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Speaker 1: learn more and buy your tickets today at New York

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Speaker 1: Comic Con dot com slash NYCC hyphen presents Welcome to

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Speaker 1: Stuff to Blow Your Mind from How Stuff Works dot com.

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Speaker 1: Hey you welcome to Stuff to Blow Your Mind. My

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Speaker 1: name is Robert Lamb, and I'm Christian Seger, and I'm

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Speaker 1: Joe McCormick. And hey, it is time for another listener

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Speaker 1: Maile episode. It's been a while since we did one, right, guys, Yeah,

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Speaker 1: it's been a while since Carney has come out of

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Speaker 1: his layer to greet us. With various bits of listener

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Speaker 1: mail from our our our listeners all over the world.

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Speaker 1: Carney's has some life changes recently, though, right guys, Well,

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Speaker 1: Carney I believe has a crush Carney the mail Bot,

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Speaker 1: of course, if you're not familiar, Formerly Arnie the mail Bot.

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Speaker 1: With the addition of Cartesian doubt, we became Carney. And

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Speaker 1: now I think he has learned to love because I've

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Speaker 1: seen him writing the name of another machine here in

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Speaker 1: the office, if y'all, if you'll notice, I noticed somebody

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Speaker 1: etched a serial number really long, went into the wall

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Speaker 1: with a saw of some sort. That would be Carney.

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Speaker 1: I get a big heart around it, Honestly, I try

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Speaker 1: to stay out of the whole thing. They both tried

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Speaker 1: to get me into a room to mitigate the whole

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Speaker 1: situation the other day, and I just you know, I'm

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Speaker 1: busy to a podcast. Sorry, Carney, you don't want to

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Speaker 1: get into machine politics. Well, maybe by the end of

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Speaker 1: today's episode he and the coffee machine can work it out.

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Speaker 1: I hope so, I hope so. But for now he

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Speaker 1: needs to do his job, that's right, and that is

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Speaker 1: to spit out listener mail for us. And it's and

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Speaker 1: we need a note here that we receive a great

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Speaker 1: deal of listener mail. We we get it in on

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Speaker 1: the email, we get it through the various social media accounts.

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Speaker 1: We get it lots of cool feedback on the discussion

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Speaker 1: module our group on Facebook. These are all tremendous ways

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Speaker 1: to get in touch with us. Occasionally, even some snail

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Speaker 1: mail comes in, but not a lot. Uh, no reason

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Speaker 1: you should stop. Actually do some stuff from Twitter this time.

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Speaker 1: Oh yeah, cool, I know we see stuff on tumbler

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Speaker 1: even so. The bottom line is we receive a great

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Speaker 1: deal of cool stuff. We try to respond to to

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Speaker 1: a lot of it, but there's a lot that we

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Speaker 1: can't even you know, we don't have time to respond to.

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Speaker 1: But we do like to have Carney bring us some

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Speaker 1: choice bits of listener mail so that we can read

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Speaker 1: them on the air and and discuss the questions. The

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Speaker 1: answers are just sort of basking, you know, the the

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Speaker 1: glory of the moment. Well, time is precious, so let's

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Speaker 1: get right into it. I can see he's spitting one

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Speaker 1: out right now. All right, what's it look like? This

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Speaker 1: came in on the discussion module that group on Facebook

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Speaker 1: that we were talking about that all of you are

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Speaker 1: welcome to to join in on uh. Darwin writes in

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Speaker 1: and says you mentioned on the podcast last week that

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Speaker 1: perhaps the living in a simulation trope might someday replace

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Speaker 1: the alien abduction narrative. Last week on BBC's Infinite Monkey Cage,

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Speaker 1: Brian Cox, this is the the younger scientists, Brian Cox,

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Speaker 1: This isn't the classic character actoran not Manhunter anyway, Cox

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Speaker 1: and his panel discussed this very topic, even submitting that

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Speaker 1: such a belief bordered on the same leap of faith

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Speaker 1: that is required for religious beliefs. I think it is fascinating,

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Speaker 1: even though I doubt that you would be able to

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Speaker 1: create certain physical phenomena as we observe them using digital methods,

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Speaker 1: the problem of pseudo random versus truly random physical events.

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Speaker 1: Of course, maybe with highly advanced technology is required to

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Speaker 1: recreate a universe such limitations and uh maybe surmountable. It

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Speaker 1: is endlessly fascinating topic and I would love to hear

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Speaker 1: you guys weigh in on it at some point. Well.

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Speaker 1: Speaking of Cartesian doubt, this is actually a good point

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Speaker 1: for it, because we talked about this during the Mandela

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Speaker 1: Effect episode. This is where I believe this This came up,

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Speaker 1: and then you guys also did it in a what

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Speaker 1: was Your Computer Simulated? Episode? Was that the created universe

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Speaker 1: is one yes. In the episode where we talked about

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Speaker 1: creating a universe in the lab, we also talked about

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Speaker 1: the idea of creating a universe and a computer simulation

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Speaker 1: and how you could know that. I'm skeptical about this idea.

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Speaker 1: I voiced some of my skepticism in that episode, and

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Speaker 1: we actually got some replies about that. We several people

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Speaker 1: send us really interesting emails about that. I'm going to

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Speaker 1: try to read at least one of those today. And

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Speaker 1: Darwin here mentions the alien abduction episode, and yeah, in

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Speaker 1: that one, we were talking about this, this trope of

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Speaker 1: of alien abduction being the narrative that you draw in

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Speaker 1: when trying to make sense of some sort of you know,

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Speaker 1: paranormal sensory experience, and to what degree we might replace

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Speaker 1: that in the future with something like the idea that

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Speaker 1: our reality is a computer simulation, Like, at what point

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Speaker 1: would there be a tipping point at which this would

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Speaker 1: become the default or one of the default narratives for

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Speaker 1: some people understanding what happened? Syndia being that like the

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Speaker 1: matrix would sort of replace alien abduction as these the

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Speaker 1: narrative of explanation for these things that we have no

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Speaker 1: scientific explanation for. Well, wait a minute, then what is

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Speaker 1: the experience narrative there? So if an alien abduction, it's

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Speaker 1: you know, there's certain patterns of like I woke up,

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Speaker 1: I was in a room surrounded by beings, I was

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Speaker 1: taken up into another place, X, Y, and Z happened

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Speaker 1: to me. What what's the simulated universe version of that? Well, Joe,

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Speaker 1: I was. I was coming back from from the joint

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Speaker 1: uptown a few nights back, and suddenly everything got a

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Speaker 1: little flashy, and the next thing I knew, these uh,

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Speaker 1: these people were come infor me. I think what had

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Speaker 1: happened is that I had I had glitched out of

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Speaker 1: the computer simulation for a moment. The anti virus software

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Speaker 1: is on your case, Yeah, they're on my case. I

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Speaker 1: think I might have flopped out of the future tank

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Speaker 1: that I'm that my actual body is positioned in. So

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Speaker 1: they put me back in and they've done something to

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Speaker 1: my memory. But I did get to see through the

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Speaker 1: veil and see through the computer simulation that we all

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Speaker 1: buy into every day. This is an actual argument that

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Speaker 1: a few people have have proposed as an explanation for

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Speaker 1: the Mandela effect, that we exist within a kind of

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Speaker 1: like hollow deck simulation, and that when the Mandela effect

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Speaker 1: is observed by people, it's because there's some glitch in

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Speaker 1: the software. We do not buy it. Our episode strongly

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Speaker 1: argues that the Mandela effect is just a false memory

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Speaker 1: and false memory shared false memory. The amazing part about

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Speaker 1: it is what it reveals about the inner working of memory. Well, yeah,

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Speaker 1: didn't we get at least one email from someone who

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Speaker 1: is fairly angry arguing that it's more likely that we

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Speaker 1: live in parallel universes or a glitchy simulation then that

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Speaker 1: people misremember things. I thought that was just you, you're

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Speaker 1: trolling Probert and me, but it maybe it was a

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Speaker 1: real person. I don't know. I think it's kind of

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Speaker 1: likely that people really often misremember things. Well, yeah, I

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Speaker 1: think that we make a strong case for that, and

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Speaker 1: it's it's connected to the alien abduction episode two. We've

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Speaker 1: had kind of like a false memory theme going for

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Speaker 1: the last month. Okay, well, I've got at least one

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Speaker 1: more email about the idea of living in a computer simulation.

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Speaker 1: I mentioned that we this came up in our episode

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Speaker 1: about how to create a universe in the Lab. Now,

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Speaker 1: a lot of that episode was on the physics idea.

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Speaker 1: It was that we talked about one book in particular,

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Speaker 1: but the work of cosmologists like Alan Gooth over the

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Speaker 1: years about how it might hypothetically be possible. It seems

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Speaker 1: like kind of a stretch, but there are plausible physical

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Speaker 1: hypotheses about how you might be able to do an

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Speaker 1: experiment in high energy particle collider that could create a

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Speaker 1: universe in the lab. But we also talked about the

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Speaker 1: idea of creating a universe as a simulation on software,

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Speaker 1: and I talked about multiple reasons I don't think this

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Speaker 1: is likely that our universe is a simulation. Uh number one,

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Speaker 1: It would just require so much energy to simulate a

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Speaker 1: realistic universe. Why is that something that we think future

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Speaker 1: civilizations would spend their limited resources on. Well, well, because

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Speaker 1: well yeah, but also a lot of people spend their

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Speaker 1: limited resources now on simulated worlds. You just you have

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Speaker 1: to extrapolate it to like a global economy where just batteries, man,

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Speaker 1: I mean, they're just taking our energy right back. Just

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Speaker 1: thinking about the information density of simulating an actual world

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Speaker 1: with actual physics that works. I mean, one of the

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Speaker 1: problems is you can do science experiments and the laws

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Speaker 1: of physics always seem to hold. So that means at

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Speaker 1: some level they're simulating everything all the way down. It's

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Speaker 1: not just like a low res simulation with some kind

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Speaker 1: of put together sprites. At the higher level, they're simulating

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Speaker 1: every physical interaction of every atom and molecule. Well, that

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Speaker 1: just seems like that would be so energy intensive, it's ridiculous.

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Speaker 1: So I'm gonna I'm just playing defl's advocate here. I

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Speaker 1: agree with you, But like I immediately think of like

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Speaker 1: rag doll physics in like the video games I play,

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Speaker 1: like like sky Rim or Fallout or something like that. Right, right,

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Speaker 1: that's a very limited version of what you're talking about,

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Speaker 1: which are just orders of magnitude simpler than simulating real physics.

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Speaker 1: And what I was saying is the easiest way to

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Speaker 1: simulate real physics would just be to have a real universe. Well,

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Speaker 1: one of the things that we brought up in that episode,

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Speaker 1: I think was was the issue of mirrors and video games.

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Speaker 1: If you see a working mirror in a video game,

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Speaker 1: you're probably you're seeing a great deal of work place

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Speaker 1: and all, and some of the times you're actually seeing

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Speaker 1: some trickery to you know, to because there's no light

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Speaker 1: in a video game. You don't have photons in a

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Speaker 1: video game. But to have this kind of simulation that

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Speaker 1: Joe is talking about, you would need to have that.

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Speaker 1: I had another objection to the idea of that, that

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Speaker 1: we're living in a simulated universe, and it went sort

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Speaker 1: of like this, Um, if we are living in a

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Speaker 1: simulated universe that perfectly mirrors a real universe, we should

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Speaker 1: be able to create a simulated universe within our simulated universe,

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Speaker 1: and then within the created simulated universe, they should be

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Speaker 1: able to create a universe within the simulated universe. If

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Speaker 1: this is all running on hardware that is upstream of

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Speaker 1: the simulations that go all the way down, you'd eventually

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Speaker 1: reach a sort of peak information density that the hardware

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Speaker 1: at the top could no longer sustain. And that's where

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Speaker 1: this next email comes in. So this comes from our

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Speaker 1: listener Jared, who says, Hi, guys, love the show. I

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Speaker 1: was listening to your Out of Chaos podcast and had

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Speaker 1: a few thoughts pertaining to the computational requirements of complex

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Speaker 1: simulation UM and he calls the section relative relativity of

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Speaker 1: our programmer God's time. I work on virtually prototyping satellite

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Speaker 1: imaging systems by simulating photo realistic imagery, taking into account

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Speaker 1: the physics of the imaging system and the lights interaction

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Speaker 1: with the observed scene. Now I can do a pretty

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Speaker 1: darn good job simulating imagery with any computer. It just

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Speaker 1: takes longer given a less powerful computer. Maybe the being

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Speaker 1: simulating us have a lot more time, so an hour

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Speaker 1: in their time is a second in hours, Or they

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Speaker 1: have us turn off for the night and start us

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Speaker 1: back up in the morning for maintenance. My simulations don't

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Speaker 1: notice any or my temporal discontinuity. Also, now the beings

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Speaker 1: want to create a simulation inside their simulation, sure, but

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Speaker 1: they have finite computing power too, so it will go

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Speaker 1: extremely slow relative to the original programmer gods, and the

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Speaker 1: embedded simulations will asymptotically approach some constant computational requirement. I

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Speaker 1: thought that was really interesting, but he goes on. Another

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Speaker 1: solution is to give your world some natural equalizer, like

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Speaker 1: an ego. I'd argue the past three years, as humans

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Speaker 1: have gotten way more computationally complex, the loss of biodiversity

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Speaker 1: has made the earth as a whole way less computationally complex.

