2: the people, no matter where they live, get that person

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Speaker 2: to work for you. If you're let's say, an empire, right,

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Speaker 2: how do we get that person to work for us?

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Speaker 2: Or how do we incentivize that person to come and

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Speaker 2: innovate in our land so that we can make use

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Speaker 2: of those inventions and innovations. Yeah.

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Speaker 3: Yeah, if you go back through the sort of dendo

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Speaker 3: chronology of human society, you can trace the tree rings

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Speaker 3: of brain train through war, disease, famine, all the hits, right,

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Speaker 3: all the slow jazz. And it's because just as it

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Speaker 3: was then it is today. Nobody wants to live in

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Speaker 3: a war zone, no one wants to get the plague,

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Speaker 3: and most people in jail federal like to have a

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Speaker 3: good idea where their next meal is coming from. So

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Speaker 3: this this also ties into I love that you're bringing

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Speaker 3: up to this point, Matt. It ties into the fact

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Speaker 3: that a certain level of economic activity has to exist

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Speaker 3: to support skilled labor. So if you're an ancient tradesman,

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Speaker 3: you're a metalsmith, you're an armorer, you have to flock

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Speaker 3: to large towns, villages and cities to survive. And when

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Speaker 3: you do that, and there's nothing wrong with you doing that,

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Speaker 3: you're leaving your old stopping grounds without the town blacksmith, yep,

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Speaker 3: you're taking that knowledge with you. You're also you're you're

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Speaker 3: not only not there to make stuff, but you're not

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Speaker 3: there to teach people to make stuff later.

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Speaker 2: Oh man, exactly. We've talked about the importance of that

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Speaker 2: that system of training, right master apprentice, and how how

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Speaker 2: important that was to humanity for so long, and how well, yes,

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Speaker 2: but how that still exists, especially in academia, right. That's

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Speaker 2: that's a lot of what's happening here. You've got circular

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Speaker 2: learning that occurs because you've got people in positions to

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Speaker 2: teach others the thing that they've mastered, which you know,

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Speaker 2: you take that master away. As you're saying, Ben put

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Speaker 2: them in a different town. Now that town is going

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Speaker 2: to benefit from what that person has to offer.

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Speaker 3: Yeah, exactly, man. I mean history is also littered with

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Speaker 3: accounts of people then as now at the tippity top

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Speaker 3: of the socioeconomic pyramid, and those folks, we call them

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Speaker 3: enlightened despots, would by hook or by crook, gather all

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Speaker 3: the smart brains from all the planet not planets, but

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Speaker 3: basically planets at that time, from all the example. Yeah, yeah,

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Speaker 3: Alexander the Great, you know, rolls through a place, Djengus

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Speaker 3: rolls through a place, and they both say who here

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Speaker 3: can read? All right? Kill the first like the second one. Yeah, yeah,

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Speaker 3: And this is this is a true story. And over time,

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Speaker 3: funny thing is that became a net positive because some

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Speaker 3: seventeenth century monarchs in Europe would gather the boffins and

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Speaker 3: they would actually listen to them. They would listen to

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Speaker 3: the experts and they would say, you know, oh that's

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Speaker 3: a that's a good point. Maybe we should try to

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Speaker 3: clean the water or do science. You know, I'm glad,

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Speaker 3: I'm glad you're not the one we killed.

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Speaker 4: Well, there lies the enlightened aspect of the deskmt. I mean,

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Speaker 4: it is still technically someone ruling with an iron fist,

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Speaker 4: but they've you know, they're open to two new ideas

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Speaker 4: and potentially good and progressive ideas.

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Speaker 2: And hey, guys, it's me the king.

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Speaker 3: We have sort of an open door policy exactly, you

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Speaker 3: know what I mean, So like, keep your eyes down,

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Speaker 3: no eye contact. But tell me about this heliocentric concept.

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Speaker 2: Oh man, It really puts into perspective the concept of

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Speaker 2: putting in place advisor around you, let's say, as a

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Speaker 2: king or a president of just people that you like

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Speaker 2: or want to hang out with. Are people who like

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Speaker 2: you enough or say they like you enough to just

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Speaker 2: you know, be copasetic when you're around everything feels good, yeah,

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Speaker 2: rather than an actual you know, a group of scientific

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Speaker 2: experts who can say things, well, what did you say

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Speaker 2: about it? We should clean the water. That is such

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Speaker 2: a perfect example, especially for our times right.

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Speaker 4: Now, sycophants versus actual experts who will speak their mind

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Speaker 4: and who are given the space to speak their mind.

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Speaker 4: When you start to have people in high levels of

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Speaker 4: power surrounding themselves with just people telling them what they

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Speaker 4: want to hear, that's its own kind of brain drain,

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Speaker 4: isn't it.

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Speaker 3: Yeah, it's it's definitely an emotional drain for the sycophants.

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Speaker 3: I imagine. I mean, like we think about what.

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Speaker 4: Happens everything, you know, It's like it's like a bosituation.

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Speaker 3: Yeah, yeah, let's let's think about it this way. So

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Speaker 3: a good hang is a yes.

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Speaker 4: At that's right.

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Speaker 3: Good science is a no, but good science is a

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Speaker 3: well actually.

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Speaker 4: Yeah, maybe a yes, but also yes. It's about diplomacy.

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Speaker 4: I mean, you want to play it, you want to

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Speaker 4: read the room, but it should ultimately result in a

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Speaker 4: butt this.

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Speaker 2: Thing, right, My favorite is a yes, but ah.

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Speaker 3: Oh, here's we'll put you on some game here, right, Yes,

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Speaker 3: because you avoid the social danger of a no, but

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Speaker 3: or well actually, and you just sort of make it

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Speaker 3: sound like the leader's idea. Right, yes, because the water

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Speaker 3: should be clean, like oh, this guy's great.

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Speaker 4: Do the dance a little bit, right.

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Speaker 3: Little parkour now? And then, I mean, this is the

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Speaker 3: other side of the the other side of the cerebellum

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Speaker 3: or the butt cheeks. People in communities who get left behind,

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Speaker 3: the folks who are not highly skilled or don't have

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Speaker 3: a resource or knowledge base to sell, or the folks

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Speaker 3: who just get afford to move. It's like your town

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Speaker 3: got bypassed by the new train line. History rolls on

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Speaker 3: and you are not on the ride. It's scary.

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Speaker 2: You're still out there digging up rud of vegas.

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Speaker 4: Yes, yes you are, and your problem. That's a very

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Speaker 4: respectable way of earning it.

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Speaker 3: And you're probably using an older shovel. So the better

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Speaker 3: shovel got invented in the.

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Speaker 2: Big big city, the auto shovel.

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Speaker 3: Right, yes, they called it the John Henry with no

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Speaker 3: trace of irony, and yeah, exactly, And thanks Illumination Global Unlimited,

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Speaker 3: our first and primary sponsor every war. We talked about

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Speaker 3: this too in the past. Guys. Every war in human

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Speaker 3: history brings this mass transfer of knowledge. And sometimes it

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Speaker 3: happens organically, but in other cases, like in post World

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Speaker 3: War two, countries purposely headhunt the best and brightest from

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Speaker 3: the losing side and then leverage that desperate situation to

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Speaker 3: their advantage. Operation paper clip.

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Speaker 4: Is that Varoner von Braun?

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Speaker 2: Yeah, yeah, yeah, and so many other let's really hit

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Speaker 2: that home. The United States has NASA, no matter how

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Speaker 2: you feel about that, right, the folks that in innovated

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Speaker 2: space travel and space exploration because of World War Two,

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Speaker 2: because of brain drain, because of Nazis.

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Speaker 3: Because of Yes, brain draine Nazi scientists, it definitely happened.

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Speaker 3: History is not original, Okay, that's what we're saying. It's

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Speaker 3: important to remember that as we record Monday, December twenty second,

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Speaker 3: twenty twenty five, history is closer than it looks in

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Speaker 3: the rear view mirror. In fact, in the course of

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Speaker 3: our investigation for this, we found that tons of experts

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Speaker 3: have examined facets of this over the past centuries and

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Speaker 3: sometimes Okay, technology modifies a few plot points, but the

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Speaker 3: story at its core, if we're writing a screenplay about

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Speaker 3: brain drain, it is always the same. It's the same thing,

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Speaker 3: beat for beat, and that means research is solid. But

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Speaker 3: it also means we can make some disturbing predictions about

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Speaker 3: the future. Yeah, real pyrrhic victory. Nice when you guys,

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Speaker 3: kind of an own goal on our part.

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Speaker 2: Uh, it's really messed up as we're about to get

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Speaker 2: into here. When you look at this a survey, right,

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Speaker 2: how do you trust surveys nowadays? When you can, you know,

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Speaker 2: open up Google and it'll just serve you surveys and

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Speaker 2: you'll get like zero point two cents if you fill

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Speaker 2: out the survey or whatever. But anyway, one of the

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Speaker 2: main things we're talking about today is based on a

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Speaker 2: survey just of how people are feeling, which is this concept. Right,

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Speaker 2: we can look to the past and then we can

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Speaker 2: feel this way, some particular way about what's coming right,

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Speaker 2: and that feeling ends up being the thing. Just the

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Speaker 2: way it moves markets. It can also move researchers and academics.

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Speaker 3: And science, and we do have some quantitative data as well.

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Speaker 3: These are not just articles of faith. We're talking about

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Speaker 3: the future of brain drain. I mean, okay. Something that

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Speaker 3: is good for the average person is that today's world

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Speaker 3: is cartoonishly more connected than it was in the past.

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Speaker 3: It is now easier at this point in history than

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Speaker 3: ever before to gather information to learn how much your

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Speaker 3: same job pays in another town and another part of

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Speaker 3: the world. It's also easier to travel, and it's also

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Speaker 3: easier for powerful people, the new enlightened despots, to find

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Speaker 3: you if they want your skills. This ties into immigration. Sure,

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Speaker 3: you know, let's play along at home. If you've got

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Speaker 3: your second screen up, if you're on your phone and

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Speaker 3: you're watching this on a different device, figure out your

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Speaker 3: dream country. Just name a country, check their immigration policy,

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Speaker 3: and you were going to see a wish list of

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Speaker 3: dream employees from that country, right, the country, you know,

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Speaker 3: Canada says well, we don't want everybody, but are you

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Speaker 3: a doctor? How much do you know about semiconductors.

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Speaker 4: As intense as the immigration rhetoric's been out of our country,

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Speaker 4: it does seem like they're certainly willing to make exceptions

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Speaker 4: kind of after the fact, after a lot of this

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Speaker 4: like Saber readily nasty talk about not wanting immigrants, but

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Speaker 4: yet we do want these particular type of immigrants that

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Speaker 4: are going to benefit us, which just I'm sorry, I'm

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Speaker 4: not trying to be politically or but does seem inherently

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Speaker 4: hypocritical to have like the two sides of that coin,

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Speaker 4: and like we want you, but not you, but the

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Speaker 4: you that we want, but then the other ones that

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Speaker 4: are not benefiting our bottom line, we you know, get

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Speaker 4: out of here.

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Speaker 3: Wait, we're letting the Nazis in. Yeah, but just like

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Speaker 3: the rocket.

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Speaker 2: Nazis, Yeah, yeah, yeah, the medical Nazis.

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Speaker 3: Well all right, guys, we're we can't have everybody on

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Speaker 3: the list, though, But see.

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Speaker 2: That's also a really tough thing because just because someone, uh,

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Speaker 2: some scientists, some research, or some academic who is living

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Speaker 2: in a country where there is an oppressive regime like

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Speaker 2: the Nazis. Operator doesn't make them Nazis. Right, of course,

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Speaker 2: you've got to we have to keep that in mind.

