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Speaker 1: Welcome to Stuff to Blow Your Mind from how Stuff

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Speaker 1: Works dot com. Hey, welcome to Stuff to Blow your Mind.

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Speaker 1: My name is Robert Lamb, and I'm Joe McCormick. And

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Speaker 1: Robert and I are going to be unavailable to record

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Speaker 1: a regular podcast this week because we're both going to

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Speaker 1: be recovering from some rather strange cranial surgery that involves

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Speaker 1: the expansion of the mind. Uh, new sences, new vistas.

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Speaker 1: So we're gonna be going to a happy place. But

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Speaker 1: in the meantime, we thought we'd take you back to

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Speaker 1: an old favorite. Yeah, this is our episode on the

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Speaker 1: science of coincidence. It's it's one that we really enjoyed

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Speaker 1: putting together. I think it's definitely an evergreen episode that

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Speaker 1: tests us, you know, it stands the test of time.

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Speaker 1: I think I recorded this one before I was actually

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Speaker 1: a host on the show. I was doing a guest episode.

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Speaker 1: This is one of the first ones I ever Did's right,

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Speaker 1: that's right. Yeah, So it's it's a strong one and

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Speaker 1: if you've heard it before, then I think it's a

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Speaker 1: perfect one to re experience. And if you are a

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Speaker 1: newer listener to the show, then hey, listen to it

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Speaker 1: for the first time. So without further ado, let's jump

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Speaker 1: into the repeat. So I've got one for you. Tell

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Speaker 1: me if you've heard this one before. Lincoln and Kennedy. Yes,

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Speaker 1: you know this. I was first exposed to this in

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Speaker 1: middle school when a teacher of mine get gave us

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Speaker 1: a list of these like it was some kind of

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Speaker 1: really important fact we needed to learn. But yeah, how

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Speaker 1: about this. Abraham Lincoln and John F. Kennedy, two American presidents.

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Speaker 1: Both were elected to Congress in the year forty six,

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Speaker 1: Lincoln in eighteen forty six, Kennedy in nineteen forty six.

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Speaker 1: Both were elected president in the year sixty, Lincoln in

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Speaker 1: eighteen sixty, Kennedy in nineteen sixty. Each of their last

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Speaker 1: names both contains seven letters. Uh. And then there's this

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Speaker 1: whole list of coincidences that keeps going. They were both

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Speaker 1: shot in the head, they were both assassinated by Southerners.

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Speaker 1: They were both succeeded by Southerners. Their vice presidents were Southerners.

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Speaker 1: Both vice presidents were named Johnson. What are the odds? Yeah,

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Speaker 1: I remember this being rolled out, perhaps in a history class,

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Speaker 1: and uh, you know that the list would start about

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Speaker 1: these coincidences, and I would kind of tune out after

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Speaker 1: the first one or two. Um, And I guess that

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Speaker 1: that kind of boils down to the type of people

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Speaker 1: in the world, like they're there are people out there

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Speaker 1: who just tune out after the first coincidence or two,

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Speaker 1: and then there are those who obsess about it and

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Speaker 1: see this as as something something really crucial and something

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Speaker 1: really telling about these two men, about the history of

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Speaker 1: this nation, et cetera. That might be the difference between us, Robert,

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Speaker 1: because I did not tune out. I was my mind

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Speaker 1: was blown to uh, to borrow from a popular phrase. Yeah,

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Speaker 1: I I sat there in my desk like, wow, what

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Speaker 1: are the odds? You know, must to be some kind

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Speaker 1: of ghost spirit controlling this. It just I was amazed

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Speaker 1: that there are two twin souls are basically the same

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Speaker 1: entity reincarnated and and and tracked hunted by the same

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Speaker 1: extra dimensional force. Yeah. Or there there was some sort

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Speaker 1: of like cosmic literature teacher trying to get me to

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Speaker 1: observe parallels between the meaning of these two men. Yeah,

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Speaker 1: it's another one of course that comes to mind is

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Speaker 1: the death of Thomas Jefferson and John Adams, two individuals who,

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Speaker 1: of course very interconnected in the history of the United

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Speaker 1: States as well. Sure, both instrumental drafting the Declaration of Independence,

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Speaker 1: which was signed to July four, seventy six. Both men

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Speaker 1: died on the same day, July four, eight twenty six,

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Speaker 1: exactly fifty years to the day after the document was ratified.

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Speaker 1: So that that you know that that kind of hits

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Speaker 1: you like. I like that one because that one's nice

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Speaker 1: and succinct. You know, what were the chances? You don't

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Speaker 1: need a list, it's right there. Yeah. I mean they

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Speaker 1: were they were good friends, so maybe there was you

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Speaker 1: could imagine some level of synchronicity about, you know, when

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Speaker 1: you're giving up and sort of handing it over to

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Speaker 1: the reaper. But but the dates are kind of compelling there.

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Speaker 1: It would be even crazier, though, if I found out

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Speaker 1: now that you played John Adams in a production of

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Speaker 1: seventeen seventy six. No, but I was in a production

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Speaker 1: of Seven Times. Here you go. I played Thomas Jefferson

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Speaker 1: in a been a production of seventeen seventy six. So

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Speaker 1: we're tied into it too. There's no escaping the black

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Speaker 1: hole of coincidence. Okay, I've got an even crazier coincidence. No,

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Speaker 1: it's probably not. This is kind of dumb, but why

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Speaker 1: do so many action heroes have the initials JB, James Bond,

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Speaker 1: Jason Bourne, Jack Bauer, Jack Burton my favorite? Well, I mean,

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Speaker 1: what are the chances? Actually, we have no idea, do we? Yeah?