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Speaker 1: Someday we'll have some computationally tricky doomsday device which will

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Speaker 1: solve its own computational problem. Uh. And then he goes

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Speaker 1: on to just say some very nice things about our

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Speaker 1: show and and all that, and we appreciate the flattery,

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Speaker 1: but really especially appreciate these ideas. I think I'm not

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Speaker 1: convinced by them that we do live in a computer simulation,

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Speaker 1: but I think that is a reasonable objection to my

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Speaker 1: time of computation and information density objection. I have another

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Speaker 1: one too. They just came to mind hearing just just

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Speaker 1: just a spring off of this fantastic response, is that

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Speaker 1: you know, we we can. We can easily think of

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Speaker 1: like a whole world simulation and all the inherent problems there,

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Speaker 1: a multi user situation and all the problems there. But

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Speaker 1: how about this. The next time you're in a small windowless,

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Speaker 1: mirror less bathroom, I think, what if this is the

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Speaker 1: simulation and it began basically the moment I walked in here. Yes,

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Speaker 1: like this is when the simulation kicked on. Everything else

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Speaker 1: is just you know, false memory essentially, and the simul

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Speaker 1: nation is going to end when I flush the toilet.

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Speaker 1: It's it's kind of like if you're filming a TV

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Speaker 1: series and you don't have a lot of money for

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Speaker 1: an episode to do what a bottle episode? Right? So

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Speaker 1: that's maybe that's how the our far future selves are

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Speaker 1: dealing with this, Like we can't actually recreate the twenty

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Speaker 1: one century, but let's just do a bathroom scene because

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Speaker 1: bathrooms from the twenty one century were pretty cool, and

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Speaker 1: that will immerse the single user in that world, and

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Speaker 1: giving the entire world full of people false memories actually

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Speaker 1: would help, because this goes right along with what y'all

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Speaker 1: were saying about the failures of memory related to the

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Speaker 1: Mandela effect. Memory is very low resolution compared to reality.

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Speaker 1: It's incredibly low resolution. It's you know, so you It

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Speaker 1: would not be all that computationally difficult to supply somebody

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Speaker 1: with the vague kind of memories people actually have, but

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Speaker 1: they have the illusion that their memories are vivid. This

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Speaker 1: may explain why sometimes when I go into the bathroom,

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Speaker 1: I imagine what life would be like if I was

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Speaker 1: stuck in there forever, Like like how would I sleep

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Speaker 1: on the floor? Would I drink water from the sink?

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Speaker 1: Would I bathe? In the toilet, et cetera. I would say,

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Speaker 1: next time you are in a work meeting that seems

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Speaker 1: to go on forever, you should contemplate the possibility that

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Speaker 1: the universe actually began at the beginning of this meeting,

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Speaker 1: and the rest of your life up until this point

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Speaker 1: is just an inserted false memory at low resolution to

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Speaker 1: justify you listening to this pitch about how you're going

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Speaker 1: to optimize your new whatever your seo. Dude. Yeah, and

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Speaker 1: then then you get to snap back into it and

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Speaker 1: try and remember what the person was telling you. Sounds good.

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Speaker 1: All right? We got another one related to uh, I

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Speaker 1: think Carney's hand in one do you Oh hey, oh

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Speaker 1: this is sharp okay. Oh, this is one about our

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Speaker 1: samurai swords episode. Oh no, wonder okay. So this is

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Speaker 1: from Steve and he says, enjoyed your program on Japanese

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Speaker 1: katana swords. Thanks. I think the development that you skipped

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Speaker 1: over was the reintroduction of swords as standard equipment for

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Speaker 1: officers and sergeants during the period just before World War Two.

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Speaker 1: Most of these individuals were not samurai class and did

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Speaker 1: not own swords, so mass produced pieces were issued to them.

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Speaker 1: These so called showato were distinguished by minuki of three

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Speaker 1: imperial chrysanthemums rather than the traditional heraldic manuki of older swords.

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Speaker 1: Most were destroyed during the occupation, but many survive. So

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Speaker 1: what Steve's referring to here is a study that we

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Speaker 1: looked at during our Samurai Swords episode that took a

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Speaker 1: sword that was recovered from presumably some battle during World

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Speaker 1: War Two, so this was the nineteen forties. The U.

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Speaker 1: S Army commissioned a metallurgical composition composition study of the

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Speaker 1: sword to determine how it was smith and they found

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Speaker 1: that the sword that they had recovered was actually significantly

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Speaker 1: lower in quality than they had been led to believe

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Speaker 1: from the history of sword smith things specifically for katanas,

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Speaker 1: like if I remember correctly, like the carbon composition was

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Speaker 1: off by percentages, the angle of the sword wasn't right way,

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Speaker 1: things like that. So it seems like Steve is telling

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Speaker 1: us here why that's the case. They had this entire

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Speaker 1: other line of swords that were made specifically for the

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Speaker 1: Big War. That's interesting. Yeah, that did not come up

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Speaker 1: in in our episode, but that adds a little more

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Speaker 1: background to what they were observing here. Yeah, and so

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Speaker 1: like let's let's try to apply this to a fictional example. Okay,

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Speaker 1: so we talked about kill Bill in the Samura Swords

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Speaker 1: episode when uh the Bride is fighting the Crazy eighty

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Speaker 1: eight with her like super awesome samurai sword that is

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Speaker 1: is smithed in the very traditional way, so it's both

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Speaker 1: sharp and flexible and has a has a solid core. Right,

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Speaker 1: she's able to cut in half. Other warriors swords from

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Speaker 1: the Crazy eight eighty eight attack her. So maybe they've

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Speaker 1: got these mass manufactured showato swords, but she's got the

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Speaker 1: real deal. She's got hottri Hanzo steel. Crazy eight eight

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Speaker 1: should have really paid more attention to their true gear,

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Speaker 1: but it's probably exactly. Yeah, each sword is priceless, so

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Speaker 1: that's priceless times eight. Yeah. And I guess the argument

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Speaker 1: too is it's like, if you're whaling on someone with

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Speaker 1: the A eight Samurai swords, they don't they really don't

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Speaker 1: even need to be sharp. They can you don't even

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Speaker 1: take to take them out of the sheath. Yep. But

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Speaker 1: thank you, Steve, I really appreciate that that clarifies that

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Speaker 1: way we assumed, I think in that episode that there

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Speaker 1: was something along those lines that probably like late uh,

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Speaker 1: nineteenth century and early twenty century katanas were not of

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Speaker 1: the same Make all right, We're gonna take a quick

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Speaker 1: break and when we come back, we will get some

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Speaker 1: more listener mail from Carney and share it with the

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Speaker 1: rest of you. All Right, we're back. We have a

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Speaker 1: little bit of listener mail here dealing with the episode

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Speaker 1: that Joe and I recorded, The buddhais a Mountain, which

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Speaker 1: was a pretty pretty fun episode about the Lashawn Buddha,

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Speaker 1: the giant Buddha uh at one of fines in China,

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Speaker 1: this enormous humanoid structure that has been carved into the

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Speaker 1: mountain itself, lording over the river below, kind of like

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Speaker 1: Stone Mountain here in Georgia. Well we we do. I

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Speaker 1: think Stone Mountain came up in that. Actually, that was

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Speaker 1: a very interest less racist Well that this was a

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Speaker 1: very interesting episode because it did come out ahead of

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Speaker 1: a lot of the a lot of the political discussions

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Speaker 1: have been going on regarding monuments and statues here in

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Speaker 1: the United States. Yeah, I guess I didn't even think

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Speaker 1: about that really, but maybe we did get a little

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Speaker 1: listener mail about that. But yeah, we talked in the

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Speaker 1: episode about the idea of statuary being a type of

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Speaker 1: depiction that inherently carries like a like a moral valence

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Speaker 1: to it. It's like if you were to have a

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Speaker 1: photograph of somebody or have well maybe not a photograph,

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Speaker 1: I don't know, But if you like write a book

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Speaker 1: about somebody, it's not assumed that you think that person

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Speaker 1: was a good person. You might write a book about

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Speaker 1: a serial killer or a horrible dictator. But if you

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Speaker 1: put up a statue of a person, it is just

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Speaker 1: part of our cultural uh language, that that is a

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Speaker 1: thing of honor. You never put up a statue of

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Speaker 1: somebody you don't like. Yeah, you know, we I think

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Speaker 1: we we barely if it all discussed Confederate monuments in

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Speaker 1: that episode, because again it was before it really picked

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Speaker 1: up as a topic here. But I do encourage anyone

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Speaker 1: out there who's interested in that topic to listen to

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Speaker 1: that episode because it's kind of an interesting way to

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Speaker 1: think about it about a controversial topic free of the actual, um,

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Speaker 1: you know, current events. But the bit of listener, may

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Speaker 1: I'm gonna read here doesn't concern anything happening here in America.

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Speaker 1: It concerns something happening in China and concerns some of

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Speaker 1: the local accounts of the Leshan Buddha. We heard from

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Speaker 1: a listener by the name of Danny. He's an American

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Speaker 1: with a with a company in Shandu, and they he

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Speaker 1: has his staff listen to our podcast to improve their English.

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Speaker 1: Oh no, sorry, sorry staff, No no, he says. He says,

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Speaker 1: they get a lot of a lot of great stuff

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Speaker 1: out of it, out of it and they enjoy They

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Speaker 1: really enjoyed the episode. Uh, since it related to something

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Speaker 1: local to uh. So he said that he had they

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Speaker 1: had no corrections aside from the fact that, uh, the

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Speaker 1: mountain itself it is you may Shawn Shawn mining mountains,

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Speaker 1: so you you may mountain if you will. But then

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Speaker 1: he he went on to share some various tidbits from

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Speaker 1: a local inhabitants about basically bits of folklore related to

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Speaker 1: the Lashan Buddha. Uh. And he he adds that we

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Speaker 1: don't actually believe any of these points, but a lot

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Speaker 1: of sexilantees do, and they are relatively well known things

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Speaker 1: that are said of the Buddha. Um. He said. They

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Speaker 1: also give a little insight into how even modern day

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Speaker 1: Chinese mythology bends up the line between the animate and

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Speaker 1: the inanimate. So I'm just gonna run through these. I

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Speaker 1: found these tremendously fascinating. Apparently the Buddhist facial expression changes

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Speaker 1: in reaction to tragic events in China. First, he points

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Speaker 1: to the lashaan Giant Buddha closed tears event. That's that's

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Speaker 1: a translation from Chinese, where apparently the Buddha closed his

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Speaker 1: eyes and shed tears for all the lost souls as

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Speaker 1: a result of the nineteen fifty nine through sixty one famine,

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Speaker 1: which killed between fifteen and thirty million people. Uh. He

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Speaker 1: says the Buddha was seen to look very angry in

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Speaker 1: nineteen seventy six, in the year when mal Zadong died.

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Speaker 1: In the same year, the same year that Tangshan earthquake

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Speaker 1: killed thousands of people, says, the Buddha also apparently expresses

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Speaker 1: joy or pride for China as well. His head started

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Speaker 1: to glow with a pulsating light in the year two thousand,

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Speaker 1: when China joined the w t O and made the

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Speaker 1: bid to host the two thousand eight to Beijing Olympic Games.

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Speaker 1: Another one that they found this kind of a random

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Speaker 1: thing that they found on the internet in Chinese. He

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Speaker 1: points to an event that supposedly happened on May seventh,

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Speaker 1: two thousand two, in the morning when there's suddenly there

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Speaker 1: were dark clouds around the Buddha and suddenly there appeared

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Speaker 1: at a halo like phenomenon. The rising sun flashed around

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Speaker 1: the statue with a diameter of about three creating a

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Speaker 1: colorful halo of light. He says. In two thousand eight,

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Speaker 1: after the earthquake, the Buddha was seen crying. Uh. It

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Speaker 1: says this one a lot of people believe, and there

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Speaker 1: are even pictures online. So this is kind of like

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Speaker 1: when we get um like like stigmata effects on like

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Speaker 1: statues or something like that. Or I'm thinking also of like, um,

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Speaker 1: have you guys ever heard of like manifestations of Jesus

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Speaker 1: and like everyday objects. When I was living in a

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Speaker 1: Massachusetts there was one of these that happened in I

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Speaker 1: think it was Malden, Massachusetts, and uh, it was in

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Speaker 1: a Catholic hospital window. There was like a manifestation that

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Speaker 1: looked like it was Jesus, but it was like some

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Speaker 1: kind of smoke damage or something to the window. Well,

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Speaker 1: I said, I would definitely say that with Lashawn Buddha.

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Speaker 1: Given the irrigation system that's worked out around it. I

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Speaker 1: mean it would make sense that it would appear to

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Speaker 1: weep certain sometimes. Uh. He also points out he says, quote,

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Speaker 1: it's often said that there is also a treasure built

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Speaker 1: into the statue behind his heart, ears and eyes. No

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Speaker 1: one can tell me what the treasure is supposed to be,

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Speaker 1: but I would not be all too surprised if something

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Speaker 1: was there because of the mystical powers that Chinese myth

430
00:23:21,200 --> 00:23:24,200
Speaker 1: gives to many minerals, such as Jade's ability to transcend

431
00:23:24,200 --> 00:23:26,840
Speaker 1: the realm of the living sometimes something I think you

432
00:23:26,840 --> 00:23:29,159
Speaker 1: guys have covered before in a previous episode. Yeah, we

433
00:23:29,200 --> 00:23:31,399
Speaker 1: talked about that in the Jade Burial Suit episode. We

434
00:23:31,480 --> 00:23:34,359
Speaker 1: sure did. So. I love these tidbits. They really they

435
00:23:34,400 --> 00:23:36,640
Speaker 1: really had to add a little more depth than a little,

436
00:23:36,640 --> 00:23:40,560
Speaker 1: you know, local intel to our episode. And I had

437
00:23:40,600 --> 00:23:42,880
Speaker 1: to read this one too. After he shared the following,

438
00:23:43,200 --> 00:23:45,680
Speaker 1: Please feel free to read any of this on the podcast,

439
00:23:45,800 --> 00:23:48,320
Speaker 1: in whole or in part, including my name. If you do,

440
00:23:48,720 --> 00:23:50,880
Speaker 1: I will take the whole company out for a day

441
00:23:50,920 --> 00:23:53,240
Speaker 1: to go visit the Buddha and we will bring you

442
00:23:53,280 --> 00:23:57,359
Speaker 1: back some pictures. Awesome. Yeah, do it so? Yeah? I

443
00:23:57,400 --> 00:24:00,320
Speaker 1: want to see some pictures. Yeah, it's always great, because

444
00:24:00,359 --> 00:24:03,760
Speaker 1: you know, we can sit here in in Atlanta, Georgia

445
00:24:03,880 --> 00:24:07,399
Speaker 1: and do research until our eyes bleed and pull up

446
00:24:07,400 --> 00:24:09,159
Speaker 1: a bunch of facts and then present them to you

447
00:24:09,280 --> 00:24:13,000
Speaker 1: the audience. But if you're actually physically close to some

448
00:24:13,040 --> 00:24:15,320
Speaker 1: of these things, like academ Gora doc, we received a

449
00:24:15,320 --> 00:24:18,600
Speaker 1: bunch of mail from people who who have visited there before.