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Speaker 2: But there's also that thing where when you're in a

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Speaker 2: country like that that is going through some oppressive regime,

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Speaker 2: perhaps your your the thing you're good at, your research,

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Speaker 2: your your innovations, inventions are being used by that crew.

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Speaker 4: You're against your will sometimes though you're not like getting

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Speaker 4: to choose which exactly they are pulling you in, and

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Speaker 4: then you are being installed in a position that uses

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Speaker 4: your skills, that benefits the regime.

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Speaker 2: But the thing is, even before any oppressive regime takes action,

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Speaker 2: let's say invades Poland or you know, invades Venezuela or whatever.

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Speaker 2: Just given some examples here, maybe you see that coming

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Speaker 2: and see it happening as one of these academics or innovators,

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Speaker 2: and you choose before that occurs to get out right, Well,

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Speaker 2: you've got a post and a pre brained drain that occurs,

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Speaker 2: and there's even a during like let's say wartime brain

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Speaker 2: drain that occurs. It just we're just trying to make

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Speaker 2: a point that it happens in stages on both sides

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Speaker 2: of some big change.

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Speaker 3: Yes, cyclically predictive, and it happens proactively and reactively. One

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Speaker 3: historical precedent that I think would be a great case

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Speaker 3: would be a scientist of Jewish heritage who saw what

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Speaker 3: was on the horizon and felt what was in the

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Speaker 3: wind right and escaped before the Nazis committed their genocide.

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Speaker 3: And for a lot of modern history, from post World

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Speaker 3: War two to recent years, the United States was often

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Speaker 3: considered the place to be the last man standing. In

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Speaker 3: the wake of a horrific global war. Uncle Sam begins

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Speaker 3: exporting all sorts of things, and one of the most

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Speaker 3: successful products the country ever exported was the idea of

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Speaker 3: what we call the American dream.

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Speaker 4: You know, you can be a new man, you know.

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Speaker 4: I mean it's like the United States has historically had

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Speaker 4: this image of we are innovation first. Innovation for that

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Speaker 4: is what we care about. Come here, we will support you.

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Speaker 4: We will you know, patronize your research and the things

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Speaker 4: that you're passionate about, whether it be the arts, whether

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Speaker 4: it be science, whether it be any number of these

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Speaker 4: types of skilled and very specific professions. That was the

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Speaker 4: reputation that we I believe have had, and I think

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Speaker 4: with good reason, especially given the state of higher education

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Speaker 4: here in the United States. People want to come here

434
00:25:55,600 --> 00:25:56,240
Speaker 4: for that as well.

435
00:25:56,600 --> 00:26:01,280
Speaker 3: Yeah, come forth, you huddled masses. We yelled, we're fair here.

436
00:26:01,600 --> 00:26:05,040
Speaker 3: We got no kings, we got no ingrained classism. Where

437
00:26:05,040 --> 00:26:08,160
Speaker 3: the world's best meritocracy. You work hard, that you pay

438
00:26:08,200 --> 00:26:12,040
Speaker 3: your dues, the future is yours double plus good thumbs up.

439
00:26:12,119 --> 00:26:15,399
Speaker 3: This turned out not to be entirely true.

440
00:26:16,480 --> 00:26:19,199
Speaker 2: It was at least partly true in ways for a

441
00:26:19,240 --> 00:26:22,360
Speaker 2: while exactly right. Parts of all of those were kind

442
00:26:22,359 --> 00:26:22,760
Speaker 2: of true.

443
00:26:22,920 --> 00:26:25,960
Speaker 3: It was true in that we all thought it was

444
00:26:26,000 --> 00:26:28,560
Speaker 3: a good idea when we wrote it down in the

445
00:26:28,680 --> 00:26:33,000
Speaker 3: writer's room. Everybody was the writer's room of the founding fathers.

446
00:26:33,080 --> 00:26:36,240
Speaker 3: Everyone said, this is a banger, you know what I mean.

447
00:26:36,400 --> 00:26:38,359
Speaker 2: They were like, played really well at the table reading.

448
00:26:38,520 --> 00:26:40,679
Speaker 3: Yeah, they were like, this is the new Seinfeld. And

449
00:26:40,720 --> 00:26:46,880
Speaker 3: someone said, what Seinfeld spoilers. So fast forward, folks, it's

450
00:26:46,960 --> 00:26:50,640
Speaker 3: twenty twenty six, Fellow conspiracy realist. As you hear this

451
00:26:51,000 --> 00:26:55,920
Speaker 3: and experts fear, America, once the dream destination for billions,

452
00:26:56,280 --> 00:27:00,800
Speaker 3: is turning into one of Earth's worst cases of brain

453
00:27:00,920 --> 00:27:05,720
Speaker 3: drained storms on the horizon of fell wind blows and

454
00:27:05,840 --> 00:27:08,399
Speaker 3: what does this fell wind mean? Well, it's going to

455
00:27:08,480 --> 00:27:10,639
Speaker 3: be tough to figure out if we don't have scientists

456
00:27:10,720 --> 00:27:11,560
Speaker 3: to do the research.

457
00:27:12,160 --> 00:27:15,040
Speaker 4: Yeah, we're just gonna have to make our best guess.

458
00:27:15,640 --> 00:27:19,160
Speaker 2: The Mozart of math will be in Australia going oh, well,

459
00:27:19,359 --> 00:27:20,200
Speaker 2: I can do it over here.

460
00:27:20,480 --> 00:27:21,400
Speaker 4: I'll do the method.

461
00:27:21,280 --> 00:27:25,600
Speaker 3: Right, and we're gonna pause for an ad break. We'll

462
00:27:25,600 --> 00:27:35,639
Speaker 3: ti back in. Okay, okay, everybody, let's pump our brakes,

463
00:27:35,680 --> 00:27:38,240
Speaker 3: cool our jets and thanks to the people who invented

464
00:27:38,280 --> 00:27:41,800
Speaker 3: breaks and jets. We don't want to be alarmist or hyperbolic,

465
00:27:42,280 --> 00:27:45,359
Speaker 3: but there is a problem. There is a problem because

466
00:27:45,520 --> 00:27:51,240
Speaker 3: historically the United States led the modern world and scientific breakthroughs.

467
00:27:51,560 --> 00:27:54,640
Speaker 3: And oddly enough this might surprise a lot of our

468
00:27:55,160 --> 00:27:59,920
Speaker 3: fellow residents of the US. Oddly enough, for decades and decades,

469
00:28:00,480 --> 00:28:04,399
Speaker 3: funding for research and design and all sorts of stuff

470
00:28:04,720 --> 00:28:08,719
Speaker 3: was stable. Investment in basic science was a given. It

471
00:28:08,760 --> 00:28:12,720
Speaker 3: was largely backed by the big dog political parties and

472
00:28:12,800 --> 00:28:16,800
Speaker 3: the fringe parties. But now Uncle Sam has closed the

473
00:28:16,880 --> 00:28:21,359
Speaker 3: wallet on tons of research. And no, you know, I

474
00:28:21,359 --> 00:28:24,639
Speaker 3: always respect it when you say, when we take pains

475
00:28:24,680 --> 00:28:28,520
Speaker 3: to say, hey, we're not here to be politicos or whatever,

476
00:28:28,920 --> 00:28:32,800
Speaker 3: but we do have to acknowledge it's because of the

477
00:28:32,840 --> 00:28:37,119
Speaker 3: recent presidential administration. This changed the game in May of

478
00:28:37,200 --> 00:28:41,400
Speaker 3: twenty twenty five, because of something called the Big Beautiful

479
00:28:41,520 --> 00:28:46,760
Speaker 3: Bill or the Fiscal twenty twenty six budget proposal. And

480
00:28:46,880 --> 00:28:49,080
Speaker 3: we've got some stats we want to kick which are

481
00:28:49,080 --> 00:28:50,520
Speaker 3: pretty sobering for sure.

482
00:28:50,520 --> 00:28:52,880
Speaker 4: I mean, also just to add that there was a time,

483
00:28:52,920 --> 00:28:55,360
Speaker 4: it would seem where the time you were describing then,

484
00:28:55,440 --> 00:28:59,560
Speaker 4: where science wasn't really a partisan thing. You know, both sides,

485
00:28:59,600 --> 00:29:01,719
Speaker 4: even the and his parties were like science good, like

486
00:29:01,760 --> 00:29:03,600
Speaker 4: what Matt was saying. So here are some of these

487
00:29:03,640 --> 00:29:06,000
Speaker 4: stats and a lot of this Big Beautiful Bill stuff,

488
00:29:06,040 --> 00:29:08,880
Speaker 4: which is a mouthful. It does seem that even though

489
00:29:08,880 --> 00:29:11,160
Speaker 4: they claimed it wasn't the direction, they were going to

490
00:29:11,280 --> 00:29:15,160
Speaker 4: be things that support that whole Project twenty twenty five initiative,

491
00:29:16,120 --> 00:29:19,000
Speaker 4: which is this dismantling of a lot of these government

492
00:29:19,080 --> 00:29:25,720
Speaker 4: agencies and installing let's just say secafants, yes, yes, people

493
00:29:25,960 --> 00:29:30,280
Speaker 4: in order to push political agendas in place of science.

494
00:29:30,640 --> 00:29:35,080
Speaker 3: Yeah. And for the record, that Project twenty twenty five

495
00:29:35,160 --> 00:29:40,520
Speaker 3: stuff is heavily plagiarized from the Foundations of geopolitics by

496
00:29:40,560 --> 00:29:45,920
Speaker 3: Alexander Dugan. So the what did we call him, Russia's

497
00:29:46,160 --> 00:29:47,400
Speaker 3: new respute.

498
00:29:47,160 --> 00:29:49,600
Speaker 4: Right, Yeah, for sure, a bit of a shadowy figure.

499
00:29:49,640 --> 00:29:52,280
Speaker 4: So here's some of the stats we're talking about. The

500
00:29:52,360 --> 00:29:56,320
Speaker 4: White House released these details surrounding fiscal year twenty twenty

501
00:29:56,360 --> 00:29:59,760
Speaker 4: six in a budget proposal that called for reducing the

502
00:29:59,800 --> 00:30:03,880
Speaker 4: Nowtional Science Foundation's budget by fifty seven percent, the National

503
00:30:03,880 --> 00:30:07,520
Speaker 4: Institute of Health's budget by roughly forty percent, and NASA's

504
00:30:07,560 --> 00:30:13,000
Speaker 4: the aforementioned NASA's science budget by forty seven percent. These

505
00:30:13,000 --> 00:30:16,200
Speaker 4: are some slicy dicey cuts here. The Department of Energies

506
00:30:16,360 --> 00:30:19,760
Speaker 4: Office of Science faces a fourteen percent cut, while the

507
00:30:19,840 --> 00:30:24,160
Speaker 4: National Institute of Standards and Technology would see a twenty

508
00:30:24,320 --> 00:30:28,400
Speaker 4: eight percent reduction in their budget. We also have cuts

509
00:30:28,400 --> 00:30:33,560
Speaker 4: to the National Oceanic and Atmospheric Administration, the weather One NOAH,

510
00:30:33,600 --> 00:30:38,400
Speaker 4: and also the Environmental Protection Agency. These are government agencies,

511
00:30:38,440 --> 00:30:41,960
Speaker 4: but they have historically had some autonomy, and they're the

512
00:30:41,960 --> 00:30:43,600
Speaker 4: ones that are supposed to be doing the science and

513
00:30:43,640 --> 00:30:45,680
Speaker 4: then recommending to the government the things that we need

514
00:30:45,720 --> 00:30:48,360
Speaker 4: to do to maybe not like blow ourselves up or completely,

515
00:30:48,480 --> 00:30:51,680
Speaker 4: you know, deplete the resources that our planet has to off.