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Speaker 1: I haven't read any I mean maybe there's some really

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Speaker 1: deep statistical study on this out there, but uh yeah,

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Speaker 1: maybe it is it that, on one hand, is just

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Speaker 1: possibly pure luck. And we only pick up right on

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Speaker 1: there there being a JB here, JB there, because we're

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Speaker 1: also not taking into account all the other j B

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Speaker 1: initials out there, like like does Jim being factor into this?

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Speaker 1: Probably not, and all of the action heroes that aren't

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Speaker 1: j B s. Yeah, And then to what extent is

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Speaker 1: it just completely almost subconscious? You know, because you have

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Speaker 1: an action hero and and by extension of action hero,

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Speaker 1: you think of mythological hero and the symbolic power of

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Speaker 1: the hero and how it resonates through uh, through our

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Speaker 1: culture and through through our our the way we view

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Speaker 1: the world, and and perhaps that ends up informing it.

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Speaker 1: You You have James Bond in your mind, and then

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Speaker 1: you end up creating Jason Bourne and Jack Bauer in

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Speaker 1: the same way, and I'm just purely spitballing here. You

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Speaker 1: could perhaps have the mythic hercules in your mind, and

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Speaker 1: then when you need to create another, you know, mythically

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Speaker 1: strong hero, perhaps you go with the Hulk. The same

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Speaker 1: kind of consonants. Yeah, we associate sounds with with ideas, certainly. Yeah,

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Speaker 1: now another crazy one. And I love this one in

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Speaker 1: part because it involves Edgar Allan Poe. Of course, Edgar

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Speaker 1: Allan Poe only wrote one novel his entire career, you know,

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Speaker 1: mostly known for his his excellent short stories. But the

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Speaker 1: novel in question published an eighteen thirty eight the narrative

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Speaker 1: of author Gordon Pym of Nantucket. I've never read it,

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Speaker 1: never mean, I never read any there. But the fiction

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Speaker 1: of this story is you have a crew of a

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Speaker 1: ship called Grampus. They wind up adrift with no food

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Speaker 1: or water, and so first they catch a towrartoise. They

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Speaker 1: eat it, but eventually they have to draw straws to

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Speaker 1: see who winds up as a dinner and uh an

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Speaker 1: individual named Richard Parker draws the short straw, so they

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Speaker 1: stab him and then they eat him. And then they

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Speaker 1: build a house on the boat so that they can

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Speaker 1: bury him behind the wall. Yeah, I mean, you gotta

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Speaker 1: play the greatest hits, right, here's where he gets crazy.

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Speaker 1: Years later, in eighteen eighty four, a yacht named the

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Speaker 1: minion Net leaves England, is headed towards Sydney, Australia, and

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Speaker 1: it sinks in a storm. Four men wind up adrift

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Speaker 1: in a lifeboat. They catch a turtle. They eat it

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Speaker 1: all right, But again you're probably thinking at this point, Okay,

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Speaker 1: you know turtles, how hard are they to catch? There

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Speaker 1: are lots of turtles in the world. They're all tasty. Yeah,

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Speaker 1: And if you're four men in a boat in the

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Speaker 1: middle of nowhere and you're hungry, you're gonna eat it.

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Speaker 1: No good deal. But then it turns to cannibalism, and

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Speaker 1: this too you might think, well, what a four guys

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Speaker 1: in the middle, in the middle of the ocean in

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Speaker 1: a little boat. They're hungry, They've only had one turtle

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Speaker 1: to eat. It's kind of inevitable, right, Well, this is

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Speaker 1: this is crazy. But aboard this vessel you have a

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Speaker 1: seventeen year old named Richard Parker, the same name as

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Speaker 1: the individual they ate in pose novel. This guy falls overboard,

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Speaker 1: drinks a bunch of seawater to quench his thirst. Uh.

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Speaker 1: And so he starts going, he starts deteriorating really quickly

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Speaker 1: here and they side, well, he's he's about to die.

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Speaker 1: We're gonna have to eat him, and they eat him.

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Speaker 1: So you have these this fictional account of cannibalism seeming

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Speaker 1: to inform this real life act of cannibalism years later,

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Speaker 1: and in almost identical circumstances. Yeah, and it's so gruesome

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Speaker 1: you can really doubt that they staged it to happen

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Speaker 1: on purpose because of the novel. Yeah, Like I can't

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Speaker 1: imagine them being on the boat and someone saying, look,

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Speaker 1: I read this book, and uh, there was a guy

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Speaker 1: in the book named Richard Parker, and they ate him

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Speaker 1: in your name is Richard Parker. So I'm not saying

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Speaker 1: we have to eat you, but come on. Yeah, it's

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Speaker 1: like the worst school play ever exactly. Alright. So in

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Speaker 1: this we're talking about coincidence, and in this episode we're

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Speaker 1: talking about coincidence and the science of coincidence, how we

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Speaker 1: perceive a coincidence. Uh, but let's let's get down to

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Speaker 1: brass tacks. What exactly is a coincidence? Yeah, and specifically