450
00:24:19,000 --> 00:24:21,480
Speaker 1: You know, it's it's especially helpful for us to hear

451
00:24:21,520 --> 00:24:24,040
Speaker 1: these firsthand accounts. All right, what do you have next

452
00:24:24,040 --> 00:24:27,040
Speaker 1: for us there, Karney? So we got one coming in

453
00:24:27,080 --> 00:24:30,320
Speaker 1: from Allison about science communication. This is going back to

454
00:24:30,359 --> 00:24:33,439
Speaker 1: our episode about science communication from after Robert went to

455
00:24:33,480 --> 00:24:36,080
Speaker 1: the World Science Festival in New York. Oh, yes, science

456
00:24:36,080 --> 00:24:39,359
Speaker 1: communication breakdown. Wait is that a led Zeppelin reference? I

457
00:24:39,359 --> 00:24:42,000
Speaker 1: think it may have been an accidental led Zeppelin reference.

458
00:24:42,359 --> 00:24:47,000
Speaker 1: Communication breakdown, but that was what the episode was about, like,

459
00:24:47,080 --> 00:24:50,520
Speaker 1: you know, breakdowns in the communication of science and scientific

460
00:24:50,960 --> 00:24:54,280
Speaker 1: news scientific topics to yeah public, especially as it relates

461
00:24:54,320 --> 00:24:58,760
Speaker 1: to climate change. Uh, let's see what else vaccines? Yeah,

462
00:24:58,840 --> 00:25:00,399
Speaker 1: I mean a lot of it was related into the

463
00:25:00,440 --> 00:25:05,560
Speaker 1: idea that people are not necessarily convinced by facts and evidence,

464
00:25:05,640 --> 00:25:08,840
Speaker 1: that there's a lot of psychology about what actually causes

465
00:25:08,880 --> 00:25:12,679
Speaker 1: people to make their minds up about controversial issues, and

466
00:25:12,840 --> 00:25:17,119
Speaker 1: that it's there's a lot of social aspects and cultural

467
00:25:17,160 --> 00:25:20,679
Speaker 1: identity wrapped up, and how we take sides on issues

468
00:25:20,720 --> 00:25:23,680
Speaker 1: that there appears to be some controversy about, and about

469
00:25:23,720 --> 00:25:26,760
Speaker 1: how how we can deal with that in science communication.

470
00:25:27,160 --> 00:25:31,080
Speaker 1: But anyway, Allison has a fantastic question and something we

471
00:25:31,119 --> 00:25:34,840
Speaker 1: actually deal with a good bit, i'd say, She says, Hi, guys,

472
00:25:35,000 --> 00:25:36,920
Speaker 1: I've enjoyed your show for a long time, but only

473
00:25:36,960 --> 00:25:39,159
Speaker 1: recently had a good excuse to send an email. You

474
00:25:39,240 --> 00:25:42,440
Speaker 1: recently did an episode on the science communication breakdown, and

475
00:25:42,480 --> 00:25:45,280
Speaker 1: I was wondering if in your research you came across

476
00:25:45,320 --> 00:25:48,680
Speaker 1: any good idea or theories about how science communicators should

477
00:25:48,680 --> 00:25:53,680
Speaker 1: address the way that scientific facts change as our understanding evolves.

478
00:25:53,760 --> 00:25:57,280
Speaker 1: For example, for a very long time, nutritional scientists have

479
00:25:57,400 --> 00:26:00,359
Speaker 1: pushed the idea that carbohydrates are a good energy source

480
00:26:00,440 --> 00:26:03,360
Speaker 1: for humans, while fat was associated with a bunch of

481
00:26:03,440 --> 00:26:08,159
Speaker 1: different health problems. Recently, though, our understanding of nutritional science

482
00:26:08,160 --> 00:26:11,239
Speaker 1: has begun to change. Perhaps fat won't kill you, and

483
00:26:11,240 --> 00:26:14,359
Speaker 1: perhaps carbs are more detrimental to health than anybody wanted

484
00:26:14,400 --> 00:26:17,320
Speaker 1: to admit. I've seen a lot of people express a

485
00:26:17,320 --> 00:26:20,520
Speaker 1: sense of betrayal over this reversal of sentiments. How are

486
00:26:20,560 --> 00:26:23,399
Speaker 1: you supposed to trust anything these scientists say? They wonder

487
00:26:23,680 --> 00:26:25,680
Speaker 1: if a few decades down the line, they're going to

488
00:26:25,800 --> 00:26:28,440
Speaker 1: do a one eight on their position? How are science

489
00:26:28,440 --> 00:26:31,600
Speaker 1: communicators supposed to convince the public to walk back from

490
00:26:31,600 --> 00:26:36,680
Speaker 1: positions they have long been considered solid theory? Also, she says,

491
00:26:37,040 --> 00:26:40,040
Speaker 1: if you guys haven't done an episode on ketosis, I'd

492
00:26:40,040 --> 00:26:41,640
Speaker 1: love to hear your take on it. I've been living

493
00:26:41,640 --> 00:26:43,639
Speaker 1: on fewer than twenty grams of carbs a day for

494
00:26:43,680 --> 00:26:47,120
Speaker 1: two years, contrary to what the dietitians tell me, I've

495
00:26:47,160 --> 00:26:51,359
Speaker 1: never felt better. Thanks so much for your educational entertainment, Allison.

496
00:26:51,840 --> 00:26:55,280
Speaker 1: So what she's talking about here reminds me of this

497
00:26:55,400 --> 00:26:58,240
Speaker 1: Lewis Black bit that you guys have probably heard before,

498
00:26:58,280 --> 00:27:00,840
Speaker 1: and I've even referenced it on the show before, where

499
00:27:00,880 --> 00:27:03,159
Speaker 1: he's like, So, when I was growing up, there were

500
00:27:03,160 --> 00:27:05,800
Speaker 1: these studies and they said milk is good for you.

501
00:27:05,800 --> 00:27:07,760
Speaker 1: You gotta drink milk. Drink milk. And then all of

502
00:27:07,760 --> 00:27:09,399
Speaker 1: a sudden there are studies and they said milk is

503
00:27:09,440 --> 00:27:11,440
Speaker 1: bad for you. Don't drink so much milk. You gotta

504
00:27:11,600 --> 00:27:13,399
Speaker 1: take the fat out of the milk, right, And then

505
00:27:13,440 --> 00:27:15,199
Speaker 1: all of a sudden it turns around again, milk is

506
00:27:15,200 --> 00:27:18,280
Speaker 1: good for you. Right. So these science studies seem to

507
00:27:18,320 --> 00:27:20,960
Speaker 1: contradict one another back and forth, and this is essentially

508
00:27:20,960 --> 00:27:23,159
Speaker 1: what she's getting at. Yeah, so I actually have several

509
00:27:23,160 --> 00:27:25,919
Speaker 1: thoughts about this, one of the one of them is

510
00:27:26,000 --> 00:27:30,200
Speaker 1: that this is partially an artifact of problems in science

511
00:27:30,200 --> 00:27:34,000
Speaker 1: communication more so than science itself, though there are problems

512
00:27:34,040 --> 00:27:37,080
Speaker 1: with some aspects of the science. So a lot of

513
00:27:37,080 --> 00:27:39,080
Speaker 1: times what will happen is there will be a new

514
00:27:39,119 --> 00:27:44,160
Speaker 1: study that says, on lab rats, we found that if

515
00:27:44,240 --> 00:27:48,080
Speaker 1: you give them this extremely high dosage of milk proteins

516
00:27:48,160 --> 00:27:51,720
Speaker 1: over this many months, they have a sixty percent higher

517
00:27:51,840 --> 00:27:55,080
Speaker 1: chance of having this effect than if you don't. And

518
00:27:55,280 --> 00:27:58,520
Speaker 1: so then the people who are running like newspapers are

519
00:27:58,560 --> 00:28:00,240
Speaker 1: doing the nightly news. I guess if this back in

520
00:28:00,280 --> 00:28:03,560
Speaker 1: the nineties or the eighties or whatever, would say scientists

521
00:28:03,600 --> 00:28:06,080
Speaker 1: have discovered that milk will give you cancer. It is

522
00:28:06,119 --> 00:28:11,200
Speaker 1: bad for you. Uh, And so they take this highly nuanced,

523
00:28:11,280 --> 00:28:15,200
Speaker 1: kind of subtle effect that's been demonstrated in one experiment

524
00:28:15,560 --> 00:28:20,800
Speaker 1: and turn that into an incredibly simple pronounced statement about

525
00:28:20,800 --> 00:28:22,840
Speaker 1: what is good for you or what is bad for you,

526
00:28:23,280 --> 00:28:25,919
Speaker 1: not really noting that maybe the effect was subtle, that

527
00:28:26,000 --> 00:28:29,320
Speaker 1: the experiment was done on a certain number of animals

528
00:28:29,320 --> 00:28:31,919
Speaker 1: that weren't even humans, you know, stuff like this. Let

529
00:28:31,960 --> 00:28:34,520
Speaker 1: me see if I can try to reverse engineer this too,

530
00:28:34,560 --> 00:28:37,639
Speaker 1: from like a media literacy standpoint, because I think even

531
00:28:37,680 --> 00:28:39,720
Speaker 1: for some members of our audience who might actually be

532
00:28:39,800 --> 00:28:43,600
Speaker 1: scientists themselves, they don't uh necessarily know how that information

533
00:28:43,640 --> 00:28:47,400
Speaker 1: comes to us science communicators in the media. Right. So

534
00:28:47,680 --> 00:28:51,240
Speaker 1: for instance, we get these press releases and it will say, uh,

535
00:28:51,560 --> 00:28:54,440
Speaker 1: what was her example, Well, she brings up a fat

536
00:28:54,560 --> 00:28:57,160
Speaker 1: versus carbs and the health effects there, Right, So we'll

537
00:28:57,200 --> 00:28:59,600
Speaker 1: get a press release and it will say that and

538
00:29:00,120 --> 00:29:01,960
Speaker 1: will have a link where you can go and you

539
00:29:02,000 --> 00:29:05,800
Speaker 1: can read the full twenty page report. But sometimes just

540
00:29:05,920 --> 00:29:09,880
Speaker 1: behind the paywall, yeah exactly. And sometimes your organization doesn't

541
00:29:09,920 --> 00:29:12,959
Speaker 1: supply you with you know, the access to the databases

542
00:29:12,960 --> 00:29:14,840
Speaker 1: behind these paywalls. Sometimes you have to go to the

543
00:29:14,840 --> 00:29:18,240
Speaker 1: researchers home, yes, or call them right, yeah, And not

544
00:29:18,520 --> 00:29:21,240
Speaker 1: every journalist is actually going to do the work to

545
00:29:21,280 --> 00:29:25,120
Speaker 1: go get primary resources, especially in this era of mass

546
00:29:25,200 --> 00:29:29,280
Speaker 1: content creation, right, so usually what ends up happening is

547
00:29:29,800 --> 00:29:32,120
Speaker 1: they just grab the information right out of the press release,

548
00:29:32,560 --> 00:29:34,840
Speaker 1: rewrite it a little bit, and focus on that one

549
00:29:34,920 --> 00:29:39,360
Speaker 1: thesis statement. Right. What doesn't happen is they don't look

550
00:29:39,480 --> 00:29:43,560
Speaker 1: at the literature review inside the actual paper that sets

551
00:29:43,720 --> 00:29:46,880
Speaker 1: up the study, within the context of all the other

552
00:29:46,920 --> 00:29:50,040
Speaker 1: studies that are done on this topic. Right. Another problem

553
00:29:50,160 --> 00:29:53,600
Speaker 1: is that within the world of journalism, especially on the Internet,

554
00:29:53,640 --> 00:29:55,480
Speaker 1: but it was probably true on TV and stuff like

555
00:29:55,480 --> 00:30:00,560
Speaker 1: that too, that there's very little incentive to accurately unicate

556
00:30:01,080 --> 00:30:05,080
Speaker 1: the subtleties and the nuances of scientific results, put everything

557
00:30:05,080 --> 00:30:08,720
Speaker 1: in context, communicate, you know, some caveats that that it

558
00:30:08,800 --> 00:30:11,000
Speaker 1: might not be as clear cut as it first seemed

559
00:30:11,040 --> 00:30:13,960
Speaker 1: from your headline, because what people want to click on

560
00:30:14,080 --> 00:30:16,920
Speaker 1: is something that says, I have the new answer for you.