516
00:30:52,080 --> 00:30:56,440
Speaker 3: And these are not propagadendistic numbers. These are actually coming

517
00:30:56,480 --> 00:31:01,440
Speaker 3: to us from the American Physical Society and Olivia Newton

518
00:31:01,520 --> 00:31:05,400
Speaker 3: John fan Club. They're they're super into physics and that

519
00:31:05,560 --> 00:31:08,680
Speaker 3: kind of science, but they probably also rock some Olivia

520
00:31:08,960 --> 00:31:10,640
Speaker 3: you know, and doesn't have a good time.

521
00:31:10,720 --> 00:31:13,440
Speaker 4: Oh no, no, Olivia is the best. Xana do is

522
00:31:13,440 --> 00:31:16,840
Speaker 4: what I think of also grease. But let's also just

523
00:31:17,200 --> 00:31:20,600
Speaker 4: not act like we are completely wearing rose colored glasses

524
00:31:20,720 --> 00:31:23,640
Speaker 4: and thinking that these organizations have not in the past

525
00:31:23,680 --> 00:31:27,160
Speaker 4: also played politics, no question about. Is not like a

526
00:31:27,200 --> 00:31:29,680
Speaker 4: cut and dried situation that we're talking here. I just

527
00:31:29,680 --> 00:31:33,560
Speaker 4: think that we're seeing a much more slippery slide into

528
00:31:33,800 --> 00:31:37,520
Speaker 4: a much more divisive use of these types of organizations.

529
00:31:37,520 --> 00:31:41,280
Speaker 3: Oh you made it sound so fun man. I miss

530
00:31:41,360 --> 00:31:42,320
Speaker 3: slip and slides.

531
00:31:42,680 --> 00:31:43,480
Speaker 4: They're dangerous.

532
00:31:43,520 --> 00:31:46,800
Speaker 3: Though they are dangerous. They are dangerous, but it's way

533
00:31:46,840 --> 00:31:49,760
Speaker 3: better than the non consensual slip and slides I've had

534
00:31:49,840 --> 00:31:53,360
Speaker 3: the past, you know what I mean. It's it's funny

535
00:31:53,360 --> 00:31:58,040
Speaker 3: because I broke my toe earlier this year, but we

536
00:31:58,080 --> 00:31:59,280
Speaker 3: record from the waist up.

537
00:31:59,200 --> 00:32:01,960
Speaker 2: Right, you know, it would be good to help out

538
00:32:01,960 --> 00:32:03,920
Speaker 2: with that. Guys, I just thought about this, and I

539
00:32:04,160 --> 00:32:05,520
Speaker 2: thought about it this whole episode.

540
00:32:05,880 --> 00:32:06,240
Speaker 4: DARPA.

541
00:32:07,000 --> 00:32:11,560
Speaker 2: We haven't talked about DARPA yet, cause there's that's one

542
00:32:12,040 --> 00:32:16,400
Speaker 2: one area of science funding that seems to be going gangbusters.

543
00:32:16,880 --> 00:32:24,000
Speaker 3: Interesting, Yeah, because DARPA has a different wallet source it does.

544
00:32:24,320 --> 00:32:28,080
Speaker 2: It's the Pentagon thing in the what is it the

545
00:32:28,120 --> 00:32:31,200
Speaker 2: Defense spending bill that just went through pretty recently here

546
00:32:31,240 --> 00:32:34,760
Speaker 2: in the US, and I think they're allocated around four

547
00:32:34,800 --> 00:32:38,360
Speaker 2: point three four point four billion dollars just for DARPA.

548
00:32:38,560 --> 00:32:41,040
Speaker 3: All right, Yeah, let's all be cool because we want

549
00:32:41,120 --> 00:32:46,600
Speaker 3: the grand Yeah. Please check out some of our earlier

550
00:32:46,640 --> 00:32:50,320
Speaker 3: episodes on DARPA. We've called them in the past the

551
00:32:50,360 --> 00:32:55,240
Speaker 3: mad scientist branch of the Pentagon, which is not inaccurate,

552
00:32:55,320 --> 00:32:59,400
Speaker 3: but maybe a little bit clickbaiting. It's a little bit

553
00:32:59,440 --> 00:33:02,520
Speaker 3: of a fun way to say to say what they do,

554
00:33:02,640 --> 00:33:06,240
Speaker 3: which is providing funding and grants. They like the enlightened

555
00:33:06,240 --> 00:33:10,280
Speaker 3: despots of old. They identify skill sets and research that

556
00:33:10,440 --> 00:33:17,719
Speaker 3: they dig and in most cases they will propose a

557
00:33:17,920 --> 00:33:21,920
Speaker 3: problem or question and you pitch them shark tank style

558
00:33:22,440 --> 00:33:26,000
Speaker 3: an answer, and they might throw a little a little

559
00:33:26,000 --> 00:33:29,760
Speaker 3: bit of scratch your way to explore the idea further.

560
00:33:30,080 --> 00:33:32,160
Speaker 3: But then in other cases, on the other side of

561
00:33:32,200 --> 00:33:35,000
Speaker 3: the spectrum, if you already have an idea and they

562
00:33:35,000 --> 00:33:40,720
Speaker 3: think it's a threat to national security mine, yeah, secrecy Act, but.

563
00:33:41,040 --> 00:33:44,080
Speaker 2: Arly talk about it, Yes you cannot. But generally, you

564
00:33:44,120 --> 00:33:48,080
Speaker 2: know north of Grumming or your Boeing's or company works.

565
00:33:48,560 --> 00:33:51,600
Speaker 2: They raise their hand, they say, we'll take that one actually,

566
00:33:52,360 --> 00:33:57,000
Speaker 2: and then now their their private company has a lot

567
00:33:57,040 --> 00:33:58,600
Speaker 2: to do for the next couple of years.

568
00:33:58,720 --> 00:34:02,080
Speaker 3: You will heed the law, they say, right back. He

569
00:34:02,200 --> 00:34:03,680
Speaker 3: jokes were to get trouble.

570
00:34:03,720 --> 00:34:06,160
Speaker 4: And all this comes, you know, on the heels of

571
00:34:06,440 --> 00:34:10,160
Speaker 4: a ton of other cuts and slices, a lot of

572
00:34:10,200 --> 00:34:16,680
Speaker 4: which took place under Elon Musk's relatively short lived DOGE initiative.

573
00:34:16,640 --> 00:34:21,160
Speaker 3: Please could dodge the Dude Governmental efficiency, it was called.

574
00:34:21,280 --> 00:34:23,719
Speaker 4: That's exactly right. And of course there were a lot

575
00:34:23,760 --> 00:34:25,719
Speaker 4: of questions surrounding how.

576
00:34:26,239 --> 00:34:28,959
Speaker 3: Politically motivated those cuts were, whether they.

577
00:34:28,840 --> 00:34:32,440
Speaker 4: Were in fact going after waste and fraud, even some

578
00:34:32,520 --> 00:34:34,520
Speaker 4: of the effectiveness of the cuts that were made, or

579
00:34:34,560 --> 00:34:37,080
Speaker 4: what cuts actually were made, because the lists of them

580
00:34:37,600 --> 00:34:40,440
Speaker 4: kept being revised as they were posted, and there was

581
00:34:40,480 --> 00:34:42,640
Speaker 4: this whole sense of we're going to be completely transparent

582
00:34:42,719 --> 00:34:46,080
Speaker 4: about this, but a lot of that information seemed very

583
00:34:46,400 --> 00:34:49,520
Speaker 4: tricksy in terms of the math. They were talking about

584
00:34:49,520 --> 00:34:52,719
Speaker 4: having cut grants that I think expired like years and

585
00:34:52,760 --> 00:34:54,920
Speaker 4: years ago, and things that had already been built they

586
00:34:54,960 --> 00:34:56,600
Speaker 4: were saying they saved money on. So there was just

587
00:34:56,640 --> 00:34:59,359
Speaker 4: a whole lot of real tricky cocktail napkin math going

588
00:34:59,400 --> 00:35:00,800
Speaker 4: on with that whole situation.

589
00:35:01,320 --> 00:35:03,760
Speaker 3: Call it it now, doje episode in the future.

590
00:35:03,920 --> 00:35:04,600
Speaker 4: I think that's right.

591
00:35:04,880 --> 00:35:08,759
Speaker 3: Yeah, yet's do it. And we know that these these

592
00:35:08,800 --> 00:35:14,400
Speaker 3: cuts were describing were controversial and resulted in thousands and

593
00:35:14,480 --> 00:35:18,840
Speaker 3: thousands of federal employees, including a lot of scientists, getting

594
00:35:18,920 --> 00:35:23,759
Speaker 3: fired but then rehired after a court order. And well

595
00:35:23,800 --> 00:35:24,839
Speaker 3: there are some whoops too.

596
00:35:24,880 --> 00:35:26,640
Speaker 4: There was some we didn't mean to get rid of

597
00:35:26,719 --> 00:35:31,000
Speaker 4: USA now people, Oh my gosh. But let's let's put

598
00:35:31,040 --> 00:35:31,319
Speaker 4: it back.

599
00:35:31,560 --> 00:35:36,040
Speaker 3: We fired the tires on our road trip. Whoops. That's

600
00:35:36,040 --> 00:35:40,240
Speaker 3: what happened, was big whoopsie. And we know some people

601
00:35:40,280 --> 00:35:43,640
Speaker 3: who had to go through that emotional roller coaster, which.

602
00:35:43,440 --> 00:35:47,799
Speaker 4: Absolute very research universities, for example, even just like in

603
00:35:48,200 --> 00:35:50,560
Speaker 4: the maintenance or it departments. You know, like I have

604
00:35:50,600 --> 00:35:52,319
Speaker 4: a friend. We both have a friend of the show,

605
00:35:52,320 --> 00:35:56,120
Speaker 4: Matt Riddle, who works maintaining MRI machines for a very

606
00:35:56,120 --> 00:36:00,960
Speaker 4: prestigious research university involving and these machines are used for research,

607
00:36:01,040 --> 00:36:04,799
Speaker 4: And when those grants were potentially pulled, there was a

608
00:36:04,800 --> 00:36:06,960
Speaker 4: lot of questions around, am I gonna even have a job?

609
00:36:06,960 --> 00:36:10,520
Speaker 4: Am I gonna have MRI machines to maintain? Not to

610
00:36:10,600 --> 00:36:13,640
Speaker 4: mention the a lot of the hot button things that

611
00:36:13,680 --> 00:36:16,480
Speaker 4: were sort of being discussed were like, we don't want

612
00:36:16,560 --> 00:36:21,160
Speaker 4: research on transgender mice or something like that. There were

613
00:36:21,160 --> 00:36:26,000
Speaker 4: a lot of these very hyperbolic, sort of manipulating ways

614
00:36:26,040 --> 00:36:28,520
Speaker 4: of describing research that when you actually dug down into

615
00:36:28,560 --> 00:36:30,799
Speaker 4: the details of the real realities of them, were not

616
00:36:30,880 --> 00:36:31,600
Speaker 4: quite accurate.