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Speaker 1: I think we should think about what's the difference between

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Speaker 1: a coincidence and just an improbable event um So of

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Speaker 1: standard Oxford dictionaries, definition is a remarkable concurrence of events

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Speaker 1: or circumstances without apparent causal connection. Okay, so that's sort

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Speaker 1: of playing up on the like the two different things coinciding,

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Speaker 1: like like the Pim right, like the Gordon Pim example,

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Speaker 1: or like Jefferson and Adams, you know, dying on the

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Speaker 1: same day. Another way of putting it is that it's

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Speaker 1: a concurrence of events that is quote perceived as meaningfully

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Speaker 1: related with no apparent causal connection. Um and and that

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Speaker 1: quotes from a paper that we're gonna end up talking

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Speaker 1: about later in this episode. But I think that's something

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Speaker 1: we should highlight, is that a coincidence has a perceptual element.

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Speaker 1: It's something that seems to be important to us, like

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Speaker 1: it has a psychic weight. But you know it, it

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Speaker 1: kind of comes back to what we're talking about earlier

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Speaker 1: about the two students in the classroom. One of them

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Speaker 1: is just enthralled by the Kennedy Lincoln coincidence list and

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Speaker 1: the other is, uh, it's just tunes out on it.

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Speaker 1: Because that that kind of comes down to how we

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Speaker 1: can look at coincidence in life. You can either say

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Speaker 1: was just pure dumblock. It is just a matter of statistics.

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Speaker 1: And then there's the the the view that there's something

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Speaker 1: else going on here, that there is some sort of connected,

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Speaker 1: connective tissue that we were just not privy to. And

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Speaker 1: we have seen some very you know, thoughtful and informed

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Speaker 1: study on both sides of the issue. Right, there have

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Speaker 1: been brilliant people throughout the years who paid way more

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Speaker 1: attention to coincidences than we might today. I mean, we

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Speaker 1: all experience coincidences. I would be shocked if there was

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Speaker 1: someone who would say, no, I've never experienced anything like

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Speaker 1: a really weird concurrence. It happens every single day. It

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Speaker 1: happened to us we were talking about while we were

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Speaker 1: researching these podcasts, like just strange topics coming up and

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Speaker 1: seemingly unrelated episodes. Yeah, I mean, of course, that kind

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Speaker 1: of gets down to that, like the power of coincidence.

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Speaker 1: Coincidence can can kill you, Coincidence can can make you rich.

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Speaker 1: Coincidence can just be this seemingly meaningless, little connective tissue

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Speaker 1: between two things. Um, and it's trapped. It's so easy

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Speaker 1: to fall into especially given how important causation and determination

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Speaker 1: are in human culture. Right, And we'll get more into

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Speaker 1: that later, but I mean you you almost can't fault

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Speaker 1: an individual for for thinking about these coincidences in terms

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Speaker 1: of some sort of connection. Now, and you see it

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Speaker 1: at every level. I mean, what is the meat cute

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Speaker 1: and every romantic comedy. It's always some kind of coincidence

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Speaker 1: that brings people together. And on the opposite end, you've

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Speaker 1: got famous scientists who have tried to investigate, you know,

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Speaker 1: what's the meaning of coincidences. I think one great example

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Speaker 1: is the Austrian biologists Paul Camera. Uh you know, if

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Speaker 1: if you ever have that feeling like wow, I think

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Speaker 1: everything's connected, he did too. So Paul Camera lived from

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Speaker 1: eighteen eighty to nineteen twenty six and he was a

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Speaker 1: proponent of Lamarckian evolution. Have you ever, I'm sure you're

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Speaker 1: familiar with this. This is the the one that, just

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Speaker 1: to give everyone a quick reminder, the idea that say, giraffes,

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Speaker 1: their next grow long because they're reaching for those top

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Speaker 1: those top leads, and so it's like one generation informing

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Speaker 1: the next. Yeah. So normally, now what we believe is

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Speaker 1: min Dalian genetics. You know, you inherit, you inherit your

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Speaker 1: genetic traits from your parents germ cells, and you pass

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Speaker 1: those same genetic traits onto your kids. And unless you

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Speaker 1: have a certain mutation, that can be basically random. But yeah,

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Speaker 1: Lamarchian ideas where that you could, you know, maybe if

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Speaker 1: you work out a lot or something, your kids will

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Speaker 1: be born with bigger muscles or something. You strain your

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Speaker 1: neck trying to reach something in this life, and in

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Speaker 1: the next life, your kids will have longer necks by

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Speaker 1: virtue of your straining. Yeah. And so in one famous experiment,

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Speaker 1: Camera claimed to have caused male specimens of a of

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Speaker 1: an animal called the midwife toad to grow these black

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Speaker 1: forearm pads that some species of male toads have, and

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Speaker 1: that they used them to hold onto females during mating. Unfortunately,

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Speaker 1: some other scientists in the field examined camera specimens and

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Speaker 1: found that the black pads on his toads had been

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Speaker 1: injected with artificial inc and so Camera denied responsibility for that.