561
00:30:17,280 --> 00:30:19,880
Speaker 1: Milk is going to kill you. You will never believe

562
00:30:20,080 --> 00:30:22,840
Speaker 1: this fact about milk, you know. And here's the other

563
00:30:22,880 --> 00:30:25,880
Speaker 1: thing too, is that so we have that we have

564
00:30:26,080 --> 00:30:29,400
Speaker 1: the the journalist, we have the scientists, but then of

565
00:30:29,440 --> 00:30:31,720
Speaker 1: course we also have a consumer in and I can't

566
00:30:31,760 --> 00:30:34,040
Speaker 1: help but think about what we know all the all

567
00:30:34,040 --> 00:30:37,480
Speaker 1: that we've been talking about with false NT memories, and misattribution,

568
00:30:37,920 --> 00:30:40,880
Speaker 1: as well as just the the idea that once a

569
00:30:40,920 --> 00:30:44,200
Speaker 1: particular narrative gets out there, take lose black pri instance. Now,

570
00:30:44,240 --> 00:30:45,520
Speaker 1: I know it's a bit, so I don't I don't

571
00:30:45,520 --> 00:30:48,520
Speaker 1: really mean to dissect a comedic bit too much. But

572
00:30:50,200 --> 00:30:53,160
Speaker 1: in this example, like, did was he actually like reading

573
00:30:53,200 --> 00:30:54,920
Speaker 1: a lot of literature about milk or is it just

574
00:30:55,040 --> 00:30:57,160
Speaker 1: in the background of his mind he picks up on

575
00:30:57,160 --> 00:31:00,320
Speaker 1: this narrative that milk is is good, and then it's ad.

576
00:31:00,960 --> 00:31:04,040
Speaker 1: I think he's specifically talking about seeing headlines on either

577
00:31:04,360 --> 00:31:08,600
Speaker 1: nightly cable news or in a newspaper. So on one level,

578
00:31:08,640 --> 00:31:11,400
Speaker 1: it's it's to what degree a certain bit of research

579
00:31:11,480 --> 00:31:13,480
Speaker 1: makes a splash and the headlines, and then to what

580
00:31:13,560 --> 00:31:16,600
Speaker 1: extent it's picked up on and and and sticks with

581
00:31:16,680 --> 00:31:19,880
Speaker 1: the individual. Again, the low resolution of your memory is

582
00:31:19,920 --> 00:31:22,760
Speaker 1: contributing to this. I can't help but be reminded of

583
00:31:22,800 --> 00:31:26,280
Speaker 1: the episode we did on Only Children and the psychology

584
00:31:26,280 --> 00:31:29,240
Speaker 1: behind it, and the fact that you had one you know,

585
00:31:29,400 --> 00:31:33,240
Speaker 1: decades and decades old though in like the late nineteenth century, Yeah,

586
00:31:33,240 --> 00:31:38,760
Speaker 1: but basically over a century old, this horrible psychological methodology, Yeah,

587
00:31:39,160 --> 00:31:43,240
Speaker 1: making the case that that only children were monsters. And

588
00:31:43,600 --> 00:31:46,320
Speaker 1: plenty of studies have come along, just one after the other,

589
00:31:46,720 --> 00:31:49,880
Speaker 1: disproving that and showing that only children are not monster,

590
00:31:49,920 --> 00:31:54,400
Speaker 1: they're not lonely, they're not you know, craven or spoiled, etcetera.

591
00:31:55,000 --> 00:31:58,840
Speaker 1: But we keep sticking to this previously established narrative just

592
00:31:58,840 --> 00:32:01,680
Speaker 1: because it made such a media splash and nothing after

593
00:32:01,760 --> 00:32:04,840
Speaker 1: that was able to achieve as much residence. And because

594
00:32:04,880 --> 00:32:07,640
Speaker 1: it's easy to remember, You've got to think, like the

595
00:32:07,680 --> 00:32:12,000
Speaker 1: access theory of memory, that things that are simple statements

596
00:32:12,040 --> 00:32:14,120
Speaker 1: that are easy to remember are going to have much

597
00:32:14,160 --> 00:32:18,480
Speaker 1: more purchase in your memory than things that are complicated

598
00:32:18,520 --> 00:32:22,200
Speaker 1: and nuanced and hard to explain and have some conflicting results,

599
00:32:22,200 --> 00:32:23,400
Speaker 1: and that you've got to put it in a lot

600
00:32:23,400 --> 00:32:26,440
Speaker 1: of context. So yeah, that's one thing. Part of this

601
00:32:26,520 --> 00:32:29,800
Speaker 1: is an artifact of how science journalism gets done. Part

602
00:32:29,800 --> 00:32:32,600
Speaker 1: of it is an artifact of our low resolution memories.

603
00:32:32,600 --> 00:32:34,120
Speaker 1: But there's another thing that has to do with the

604
00:32:34,120 --> 00:32:38,280
Speaker 1: science itself, which is that some subjects are as it

605
00:32:38,360 --> 00:32:42,719
Speaker 1: stands today, more unstable than others regarding the scientific consensus.

606
00:32:43,240 --> 00:32:47,080
Speaker 1: And if you read scientific literature critically, you can usually

607
00:32:47,120 --> 00:32:50,720
Speaker 1: start to get a sense of which subject areas are

608
00:32:50,760 --> 00:32:54,600
Speaker 1: producing more solid, dependable results in which ones are still

609
00:32:54,680 --> 00:32:59,640
Speaker 1: mired in some kind of legitimate controversy. Experimental design plays

610
00:32:59,640 --> 00:33:02,800
Speaker 1: a big role in this. Nutrition is a classic example

611
00:33:02,800 --> 00:33:06,920
Speaker 1: of an area that can be extremely difficult to properly control.

612
00:33:07,040 --> 00:33:10,160
Speaker 1: Experiments like studies need to take place over a long

613
00:33:10,240 --> 00:33:13,280
Speaker 1: period of time to see long term effects. They often

614
00:33:13,320 --> 00:33:16,480
Speaker 1: rely on people to accurately report what they eat. You

615
00:33:16,520 --> 00:33:19,160
Speaker 1: can kind of imagine what some problems with that might

616
00:33:19,200 --> 00:33:22,080
Speaker 1: be um and add that to the fact that that

617
00:33:22,120 --> 00:33:24,280
Speaker 1: there have been a lot of financial interest in the

618
00:33:24,320 --> 00:33:27,400
Speaker 1: production of certain results in nutrition science. So a lot

619
00:33:27,440 --> 00:33:29,400
Speaker 1: of the stuff you might have heard in the history

620
00:33:29,400 --> 00:33:33,520
Speaker 1: of science isn't necessarily being done by some independently funded

621
00:33:33,920 --> 00:33:37,600
Speaker 1: university experiment, but it's done by some research group that's

622
00:33:37,640 --> 00:33:41,000
Speaker 1: funded by the sugar industry, and what do you know,

623
00:33:41,160 --> 00:33:43,240
Speaker 1: they find out that fats are bad for you and

624
00:33:43,280 --> 00:33:46,239
Speaker 1: sugar is good. We actually have a one of my

625
00:33:46,320 --> 00:33:48,720
Speaker 1: favorite things that's ever been done at How Stuff Works,

626
00:33:48,760 --> 00:33:51,720
Speaker 1: was created by one of our video producers, Paul Decan,

627
00:33:52,240 --> 00:33:54,920
Speaker 1: and it is a in depth look at the sugar

628
00:33:54,960 --> 00:33:59,640
Speaker 1: industry's influence on academic papers about the nutritional effects of

629
00:33:59,640 --> 00:34:03,160
Speaker 1: sugar over the last like fifty years, so, so there

630
00:34:03,200 --> 00:34:05,360
Speaker 1: are a lot of things to take into consideration. Some

631
00:34:05,400 --> 00:34:08,680
Speaker 1: subject areas are just they're just swampy, or than others

632
00:34:08,680 --> 00:34:11,279
Speaker 1: they've got more problems. I mean, you'll notice that in

633
00:34:11,640 --> 00:34:16,280
Speaker 1: I don't know, uh, you know, very like material science areas,

634
00:34:16,360 --> 00:34:18,480
Speaker 1: there's just not going to be a lot of controversy

635
00:34:18,520 --> 00:34:21,839
Speaker 1: about whether this new alloy is actually as strong as

636
00:34:21,880 --> 00:34:24,520
Speaker 1: they say it is um, but there might be if

637
00:34:24,560 --> 00:34:26,800
Speaker 1: there's somebody who's got a financial interest in it and

638
00:34:26,840 --> 00:34:31,399
Speaker 1: they're publishing the you know, in studies that they've funded. Anyway,

639
00:34:31,200 --> 00:34:34,080
Speaker 1: I think it's an excellent question you ask Allison. It's

640
00:34:34,080 --> 00:34:36,880
Speaker 1: something that we wrestle with all the time, and and

641
00:34:36,960 --> 00:34:39,799
Speaker 1: the answer is difficult. There's no silver bullet on how

642
00:34:39,840 --> 00:34:42,279
Speaker 1: to fix this. I think it has to do with

643
00:34:42,360 --> 00:34:46,640
Speaker 1: helping people understand the complexities of science and understand the

644
00:34:46,719 --> 00:34:50,319
Speaker 1: meta complexity of how other people come to believe in

645
00:34:50,360 --> 00:34:53,520
Speaker 1: the ideas about scientific consensus and where they get their

646
00:34:53,520 --> 00:34:56,960
Speaker 1: impressions about what scientists say. Yeah, I mean, I guess

647
00:34:56,960 --> 00:35:00,279
Speaker 1: like this is a difficult problem to solve of but

648
00:35:00,360 --> 00:35:02,719
Speaker 1: I think like two steps that could be taken to

649
00:35:02,840 --> 00:35:05,840
Speaker 1: help it, which probably, let's be honest, won't happen in

650
00:35:05,840 --> 00:35:09,600
Speaker 1: the near future. Are that media organizations need to be

651
00:35:09,680 --> 00:35:14,239
Speaker 1: more thorough in their research and their depiction of these studies.

652
00:35:14,560 --> 00:35:18,040
Speaker 1: But then also the consumers themselves need to have media

653
00:35:18,120 --> 00:35:22,319
Speaker 1: literacy skills that they can rely on to understand these

654
00:35:22,320 --> 00:35:25,359
Speaker 1: studies better, or to look at multiple sources and kind

655
00:35:25,400 --> 00:35:29,000
Speaker 1: of triangulate what's actually going on here? All right, what

656
00:35:28,960 --> 00:35:31,359
Speaker 1: it looks like Carney is coming at you, Christian with

657
00:35:31,520 --> 00:35:33,759
Speaker 1: another piece of listener mail. What what's he got there

658
00:35:33,800 --> 00:35:36,120
Speaker 1: for you? Well, this one is great. This is actually

659
00:35:36,320 --> 00:35:39,760
Speaker 1: a letter from a listener named Lindsay telling us about

660
00:35:39,800 --> 00:35:44,000
Speaker 1: her personal alien abduction experience based on our two alien

661
00:35:44,000 --> 00:35:48,360
Speaker 1: abduction episodes. Lindsay says, when I was growing up, about

662
00:35:48,400 --> 00:35:50,880
Speaker 1: ten years old, I had a clubhouse outside of my

663
00:35:51,000 --> 00:35:54,000
Speaker 1: house and would camp out and sleep inside of it

664
00:35:54,080 --> 00:35:57,920
Speaker 1: on some summer nights. It was sturdy and constructed by hand,

665
00:35:58,400 --> 00:36:01,759
Speaker 1: lofted on wooden posts acted as stilts, about eight feet

666
00:36:01,760 --> 00:36:04,360
Speaker 1: off the ground. One night, I climbed up the ladder

667
00:36:04,400 --> 00:36:06,960
Speaker 1: with my sleeping bag, pulled up the ladder so nothing

668
00:36:06,960 --> 00:36:09,239
Speaker 1: else could come up. I read some comic books and

669
00:36:09,280 --> 00:36:11,320
Speaker 1: fell asleep. This is, by the way, like my ideal

670
00:36:11,360 --> 00:36:14,720
Speaker 1: way to go to bed. Lindsay. The clubhouse had one

671
00:36:14,840 --> 00:36:18,279
Speaker 1: side of double paned windows, one side that had a

672
00:36:18,320 --> 00:36:21,320
Speaker 1: doorless doorway through which you could see my neighbor's yard,

673
00:36:21,640 --> 00:36:25,760
Speaker 1: and the other two were solid wood walls. I slept

674
00:36:25,960 --> 00:36:28,799
Speaker 1: facing out the doorway. I woke up in the middle

675
00:36:28,840 --> 00:36:30,960
Speaker 1: of the night one night and was frozen in fear

676
00:36:31,040 --> 00:36:33,799
Speaker 1: because in my neighbor's yard I saw a saucer about

677
00:36:33,840 --> 00:36:37,760
Speaker 1: the size of an average circular above ground pool, hovering

678
00:36:37,840 --> 00:36:41,200
Speaker 1: over their yard, absolutely still about a hundred feet into

679
00:36:41,239 --> 00:36:45,080
Speaker 1: the air. It was large and very cinematically stereotypical, a

680
00:36:45,160 --> 00:36:48,680
Speaker 1: green glow metallic saucer, a beam coming down from the saucer,

681
00:36:48,760 --> 00:36:51,480
Speaker 1: that sort of thing. I couldn't see anything inside of

682
00:36:51,520 --> 00:36:54,800
Speaker 1: it because it was oriented above me. I sat still,

683
00:36:55,080 --> 00:36:58,960
Speaker 1: thinking that whatever was inside could possibly sense movement, and

684
00:36:59,000 --> 00:37:01,880
Speaker 1: I felt like I was having trouble breathing. It was

685
00:37:01,880 --> 00:37:04,080
Speaker 1: silent at first, and then I started to hear something

686
00:37:04,080 --> 00:37:06,920
Speaker 1: that was difficult to describe. It was quiet, but in

687
00:37:06,920 --> 00:37:10,319
Speaker 1: a way that felt loud and overwhelming. I could hear

688
00:37:10,360 --> 00:37:12,560
Speaker 1: a ring in my ears, and I think it felt

689
00:37:12,600 --> 00:37:15,480
Speaker 1: louder than it was because the world was quiet, but

690
00:37:15,520 --> 00:37:19,440
Speaker 1: the inside of my head, wasn't. I remember being terrified,

691
00:37:19,520 --> 00:37:21,640
Speaker 1: but not that I was going to be hurt, just

692
00:37:21,719 --> 00:37:24,440
Speaker 1: that I didn't know what was going to happen. I

693
00:37:24,480 --> 00:37:26,920
Speaker 1: believe I forced myself to close my eyes, thinking that

694
00:37:27,000 --> 00:37:29,759
Speaker 1: maybe the saucer couldn't move while I was looking at it,

695
00:37:29,920 --> 00:37:31,920
Speaker 1: and I either fell asleep or I woke up again

696
00:37:32,080 --> 00:37:34,680
Speaker 1: and it was gone. I didn't tell anybody because the

697
00:37:34,719 --> 00:37:37,960
Speaker 1: whole situation felt fishy to me, and while I believe

698
00:37:38,000 --> 00:37:41,279
Speaker 1: in aliens, I don't believe we've had any contact with them,

699
00:37:41,360 --> 00:37:45,280
Speaker 1: nor they with us. Years later, after keeping better track

700
00:37:45,320 --> 00:37:48,800
Speaker 1: of my sleep habits and dreams, I learned about sleep

701
00:37:48,840 --> 00:37:51,920
Speaker 1: paralysis and had experienced it a couple of other times

702
00:37:51,920 --> 00:37:54,920
Speaker 1: throughout high school. When i'd wake up with it in

703
00:37:55,000 --> 00:37:57,560
Speaker 1: my room, I could hear something that sounded like tribal

704
00:37:57,600 --> 00:38:00,680
Speaker 1: percussion from the living room, though nobody you was in there,

705
00:38:00,920 --> 00:38:03,000
Speaker 1: and I could see that the lights were not on.