617
00:36:32,120 --> 00:36:35,600
Speaker 3: Yeah, political theater, that's one way to put it. In

618
00:36:35,719 --> 00:36:39,080
Speaker 3: our Doge episode, which I'm instantly super excited about too,

619
00:36:41,239 --> 00:36:45,440
Speaker 3: we've got several conspiracies involved regarding the motivation of what

620
00:36:45,560 --> 00:36:50,839
Speaker 3: was targeted to be cut. We also know we've got

621
00:36:50,880 --> 00:36:54,480
Speaker 3: close friends at the CDC, which I hate that that

622
00:36:54,560 --> 00:36:58,400
Speaker 3: sounds sketchy now, but here in the Atlanta area and

623
00:36:58,400 --> 00:37:03,040
Speaker 3: our fair metropolis, we have the Center for Disease Control

624
00:37:03,840 --> 00:37:08,120
Speaker 3: and those folks are rightly asking, why are you cutting

625
00:37:08,560 --> 00:37:12,799
Speaker 3: us from the game. You know, these budget cuts. This

626
00:37:12,920 --> 00:37:16,320
Speaker 3: is the point. These budget cuts are not hitting playing

627
00:37:16,360 --> 00:37:22,239
Speaker 3: all abstract science. Nobody is fruitlessly trying to reinvent the

628
00:37:22,360 --> 00:37:27,719
Speaker 3: number nine. Instead, these cuts are directly impacting programs that

629
00:37:27,800 --> 00:37:33,000
Speaker 3: result in better training in scientific breakthroughs, innovations, jobs. We

630
00:37:33,080 --> 00:37:38,000
Speaker 3: saw a twenty twenty three survey by Research America that

631
00:37:38,320 --> 00:37:42,600
Speaker 3: proves the public supports this. More than three and four Americans,

632
00:37:42,760 --> 00:37:48,440
Speaker 3: more than seventy five percent of three hundred plus million

633
00:37:48,520 --> 00:37:52,239
Speaker 3: people who ordinarily do not get along, they agree that

634
00:37:52,360 --> 00:37:57,080
Speaker 3: investing in research creates jobs in the United States. And

635
00:37:57,120 --> 00:38:00,239
Speaker 3: then there was a related question on that survey than

636
00:38:00,440 --> 00:38:05,040
Speaker 3: eight and ten, so more than eighty percent of Americans say, yeah,

637
00:38:05,400 --> 00:38:10,960
Speaker 3: the federal government should help out with research. It's not controversialist.

638
00:38:11,120 --> 00:38:13,640
Speaker 4: No, it shouldn't be for sure. And just to clarify

639
00:38:13,800 --> 00:38:16,960
Speaker 4: the thing I was mentioning that kind of here's the headline.

640
00:38:17,120 --> 00:38:20,840
Speaker 4: You know, NIH money is being used to fund research

641
00:38:20,920 --> 00:38:25,240
Speaker 4: on transgender mice, on you know, gender affirming care for mice.

642
00:38:25,560 --> 00:38:28,200
Speaker 4: But that was just a tiny fraction one point four

643
00:38:28,239 --> 00:38:30,920
Speaker 4: million of an eight million dollar funding grant, and the

644
00:38:30,960 --> 00:38:35,320
Speaker 4: rest of it was actually used for Alzheimer's breakthroughs PTSD

645
00:38:35,760 --> 00:38:38,960
Speaker 4: and clinical depression, like the kinds of stuff that could

646
00:38:39,040 --> 00:38:43,960
Speaker 4: benefit not just members of the trans community, but anybody

647
00:38:44,160 --> 00:38:46,120
Speaker 4: you know and people you know, your grandma, you know,

648
00:38:46,200 --> 00:38:49,879
Speaker 4: your mother who's dealing with a slide into dementia, things

649
00:38:49,920 --> 00:38:52,440
Speaker 4: like that. So there's this a lot of this demonization

650
00:38:52,520 --> 00:38:54,839
Speaker 4: that's going on and pulling out just the thing that's

651
00:38:54,880 --> 00:38:57,799
Speaker 4: easy to kind of weaponize and throw around and make

652
00:38:57,840 --> 00:39:01,320
Speaker 4: people think that there's all this like super whatever liberal

653
00:39:01,520 --> 00:39:03,720
Speaker 4: research going on and it's just not the case.

654
00:39:04,120 --> 00:39:08,200
Speaker 3: Yeah, it's easy to make a breathless, misleading claim when

655
00:39:08,239 --> 00:39:11,799
Speaker 3: you have three minutes, right, and the people who are

656
00:39:12,200 --> 00:39:15,880
Speaker 3: on the receiving end of that propaganda typically are not

657
00:39:15,960 --> 00:39:20,160
Speaker 3: going to take additional time to delve into this. This

658
00:39:20,360 --> 00:39:24,160
Speaker 3: is why, like, all right, here's the thing, folks. Good

659
00:39:24,360 --> 00:39:30,160
Speaker 3: research is good for everyone. Solid research, even if you're saying, hey,

660
00:39:30,200 --> 00:39:34,440
Speaker 3: Alzheimer's doesn't run in my family, that solid research will

661
00:39:34,520 --> 00:39:38,279
Speaker 3: make the world a better place. It is important. It's

662
00:39:38,360 --> 00:39:43,040
Speaker 3: kind of like it's similar to the way the Hope

663
00:39:43,080 --> 00:39:47,000
Speaker 3: Scholarship here in this in our fair home of Georgia

664
00:39:48,120 --> 00:39:52,520
Speaker 3: helped improve society by allowing more kids to go to college.

665
00:39:52,560 --> 00:39:54,360
Speaker 4: Would you also say that that was a way of

666
00:39:54,440 --> 00:39:59,120
Speaker 4: preventing brain drain here in Georgia by giving you know, locals,

667
00:39:59,160 --> 00:40:01,960
Speaker 4: people that grew up born and raised here an opportunity

668
00:40:02,040 --> 00:40:03,080
Speaker 4: to stay in state.

669
00:40:03,640 --> 00:40:06,560
Speaker 3: Yeah, that's a great point. It also it also shows

670
00:40:06,680 --> 00:40:11,080
Speaker 3: measurable reductions in certain types of crime, because now if

671
00:40:11,080 --> 00:40:15,160
Speaker 3: you're able to go to college or pursuing a career,

672
00:40:16,080 --> 00:40:22,320
Speaker 3: that's one less radio stolen off of pods.

673
00:40:22,560 --> 00:40:24,799
Speaker 4: I know, yeah, I remember when people to take their

674
00:40:24,840 --> 00:40:26,960
Speaker 4: CD players face the car.

675
00:40:28,360 --> 00:40:32,480
Speaker 3: Yeah I remember that. Yeah, Ed and economists are making

676
00:40:32,600 --> 00:40:37,239
Speaker 3: frightening predictions right now. I was looking at these studies

677
00:40:37,320 --> 00:40:41,560
Speaker 3: that indicate a twenty five percent cut in research funding

678
00:40:42,080 --> 00:40:46,759
Speaker 3: will reduce the United States GDP gross domestic product by

679
00:40:46,920 --> 00:40:50,720
Speaker 3: three point eight percent over the next several decades. Sounds

680
00:40:50,719 --> 00:40:54,680
Speaker 3: like a small number, but it's four percent of a

681
00:40:54,920 --> 00:40:58,960
Speaker 3: very big pie. A fifty percent cut just to spend

682
00:40:58,960 --> 00:41:02,919
Speaker 3: this out further will reduce GDP by seven point six

683
00:41:03,000 --> 00:41:06,200
Speaker 3: percent across the same timeline. That would be a drop

684
00:41:06,560 --> 00:41:10,360
Speaker 3: bigger than anything since the Great Depression, which again is

685
00:41:10,400 --> 00:41:11,359
Speaker 3: a terrible name.

686
00:41:12,960 --> 00:41:17,560
Speaker 4: It wasn't yeah, because it was great.

687
00:41:18,640 --> 00:41:21,560
Speaker 2: I'm thinking about what all of that like, this is

688
00:41:21,760 --> 00:41:25,200
Speaker 2: just this is knowledge that we've researched, y'all that you

689
00:41:25,280 --> 00:41:29,040
Speaker 2: can go out and find. Right now, I'm imagining what

690
00:41:29,440 --> 00:41:34,560
Speaker 2: this is doing to the morale of highly intelligent people,

691
00:41:34,600 --> 00:41:37,359
Speaker 2: people that are far smarter than I am. But people

692
00:41:37,360 --> 00:41:39,560
Speaker 2: who are out there, let's say, going for a PhD,

693
00:41:39,760 --> 00:41:42,720
Speaker 2: Like they want to become a PhD student, and they're

694
00:41:42,760 --> 00:41:45,960
Speaker 2: looking I feel like people and maybe I'm wrong, but

695
00:41:46,000 --> 00:41:48,760
Speaker 2: I feel as though people who are at that level

696
00:41:49,120 --> 00:41:53,040
Speaker 2: make five year plans, ten year plans, concepts of where

697
00:41:53,080 --> 00:41:56,279
Speaker 2: they will be in the future, and they plan out

698
00:41:56,520 --> 00:41:58,480
Speaker 2: there are steps I need to take in order to

699
00:41:58,480 --> 00:42:01,960
Speaker 2: get to end goal X, right, and then why we'll

700
00:42:02,000 --> 00:42:04,200
Speaker 2: be on the other side of that one. When you

701
00:42:04,719 --> 00:42:08,799
Speaker 2: when it feels like you just can't see yourself on

702
00:42:08,960 --> 00:42:12,960
Speaker 2: any kind of pathway forward, why in the heck would

703
00:42:12,960 --> 00:42:15,440
Speaker 2: you try to make it work in a place that

704
00:42:15,719 --> 00:42:17,600
Speaker 2: is putting up those roadblocks for you.

705
00:42:18,120 --> 00:42:22,279
Speaker 3: It's demoralizing. Yeah. Shout out to the postgrads, Shout out

706
00:42:22,320 --> 00:42:26,000
Speaker 3: to the grad student. Shout out to the best and

707
00:42:26,960 --> 00:42:32,640
Speaker 3: brightest minds who are pursuing internships or in high school

708
00:42:32,920 --> 00:42:35,440
Speaker 3: and saying I want to be a physicist. But should

709
00:42:35,520 --> 00:42:40,960
Speaker 3: I institutions have reacted swiftly to these cuts. Hiring freezes

710
00:42:41,080 --> 00:42:46,279
Speaker 3: went into effect, grant request got stonewalled, research got mothballed,

711
00:42:46,320 --> 00:42:50,400
Speaker 3: some really good tasted research too, and scientists across the

712
00:42:50,480 --> 00:42:54,480
Speaker 3: country had to face some serious, like Dark Knight of

713
00:42:54,520 --> 00:42:58,560
Speaker 3: the Sole questions about the future. This all poses two

714
00:42:58,719 --> 00:43:03,920
Speaker 3: big problems. First, the United States has this obsession with itself.

715
00:43:03,960 --> 00:43:08,840
Speaker 3: It kind of suffers from main character syndrome like people

716
00:43:08,880 --> 00:43:11,680
Speaker 3: who are not good at asking other people questions. The

717
00:43:11,800 --> 00:43:16,640
Speaker 3: United States is a very self centered enterprise. But the

718
00:43:16,800 --> 00:43:22,480
Speaker 3: research is global. Research will continue with or without Uncle Sam.