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Speaker 1: And I guess nobody really knows whose fault that was,

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Speaker 1: but the accusation here would be that he cheated, which

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Speaker 1: is important because we'll come back to cheating, right. But

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Speaker 1: Camera wasn't only interested in toads and inheritance. He was

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Speaker 1: also interested in coincidences, like he kept a diary of

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Speaker 1: daily coincidences. And just one example against id it in

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Speaker 1: a in a paper that we're going to bring up

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Speaker 1: in a bit, his brother in law tells him that

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Speaker 1: he attended a concert and held both the ticket for

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Speaker 1: seat number nine and the coach check ticket numbered nine. WHOA, yeah, yeah.

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Speaker 1: But anyway, that itself doesn't seem all that interesting until

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Speaker 1: you start making lists, which Camera did, and he added

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Speaker 1: them up over time, and I have to admit, when

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Speaker 1: you add it's it's kind of like the Lincoln Kennedy thing.

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Speaker 1: The first one isn't all that interesting until you start

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Speaker 1: adding them together, and then it really gets your attention.

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Speaker 1: There's this cumulative effect of this like snowballing kind of attention,

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Speaker 1: getting significance of coincidences that pile up on each other.

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Speaker 1: So Camera organized these thoughts into a hypothesis he called

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Speaker 1: the law of seriality uh, and he posited basically this

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Speaker 1: underlying force in reality that was a quote world mosaic

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Speaker 1: or cosmic kaleidoscope that brings like objects and events together.

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Speaker 1: So almost a kind of emergent order, uh in the

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Speaker 1: Chaos show, which I can buy into. And we see

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Speaker 1: in emergence as as a major topic in understanding and intelligence, evolution, etcetera.

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Speaker 1: So why not coincidence? Sure? But of course Camera wasn't

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Speaker 1: the only scientist who has been interested in coincidences and

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Speaker 1: who has attributed some significant role in the universe to them.

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Speaker 1: Carl Young. Carl Young loved coincidences. Carl So, Carl Young

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Speaker 1: was a Swiss psychiatrist. You probably heard of him as

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Speaker 1: sort of like a he's one of the big names

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Speaker 1: in psychology and psychiatry following Freud. It's like the Mantle.

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Speaker 1: But Young was was very much into sort of interesting

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Speaker 1: borderline magical esoteric ideas. So he loved the paranormal. He

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Speaker 1: was interested in meaningful connections and mystical truths, esp astrology, psychokinesis,

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Speaker 1: all kinds of stuff like that. And so naturally he

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Speaker 1: was really interested in coincidences. And so he wrote a

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Speaker 1: book called Synchronicity and a Causal Connecting Principle. And this

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Speaker 1: book was actually uh, it was I think extracted from

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Speaker 1: a larger volume of his work and eventually published on

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Speaker 1: its own. But I read this book when I was

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Speaker 1: in college, and I remember thinking at the time, yet

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Speaker 1: again playing up on my I guess I'm susceptible to

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Speaker 1: this kind of thing. I was like, I wonder if

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Speaker 1: he's onto something here. It seemed really interesting. So what

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Speaker 1: kind of coincidences did Young notice? Well, he gives one example.

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Speaker 1: This is the one that's always cited. It's it's it's

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Speaker 1: his favorite example. It's the Golden Scarub. So in a

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Speaker 1: ninety one I believe it was essay on synchronicity. Young

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Speaker 1: told the story that he had been seeing a female

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Speaker 1: patient for psychoanalysis, and Young believed basically that she was

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Speaker 1: languishing because she was in sort of a prison of rationality.

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Speaker 1: She was just too rational. She she wouldn't quote open

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Speaker 1: up to the human side of life. For Young, I

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Speaker 1: think this had a decidedly sort of supernatural tinge to it.

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Speaker 1: And um, he wanted to uh and this is from

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Speaker 1: a particular translation quote sweeten her rationalism with a somewhat

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Speaker 1: more human understanding. So one day she was in psychoanalysis

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Speaker 1: telling him about a dream she had had where one

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Speaker 1: gave her a golden scarrub. And Young claims at that

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Speaker 1: very moment an insects started knocking against the window of

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Speaker 1: the office where they were, and he opened the window

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Speaker 1: and he caught the insect and it was a beatle.

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Speaker 1: It was a scarub type of beatle. And he said

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Speaker 1: it was like a green color, but in the right

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Speaker 1: light it reflected the light and looked gold. And then

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Speaker 1: he presented it to her in this moment of you know,

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Speaker 1: one of those there are more things in Heaven and

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Speaker 1: Earth than I dreamt of in your philosophy kind of moments,

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Speaker 1: and and he hoped that this helped shatter her rationalism.

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Speaker 1: And so I don't know if that happened to me.

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Speaker 1: If I had just been talking about a beatle and

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Speaker 1: then a beatle started knocking against the window, I'd probably

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Speaker 1: think that was interesting. But I don't know if I

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Speaker 1: had designed any meaning to it. Yeah, it doesn't really

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Speaker 1: smack of just Heaven sent beetle sent to you, open

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Speaker 1: up my mind and make me more, you know, in

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Speaker 1: love with life because of just a lot of beetles

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Speaker 1: flying around out there. Sure, but Young commented that when

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Speaker 1: coincidences like these accumulate, it's what we were talking about earlier.