706
00:38:03,480 --> 00:38:06,960
Speaker 1: In these moments, it was the scariest that I couldn't move.

707
00:38:07,080 --> 00:38:09,640
Speaker 1: It felt the same way an arm does when you

708
00:38:09,680 --> 00:38:11,279
Speaker 1: wake up in the middle of the night with your

709
00:38:11,360 --> 00:38:14,160
Speaker 1: arm behind you and you need to use your other

710
00:38:14,320 --> 00:38:16,319
Speaker 1: arm to pick it up and put it back to

711
00:38:16,360 --> 00:38:19,399
Speaker 1: get the blood flowing again. The difference is that none

712
00:38:19,440 --> 00:38:21,640
Speaker 1: of your body parts are able to move the other

713
00:38:21,680 --> 00:38:24,440
Speaker 1: ones back into place or shake them out. Though I

714
00:38:24,520 --> 00:38:30,279
Speaker 1: never again had visual hallucinations from sleep paralysis, only auditory sensations,

715
00:38:30,600 --> 00:38:33,719
Speaker 1: I am thoroughly convinced that what I experienced with the

716
00:38:33,760 --> 00:38:38,000
Speaker 1: saucer in my neighbor's yard was indeed sleep paralysis. Being

717
00:38:38,080 --> 00:38:42,640
Speaker 1: frozen in fear was probably physically being frozen and unable

718
00:38:42,680 --> 00:38:45,280
Speaker 1: to move due to this. And it all went away

719
00:38:45,480 --> 00:38:48,480
Speaker 1: when I went back to sleep and somehow broke the cycle.

720
00:38:49,480 --> 00:38:51,719
Speaker 1: H Well, that's interesting, and that does line up with

721
00:38:51,760 --> 00:38:54,239
Speaker 1: a lot of what we talked about, uh, because what

722
00:38:54,400 --> 00:38:56,040
Speaker 1: Luke just think of the elements, they're not only the

723
00:38:56,040 --> 00:38:59,200
Speaker 1: sleep paralysis, but uh, the reading of the comic book

724
00:38:59,239 --> 00:39:04,239
Speaker 1: before one goes to bed, potentially contributing to some of

725
00:39:04,239 --> 00:39:07,480
Speaker 1: the like the narrative information you have on hand for

726
00:39:07,600 --> 00:39:13,520
Speaker 1: the interpretation of of stimuli within that that murky period

727
00:39:13,560 --> 00:39:17,280
Speaker 1: of waking and which certain hallucinations can occur, Right, Yeah,

728
00:39:17,320 --> 00:39:19,680
Speaker 1: I mean, I think what Lindsay experienced is what we

729
00:39:19,800 --> 00:39:21,839
Speaker 1: described in those episodes as being sort of like the

730
00:39:21,880 --> 00:39:25,040
Speaker 1: first stage of the alien abduction experience, right, you have

731
00:39:25,120 --> 00:39:28,640
Speaker 1: sleep paralysis or some other kind of event that is

732
00:39:28,680 --> 00:39:32,640
Speaker 1: difficult to explain, and then it sounds like lindsay didn't

733
00:39:32,680 --> 00:39:35,120
Speaker 1: go on to the next phase, which was going to

734
00:39:35,360 --> 00:39:39,800
Speaker 1: a therapist or a hypnotist and having false memories created

735
00:39:39,840 --> 00:39:43,520
Speaker 1: that then somehow are extrapolated outward into something worse, right,

736
00:39:43,560 --> 00:39:46,200
Speaker 1: like actually being taken aboard the ship, right, or just

737
00:39:46,280 --> 00:39:50,040
Speaker 1: any kind of like repeated self analysis of the memory

738
00:39:50,080 --> 00:39:54,239
Speaker 1: that props up the supernatural explanation. Yeah, but again, this

739
00:39:54,320 --> 00:39:57,080
Speaker 1: is a great example of like, we read lots of

740
00:39:57,120 --> 00:40:00,000
Speaker 1: studies that were about sleep paralysis connected to the idea

741
00:40:00,080 --> 00:40:03,319
Speaker 1: of alien abduction, but to have a firsthand account like

742
00:40:03,400 --> 00:40:06,359
Speaker 1: this is really nice. I think like the closest thing

743
00:40:06,360 --> 00:40:08,360
Speaker 1: we had to that was we talked about that documentary

744
00:40:08,400 --> 00:40:10,200
Speaker 1: That Nightmare, and how there are many people in that

745
00:40:10,280 --> 00:40:14,279
Speaker 1: documentary who thought that their sleep paralysis events were alien abductions.

746
00:40:15,040 --> 00:40:17,279
Speaker 1: You know, something I think might be interesting would be

747
00:40:17,360 --> 00:40:21,520
Speaker 1: to sort of come up with standard narratives about how

748
00:40:21,560 --> 00:40:25,600
Speaker 1: people get from having an experience like this to one

749
00:40:25,640 --> 00:40:28,160
Speaker 1: of two end points. You know, the path diverges, it

750
00:40:28,280 --> 00:40:30,280
Speaker 1: forks off, and you can end up in the place

751
00:40:30,320 --> 00:40:34,279
Speaker 1: where you say I think I had a strange experience

752
00:40:34,280 --> 00:40:36,520
Speaker 1: and I would explain it through sleep paralysis or I

753
00:40:36,520 --> 00:40:38,680
Speaker 1: don't know what happened or something like that, and then

754
00:40:38,680 --> 00:40:41,280
Speaker 1: on the other hand, you have it was absolutely real

755
00:40:41,440 --> 00:40:44,560
Speaker 1: and people won't believe me, Like, how do you get

756
00:40:44,560 --> 00:40:50,440
Speaker 1: what determines which path you follow? Well, I mean, I

757
00:40:50,440 --> 00:40:53,040
Speaker 1: think there are a number of different factors there, but

758
00:40:53,080 --> 00:40:54,520
Speaker 1: I mean one of them is just like, what do

759
00:40:54,560 --> 00:40:56,440
Speaker 1: you need in your life? Do you? Is there a

760
00:40:56,480 --> 00:41:00,800
Speaker 1: part of you that needs an experience great than yourselves

761
00:41:00,800 --> 00:41:02,320
Speaker 1: that no one else is going to be able to

762
00:41:02,400 --> 00:41:06,400
Speaker 1: understand or only a select inviting community is going to

763
00:41:06,480 --> 00:41:09,240
Speaker 1: understand it. So you know, it's a desire for religious experience,

764
00:41:09,280 --> 00:41:13,040
Speaker 1: a desire to see God. This is why a number

765
00:41:13,080 --> 00:41:16,640
Speaker 1: of abductees report that their experience, even though scary, is

766
00:41:16,719 --> 00:41:21,000
Speaker 1: ultimately a positive experience for them because they come away

767
00:41:21,040 --> 00:41:23,400
Speaker 1: from it feeling like, oh, I now know my place

768
00:41:23,400 --> 00:41:25,440
Speaker 1: in the universe and that there's something above me that

769
00:41:25,480 --> 00:41:28,040
Speaker 1: could be taking care of me. It almost makes me

770
00:41:28,080 --> 00:41:30,279
Speaker 1: wonder if this is parallel to what we're talking about

771
00:41:30,320 --> 00:41:33,840
Speaker 1: with the science communication episode, where something that should be

772
00:41:33,880 --> 00:41:37,000
Speaker 1: a question of you making judgments based on like facts

773
00:41:37,000 --> 00:41:39,239
Speaker 1: and reading evidence and stuff like that is really more

774
00:41:39,280 --> 00:41:43,359
Speaker 1: determined about your social environment. Yeah, absolutely, And I mean

775
00:41:43,440 --> 00:41:44,920
Speaker 1: I think both of these things I meant to say

776
00:41:44,960 --> 00:41:47,480
Speaker 1: this when we were talking about science communication. They both

777
00:41:47,520 --> 00:41:51,080
Speaker 1: come back to a fact that we hit over and

778
00:41:51,160 --> 00:41:52,960
Speaker 1: over and over again on the show, which is just

779
00:41:53,000 --> 00:41:57,400
Speaker 1: that like human beings as social animals, just are prone

780
00:41:57,480 --> 00:42:00,440
Speaker 1: to making mistakes like this, you know, and how we

781
00:42:00,760 --> 00:42:03,719
Speaker 1: interpret our events and and especially how we build culture

782
00:42:04,080 --> 00:42:05,960
Speaker 1: around things that happened to us so that we can

783
00:42:06,000 --> 00:42:09,120
Speaker 1: explain the world around us. Alright, on that note, we're

784
00:42:09,160 --> 00:42:11,919
Speaker 1: gonna take one more quick break, and when we come back,

785
00:42:12,160 --> 00:42:16,200
Speaker 1: Carney will dish out the final trio of listener mail

786
00:42:16,239 --> 00:42:21,600
Speaker 1: for us here today, Thank you, thank you. All Right,

787
00:42:21,600 --> 00:42:24,799
Speaker 1: we're back. There's another piece of listener mail brought to

788
00:42:24,880 --> 00:42:29,040
Speaker 1: us by Carney, and this one is from listener Allison.

789
00:42:29,680 --> 00:42:33,680
Speaker 1: Allison writes in and says Mara Hart might be one

790
00:42:33,760 --> 00:42:36,880
Speaker 1: of the coolest people out there, although that may be

791
00:42:36,960 --> 00:42:40,800
Speaker 1: a bit biased, as I am also a fellow marine biologist,

792
00:42:41,320 --> 00:42:44,319
Speaker 1: a theologist to be exact. I love your podcast and

793
00:42:44,360 --> 00:42:47,200
Speaker 1: listen every day while conducting my many hours of lab work.

794
00:42:47,480 --> 00:42:50,080
Speaker 1: Among my favorite episodes are the ones where you had

795
00:42:50,160 --> 00:42:52,800
Speaker 1: Mara Heart as a guest speaker, so I was beyond

796
00:42:52,800 --> 00:42:55,600
Speaker 1: excited when I had the opportunity to meet Dr Hart

797
00:42:55,800 --> 00:42:59,759
Speaker 1: this past week at the American Fisheries Society Symposium in

798
00:43:00,040 --> 00:43:02,840
Speaker 1: the Bay, Florida, where she was one of the planary speakers.

799
00:43:03,040 --> 00:43:05,680
Speaker 1: I was able to find her after her talk and

800
00:43:05,719 --> 00:43:08,879
Speaker 1: have a quick conversation with her one on one, where

801
00:43:08,920 --> 00:43:11,400
Speaker 1: I asked her for her for some advice and commented

802
00:43:11,440 --> 00:43:14,239
Speaker 1: on how much I love your podcast. Just like you guys.

803
00:43:14,360 --> 00:43:17,200
Speaker 1: Dr Hart is an amazing communicator of science, breaking down

804
00:43:17,200 --> 00:43:19,480
Speaker 1: the barriers of the ivory tower that is often scientific

805
00:43:19,520 --> 00:43:22,840
Speaker 1: research and laying it out in a way that is interesting, engaging,

806
00:43:23,000 --> 00:43:26,279
Speaker 1: and most importantly fun. It was really inspiring to listen

807
00:43:26,280 --> 00:43:28,799
Speaker 1: to her speak, especially as a female scientist in the

808
00:43:28,840 --> 00:43:32,399
Speaker 1: early stages of my career as a researcher. Seeing how

809
00:43:32,440 --> 00:43:35,880
Speaker 1: confident and engaging she was gave me some serious hashtag

810
00:43:35,920 --> 00:43:39,040
Speaker 1: science goals. And I hope that I can quote unquote

811
00:43:39,080 --> 00:43:43,080
Speaker 1: grow up to be just like her. Oh that's so cool. Yeah,

812
00:43:43,040 --> 00:43:46,720
Speaker 1: I can't wait for your next episode. What a wonderful email.