719
00:43:22,760 --> 00:43:26,080
Speaker 3: The train rolls on, and there are other countries that

720
00:43:26,160 --> 00:43:30,000
Speaker 3: are eager to capitalize on this misstep. And that's the

721
00:43:30,040 --> 00:43:34,040
Speaker 3: first problem. Second problem, people doing that research, just like

722
00:43:34,080 --> 00:43:36,920
Speaker 3: in the days of ancient empires, they are going to

723
00:43:36,960 --> 00:43:39,399
Speaker 3: look for somewhere else to go. They put too much

724
00:43:39,440 --> 00:43:42,719
Speaker 3: time in. They're not gonna shrug their shoulders and say, oh,

725
00:43:42,800 --> 00:43:45,600
Speaker 3: my career is over. I guess the world will never

726
00:43:45,680 --> 00:43:49,480
Speaker 3: learn about zero point energy. They want to get this

727
00:43:49,520 --> 00:43:53,279
Speaker 3: stuff across the finish line. And that's why one of

728
00:43:53,280 --> 00:43:58,520
Speaker 3: the things that informed our Strange News conversation later informed.

729
00:43:58,560 --> 00:44:02,759
Speaker 3: This episode was when the journal Nature asked something like

730
00:44:03,080 --> 00:44:07,000
Speaker 3: one thousand, six hundred and eight American scientists if they

731
00:44:07,000 --> 00:44:10,840
Speaker 3: were considering leaving the country due to these harsh budget cuts.

732
00:44:11,800 --> 00:44:18,359
Speaker 3: Three fourths of those responders said, yeah, I'm thinking about

733
00:44:18,360 --> 00:44:23,640
Speaker 3: skip and town, dude, And they were across scientific disciplines. Again,

734
00:44:23,880 --> 00:44:26,680
Speaker 3: this is like three fourths bla blah. So it's like

735
00:44:28,239 --> 00:44:31,919
Speaker 3: round one thousand, two hundred of the scientists. So again,

736
00:44:32,040 --> 00:44:36,040
Speaker 3: seventy The breathless headline, right, the three second headline is

737
00:44:36,080 --> 00:44:39,520
Speaker 3: seventy five percent of scientists are going to leave the

738
00:44:39,640 --> 00:44:43,560
Speaker 3: United States. That's not quite the case, but it's still very,

739
00:44:43,680 --> 00:44:47,480
Speaker 3: very bad for us because there are a lot of

740
00:44:47,520 --> 00:44:51,200
Speaker 3: other countries that can't wait to have some science refugees.

741
00:44:51,719 --> 00:44:53,960
Speaker 3: How is that a term? How did we get to

742
00:44:54,000 --> 00:44:57,759
Speaker 3: this point where science refugee is a term? I want

743
00:44:57,800 --> 00:45:00,920
Speaker 3: to be a science refugee.

744
00:45:01,160 --> 00:45:06,000
Speaker 2: What kind of science you got work in? Bowling? Hey, hey,

745
00:45:06,120 --> 00:45:08,439
Speaker 2: tell us more information. We'll figure out if it's worth

746
00:45:08,480 --> 00:45:09,120
Speaker 2: our time.

747
00:45:09,600 --> 00:45:12,960
Speaker 3: Yeah. I just need a passport. I need a lifetime

748
00:45:13,080 --> 00:45:16,000
Speaker 3: Dave and Buster's card. Do you guys have Dave and Busters?

749
00:45:16,200 --> 00:45:18,480
Speaker 3: Because if not, I'm going to talk to the next

750
00:45:18,520 --> 00:45:19,160
Speaker 3: country over.

751
00:45:19,400 --> 00:45:21,520
Speaker 2: Yes, sorry, we don't do that here. We're strictly and

752
00:45:22,239 --> 00:45:23,680
Speaker 2: in this.

753
00:45:23,080 --> 00:45:28,520
Speaker 3: Place, right, okay, all right, it's a dilemma. Yeah, and

754
00:45:29,280 --> 00:45:33,840
Speaker 3: this introduces us to the concept of a new project

755
00:45:33,920 --> 00:45:42,799
Speaker 3: paper clip, and we've returned. So not for nothing did

756
00:45:42,800 --> 00:45:47,160
Speaker 3: we mention paper clip. There are several new things that

757
00:45:47,239 --> 00:45:50,680
Speaker 3: are kind of like a less agro version of paper

758
00:45:50,719 --> 00:45:53,760
Speaker 3: clip that are happening right now. We talked about this earlier.

759
00:45:54,320 --> 00:45:59,000
Speaker 3: There are several outfits in France that in March and

760
00:45:59,040 --> 00:46:04,120
Speaker 3: April of twenty twelve five said, hey, we have created

761
00:46:04,160 --> 00:46:08,959
Speaker 3: something called a Safe Place for Science program. We create

762
00:46:09,000 --> 00:46:13,480
Speaker 3: a safe and stimulating environment for scientists wishing to pursue

763
00:46:13,480 --> 00:46:16,040
Speaker 3: their research in complete freedom.

764
00:46:16,480 --> 00:46:19,680
Speaker 4: Uh oh, real opportunity for some other parts of the world.

765
00:46:19,719 --> 00:46:20,440
Speaker 4: What's happening here?

766
00:46:20,680 --> 00:46:25,640
Speaker 3: Yeah, yeah, If I'm a scientist, I'm saying, oh yeah, yeah.

767
00:46:25,680 --> 00:46:29,279
Speaker 2: So but here's the thing, Yeah, these are this is

768
00:46:29,280 --> 00:46:32,600
Speaker 2: an incredible opportunity for you know, someone to become a

769
00:46:32,680 --> 00:46:36,080
Speaker 2: science refugee from another country, let's say the United States,

770
00:46:37,120 --> 00:46:40,240
Speaker 2: or or a lot of other places, even places like Venezuela, Cuba.

771
00:46:40,280 --> 00:46:42,520
Speaker 2: I mean, just think about places that are that you

772
00:46:42,520 --> 00:46:45,760
Speaker 2: could have a scientific mind in that in that country

773
00:46:45,960 --> 00:46:47,600
Speaker 2: that is going to have a really hard time in

774
00:46:47,640 --> 00:46:53,000
Speaker 2: that country, here's an opportunity. The only thing is, it's

775
00:46:53,040 --> 00:46:56,160
Speaker 2: almost like it's like any time you're giving out grants, right,

776
00:46:56,320 --> 00:47:00,040
Speaker 2: as a research institute, you can only give out so many.

777
00:47:00,960 --> 00:47:05,160
Speaker 3: Right, there's a limited number of seats on the train.

778
00:47:05,520 --> 00:47:10,399
Speaker 3: And the issue then becomes one of it's a real

779
00:47:10,440 --> 00:47:13,240
Speaker 3: sticky wicket. It's a real bag of badgers, folks. Because

780
00:47:13,239 --> 00:47:16,560
Speaker 3: if you were the person approving the grants, then you

781
00:47:16,640 --> 00:47:20,200
Speaker 3: have a couple of things. First, are you saving someone's life?

782
00:47:20,440 --> 00:47:23,240
Speaker 3: Is their life in danger because of their research still

783
00:47:23,280 --> 00:47:29,399
Speaker 3: happens today? Secondly, is there and actually probably flip those

784
00:47:30,000 --> 00:47:34,800
Speaker 3: The next one is how does our nation state prioritize

785
00:47:34,840 --> 00:47:35,640
Speaker 3: this research?

786
00:47:35,960 --> 00:47:36,160
Speaker 2: Right?

787
00:47:36,280 --> 00:47:41,520
Speaker 3: If we know somebody is going to die because they're

788
00:47:41,560 --> 00:47:46,640
Speaker 3: doing research on hormone therapy and their country hates it,

789
00:47:47,320 --> 00:47:51,720
Speaker 3: do we save them or do we prioritize someone who's

790
00:47:51,760 --> 00:47:56,560
Speaker 3: doing some really cool stuff with semiconductors over in Massachusetts?

791
00:47:56,760 --> 00:48:00,440
Speaker 3: You know what I mean? What choice we make? And

792
00:48:00,480 --> 00:48:02,640
Speaker 3: how do we phrase it as the greater good? In

793
00:48:02,719 --> 00:48:06,000
Speaker 3: just like one month after putting out the Safe Place

794
00:48:06,080 --> 00:48:13,200
Speaker 3: for Space applications, this university in France received some ballpark

795
00:48:13,360 --> 00:48:17,920
Speaker 3: three hundred applications from scientists. The vast majority We're American,

796
00:48:18,160 --> 00:48:22,720
Speaker 3: and they were seeking refugee status America's best and brightest.

797
00:48:23,200 --> 00:48:27,000
Speaker 3: We're officially in a world where science refugee has become

798
00:48:27,040 --> 00:48:27,399
Speaker 3: a thing.

799
00:48:28,600 --> 00:48:32,920
Speaker 2: I can't believe American science refugees.

800
00:48:33,880 --> 00:48:35,160
Speaker 3: You sounds like an album name.

801
00:48:36,000 --> 00:48:37,799
Speaker 2: You know, you may be finding us for the first

802
00:48:37,840 --> 00:48:39,719
Speaker 2: time right now, But if you go back in the

803
00:48:39,719 --> 00:48:41,880
Speaker 2: old archives and all the places you can find stuff

804
00:48:41,880 --> 00:48:44,480
Speaker 2: they don't want you to know, you'll find many an

805
00:48:44,520 --> 00:48:49,359
Speaker 2: episode about similar topics. One of those is the time

806
00:48:49,400 --> 00:48:54,880
Speaker 2: we covered Iranian scientists specializing in fissile materials. If you

807
00:48:54,960 --> 00:48:59,359
Speaker 2: get our meaning there, who kept dying And when you

808
00:48:59,400 --> 00:49:03,080
Speaker 2: imagine when we're talking about the stakes that are potentially

809
00:49:03,560 --> 00:49:08,600
Speaker 2: at play here for specific types of science work that's

810
00:49:08,640 --> 00:49:11,040
Speaker 2: being done, you could take your mind back to that,

811
00:49:11,120 --> 00:49:12,880
Speaker 2: because that's a real thing. You can look that up

812
00:49:12,920 --> 00:49:14,480
Speaker 2: if you want and go listen to our episode if

813
00:49:14,520 --> 00:49:18,879
Speaker 2: you want. There are there can be real stakes for

814
00:49:19,000 --> 00:49:21,960
Speaker 2: an individual attempting to escape a country.

815
00:49:22,239 --> 00:49:26,279
Speaker 3: Absolutely. Yeah, that's another part about brain draining, because sometimes

816
00:49:26,320 --> 00:49:30,480
Speaker 3: depending on the point in history or the regime you're

817
00:49:30,520 --> 00:49:35,440
Speaker 3: talking about, sometimes you can't leave. They won't let you go, right,

818
00:49:35,680 --> 00:49:38,920
Speaker 3: or they will let you go like aq con Folks

819
00:49:39,120 --> 00:49:43,200
Speaker 3: who was sent from check out the episode. You know,

820
00:49:43,320 --> 00:49:45,640
Speaker 3: write to us if you want, if you want full

821
00:49:45,719 --> 00:49:49,520
Speaker 3: sources examination of that. But yeah, a lot of scientists

822
00:49:49,600 --> 00:49:54,480
Speaker 3: are being treated as casualties in a greater war. Other

823
00:49:54,560 --> 00:49:59,759
Speaker 3: countries have similar programs for American science refugees, or they

824
00:49:59,760 --> 00:50:04,080
Speaker 3: play and to implement them. A guy named Epo Bruns

825
00:50:04,880 --> 00:50:08,680
Speaker 3: perfect name, sir, is the Minister of Education, Culture and

826
00:50:08,719 --> 00:50:12,960
Speaker 3: Science for the Netherlands, and he's been making a pretty

827
00:50:13,000 --> 00:50:18,879
Speaker 3: successful pitch to start the Netherlands version of the refugee

828
00:50:18,920 --> 00:50:22,399
Speaker 3: program right, and the Netherlands is pretty great if you've

829
00:50:22,440 --> 00:50:26,319
Speaker 3: ever been there. Can you imagine your sweating grants? One day,

830
00:50:26,600 --> 00:50:30,200
Speaker 3: you've got a hiring freeze, your advisor tells you your

831
00:50:30,320 --> 00:50:34,080
Speaker 3: work is amazing, but the government's not going to help you.