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Speaker 1: The more of them happen, the more we take note

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Speaker 1: of them. Uh, and with good reason, because it's harder

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Speaker 1: to explain them away by random chance. The more they accumulate,

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Speaker 1: you fill up that entire diary with them, right, Yeah,

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Speaker 1: it has way to it exactly. So Young came up

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Speaker 1: with this term synchronicity to describe the a causal connecting

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Speaker 1: principle that links meaningfully significant events that couldn't be connected

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Speaker 1: by physical causes. So he's not saying that there's like

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Speaker 1: a there's like a you know, a ghost that put

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Speaker 1: the beetle there, because that would be in some way causal. Instead,

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Speaker 1: he's saying, there's another force in the universe other than causality.

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Speaker 1: It sort of runs parallel to causality that connects events

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Speaker 1: and and creates links of significance. But it's not physics.

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Speaker 1: Like I kind of in making sense of it in

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Speaker 1: my own head, I thought of it in terms of

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Speaker 1: this room or recording, in in which case we have

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Speaker 1: wires that are running outside of the walls, then running

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Speaker 1: across the floor and under the table, and then there

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Speaker 1: are the wires within the wall that we cannot see.

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Speaker 1: And so the wires that are running outside of the

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Speaker 1: walls are are kind of like causality. We can we

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Speaker 1: can see them. We're in causality. We our brain spends

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Speaker 1: a lot of time making sense of cause and effect.

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Speaker 1: But then there's this idea that there might be some

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Speaker 1: other force at work within the walls. We can't see it,

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Speaker 1: we're not we're not privy to it. It's exact in

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Speaker 1: an ins and outs, but it's it's making things interconnected.

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Speaker 1: It's it's these connections are popping up throughout our life,

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Speaker 1: throughout the Times game. Yeah, causality connects events in the

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Speaker 1: physical realm, and according to Young, synchronicity would connect events

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Speaker 1: in sort of like the psychic meaningfulness realm. That it

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Speaker 1: was this force it makes things have meaning and shows

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Speaker 1: us meaning by bringing unlikely events together. Okay, so this

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Speaker 1: would be kind of like an um. Have you seen Interstellar? Yes? Okay,

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Speaker 1: so there's the whole bit in there about love. Is

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Speaker 1: this uh, this connecting force like that seems to line

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Speaker 1: up rather closely with this idea of synchronicity. Yeah, I

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Speaker 1: think that makes sense. So coincidences obviously have this power

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Speaker 1: over us. They captivate us, they seem significance, They make

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Speaker 1: us wonder if there is some kind of magical or

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Speaker 1: super psychic force at work, and sometimes it can be

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Speaker 1: hard to tell because we don't know how to analyze coincidences,

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Speaker 1: you know, like there, when something happens, like you get

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Speaker 1: a number nine from the coach check and then you're

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Speaker 1: in seat number nine, there's really no reason to ask

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Speaker 1: why something like that happened, but you can perhaps ask,

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Speaker 1: wait a minute, did anything significant actually happen. Indeed, now

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Speaker 1: we've talked about the the sort of supernatural end of

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Speaker 1: the pool, the idea that there is some sort of

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Speaker 1: of intrinsic synchronicity connecting these these events, and now we're

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Speaker 1: gonna we're gonna look at a more critical and more

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Speaker 1: skeptical side of the pool. Right, So, several times so

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Speaker 1: far in this podcast we've referred ahead to a paper,

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Speaker 1: and this is sort of a classic paper in statistics

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Speaker 1: and mathematical analysis of coincidences, and it's called Methods for

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Speaker 1: Studying Coincidences. It was published by the Journal of the

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Speaker 1: American Statistical Association in December nineteen eighty nine. I think

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Speaker 1: it had been given at a been given as a

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Speaker 1: presentation in eighty seven a couple of years before. But

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Speaker 1: it's by Percy Diaconis and Frederick Moss Stellar, and they

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Speaker 1: were I believe, Harvard mathematicians, and Diaconis and Moss Stellar

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Speaker 1: offer four main categories of explanation for seeming examples of synchronicity.

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Speaker 1: You know, they refer to camera, they refer to young,

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Speaker 1: and they say, what what do we make of these events?

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Speaker 1: And and how can we tell if something is actually

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Speaker 1: going on that's worth noting. So the first of the

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Speaker 1: options is that there is an actual causal link. It's

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Speaker 1: not a coincidence, because there's a cause that to seemingly

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Speaker 1: disparate events happen together. The second one is psychology. It's

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Speaker 1: something about the way our brains work, the fact that

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Speaker 1: we're noticing what seemed to be coincidences, and will definitely

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Speaker 1: have more on that later. Another point is what they

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Speaker 1: call the multiplicity of end points, and this is going

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Speaker 1: to be about how how we count something as a hit.

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Speaker 1: And then the last one that they cite is called

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Speaker 1: the law of truly large numbers, and that's going to

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Speaker 1: be about statistical context. So I think we should go

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Speaker 1: back and look at causes first. So when something happens

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Speaker 1: that's seemingly just a huge coincidence, you should always consider

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Speaker 1: the fact that there might be a cause that's more

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Speaker 1: obvious than you realize. This would, of course be the

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Speaker 1: birthday problem, right, which is a problem that that people

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Speaker 1: will encounter just everywhere, right and in your workplace that's Google, etcetera.

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Speaker 1: I mean we can encounter it right here in the

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Speaker 1: podcast Chamber Joe Win your birthday July six, mind Sectober six?

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Speaker 1: Whoa synchronicity? Are you serious? I'm serious? Were sixteen sixteen? Okay?

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Speaker 1: What happened when you were sixteen? What city were you in? Oh, Paris, Tennessee.