813
00:43:46,840 --> 00:43:49,080
Speaker 1: She's got one up on us. We've never met Mara

814
00:43:49,200 --> 00:43:51,520
Speaker 1: in real life. We've only just been able to talk

815
00:43:51,520 --> 00:43:53,520
Speaker 1: to Morrow on the phone before. But you're right, she

816
00:43:53,760 --> 00:43:56,080
Speaker 1: is delightful. She is one of my favorite guests to

817
00:43:56,120 --> 00:43:58,680
Speaker 1: have on the show. What I love about having Mara

818
00:43:58,800 --> 00:44:01,400
Speaker 1: on the show is that she's so down to earth

819
00:44:01,920 --> 00:44:05,600
Speaker 1: about the science that she's involved in, but also how

820
00:44:05,640 --> 00:44:08,799
Speaker 1: she this gets back to science communication, how she communicates

821
00:44:08,840 --> 00:44:12,200
Speaker 1: it to the public, and how she she really expresses

822
00:44:12,239 --> 00:44:15,680
Speaker 1: her wonder and awe over the things that she's studying.

823
00:44:15,760 --> 00:44:18,279
Speaker 1: You know. It's yeah, always fun to have her. So

824
00:44:18,360 --> 00:44:22,040
Speaker 1: let's see what episodes the Osadas boneworm episode, she was on,

825
00:44:22,800 --> 00:44:26,319
Speaker 1: the Coral Reef episode, and then we just recently had

826
00:44:26,320 --> 00:44:30,320
Speaker 1: her on again for our our Shark reproduction episode earlier

827
00:44:30,360 --> 00:44:35,319
Speaker 1: this summer. Alright, well, our next email comes in in

828
00:44:35,400 --> 00:44:37,560
Speaker 1: reference to the episode that Robert and I did about

829
00:44:37,600 --> 00:44:41,040
Speaker 1: the Tower of Babel and the confusion of languages. This

830
00:44:41,120 --> 00:44:43,480
Speaker 1: was a fun one, wasn't it, Robert? Oh? Yeah, this

831
00:44:43,520 --> 00:44:45,520
Speaker 1: was This one was great because you had that wonderful

832
00:44:45,560 --> 00:44:51,359
Speaker 1: convergence of history, mythology, science, linguistics. It all came together. Yeah,

833
00:44:51,400 --> 00:44:54,080
Speaker 1: And so we talked about the idea of or one

834
00:44:54,120 --> 00:44:56,080
Speaker 1: of the things we discussed in the episode was the

835
00:44:56,160 --> 00:44:59,440
Speaker 1: idea of the confusion of languages. In the biblical story

836
00:44:59,480 --> 00:45:02,160
Speaker 1: of the Tower Babble, it's the confusion of tongues. You know,

837
00:45:02,560 --> 00:45:05,480
Speaker 1: God gets threatened by the Tower project and says, I'm

838
00:45:05,480 --> 00:45:07,680
Speaker 1: going to make everybody speak different languages. But instead we

839
00:45:07,719 --> 00:45:10,880
Speaker 1: talked about how languages actually diverge, and one of the

840
00:45:10,880 --> 00:45:14,040
Speaker 1: things we talked about was the the possible idea of

841
00:45:14,360 --> 00:45:17,640
Speaker 1: language barriers around the world being a kind of cultural

842
00:45:17,840 --> 00:45:22,759
Speaker 1: immunity barrier that helps prevent harmful memes from spreading as

843
00:45:22,800 --> 00:45:25,720
Speaker 1: quickly as they could if everybody in the world spoke

844
00:45:25,760 --> 00:45:29,040
Speaker 1: the same language, essentially like a like a firewall. Yeah,

845
00:45:29,280 --> 00:45:31,520
Speaker 1: and so like if you've got a language, you've got

846
00:45:31,560 --> 00:45:35,040
Speaker 1: some horrible meme, Like I think the obvious example would

847
00:45:35,040 --> 00:45:38,320
Speaker 1: be Nazism. But you know things like that that catch

848
00:45:38,400 --> 00:45:40,480
Speaker 1: on really quickly with a bunch of people and are

849
00:45:40,560 --> 00:45:43,360
Speaker 1: very destructive, they do seem to be very rooted to

850
00:45:43,440 --> 00:45:46,400
Speaker 1: the language system in which they emerged very often, and

851
00:45:46,440 --> 00:45:49,719
Speaker 1: so they don't spread quite as easily across language barriers.

852
00:45:49,960 --> 00:45:52,840
Speaker 1: So this is why like I can't as cheeseburger isn't

853
00:45:52,880 --> 00:45:55,520
Speaker 1: that big, and like I don't know Papua New Guinea

854
00:45:55,880 --> 00:45:58,759
Speaker 1: that's exactly where we're going with this. Well, it's like

855
00:45:58,800 --> 00:46:01,439
Speaker 1: I read the I didn't, but it's like I read

856
00:46:01,480 --> 00:46:04,799
Speaker 1: the letter. So this is from Chris. Chris says, Hi,

857
00:46:05,000 --> 00:46:07,120
Speaker 1: my name is Chris, and I was really fascinated by

858
00:46:07,120 --> 00:46:10,080
Speaker 1: your Tower of Babel episode from last month. I love

859
00:46:10,160 --> 00:46:13,279
Speaker 1: thinking about the great global flow of ideas and how

860
00:46:13,360 --> 00:46:17,240
Speaker 1: languages play into the movement of philosophies and cultural norms.

861
00:46:17,680 --> 00:46:19,920
Speaker 1: There were two things from your episode that really stood

862
00:46:19,960 --> 00:46:22,560
Speaker 1: out to me. The first was your brief acknowledgement that

863
00:46:22,680 --> 00:46:26,640
Speaker 1: Japanese as a language has not drastically evolved over time.

864
00:46:27,120 --> 00:46:30,320
Speaker 1: I studied Japanese for about six years and have traveled

865
00:46:30,320 --> 00:46:32,920
Speaker 1: there twice for about a month each. I have a

866
00:46:32,960 --> 00:46:36,440
Speaker 1: theory that Japanese has not evolved very drastically because they

867
00:46:36,480 --> 00:46:40,960
Speaker 1: actually have two phonetic alphabets and a symbol based method

868
00:46:41,000 --> 00:46:44,480
Speaker 1: of writing. Here a Ghana is their phonetic alphabet used

869
00:46:44,480 --> 00:46:48,600
Speaker 1: for vocabulary that originated in Japan. Kata Kana is their

870
00:46:48,640 --> 00:46:52,279
Speaker 1: phonetic alphabet used for all foreign words or expressions that

871
00:46:52,320 --> 00:46:57,200
Speaker 1: were introduced to Japanese culture. Because foreign concepts are isolated

872
00:46:57,239 --> 00:47:00,800
Speaker 1: to a separate system of expression, the original Hiragana is

873
00:47:00,920 --> 00:47:04,120
Speaker 1: very rarely forced to adapt or evolve. I guess it

874
00:47:04,160 --> 00:47:06,680
Speaker 1: would maybe be more accurate to say that one of

875
00:47:06,719 --> 00:47:10,480
Speaker 1: the Japanese alphabets is constantly adapting and taking in new

876
00:47:10,520 --> 00:47:14,040
Speaker 1: words and concepts, while the core original method of writing

877
00:47:14,239 --> 00:47:18,279
Speaker 1: remains comparatively unchanged. I thought that was really interesting that. Yeah,

878
00:47:18,320 --> 00:47:21,200
Speaker 1: that is a fascist It's true too. I studied Japanese

879
00:47:21,200 --> 00:47:24,440
Speaker 1: in college, but yeah, I never thought of it that

880
00:47:24,560 --> 00:47:29,000
Speaker 1: way before. It's kind of a way to enforce cultural tradition. Yeah. Uh.

881
00:47:29,040 --> 00:47:32,880
Speaker 1: And it's certainly true that loan concepts and loan words

882
00:47:32,920 --> 00:47:34,880
Speaker 1: from other languages is one of the main ways that

883
00:47:34,960 --> 00:47:38,279
Speaker 1: languages seem to evolve in the modern day, or you know,

884
00:47:38,320 --> 00:47:41,200
Speaker 1: relatively modern day. I mean, you think about the way

885
00:47:41,360 --> 00:47:43,960
Speaker 1: English came to it came to us as it is.

886
00:47:44,040 --> 00:47:48,120
Speaker 1: You know, it's this crazy fusion of German and Old

887
00:47:48,200 --> 00:47:53,120
Speaker 1: Norse and Spanish and all the Latin derived languages French, um,

888
00:47:53,280 --> 00:47:55,839
Speaker 1: and the way those cultures came together. But so, yeah,

889
00:47:56,080 --> 00:47:59,040
Speaker 1: really interesting. I love the how you brought up uh.

890
00:47:59,400 --> 00:48:02,399
Speaker 1: I can I can has cheeseburger earlier, because I think

891
00:48:02,480 --> 00:48:05,839
Speaker 1: humor is a key way to look at at how

892
00:48:05,920 --> 00:48:09,680
Speaker 1: memes travel like not physical humor, because everybody can get

893
00:48:09,719 --> 00:48:13,840
Speaker 1: into the idea of like slapsticks. Slapstick tends to like

894
00:48:13,880 --> 00:48:16,000
Speaker 1: if you're if you're trying to check out comedy from

895
00:48:16,000 --> 00:48:19,319
Speaker 1: other cultures and cultures with a foreign language. Uh, the

896
00:48:19,360 --> 00:48:21,520
Speaker 1: slapstick is going to be the easiest to understand or

897
00:48:21,560 --> 00:48:24,480
Speaker 1: the outright like silly, goofy clowney behavior. But when it

898
00:48:24,520 --> 00:48:26,640
Speaker 1: has a linguistic quality to it and you're having to

899
00:48:26,680 --> 00:48:30,719
Speaker 1: deal with the barrier of translation, I think that's where

900
00:48:30,719 --> 00:48:32,759
Speaker 1: you a lot of the stuff ends up falling flat. Well,

901
00:48:32,800 --> 00:48:34,919
Speaker 1: I think you'll be really interested to see where Chris

902
00:48:34,920 --> 00:48:37,520
Speaker 1: goes next. So Chris says, the other thing I was

903
00:48:37,560 --> 00:48:40,200
Speaker 1: really inspired by was the section towards the end in

904
00:48:40,239 --> 00:48:43,800
Speaker 1: regards to snow Crash, and Chris says, I love that book.

905
00:48:44,200 --> 00:48:47,080
Speaker 1: Um and the notion of a universal language actually being

906
00:48:47,200 --> 00:48:50,400
Speaker 1: detrimental to global human consciousness as it would allow the

907
00:48:50,440 --> 00:48:54,880
Speaker 1: spread of potentially evil belief systems. I firmly believe that

908
00:48:54,920 --> 00:48:58,200
Speaker 1: we are already witnessing the growth of a new global language.

909
00:48:58,600 --> 00:49:03,360
Speaker 1: The kernel of this growth is modern meme culture. Memes

910
00:49:03,400 --> 00:49:06,880
Speaker 1: as a language or a combination of non technical English

911
00:49:06,960 --> 00:49:12,120
Speaker 1: and images or symbols, images are universally understood and very simplistic.

912
00:49:12,200 --> 00:49:14,560
Speaker 1: English is as close as you can get to a

913
00:49:14,600 --> 00:49:18,040
Speaker 1: global language at this moment. When you combine the two,

914
00:49:18,160 --> 00:49:20,080
Speaker 1: you end up with a type of messaging that can

915
00:49:20,120 --> 00:49:24,080
Speaker 1: be understood and recreated on a global scale. Combined with

916
00:49:24,160 --> 00:49:27,920
Speaker 1: the preferred method of distributing memes the Internet and social media,

917
00:49:28,440 --> 00:49:31,480
Speaker 1: you have a way to very cheaply communicate ideas on

918
00:49:31,520 --> 00:49:34,719
Speaker 1: a global scale with rapid fire quickness, and not have

919
00:49:34,880 --> 00:49:39,480
Speaker 1: those ideas particularly hampered by translation. A scary part of

920
00:49:39,520 --> 00:49:41,799
Speaker 1: this is that memes allowed for the global spread of

921
00:49:41,840 --> 00:49:45,799
Speaker 1: anti democratic political ideals. It's a fact, a fact that

922
00:49:45,840 --> 00:49:49,480
Speaker 1: we witnessed in Brexit, in the U s presidential election

923
00:49:49,600 --> 00:49:52,839
Speaker 1: and the French election. We witness non English and non

924
00:49:52,920 --> 00:49:57,120
Speaker 1: French speaking actors communicating anti democratic ideas to English and

925
00:49:57,200 --> 00:50:01,640
Speaker 1: French speaking American, British, and French said. Since Russia has

926
00:50:01,680 --> 00:50:06,120
Speaker 1: been known to weaponize thought viruses as a comic wo nerd,

927
00:50:06,200 --> 00:50:09,160
Speaker 1: I'm excited to write that phrase and spread them through

928
00:50:09,280 --> 00:50:13,840
Speaker 1: memes and massive disinformation dumps. What really irks me is

929
00:50:13,880 --> 00:50:17,080
Speaker 1: that it's a one way flow because countries like Russia

930
00:50:17,120 --> 00:50:21,120
Speaker 1: and China maintain such stringent censorship laws and control over

931
00:50:21,200 --> 00:50:24,719
Speaker 1: the Internet. They can keep their population somewhat inoculated from

932
00:50:24,760 --> 00:50:27,960
Speaker 1: pro democratic ideas that could potentially flow from us to

933
00:50:28,040 --> 00:50:31,680
Speaker 1: them in meme form. Meanwhile, we hold freedom of speech

934
00:50:31,719 --> 00:50:33,759
Speaker 1: as a core value of ours, so that we lack

935
00:50:33,800 --> 00:50:37,760
Speaker 1: the kind of isolation inoculation that would prevent Russian anti

936
00:50:37,760 --> 00:50:41,640
Speaker 1: democratic memes from infecting us. And that's pretty much what

937
00:50:41,680 --> 00:50:44,560
Speaker 1: I've got. Sorry, it's so long. Thanks for reading. I'd

938
00:50:44,560 --> 00:50:46,480
Speaker 1: love to hear back. Keep up the great work on

939
00:50:46,520 --> 00:50:50,640
Speaker 1: the podcast. Thanks again, Chris. I have so many things

940
00:50:50,719 --> 00:50:53,560
Speaker 1: I want to talk about related to this. I think, Yeah,

941
00:50:53,600 --> 00:50:55,279
Speaker 1: I think this is a really and this is something

942
00:50:55,320 --> 00:50:58,200
Speaker 1: we've actually talked about a fair bit off off, Mike.