832
00:50:34,160 --> 00:50:37,480
Speaker 3: And then all of a sudden, some folks in Amsterdam

833
00:50:37,520 --> 00:50:38,879
Speaker 3: are like, hey, you want to hang out.

834
00:50:39,920 --> 00:50:41,160
Speaker 2: We think you're the best.

835
00:50:41,200 --> 00:50:43,680
Speaker 3: Actually, I think you're cool. Will also give you money.

836
00:50:43,840 --> 00:50:47,920
Speaker 3: Have you ever considered living on a canal? Yes?

837
00:50:48,280 --> 00:50:54,400
Speaker 4: And we haven't really mentioned the h one B visa situation.

838
00:50:54,719 --> 00:50:56,840
Speaker 4: Of it all. I just thought maybe we could briefly

839
00:50:56,880 --> 00:50:58,880
Speaker 4: touch on that, because we were talking a lot about

840
00:50:58,920 --> 00:51:02,040
Speaker 4: science and health care and that kind of research that

841
00:51:02,120 --> 00:51:04,400
Speaker 4: you know, really could help people in terms of quality

842
00:51:04,440 --> 00:51:06,000
Speaker 4: of life and things like that. But we of course

843
00:51:06,040 --> 00:51:09,760
Speaker 4: also have these giant tech corporations like Apple and Google

844
00:51:10,080 --> 00:51:14,400
Speaker 4: that rely a lot on skilled workers from abroad to

845
00:51:14,840 --> 00:51:19,279
Speaker 4: staff these positions. And with various changes in H one

846
00:51:19,560 --> 00:51:22,360
Speaker 4: B visas, which are of course worker visas that the

847
00:51:22,400 --> 00:51:27,640
Speaker 4: Trump administration has been putting forth, we're seeing folks from

848
00:51:27,680 --> 00:51:30,960
Speaker 4: these companies, leadership from these companies telling their workers that

849
00:51:31,000 --> 00:51:33,560
Speaker 4: they shouldn't leave the US. Well, things are in such

850
00:51:33,560 --> 00:51:37,359
Speaker 4: a sketchy sort of you know, tenuous position. We're talking

851
00:51:37,400 --> 00:51:40,400
Speaker 4: about them encouraging people who are in this country on

852
00:51:40,560 --> 00:51:42,839
Speaker 4: H one B visas not to go home and visit

853
00:51:42,880 --> 00:51:47,000
Speaker 4: by families lest they be rejected upon re entry, which.

854
00:51:46,800 --> 00:51:49,440
Speaker 3: Is a very real concern, you know, so much so

855
00:51:50,000 --> 00:51:53,680
Speaker 3: that there were folks who were traveling to India recently

856
00:51:53,719 --> 00:51:57,520
Speaker 3: earlier this year who got the news about the visa

857
00:51:57,600 --> 00:52:02,120
Speaker 3: controversy and then demanded that their play not leave with

858
00:52:02,239 --> 00:52:04,479
Speaker 3: them on it and said, look, I'm going to stay

859
00:52:04,520 --> 00:52:07,360
Speaker 3: in the United States. This is a frightening thing. H

860
00:52:07,440 --> 00:52:14,000
Speaker 3: one B visas essentially are for specialty, special career roles

861
00:52:14,200 --> 00:52:18,680
Speaker 3: that require a bachelor's degree or above, and there's an

862
00:52:18,719 --> 00:52:23,520
Speaker 3: annual cap of sixty five thousand. But then you can,

863
00:52:23,719 --> 00:52:25,520
Speaker 3: I mean, you can play with it a little bit

864
00:52:25,520 --> 00:52:28,200
Speaker 3: and get an additional twenty thousand. We're talking about a

865
00:52:28,239 --> 00:52:31,719
Speaker 3: lot of people who are doing good work, and I'll

866
00:52:31,719 --> 00:52:36,320
Speaker 3: say it, often underpaid, and now, through no fault of

867
00:52:36,360 --> 00:52:39,840
Speaker 3: their own, their lives are in danger. You know, this

868
00:52:40,040 --> 00:52:45,120
Speaker 3: is something that other countries. I can't say that it's

869
00:52:45,160 --> 00:52:48,840
Speaker 3: actually altruistic, folks, but this is something that other countries

870
00:52:48,840 --> 00:52:52,440
Speaker 3: have clocked and they're moving quickly to leverage it. They

871
00:52:52,480 --> 00:52:57,520
Speaker 3: are Chinese universities right now that are I don't want

872
00:52:57,520 --> 00:53:04,040
Speaker 3: to say targeting, but aggressively recruiting Chinese undergrads in other

873
00:53:04,120 --> 00:53:07,160
Speaker 3: countries and saying, hey, all right, you don't want to

874
00:53:07,200 --> 00:53:08,840
Speaker 3: do the game, you don't want to have to do

875
00:53:08,920 --> 00:53:12,000
Speaker 3: the whole dog and pony show and publish or parish

876
00:53:12,000 --> 00:53:15,759
Speaker 3: and all that crap. Come back home or just come

877
00:53:15,800 --> 00:53:19,560
Speaker 3: to China and we will enroll you directly in some

878
00:53:19,640 --> 00:53:24,759
Speaker 3: of our most prestigious PhD programs. Also, what is your

879
00:53:24,840 --> 00:53:29,480
Speaker 3: take on robotics. And I loved your paper about semiconductors.

880
00:53:29,920 --> 00:53:34,920
Speaker 2: Oh god, Chaus, let's let's talk about this thing. Because

881
00:53:34,960 --> 00:53:37,520
Speaker 2: even that all of that you're describing there, Ben, and

882
00:53:37,560 --> 00:53:41,400
Speaker 2: we talked about it before. The change in what is

883
00:53:41,440 --> 00:53:44,040
Speaker 2: it if you cut funding now? The change in like

884
00:53:44,080 --> 00:53:48,160
Speaker 2: the result of the future. While so a lot of

885
00:53:48,200 --> 00:53:54,560
Speaker 2: these large scale research studies and research experiments and projects

886
00:53:54,680 --> 00:53:57,160
Speaker 2: that go into effect, right, you get funding not just

887
00:53:57,200 --> 00:54:00,839
Speaker 2: for one semester or one year. You get you'll get

888
00:54:00,880 --> 00:54:05,080
Speaker 2: a large scale funding for you know, several years, for

889
00:54:05,120 --> 00:54:08,280
Speaker 2: a decade if depending on the types of projects, especially

890
00:54:08,320 --> 00:54:10,279
Speaker 2: if you're looking at things like climate that take a

891
00:54:10,320 --> 00:54:16,600
Speaker 2: long time to study, right or or large scale term yes, yes, okay.

892
00:54:16,640 --> 00:54:20,759
Speaker 2: Gen Xer is a great example. Funding that type of

893
00:54:20,840 --> 00:54:26,080
Speaker 2: research is such a future focused action, right, because you're

894
00:54:26,120 --> 00:54:29,879
Speaker 2: not you're not taking steps now to make profits, short

895
00:54:29,960 --> 00:54:33,840
Speaker 2: term profits even long term profits. Necessarily, you're taking steps

896
00:54:33,880 --> 00:54:38,440
Speaker 2: to to innovate and invent and change things. I guess

897
00:54:38,320 --> 00:54:41,439
Speaker 2: as as a future investment, right, but it is. It's

898
00:54:41,880 --> 00:54:45,600
Speaker 2: in order to in order to focus on the future

899
00:54:45,640 --> 00:54:48,600
Speaker 2: and imagine where you could go. That's why you put

900
00:54:48,600 --> 00:54:52,200
Speaker 2: funding in in the now. Yeah, and it just feels

901
00:54:52,239 --> 00:54:56,120
Speaker 2: to me like it feels to me like there there

902
00:54:56,160 --> 00:54:59,320
Speaker 2: are some people who are really looking at the short

903
00:54:59,400 --> 00:55:02,440
Speaker 2: term as the the only thing that's necessary to focus on.

904
00:55:03,160 --> 00:55:09,840
Speaker 3: Yeah, the issue is the issue is well known throughout history.

905
00:55:10,719 --> 00:55:14,000
Speaker 3: It reminds me of the old quotation that I think

906
00:55:14,000 --> 00:55:19,120
Speaker 3: we should all hear paraphrase. It is that civilization exists

907
00:55:19,760 --> 00:55:24,560
Speaker 3: when one generation plants a tree and they know that

908
00:55:24,600 --> 00:55:27,200
Speaker 3: they'll never sit under the shade, right, It's for the

909
00:55:27,239 --> 00:55:31,200
Speaker 3: next generation, you know. And that is something that is

910
00:55:31,280 --> 00:55:40,399
Speaker 3: increasingly forgotten right or glided over in our current instant gratification,

911
00:55:40,800 --> 00:55:45,520
Speaker 3: instant answer economy of attention. I mean also, in all

912
00:55:45,600 --> 00:55:48,480
Speaker 3: of these cases we have described so far, the reason

913
00:55:48,480 --> 00:55:51,480
Speaker 3: we're calling it like a paper clip light is because

914
00:55:51,760 --> 00:55:56,359
Speaker 3: the movement the great brain drain is technically consensual thing.

915
00:55:56,840 --> 00:56:00,319
Speaker 3: Most of these scientists are not being kidnapped by some

916
00:56:00,360 --> 00:56:04,600
Speaker 3: greater good nuclear non proliferation thing. In most cases, the

917
00:56:04,719 --> 00:56:08,120
Speaker 3: United States is not quote unquote kicking them out just yet.

918
00:56:08,360 --> 00:56:11,680
Speaker 3: These folks are choosing to move sort of, but they

919
00:56:11,719 --> 00:56:15,960
Speaker 3: feel their hands are tied because moving to a different country.

920
00:56:16,160 --> 00:56:19,080
Speaker 3: I know a lot of us watching or listening tonight,

921
00:56:19,120 --> 00:56:20,920
Speaker 3: I know, a lot of us have experienced this, so

922
00:56:21,040 --> 00:56:25,200
Speaker 3: you can confirm moving to a different country is pretty difficult,

923
00:56:25,480 --> 00:56:29,040
Speaker 3: even if you already speak the language. Right. Shout out

924
00:56:29,080 --> 00:56:30,480
Speaker 3: to a lot of people who said they were going

925
00:56:30,560 --> 00:56:33,480
Speaker 3: to move to Canada from the United States because of

926
00:56:33,560 --> 00:56:37,040
Speaker 3: some political stuff and then found out how difficult it

927
00:56:37,200 --> 00:56:39,040
Speaker 3: is to legally immigrate to Canada.

928
00:56:39,760 --> 00:56:41,640
Speaker 2: Yeah, I know. We just want to do the whole

929
00:56:41,680 --> 00:56:45,000
Speaker 2: winter festival thing. Remember we talked about that. There's a

930
00:56:45,040 --> 00:56:47,839
Speaker 2: big snowman guy up there and Quebec. We just want that.