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Speaker 1: I was in Tennessee too when I was sorry, I

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Speaker 1: was in faith fal Tennessee. But still Tennessee, Tennessee. Man,

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Speaker 1: some weirds going on? Yeah or but but worth noting

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Speaker 1: here is notice how we're we're singling in on the hits.

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Speaker 1: We totally missed the same day birthday by by many months,

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Speaker 1: but we're counting as a hit because we both had sixteen. Yeah,

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Speaker 1: so here's the birthday problem. Let's say you're in a

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Speaker 1: subway car and you're riding around with some random strangers,

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Speaker 1: and because you are extremely rude, you start getting people's attention,

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Speaker 1: getting them to take their headphones off, and you you

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Speaker 1: asked the strangers in the car all of their birthdays.

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Speaker 1: That's not rude, that's just good manners. I mean, it's

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Speaker 1: a it's a nice breaker. Okay, Yeah, you might want

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Speaker 1: to know if today's their birthday and you should for

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Speaker 1: them this cake that you found on the ground. Yeah,

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Speaker 1: So how many people would you have to ask before

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Speaker 1: it's more likely than not that you'd find two people

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Speaker 1: with the same exact birthday. Well, let's see, three sixty

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Speaker 1: five days in a year. Uh so you think, well,

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Speaker 1: maybe I need a talk to three sixty five people, right,

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Speaker 1: or maybe twice that. Yeah, I mean, I'm I'm not

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Speaker 1: good at doing math like that immediately, but that's where

425
00:24:25,600 --> 00:24:27,600
Speaker 1: I would have gone the first place in my head. Okay,

426
00:24:27,640 --> 00:24:30,399
Speaker 1: it's got to be like one in three sixty five

427
00:24:30,640 --> 00:24:34,040
Speaker 1: times two or something like that. But no, the answer

428
00:24:34,200 --> 00:24:37,800
Speaker 1: is twenty three. Okay, but we're not going to take

429
00:24:37,840 --> 00:24:39,399
Speaker 1: the time to explain all the math. You can go

430
00:24:39,520 --> 00:24:42,639
Speaker 1: look that up online. It is well documented. Uh, this

431
00:24:42,800 --> 00:24:46,000
Speaker 1: is a classic problem. If you ask twenty three people

432
00:24:46,800 --> 00:24:49,000
Speaker 1: in a room, in a train car, whatever, you have

433
00:24:49,119 --> 00:24:51,880
Speaker 1: reached the fifty fifty odds that two of them will

434
00:24:51,960 --> 00:24:54,399
Speaker 1: have the same birthday. And one of the key points

435
00:24:54,480 --> 00:24:57,760
Speaker 1: here is that you're not starting with the specified birthday.

436
00:24:57,800 --> 00:25:00,240
Speaker 1: You're not saying how many people do I have ask

437
00:25:00,359 --> 00:25:03,720
Speaker 1: before I find somebody with my birthday? You're trying to

438
00:25:03,800 --> 00:25:07,359
Speaker 1: find one match, right, Yeah, in this group of if

439
00:25:07,440 --> 00:25:10,639
Speaker 1: you ask twenty three people, odds are two of them

440
00:25:10,680 --> 00:25:13,280
Speaker 1: will have the same birthday. What if you want to

441
00:25:13,320 --> 00:25:16,040
Speaker 1: find three people with the same birthday, that's got to

442
00:25:16,080 --> 00:25:18,840
Speaker 1: be astronomical, right, I would think, so, I mean you

443
00:25:18,920 --> 00:25:21,800
Speaker 1: think that would just multiply it. Yeah, No, Actually, if

444
00:25:21,840 --> 00:25:24,800
Speaker 1: your train car can hold people, chances are in your

445
00:25:24,800 --> 00:25:27,640
Speaker 1: favor you reach odds again if you ask a D eight.

446
00:25:29,920 --> 00:25:33,879
Speaker 1: So that just shows that the statistical probability of in

447
00:25:34,000 --> 00:25:36,880
Speaker 1: this case this is a birthday match occurring, he's actually,

448
00:25:37,240 --> 00:25:43,400
Speaker 1: uh far greater than we we we may get a credit. Yeah.

449
00:25:43,560 --> 00:25:46,240
Speaker 1: I think the point is that we are often surprised

450
00:25:46,400 --> 00:25:51,280
Speaker 1: by events that are not statistically unlikely at all, Like

451
00:25:51,680 --> 00:25:55,960
Speaker 1: they just don't match our intuitions. Basically, what we we

452
00:25:56,119 --> 00:26:00,600
Speaker 1: have exaggerated intuitions for how unlikely some things are. Especially

453
00:26:00,720 --> 00:26:04,240
Speaker 1: it turns out particular types of things, for example, things

454
00:26:04,320 --> 00:26:06,800
Speaker 1: that happened to us. This is a funny thing we're

455
00:26:06,880 --> 00:26:10,439
Speaker 1: we're way more surprised about coincidences that happened to us

456
00:26:10,560 --> 00:26:13,760
Speaker 1: than coincidences that happened to other people. Oh yeah, because

457
00:26:13,760 --> 00:26:15,800
Speaker 1: we're all the center of our own stories, right, We're

458
00:26:15,840 --> 00:26:18,960
Speaker 1: gonna be We're more interesting, We're more invested in this one. Um.