943
00:50:58,600 --> 00:51:02,319
Speaker 1: Is the idea of the ways new forms of communication

944
00:51:02,360 --> 00:51:05,600
Speaker 1: allow ideas to spread over the Internet so much more easily,

945
00:51:05,600 --> 00:51:07,840
Speaker 1: but I've never put it in words like this. I

946
00:51:07,880 --> 00:51:10,239
Speaker 1: think Chris has got a really interesting idea about the

947
00:51:10,360 --> 00:51:12,960
Speaker 1: role memes play and you can absolutely see it for

948
00:51:13,000 --> 00:51:17,640
Speaker 1: yourself if you watch say, disinformation bots operating on Twitter.

949
00:51:17,920 --> 00:51:22,760
Speaker 1: They love memes, right, Yeah, So to his point about

950
00:51:22,800 --> 00:51:26,760
Speaker 1: this being very comic, Bookie, there is a classic issue

951
00:51:26,880 --> 00:51:30,760
Speaker 1: of of a book called Global frequency. The uh warren

952
00:51:30,760 --> 00:51:32,960
Speaker 1: Ellis who I end up referencing on the show all

953
00:51:32,960 --> 00:51:35,359
Speaker 1: the time, wrote and it was drawn by the late

954
00:51:35,440 --> 00:51:39,160
Speaker 1: Steve Dylan, and the premise was that a signal was

955
00:51:39,200 --> 00:51:44,160
Speaker 1: intercepted by set and translated and then subsequently broadcast as

956
00:51:44,239 --> 00:51:48,000
Speaker 1: a mimetic information to the entire world. Because it was

957
00:51:48,080 --> 00:51:52,880
Speaker 1: in meme format, it starts infecting people. Uh, it's designed

958
00:51:52,920 --> 00:51:57,480
Speaker 1: it's to infect people essentially, so that like memes are

959
00:51:57,520 --> 00:52:01,319
Speaker 1: the best carrier for this virus, right, So that is

960
00:52:01,600 --> 00:52:04,160
Speaker 1: a really interesting concept on a sci fi level. But

961
00:52:04,200 --> 00:52:07,480
Speaker 1: then also I think it's interesting to step back and

962
00:52:07,520 --> 00:52:10,920
Speaker 1: remember like the difference between the term meme that we

963
00:52:11,040 --> 00:52:14,600
Speaker 1: used to describe JPEG's with the fun impact on them

964
00:52:15,239 --> 00:52:19,320
Speaker 1: on the Internet versus what like people like Richard Dawkins

965
00:52:19,360 --> 00:52:21,560
Speaker 1: and Susan Blackmore had in mind when we first came

966
00:52:21,600 --> 00:52:24,520
Speaker 1: up with the terminology. So maybe we should do a

967
00:52:24,600 --> 00:52:28,040
Speaker 1: memetics episode. I mean, we've definitely touched on the medics

968
00:52:28,040 --> 00:52:30,200
Speaker 1: and lots of episodes in the past, but maybe we

969
00:52:30,200 --> 00:52:32,480
Speaker 1: could devote something to the core idea. I mean, the

970
00:52:32,480 --> 00:52:35,440
Speaker 1: basic concept scept of a meme originally is just the

971
00:52:35,480 --> 00:52:39,440
Speaker 1: idea of a self reproducing bit of cultural information. So

972
00:52:39,480 --> 00:52:42,000
Speaker 1: it could be a song, it could be a political belief,

973
00:52:42,080 --> 00:52:45,400
Speaker 1: it could be anything that tends to make copies of

974
00:52:45,440 --> 00:52:48,399
Speaker 1: itself in the minds of people who share some kind

975
00:52:48,400 --> 00:52:51,320
Speaker 1: of language or cult cultural Well, I guess between anybody

976
00:52:51,320 --> 00:52:54,360
Speaker 1: really um in the same way that genes make copies

977
00:52:54,400 --> 00:52:58,480
Speaker 1: of themselves in the gene pool, right. Yeah, and then again,

978
00:52:58,600 --> 00:53:00,680
Speaker 1: it's funny there's a theme for this listener meal that

979
00:53:00,719 --> 00:53:02,440
Speaker 1: seems to be coming around. Or maybe it's just I'm

980
00:53:02,440 --> 00:53:06,120
Speaker 1: obsessed with this topic again, it seems to me media

981
00:53:06,200 --> 00:53:09,719
Speaker 1: literacy is super important here, right, and that like what

982
00:53:09,840 --> 00:53:12,399
Speaker 1: you see if you're if you see some of these

983
00:53:12,440 --> 00:53:17,200
Speaker 1: memes that are designed specifically as a persuasive tools right there,

984
00:53:17,239 --> 00:53:22,000
Speaker 1: like rhetorical weapons almost that go out there, right. Uh,

985
00:53:22,080 --> 00:53:24,400
Speaker 1: if you don't stop and try to judge them based

986
00:53:24,440 --> 00:53:26,600
Speaker 1: on their merit, how they were created, who they were

987
00:53:26,640 --> 00:53:30,600
Speaker 1: designed for, etcetera, then you're more likely to be susceptible

988
00:53:30,640 --> 00:53:33,239
Speaker 1: to them and subsequently fooled by them, which brings us

989
00:53:33,280 --> 00:53:37,560
Speaker 1: to the emoji movie right exactly hit of the summer.

990
00:53:38,520 --> 00:53:41,080
Speaker 1: You know, when we talk about issues like this, uh

991
00:53:41,120 --> 00:53:44,360
Speaker 1: that the you know, they involve global politics, interaction between

992
00:53:44,360 --> 00:53:46,759
Speaker 1: governments around the world. One thing that I helped that

993
00:53:46,840 --> 00:53:50,520
Speaker 1: I think helps in how we we use language carefully

994
00:53:50,560 --> 00:53:54,920
Speaker 1: in describing problems like this is to correctly identify the culprits.

995
00:53:54,960 --> 00:53:57,399
Speaker 1: So when we talk about something like this, I think

996
00:53:57,400 --> 00:53:59,640
Speaker 1: it is undeniably true. There have been, you know, enough

997
00:53:59,680 --> 00:54:03,359
Speaker 1: report there's really no question that the Russian government does

998
00:54:03,480 --> 00:54:07,640
Speaker 1: operate tons of disinformation campaigns on the Internet and stuff

999
00:54:07,680 --> 00:54:10,080
Speaker 1: like that. But I like to think of those as

1000
00:54:10,360 --> 00:54:15,520
Speaker 1: Crimlin disinformation product products, not Russian disinformation products, such that

1001
00:54:15,560 --> 00:54:19,759
Speaker 1: you don't identify them with the Russian people's being responsible

1002
00:54:19,800 --> 00:54:22,960
Speaker 1: for the same thing is accusing us of some similar

1003
00:54:23,040 --> 00:54:26,399
Speaker 1: kind of disinformation mation campaign or hacking campaign that our

1004
00:54:26,440 --> 00:54:30,800
Speaker 1: government might be up to behind the scenes. Right, yeah, exactly. Alright,

1005
00:54:30,800 --> 00:54:33,319
Speaker 1: it looks like we have one more bit of listener mail.

1006
00:54:33,400 --> 00:54:37,040
Speaker 1: When last scrap here from Carney looks like it's for

1007
00:54:37,080 --> 00:54:39,200
Speaker 1: you to read here, Christian. Yeah, this last one comes

1008
00:54:39,239 --> 00:54:42,680
Speaker 1: to us from Duncan. And I kind of struggled with

1009
00:54:42,680 --> 00:54:45,319
Speaker 1: whether or not I for we got it about a

1010
00:54:45,320 --> 00:54:47,520
Speaker 1: week and a half ago, and I was like, I

1011
00:54:47,560 --> 00:54:50,000
Speaker 1: don't know how to respond to this. And so the

1012
00:54:50,040 --> 00:54:52,320
Speaker 1: fact that we were doing a listener mail episode seems

1013
00:54:52,360 --> 00:54:54,600
Speaker 1: like a great place for us to address it because

1014
00:54:54,800 --> 00:54:58,279
Speaker 1: it's a complicated topic. He touches on two episodes that

1015
00:54:58,320 --> 00:55:01,759
Speaker 1: we've covered, the first being Wicked Problems episode that Robert

1016
00:55:01,800 --> 00:55:05,120
Speaker 1: and I did about a year ago maybe, and then

1017
00:55:05,360 --> 00:55:09,239
Speaker 1: Cleo Dynamics, which we covered in the last two weeks now.

1018
00:55:09,440 --> 00:55:13,000
Speaker 1: Duncan says, Hi, guys, in two separate podcasts, you have

1019
00:55:13,040 --> 00:55:16,920
Speaker 1: referred to poverty and social inequality as wicked problems, and

1020
00:55:16,960 --> 00:55:20,560
Speaker 1: I feel that this is not only inaccurate, but also dangerous.

1021
00:55:20,880 --> 00:55:23,319
Speaker 1: It is hard to act from a place of pessimism

1022
00:55:23,400 --> 00:55:26,520
Speaker 1: and feeling that these problems are too complicated, and that

1023
00:55:26,560 --> 00:55:29,080
Speaker 1: makes most people throw up their hands and go what

1024
00:55:29,280 --> 00:55:33,120
Speaker 1: is the point in trying definitions? One of the features

1025
00:55:33,120 --> 00:55:36,880
Speaker 1: of wicked problems is the difficulty of defining them. Poverty

1026
00:55:37,000 --> 00:55:41,240
Speaker 1: has a fairly clear, those scalar definition, although different people

1027
00:55:41,239 --> 00:55:43,520
Speaker 1: will draw the line at different points on the scale,

1028
00:55:43,800 --> 00:55:48,319
Speaker 1: the measurable features of poverty are fairly clearly defined. Similarly,

1029
00:55:48,520 --> 00:55:52,280
Speaker 1: defining the success of a solution is simply a measure

1030
00:55:52,280 --> 00:55:56,120
Speaker 1: of whether people move up the scale in a meaningful way. Obviously,

1031
00:55:56,280 --> 00:55:59,840
Speaker 1: there are some complexities in ways to subdivide the concepts,

1032
00:56:00,080 --> 00:56:04,680
Speaker 1: but in general definition is not a problem solutions. Here again,

1033
00:56:04,800 --> 00:56:08,080
Speaker 1: a primary feature of wicked problems falls down. There are

1034
00:56:08,120 --> 00:56:12,040
Speaker 1: solutions to the majority of poverty situations, not a magic

1035
00:56:12,080 --> 00:56:14,880
Speaker 1: bullet for all of them, but a portfolio of policy

1036
00:56:14,920 --> 00:56:18,480
Speaker 1: measures that can have drastic effects if used together. In

1037
00:56:18,480 --> 00:56:21,319
Speaker 1: the repeating history episode, this is the Cleo dynamics one.

1038
00:56:21,520 --> 00:56:25,760
Speaker 1: You quoted Cleo dynamics historians who said that reducing inequality

1039
00:56:25,880 --> 00:56:29,880
Speaker 1: is critical. These historians would, I am sure, be able

1040
00:56:29,920 --> 00:56:33,160
Speaker 1: to provide a series of policies that would achieve this

1041
00:56:33,360 --> 00:56:38,120
Speaker 1: based on fairly reliable historical data. Most economists that favor

1042
00:56:38,200 --> 00:56:42,759
Speaker 1: reducing inequality should be able to if asked. Most importantly,

1043
00:56:42,920 --> 00:56:45,799
Speaker 1: most of these solutions do not have major cyclical or

1044
00:56:45,840 --> 00:56:49,640
Speaker 1: intermeshed knock on effects, which make them impossible to implement.

1045
00:56:50,000 --> 00:56:54,080
Speaker 1: In most cases, well thought out equality policy improves a

1046
00:56:54,160 --> 00:56:57,040
Speaker 1: lot of nearby issues like crime and drug addiction, but

1047
00:56:57,160 --> 00:57:00,960
Speaker 1: rarely do they result in any major detrimental eye effects.

1048
00:57:01,000 --> 00:57:04,480
Speaker 1: So uh, he says. Finally, in fact, poverty and inequality

1049
00:57:04,480 --> 00:57:07,759
Speaker 1: are among the most well behaved, predictable social problems we have.