931
00:56:47,880 --> 00:56:49,480
Speaker 4: I want to go to I'm gonna go to Montreal

932
00:56:49,560 --> 00:56:51,040
Speaker 4: for the first time real soon. I hope they let

933
00:56:51,040 --> 00:56:53,919
Speaker 4: me back in. I wanted to just dovetailor, like maybe

934
00:56:53,920 --> 00:56:55,319
Speaker 4: put a little bow on the thing I was saying

935
00:56:55,320 --> 00:56:57,440
Speaker 4: about H one B visas and a comment that I

936
00:56:57,480 --> 00:56:59,840
Speaker 4: made up top about how there's this sense of we

937
00:57:00,080 --> 00:57:02,759
Speaker 4: don't want these immigrants, but we do want these There

938
00:57:02,800 --> 00:57:06,520
Speaker 4: is some complexity in the President's perspective on H one

939
00:57:06,640 --> 00:57:11,400
Speaker 4: b's and on skilled workers in situations where it affects

940
00:57:12,040 --> 00:57:16,320
Speaker 4: commerce directly, you know, like chip manufacturers, for example. He

941
00:57:16,320 --> 00:57:18,080
Speaker 4: says that there's an article from Politico. I'm just going

942
00:57:18,120 --> 00:57:20,120
Speaker 4: to quote from He pointed to the multi billion dollar

943
00:57:20,120 --> 00:57:23,360
Speaker 4: expansion of chip production in Arizona, saying the company Taiwan

944
00:57:23,440 --> 00:57:27,720
Speaker 4: Semiconductor Manufacturing Company will bring in thousands of workers that

945
00:57:27,760 --> 00:57:31,440
Speaker 4: he will welcome those people. I love my conservative friends,

946
00:57:31,440 --> 00:57:33,920
Speaker 4: I love MAGA, but those people are going to teach

947
00:57:34,000 --> 00:57:36,840
Speaker 4: our people how to make computer chips, and in a

948
00:57:36,920 --> 00:57:39,520
Speaker 4: short period of time, our people are going to be

949
00:57:39,640 --> 00:57:43,160
Speaker 4: doing great. So I'm a little confused as to what

950
00:57:43,800 --> 00:57:46,840
Speaker 4: the real hard line is here, because it seems like

951
00:57:46,880 --> 00:57:50,240
Speaker 4: he was saying these things in a way where he

952
00:57:50,320 --> 00:57:51,720
Speaker 4: kind of had to hedge it a little because he

953
00:57:51,760 --> 00:57:55,040
Speaker 4: knows it's not a popular thing. But it does seem

954
00:57:55,080 --> 00:57:57,200
Speaker 4: like he's thinking about the bottom line of it all,

955
00:57:57,360 --> 00:57:59,880
Speaker 4: even though the bigger discussion is about this brain drain

956
00:58:00,120 --> 00:58:02,640
Speaker 4: and about these people turn and tail and going out

957
00:58:02,680 --> 00:58:05,520
Speaker 4: somewhere where they're more welcome or they have more opportunity.

958
00:58:05,680 --> 00:58:08,080
Speaker 4: Yet there does seem to be some discussion within the

959
00:58:08,120 --> 00:58:11,640
Speaker 4: Trump administration. But how can we attract skilled workers from

960
00:58:11,680 --> 00:58:12,280
Speaker 4: other countries?

961
00:58:13,120 --> 00:58:16,560
Speaker 3: Yeah, it's the question that all these countries have been

962
00:58:16,600 --> 00:58:20,400
Speaker 3: asking historically, even before modern nation states were a thing,

963
00:58:20,920 --> 00:58:25,320
Speaker 3: and earlier we said moving to a different country is

964
00:58:25,360 --> 00:58:28,120
Speaker 3: easier now than it has ever been at any point

965
00:58:28,120 --> 00:58:31,920
Speaker 3: in history. That is true, but it's still pretty difficult.

966
00:58:32,000 --> 00:58:35,200
Speaker 3: I'm looking at Australia, by the way, so any advice

967
00:58:35,320 --> 00:58:38,600
Speaker 3: is welcome. Folks, hit us up. You are even in

968
00:58:38,640 --> 00:58:44,320
Speaker 3: the best case of international movement, you are losing a community.

969
00:58:44,960 --> 00:58:47,680
Speaker 3: If you have kids, you're definitely throwing a plot twist

970
00:58:47,720 --> 00:58:51,160
Speaker 3: to your kid's childhood. You could also compromise your spouse

971
00:58:51,280 --> 00:58:54,880
Speaker 3: or your partner's career in the process. The good thing

972
00:58:54,960 --> 00:58:59,800
Speaker 3: is the scientific community is international. Right. If you are

973
00:59:00,120 --> 00:59:04,120
Speaker 3: one of twelve or twenty people who understand a thing,

974
00:59:04,720 --> 00:59:08,240
Speaker 3: guess what you know? The other eleven you know the

975
00:59:08,400 --> 00:59:12,160
Speaker 3: other nineteen people. They're the only ones who like get

976
00:59:12,200 --> 00:59:16,160
Speaker 3: you man. And so the scientific community has a lot

977
00:59:16,240 --> 00:59:21,240
Speaker 3: of brain drain folks aiming toward countries and institutions where

978
00:59:21,240 --> 00:59:25,120
Speaker 3: they already have friends, they already have colleagues, they already

979
00:59:25,120 --> 00:59:28,560
Speaker 3: have a previous worker publishing history. So this is not

980
00:59:28,640 --> 00:59:31,880
Speaker 3: the end of the world, but it is alarming. I

981
00:59:31,920 --> 00:59:33,720
Speaker 3: want to go back to a point we raised or

982
00:59:33,840 --> 00:59:38,160
Speaker 3: briefly touched on here. There are some bulwarks for the

983
00:59:38,160 --> 00:59:41,400
Speaker 3: great US brain drain. The United States in particular has

984
00:59:41,440 --> 00:59:44,360
Speaker 3: some of the best higher education on the planet. So

985
00:59:44,880 --> 00:59:48,960
Speaker 3: the presence of outfits like Harvard Mit at all, they

986
00:59:48,960 --> 00:59:52,480
Speaker 3: can stem the bleed a little bit. And we are

987
00:59:52,520 --> 00:59:54,520
Speaker 3: still you know, I get it, we're talking about a

988
00:59:54,560 --> 01:00:00,439
Speaker 3: relatively small slice of the country's population. But when these

989
01:00:00,480 --> 01:00:04,600
Speaker 3: folks move, just like in empires of old folks, they're

990
01:00:04,640 --> 01:00:08,240
Speaker 3: not just taking themselves and their families. They're taking the

991
01:00:08,360 --> 01:00:13,600
Speaker 3: knowledge that leads to new stuff like medicine, breakthroughs in astrophysics,

992
01:00:13,640 --> 01:00:16,600
Speaker 3: the next leg of the space race. I mean, heck,

993
01:00:16,720 --> 01:00:20,720
Speaker 3: even we might be losing new snack technology and I

994
01:00:20,760 --> 01:00:23,160
Speaker 3: take that personally flavor science man.

995
01:00:23,240 --> 01:00:24,000
Speaker 4: Yeah, we love it.

996
01:00:24,040 --> 01:00:26,480
Speaker 2: Well, we were also losing research studies that have been

997
01:00:26,480 --> 01:00:29,000
Speaker 2: going on for years, and you know, you take the

998
01:00:29,040 --> 01:00:31,920
Speaker 2: individuals out of there and that research is gone and

999
01:00:31,960 --> 01:00:34,240
Speaker 2: they're potentially taking it with them to some other place,

1000
01:00:34,440 --> 01:00:37,760
Speaker 2: or it's just it's not usable anymore. It's it's over.

1001
01:00:37,600 --> 01:00:40,640
Speaker 4: Talking about longitudinal studies that like involve the same people,

1002
01:00:40,880 --> 01:00:43,280
Speaker 4: like for a very very long generation, yes, period of time.

1003
01:00:43,360 --> 01:00:46,960
Speaker 2: Yes, and from places like UCLA. If you can head

1004
01:00:46,960 --> 01:00:48,959
Speaker 2: over to PBS News Hour and read a whole story

1005
01:00:49,000 --> 01:00:53,440
Speaker 2: about this guy, UCLA professor Terrence Tao and how he

1006
01:00:53,600 --> 01:00:56,840
Speaker 2: is really considering going back to Australia and he's having

1007
01:00:56,920 --> 01:00:59,240
Speaker 2: to consider that because funding is drying up for all

1008
01:00:59,320 --> 01:01:01,959
Speaker 2: the things that he's attempting to do, not just for him,

1009
01:01:02,360 --> 01:01:04,760
Speaker 2: but also for students that he's attempting to teach.

1010
01:01:05,440 --> 01:01:09,000
Speaker 3: Yeah, gave that out a little bit further, folks, also

1011
01:01:09,200 --> 01:01:12,280
Speaker 3: past the students for everyone on the planet.

1012
01:01:12,640 --> 01:01:15,880
Speaker 2: Yes, because it is more of a philosophical thing at

1013
01:01:15,960 --> 01:01:20,560
Speaker 2: stake here, a public good thing that is at stake here.

1014
01:01:20,600 --> 01:01:23,080
Speaker 2: And it's not about profits, It's not about any of

1015
01:01:23,080 --> 01:01:26,800
Speaker 2: the short term stuff. It's about how do we increase

1016
01:01:27,040 --> 01:01:30,400
Speaker 2: humanity's experience here for the good, Like how do we

1017
01:01:30,440 --> 01:01:34,120
Speaker 2: make things better for everybody, not just for people that

1018
01:01:34,200 --> 01:01:37,400
Speaker 2: are invested in some weapons manufacturer.

1019
01:01:37,440 --> 01:01:39,360
Speaker 4: And maybe just to remind everyone too. So then we

1020
01:01:39,400 --> 01:01:43,360
Speaker 4: mentioned at the top that this is not a big picture.

1021
01:01:43,640 --> 01:01:47,920
Speaker 4: The research will continue somewhere, you know, these contributions to

1022
01:01:48,080 --> 01:01:51,960
Speaker 4: the greater good, hopefully in theory, will continue and will

1023
01:01:52,160 --> 01:01:55,720
Speaker 4: still happen, and humanity will still benefit from them. They

1024
01:01:55,800 --> 01:01:58,000
Speaker 4: just might not be happening here.

1025
01:01:58,640 --> 01:02:02,920
Speaker 3: Right, And then I would argue that a lot of

1026
01:02:02,960 --> 01:02:07,200
Speaker 3: the technology or research post brain drain will make it

1027
01:02:07,240 --> 01:02:09,560
Speaker 3: back to the United States. But there's an important point

1028
01:02:09,640 --> 01:02:13,080
Speaker 3: to remember. It will arrive as a stranger. It will

1029
01:02:13,120 --> 01:02:15,920
Speaker 3: be in the form of an import and Uncle Sam

1030
01:02:16,440 --> 01:02:20,320
Speaker 3: to explore our capitalism. Think here, Uncle Sam, who once

1031
01:02:20,560 --> 01:02:25,240
Speaker 3: ran the general store, now becomes the customer. And at

1032
01:02:25,280 --> 01:02:29,640
Speaker 3: this level of trade and interaction and transmission of research

1033
01:02:29,680 --> 01:02:33,640
Speaker 3: and ideas, the customer is not always right. Instead, the

1034
01:02:33,720 --> 01:02:37,680
Speaker 3: customer is beholden now to the whims of foreign countries

1035
01:02:37,800 --> 01:02:39,920
Speaker 3: and foreign corporations.

1036
01:02:39,560 --> 01:02:40,880
Speaker 2: Including their tariffs.

1037
01:02:41,400 --> 01:02:45,680
Speaker 3: It is a bad look, and I guess this leads

1038
01:02:45,720 --> 01:02:49,160
Speaker 3: us to a different place. There's so much further that

1039
01:02:49,240 --> 01:02:52,800
Speaker 3: we could go with this conversation, but one of the

1040
01:02:52,880 --> 01:02:58,160
Speaker 3: best questions is why is this happening? What prompted these cuts?