459
00:26:19,280 --> 00:26:20,720
Speaker 1: I mean, just to come back to back to the

460
00:26:21,640 --> 00:26:24,240
Speaker 1: statistical possibilities, I mean, just thinking back to how we

461
00:26:24,320 --> 00:26:27,000
Speaker 1: both were like whoa sixteen, whoa Tennessee. But when you

462
00:26:27,040 --> 00:26:29,040
Speaker 1: really break it down, like the chances of us scoring

463
00:26:29,119 --> 00:26:32,440
Speaker 1: the same day, I mean the same date within a month,

464
00:26:32,560 --> 00:26:35,000
Speaker 1: that's what one and thirty one and thirty one chance

465
00:26:35,400 --> 00:26:38,359
Speaker 1: for the most part. And Tennessee, what we could say, Well,

466
00:26:38,400 --> 00:26:42,000
Speaker 1: we're both living and working in Atlanta, so there's probably

467
00:26:42,119 --> 00:26:45,720
Speaker 1: a reasonable chance that we would come from a southern state,

468
00:26:46,480 --> 00:26:50,680
Speaker 1: of which there are I mean, but not that many.

469
00:26:50,760 --> 00:26:54,040
Speaker 1: There's very many literature majors from Tennessee end up in Atlanta.

470
00:26:55,119 --> 00:26:58,840
Speaker 1: That's not unusual. Yeah, um, but so hey, there could

471
00:26:58,840 --> 00:27:02,000
Speaker 1: be another cause though. So that's just the apparent cause.

472
00:27:02,080 --> 00:27:06,480
Speaker 1: The cause that's um readily available. You just haven't looked

473
00:27:06,520 --> 00:27:10,240
Speaker 1: at the math. There could also be a hidden cause.

474
00:27:10,680 --> 00:27:13,200
Speaker 1: When something appears to be a coincidence, it's not actually

475
00:27:13,280 --> 00:27:16,359
Speaker 1: a coincidence because there's an actual causal link that you

476
00:27:16,520 --> 00:27:20,280
Speaker 1: don't know about. Um. The classic example of this would

477
00:27:20,320 --> 00:27:23,840
Speaker 1: be cheating and gambling. Yes, this is where a person

478
00:27:23,960 --> 00:27:26,040
Speaker 1: rolls a dice, right, Yeah, So so you roll a

479
00:27:26,080 --> 00:27:28,359
Speaker 1: pair of dice, you know, a hundred times in a row,

480
00:27:29,119 --> 00:27:33,040
Speaker 1: and let's say you you roll a seven nineties six

481
00:27:33,160 --> 00:27:36,080
Speaker 1: out of those hundred times. Yeah, like the more the

482
00:27:36,480 --> 00:27:38,200
Speaker 1: more every time you roll and you get the same

483
00:27:38,320 --> 00:27:42,000
Speaker 1: number he gets. That gets even more astronomical that have happened.

484
00:27:42,240 --> 00:27:45,760
Speaker 1: How could that possibly have happened? Well, obviously if there's

485
00:27:45,760 --> 00:27:48,240
Speaker 1: a hidden cause, which is the dice are loaded so

486
00:27:48,520 --> 00:27:51,200
Speaker 1: that they will turn up a seven pretty much every time.

487
00:27:52,119 --> 00:27:53,520
Speaker 1: So there you you you don't have to be a

488
00:27:53,560 --> 00:27:55,159
Speaker 1: god to do it. You just have to be a

489
00:27:55,280 --> 00:27:58,240
Speaker 1: cheater with a pair of loaded dice exactly. And another

490
00:27:58,320 --> 00:28:00,399
Speaker 1: example comes to mind. This was a going back to

491
00:28:00,480 --> 00:28:05,679
Speaker 1: Carl Young. Carl Young was associated with the physicist Wolfgang Polly,

492
00:28:06,640 --> 00:28:10,280
Speaker 1: and Polly was famous for coming up with the Polly

493
00:28:10,400 --> 00:28:13,400
Speaker 1: exclusion principle, which is important in quantum mechanics. I don't

494
00:28:13,440 --> 00:28:17,800
Speaker 1: remember exactly what it does right now, but that's right,

495
00:28:17,920 --> 00:28:21,040
Speaker 1: but yeah, he um, so he was a known physicist

496
00:28:21,119 --> 00:28:24,399
Speaker 1: and it did really important work. But Polly, I think,

497
00:28:24,520 --> 00:28:27,200
Speaker 1: was also sort of interested in the you know, strange

498
00:28:27,280 --> 00:28:32,479
Speaker 1: synchronicity type ideas, and Polly, in addition to the Polly principle,

499
00:28:32,520 --> 00:28:35,520
Speaker 1: which is an actual principle of science, wasn't known for

500
00:28:35,680 --> 00:28:39,800
Speaker 1: the Polly effect, which is a more anecdotal effect. But

501
00:28:40,480 --> 00:28:45,360
Speaker 1: the story goes like this, everywhere Wolfgang Polly went, machines broke. Ah.