1050
00:57:08,120 --> 00:57:10,919
Speaker 1: He gives a number of examples here for US that

1051
00:57:11,000 --> 00:57:13,399
Speaker 1: are their weblinks, So I'm not going to read you

1052
00:57:13,440 --> 00:57:16,040
Speaker 1: U r L s over our listener mail episode. Then

1053
00:57:16,080 --> 00:57:19,000
Speaker 1: he he ends by saying, I am not an expert,

1054
00:57:19,200 --> 00:57:21,480
Speaker 1: but I am sure there are hundreds of clever ideas

1055
00:57:21,560 --> 00:57:25,440
Speaker 1: for improving social equality among those that are. The reason

1056
00:57:25,480 --> 00:57:28,000
Speaker 1: we are not working to solve poverty is a lack

1057
00:57:28,040 --> 00:57:31,280
Speaker 1: of political will to do so, not because the problem

1058
00:57:31,400 --> 00:57:35,200
Speaker 1: is inherently difficult to solve. In my opinion, the reason

1059
00:57:35,280 --> 00:57:38,840
Speaker 1: there is a lack of political will is because inequality

1060
00:57:38,920 --> 00:57:42,080
Speaker 1: is a driving force of our current financial and political

1061
00:57:42,120 --> 00:57:45,320
Speaker 1: systems and the mechanism by which those who have power

1062
00:57:45,400 --> 00:57:48,480
Speaker 1: hold onto it. Why would the ruling class want to

1063
00:57:48,600 --> 00:57:53,760
Speaker 1: change it? Please give people hope. Regards Duncan, well, you know,

1064
00:57:54,480 --> 00:57:57,400
Speaker 1: I think he makes some good points here. Um I

1065
00:57:57,880 --> 00:58:00,520
Speaker 1: do want to agree that first of all, that that

1066
00:58:00,600 --> 00:58:04,840
Speaker 1: I think pessimism uh is an area of inactivity, and

1067
00:58:04,920 --> 00:58:08,520
Speaker 1: it is difficult to act from a place of pessimism.

1068
00:58:08,520 --> 00:58:12,080
Speaker 1: We have to act as optimists uh and uh on.

1069
00:58:12,320 --> 00:58:14,880
Speaker 1: I would also like to return to the topic at

1070
00:58:14,880 --> 00:58:16,600
Speaker 1: some point in the future and and do an episode

1071
00:58:16,680 --> 00:58:19,440
Speaker 1: on the idea of a post scarcity world, like what

1072
00:58:19,440 --> 00:58:21,840
Speaker 1: what are what are some of the possible road maps

1073
00:58:21,920 --> 00:58:24,720
Speaker 1: to a post scarcity world, What would it look like?

1074
00:58:24,800 --> 00:58:26,760
Speaker 1: What are the you know, what are the ideals that

1075
00:58:26,800 --> 00:58:28,280
Speaker 1: are wrapped up there? And how long have we've been

1076
00:58:28,320 --> 00:58:31,880
Speaker 1: we've been uh dreaming of it and trying to figure

1077
00:58:31,920 --> 00:58:36,800
Speaker 1: out how to get there. Um. In terms of Wicked Problems,

1078
00:58:37,720 --> 00:58:39,240
Speaker 1: I know that when we did that episode, and it's

1079
00:58:39,280 --> 00:58:41,800
Speaker 1: been a little while, we weren't so much trying to

1080
00:58:42,000 --> 00:58:45,120
Speaker 1: get people to focus on objectives like this, but it

1081
00:58:45,160 --> 00:58:47,400
Speaker 1: was more like, Okay, when someone comes at you, particularly

1082
00:58:47,480 --> 00:58:50,320
Speaker 1: the politician comes to you, and they have a solution

1083
00:58:50,960 --> 00:58:55,560
Speaker 1: to a complex problem in society, Uh, question what they

1084
00:58:55,560 --> 00:58:59,840
Speaker 1: are saying. Question the validity of this so called solution

1085
00:59:00,040 --> 00:59:03,280
Speaker 1: comes down to critical thinking. Again. Yeah, I actually pulled

1086
00:59:03,320 --> 00:59:06,160
Speaker 1: some of our notes from that Wicked Problems episode so

1087
00:59:06,200 --> 00:59:09,080
Speaker 1: that I could reference them back. And I thought it

1088
00:59:09,120 --> 00:59:12,600
Speaker 1: was interesting actually because when you turn back and you

1089
00:59:12,640 --> 00:59:15,960
Speaker 1: look at the guys who phrased this riddle and Weber,

1090
00:59:16,400 --> 00:59:18,800
Speaker 1: they really dove into this in the nineteen seventy three

1091
00:59:18,840 --> 00:59:23,480
Speaker 1: paper Dilemmas in a General Theory of Planning. They specifically

1092
00:59:23,600 --> 00:59:28,000
Speaker 1: used poverty as an example. Uh, and they said, uh, poverty,

1093
00:59:28,080 --> 00:59:30,440
Speaker 1: it's like tugging a loose string on a garment. What

1094
00:59:30,560 --> 00:59:33,600
Speaker 1: causes poverty? What is it? If it's merely low income,

1095
00:59:33,880 --> 00:59:37,080
Speaker 1: then that alone explodes out into concerns of both national

1096
00:59:37,120 --> 00:59:40,320
Speaker 1: and regional issues. But what about the economic aspects, the

1097
00:59:40,360 --> 00:59:44,240
Speaker 1: health and psychological aspects, and the cultural issues. Right, So,

1098
00:59:44,560 --> 00:59:47,480
Speaker 1: in regards to what Duncan was just saying to us, yeah,

1099
00:59:47,560 --> 00:59:49,680
Speaker 1: I think it's easy. Like if you look at it

1100
00:59:49,800 --> 00:59:53,520
Speaker 1: on a scalar level, especially like an economic one, you

1101
00:59:53,560 --> 00:59:56,560
Speaker 1: can say, oh, yeah, this is a very easily solvable problem.

1102
00:59:56,760 --> 00:59:59,880
Speaker 1: But Duncan himself at the end talks about how the

1103
01:00:00,040 --> 01:00:03,000
Speaker 1: real difficulty that makes it inherently difficult to solve is

1104
01:00:03,120 --> 01:00:06,960
Speaker 1: political will inequality and how that leads to our political

1105
01:00:06,960 --> 01:00:11,200
Speaker 1: systems and our financial systems, right, and ultimately the the

1106
01:00:11,240 --> 01:00:13,360
Speaker 1: ideas that those who have the power to change it

1107
01:00:13,400 --> 01:00:16,120
Speaker 1: aren't willing to do so. Right, That is the wicked

1108
01:00:16,120 --> 01:00:19,240
Speaker 1: problem nature of poverty in my mind. I mean, one

1109
01:00:19,240 --> 01:00:22,960
Speaker 1: obvious response that occurs to me is that saying a

1110
01:00:23,040 --> 01:00:26,840
Speaker 1: problem is difficult to eradicate with a simple solution is

1111
01:00:26,920 --> 01:00:32,200
Speaker 1: very different than saying a problem cannot be improved upon. Yeah, yeah, exactly. Yeah,

1112
01:00:32,280 --> 01:00:35,400
Speaker 1: I think wicked problems are more how do how do

1113
01:00:35,400 --> 01:00:37,880
Speaker 1: we put this, Like, are something that you should be

1114
01:00:37,920 --> 01:00:40,680
Speaker 1: on the lookout for in terms of the rhetoric that

1115
01:00:40,840 --> 01:00:44,200
Speaker 1: is being pushed your way, right, in terms of how

1116
01:00:44,280 --> 01:00:47,280
Speaker 1: easy and or difficult something is to solve, for instance,

1117
01:00:47,400 --> 01:00:49,920
Speaker 1: right now, and I think this debate is only become

1118
01:00:50,080 --> 01:00:53,840
Speaker 1: even stronger since we recorded that wicked episode, Wicked problems episode.

1119
01:00:53,840 --> 01:00:56,560
Speaker 1: But healthcare, how many people in the last year, how

1120
01:00:56,560 --> 01:00:59,440
Speaker 1: many politicians in the last year said, oh, healthcare so

1121
01:00:59,520 --> 01:01:03,000
Speaker 1: easy to solve, right, Uh, We've got a perfect plan,

1122
01:01:03,080 --> 01:01:04,880
Speaker 1: This is so easy to solve. Then you see in

1123
01:01:05,040 --> 01:01:09,080
Speaker 1: action how difficult it actually is. Right, Like, if someone

1124
01:01:09,080 --> 01:01:13,120
Speaker 1: makes the argument, this would be easy to solve, but politics,

1125
01:01:13,800 --> 01:01:16,760
Speaker 1: you're missing the point, Like politics and the political system.

1126
01:01:16,840 --> 01:01:20,400
Speaker 1: That's part of addressing the problem, That the problem is

1127
01:01:20,440 --> 01:01:23,080
Speaker 1: wrapped around there, that's where the thread is tangled. Like

1128
01:01:23,160 --> 01:01:25,440
Speaker 1: it would be so easy to lose weight if not

1129
01:01:25,560 --> 01:01:30,440
Speaker 1: for my willpower. Yeah, exactly, exactly, Yeah. Now I want

1130
01:01:30,440 --> 01:01:31,880
Speaker 1: to go back to the notes here for just one

1131
01:01:31,960 --> 01:01:35,760
Speaker 1: last bit here on wicked problems. Wicked problems can't be solved,

1132
01:01:35,760 --> 01:01:39,280
Speaker 1: they can only be mitigated, right Uh. And one proposal

1133
01:01:39,400 --> 01:01:44,960
Speaker 1: for this is strategic design using empathy and favoring abductive

1134
01:01:45,000 --> 01:01:48,960
Speaker 1: reasoning and rapid prototyping. So essentially the idea here for

1135
01:01:49,000 --> 01:01:52,240
Speaker 1: abductive reasoning is that the premise doesn't guarantee a solution.

1136
01:01:52,440 --> 01:01:56,320
Speaker 1: Rather that is uh, that's deductive or logic reasoning. So

1137
01:01:56,640 --> 01:02:00,760
Speaker 1: this is essentially inferring the best, most simple solution. Yeah,

1138
01:02:01,120 --> 01:02:05,520
Speaker 1: abductive the search for the best explanation. So I appreciate

1139
01:02:05,920 --> 01:02:08,360
Speaker 1: Duncan your letter because it really did make me think

1140
01:02:08,400 --> 01:02:10,720
Speaker 1: for a good long week about like how do we

1141
01:02:10,840 --> 01:02:12,760
Speaker 1: respond to this? But at the end of the day,

1142
01:02:12,800 --> 01:02:16,320
Speaker 1: I do think that poverty can be defined as a

1143
01:02:16,320 --> 01:02:20,200
Speaker 1: wicked problem. I don't disagree with you though, that we

1144
01:02:20,240 --> 01:02:22,040
Speaker 1: need to give people hope and we do need to

1145
01:02:22,120 --> 01:02:25,800
Speaker 1: think from an optimistic place, and I don't see defining

1146
01:02:25,840 --> 01:02:29,600
Speaker 1: things as a wicked problem is necessarily pessimistic. No, I

1147
01:02:29,600 --> 01:02:32,480
Speaker 1: mean another side of that coin is you don't want

1148
01:02:32,520 --> 01:02:34,720
Speaker 1: to discourage people, but you also want to help give

1149
01:02:34,720 --> 01:02:39,120
Speaker 1: people reasonable expectations. Um Like, if you promise somebody the

1150
01:02:39,160 --> 01:02:42,760
Speaker 1: moon and then you can't quite deliver it, they're going

1151
01:02:42,800 --> 01:02:46,600
Speaker 1: to get disillusioned with whatever mechanism or system tried to

1152
01:02:46,680 --> 01:02:49,840
Speaker 1: deliver them the moon and failed. Instead, if you. If

1153
01:02:49,880 --> 01:02:54,240
Speaker 1: you promise people reasonably attainable goals and you do attain those,

1154
01:02:54,640 --> 01:02:57,520
Speaker 1: that actually has a positive knock on effect that gives

1155
01:02:57,560 --> 01:03:01,200
Speaker 1: people confidence in the the ability of or system of

1156
01:03:01,240 --> 01:03:04,680
Speaker 1: problem solving to succeed again in the future. Anyways, if

1157
01:03:04,800 --> 01:03:07,240
Speaker 1: you have more information that you want to relate to us,

1158
01:03:07,280 --> 01:03:11,560
Speaker 1: either about Wicked Problems, Cleo dynamics, poverty, or any of

1159
01:03:11,600 --> 01:03:13,880
Speaker 1: the other topics that we talked about here today, you

1160
01:03:13,920 --> 01:03:16,160
Speaker 1: can send them to Carney the Robot. How do they

1161
01:03:16,160 --> 01:03:18,680
Speaker 1: get in touch with Carney the Robot? Oh, well, you know,

1162
01:03:18,680 --> 01:03:20,880
Speaker 1: there are a number of different ways to go about that.

1163
01:03:20,960 --> 01:03:23,680
Speaker 1: You can head on over to our various social media accounts.

1164
01:03:23,720 --> 01:03:26,760
Speaker 1: So we're on Facebook. That's where you'll find the Discussion

1165
01:03:26,840 --> 01:03:31,400
Speaker 1: Module group if you want to join that and interact

1166
01:03:31,440 --> 01:03:34,720
Speaker 1: with other listeners as well as as us. UH. You

1167
01:03:34,760 --> 01:03:38,480
Speaker 1: can also find us on Twitter, Tumbler, Instagram, The mothership

1168
01:03:38,960 --> 01:03:41,200
Speaker 1: is Stuff to Blow your Mind dot com. Yeah, that's

1169
01:03:41,200 --> 01:03:42,800
Speaker 1: where you'll find everything you need to know. That's where

1170
01:03:42,800 --> 01:03:44,960
Speaker 1: all the podcast episodes are, as well as links out

1171
01:03:44,960 --> 01:03:47,200
Speaker 1: to those other accounts, And if you want to get

1172
01:03:47,200 --> 01:03:49,600
Speaker 1: in touch with us directly, as always, you can email

1173
01:03:49,680 --> 01:03:52,280
Speaker 1: us at Blow the mind at how stuff works dot

1174
01:03:52,320 --> 01:04:04,320
Speaker 1: com for more on this and thousands of other topics.

1175
01:04:04,520 --> 01:04:28,800
Speaker 1: Does it How stuff works dot Com