1041
01:02:58,200 --> 01:03:01,360
Speaker 3: For critics of the current a minute stration, this is

1042
01:03:01,600 --> 01:03:04,920
Speaker 3: political theater. As we said, it's a cynical grift and

1043
01:03:05,040 --> 01:03:09,200
Speaker 3: it just happens to have unfortunately real consequences. Supporters, to

1044
01:03:09,240 --> 01:03:13,240
Speaker 3: be fair, argue it's a necessary move against government bloat.

1045
01:03:13,720 --> 01:03:17,120
Speaker 3: They're saying we've been handed out free money with little

1046
01:03:17,240 --> 01:03:20,560
Speaker 3: in the way of results. That last part is pretty

1047
01:03:20,640 --> 01:03:25,160
Speaker 3: easy to disprove. Actually, in about five minutes, you can

1048
01:03:25,240 --> 01:03:27,800
Speaker 3: go to your platform of choice and you can verify

1049
01:03:27,920 --> 01:03:31,200
Speaker 3: that this funding has, indeed, as we've been saying, made

1050
01:03:31,240 --> 01:03:34,800
Speaker 3: the world and the United States a better place. But

1051
01:03:34,960 --> 01:03:39,040
Speaker 3: the long tail effects of the great US brain drain,

1052
01:03:40,080 --> 01:03:42,560
Speaker 3: they're not going to be apparent to the average American

1053
01:03:42,760 --> 01:03:48,800
Speaker 3: until a lot of time has passed. You know, it's worrisome,

1054
01:03:49,600 --> 01:03:52,920
Speaker 3: there are conspiratorial thoughts of play, but it's happening. It

1055
01:03:53,040 --> 01:03:56,320
Speaker 3: is definitely happening. I think I mentioned to you guys,

1056
01:03:56,720 --> 01:03:59,960
Speaker 3: I got a little bit of a headhunt for research

1057
01:04:00,080 --> 01:04:02,000
Speaker 3: position I passed.

1058
01:04:03,080 --> 01:04:04,560
Speaker 2: Yeah, you got head hunted.

1059
01:04:04,800 --> 01:04:07,360
Speaker 4: Well, yeah, I mean it's it's not It's not unheard

1060
01:04:07,360 --> 01:04:09,520
Speaker 4: of for that to happen from time to time for

1061
01:04:09,560 --> 01:04:11,360
Speaker 4: any any of us in the company, or folks that

1062
01:04:11,360 --> 01:04:13,160
Speaker 4: are part of an industry that have been you know,

1063
01:04:13,240 --> 01:04:16,520
Speaker 4: around for a long time and that have that legacy expertise,

1064
01:04:16,880 --> 01:04:20,040
Speaker 4: because there are other companies and other countries that want

1065
01:04:20,080 --> 01:04:23,880
Speaker 4: to capitalize on that and benefit from that and potentially

1066
01:04:23,920 --> 01:04:27,000
Speaker 4: gain a leg up from their competition by you know,

1067
01:04:27,120 --> 01:04:30,400
Speaker 4: pulling those experts in those individuals away from that competition,

1068
01:04:30,440 --> 01:04:32,880
Speaker 4: whether that competition be another company or another country.

1069
01:04:33,920 --> 01:04:35,240
Speaker 3: I'm just a humble Farber.

1070
01:04:37,120 --> 01:04:41,000
Speaker 2: Congratulations been that's awesome. We would I'd love for you

1071
01:04:41,040 --> 01:04:43,000
Speaker 2: to hang around us if we can still do that,

1072
01:04:43,000 --> 01:04:43,680
Speaker 2: that'd be cool.

1073
01:04:44,720 --> 01:04:47,360
Speaker 3: Oh yeah, no, no, we passed. It was sketchy. It

1074
01:04:47,400 --> 01:04:50,439
Speaker 3: was it was a we're not going to talk about

1075
01:04:50,480 --> 01:04:50,880
Speaker 3: it out.

1076
01:04:50,720 --> 01:04:53,520
Speaker 2: Are well, let's let's let's continue down the sketchy path

1077
01:04:53,560 --> 01:04:56,160
Speaker 2: a little bit because something that just happened here in

1078
01:04:56,200 --> 01:04:59,280
Speaker 2: the US, and it happened with very little fanfare. There

1079
01:04:59,360 --> 01:05:01,600
Speaker 2: was a lot of others stuff happening in the news.

1080
01:05:02,040 --> 01:05:05,520
Speaker 2: The Jeffrey Epstein files kind of a little bit got

1081
01:05:05,560 --> 01:05:07,800
Speaker 2: trickled out. Yeah, kind of the means.

1082
01:05:07,520 --> 01:05:11,560
Speaker 4: Of priceless black black pages, just like what is that

1083
01:05:11,640 --> 01:05:13,240
Speaker 4: pantone color. It's fantastic.

1084
01:05:13,600 --> 01:05:15,480
Speaker 2: There's a lot more to cover there, and you will

1085
01:05:15,480 --> 01:05:17,760
Speaker 2: certainly see us on here talking about that very soon.

1086
01:05:18,200 --> 01:05:23,440
Speaker 2: But this thing, NDAA twenty six passed and it just occurred,

1087
01:05:24,080 --> 01:05:26,760
Speaker 2: and it was to the tune of nine hundred and

1088
01:05:26,880 --> 01:05:31,320
Speaker 2: one billion dollars for defense slash war spending here in

1089
01:05:31,360 --> 01:05:34,960
Speaker 2: the United States. And when you think about that in

1090
01:05:35,000 --> 01:05:38,200
Speaker 2: compared to the money that is being saved by research

1091
01:05:38,280 --> 01:05:42,000
Speaker 2: dollars going away and a lot of that funding, you

1092
01:05:42,040 --> 01:05:45,800
Speaker 2: can really see kind of the future, or at least

1093
01:05:45,800 --> 01:05:49,040
Speaker 2: the way the United States is posturing itself for the future,

1094
01:05:49,440 --> 01:05:51,760
Speaker 2: and you can see why. Just as we talked about

1095
01:05:51,840 --> 01:05:54,040
Speaker 2: the top of this episode, about Operation paper Clip and

1096
01:05:54,080 --> 01:05:56,280
Speaker 2: all these things where scientists are choosing to get out,

1097
01:05:56,600 --> 01:05:59,280
Speaker 2: there's writing that's already on the wall, right and that's

1098
01:05:59,320 --> 01:06:01,680
Speaker 2: sitting there and anybody who's paying attention can see it.

1099
01:06:02,280 --> 01:06:05,960
Speaker 2: So it is really it's important that we know this.

1100
01:06:06,000 --> 01:06:08,240
Speaker 2: We think about this, and I don't know is there

1101
01:06:08,240 --> 01:06:10,720
Speaker 2: anything any of us can do as we're just sitting

1102
01:06:10,760 --> 01:06:13,080
Speaker 2: here and imagining this if we're not a PhD student

1103
01:06:13,160 --> 01:06:14,360
Speaker 2: or a professor or something.

1104
01:06:14,720 --> 01:06:18,720
Speaker 3: Yeah, love to hear your answers on this, folks. Again,

1105
01:06:18,800 --> 01:06:22,200
Speaker 3: the big question. Okay, it's definitely happening. The brain drain

1106
01:06:22,560 --> 01:06:26,880
Speaker 3: is definitely occurring and probably will continue. But why and

1107
01:06:27,040 --> 01:06:31,640
Speaker 3: what happens next? What is the role the average person

1108
01:06:32,040 --> 01:06:35,840
Speaker 3: could do to mitigate this. We'd love to hear, especially

1109
01:06:35,880 --> 01:06:40,040
Speaker 3: from our friends in academia or in research positions. How

1110
01:06:40,080 --> 01:06:43,520
Speaker 3: has this affected you? What do you see next? And

1111
01:06:44,080 --> 01:06:47,680
Speaker 3: again I keep going back to this, why why do

1112
01:06:47,720 --> 01:06:51,080
Speaker 3: these cuts in the first place? That for now is

1113
01:06:51,120 --> 01:06:54,880
Speaker 3: the stuff they don't want you to know. Let's continue

1114
01:06:54,960 --> 01:06:58,000
Speaker 3: the conversation, folks. We'd love to hear from you. You

1115
01:06:58,040 --> 01:07:00,200
Speaker 3: can give us a phone call. You can always please

1116
01:07:00,280 --> 01:07:05,160
Speaker 3: send us an email with anything you want ed. You

1117
01:07:05,200 --> 01:07:08,440
Speaker 3: can find us on the lines and sip those social medis.

1118
01:07:08,880 --> 01:07:10,600
Speaker 4: That's right. You can find this on most of the

1119
01:07:10,600 --> 01:07:13,960
Speaker 4: social media platforms of note at the handle conspiracy Stuff,

1120
01:07:13,960 --> 01:07:16,080
Speaker 4: and that includes Facebook with our Facebook group Here's where

1121
01:07:16,160 --> 01:07:19,479
Speaker 4: It's Crazy, XFKA, Twitter and YouTube where we have video

1122
01:07:19,720 --> 01:07:23,960
Speaker 4: clips galore for your enjoyment. On Instagram and TikTok. However,

1123
01:07:24,040 --> 01:07:25,720
Speaker 4: we're conspiracy Stuff show.

1124
01:07:26,720 --> 01:07:29,080
Speaker 2: Hey, we have a phone number. It's a voicemail system.

1125
01:07:29,120 --> 01:07:30,960
Speaker 2: You can call it with your phone right now if

1126
01:07:31,000 --> 01:07:35,800
Speaker 2: you want to. It is one eight three three std WYTK.

1127
01:07:36,160 --> 01:07:38,960
Speaker 2: Turn those letters into numbers. Then you'll be on your way.

1128
01:07:39,000 --> 01:07:41,360
Speaker 2: You've got three minutes. Give yourself a cool nickname and

1129
01:07:41,440 --> 01:07:42,840
Speaker 2: let us know if we can use your name and

1130
01:07:42,840 --> 01:07:46,840
Speaker 2: message on the air. You'll find that on our audio podcast.

1131
01:07:47,200 --> 01:07:48,920
Speaker 2: If you want to send us an email, you can

1132
01:07:48,960 --> 01:07:49,400
Speaker 2: do that too.

1133
01:07:49,560 --> 01:07:50,600
Speaker 4: We are the.

1134
01:07:50,720 --> 01:07:53,880
Speaker 3: Entities the read each piece of correspondence we receive. Be

1135
01:07:54,000 --> 01:07:59,000
Speaker 3: well aware, yet unafraid. Sometimes the void rights back. Now

1136
01:07:59,320 --> 01:08:01,920
Speaker 3: pick up your phone if your phone is nearby, folks,

1137
01:08:01,960 --> 01:08:07,800
Speaker 3: and play a little game with US conspiracy at iHeartRadio

1138
01:08:08,280 --> 01:08:12,120
Speaker 3: dot com. Write to us now right now. No you specifically,

1139
01:08:12,160 --> 01:08:14,760
Speaker 3: you do it. I don't care what they're saying. Do it.

1140
01:08:33,680 --> 01:08:35,719
Speaker 2: Stuff they don't want you to know. Is a production

1141
01:08:35,840 --> 01:08:40,360
Speaker 2: of iHeartRadio. For more podcasts from iHeartRadio, visit the iHeartRadio app,

1142
01:08:40,439 --> 01:08:43,320
Speaker 2: Apple Podcasts, or wherever you listen to your favorite shows.