502
00:28:45,520 --> 00:28:49,000
Speaker 1: This is the classic watch stopper scenario. Yeah, so he

503
00:28:49,040 --> 00:28:51,800
Speaker 1: would show up in a lab somewhere to test out

504
00:28:51,880 --> 00:28:54,480
Speaker 1: some equipment and what do you know, the equipment and

505
00:28:54,600 --> 00:28:56,600
Speaker 1: working today. Can't figure it out, And then he'd leave

506
00:28:56,680 --> 00:29:00,200
Speaker 1: the lab and suddenly it'd start working again. Uh. Don't

507
00:29:00,200 --> 00:29:02,000
Speaker 1: know how many of these stories are actually true, but

508
00:29:02,400 --> 00:29:06,440
Speaker 1: this is a popular anecdotal legend, and we'll just accept

509
00:29:06,560 --> 00:29:08,840
Speaker 1: that it's true for the purpose of the conversation. That

510
00:29:09,000 --> 00:29:11,720
Speaker 1: everywhere he went it seemed like stuff wouldn't work. In fact,

511
00:29:11,760 --> 00:29:15,560
Speaker 1: there was even one anecdote I read about where some

512
00:29:15,720 --> 00:29:18,120
Speaker 1: people were working in a lab and their equipment stopped

513
00:29:18,160 --> 00:29:21,320
Speaker 1: working and they joked, is you know Wolfgang here is

514
00:29:21,680 --> 00:29:24,120
Speaker 1: as he come down the hall uh and then later

515
00:29:24,240 --> 00:29:27,040
Speaker 1: they found out that he just happened to have been

516
00:29:27,240 --> 00:29:31,080
Speaker 1: changing trains in that city on that day at the

517
00:29:31,160 --> 00:29:35,480
Speaker 1: time that their equipment malfunction. He has some long reaching effects.

518
00:29:36,960 --> 00:29:42,320
Speaker 1: So whether or not that's true, right, let's go ahead

519
00:29:42,320 --> 00:29:45,400
Speaker 1: and settle now. But but if it were true, you

520
00:29:45,520 --> 00:29:49,280
Speaker 1: could perhaps look for actual hidden causes. It might not

521
00:29:49,520 --> 00:29:52,880
Speaker 1: be a synchronistic coincidence that, you know that the universe,

522
00:29:53,040 --> 00:29:57,840
Speaker 1: the the Unice Eunice Mundi is trying to tell Wolfgang

523
00:29:57,920 --> 00:30:00,680
Speaker 1: Polly something about his relationship with miche Jeans or something.

524
00:30:01,040 --> 00:30:03,920
Speaker 1: It could be perhaps that Polly had a habit of

525
00:30:04,000 --> 00:30:06,720
Speaker 1: scuffing around his office carpet before heading into the lab,

526
00:30:07,120 --> 00:30:09,280
Speaker 1: and that led him to discharge a lot of static

527
00:30:09,320 --> 00:30:13,120
Speaker 1: electricity which could break some really delicate instruments. Or Polly

528
00:30:13,400 --> 00:30:16,160
Speaker 1: is just really clumsy. Yeah, and of course he's also

529
00:30:16,200 --> 00:30:18,040
Speaker 1: not taken to account all of the machines that are

530
00:30:18,080 --> 00:30:21,680
Speaker 1: not breaking in Polly's life, right, it's literally everything he touches.

531
00:30:21,840 --> 00:30:24,360
Speaker 1: Does it just fall apart and rust, you know, before

532
00:30:24,520 --> 00:30:27,240
Speaker 1: his very eyes? Or is it just oh, this thing broke?

533
00:30:28,400 --> 00:30:30,760
Speaker 1: How could that happen? How could a machine and this

534
00:30:30,880 --> 00:30:34,960
Speaker 1: little device made by human how could this possibly stop working?

535
00:30:35,880 --> 00:30:37,360
Speaker 1: You know, so you end up that you end up

536
00:30:37,440 --> 00:30:40,520
Speaker 1: honing in on those instances where it doesn't work right.

537
00:30:40,560 --> 00:30:43,680
Speaker 1: And it's also i think probably not communicating the reality

538
00:30:43,800 --> 00:30:46,680
Speaker 1: about lab equipment, which is that it probably breaks all

539
00:30:46,760 --> 00:30:48,360
Speaker 1: the time, and there's a lot of it. Any lab

540
00:30:48,480 --> 00:30:50,160
Speaker 1: is going to have a lot of equipment, and all

541
00:30:50,240 --> 00:30:53,240
Speaker 1: of it has a half life and and and a

542
00:30:53,920 --> 00:30:57,760
Speaker 1: death point. Yeah. Um so, so yeah, that's the idea

543
00:30:57,800 --> 00:30:59,840
Speaker 1: of the hidden cause. And then of course those are

544
00:30:59,880 --> 00:31:03,400
Speaker 1: just some hypothetical examples were offering. The true hidden cause

545
00:31:03,440 --> 00:31:05,840
Speaker 1: would be the one we haven't even thought of, you know,

546
00:31:06,000 --> 00:31:09,480
Speaker 1: the cause that's an actual physical causal link that's causing

547
00:31:09,880 --> 00:31:13,600
Speaker 1: things to malfunction in Poulic's presence, but we can't even

548
00:31:13,640 --> 00:31:17,920
Speaker 1: guess what it is. It might be there. Yeah, so

549
00:31:17,960 --> 00:31:19,760
Speaker 1: I think we should move on to another one of

550
00:31:19,840 --> 00:31:22,560
Speaker 1: the points that Diaconis and Mostell are making their paper,

551
00:31:22,840 --> 00:31:26,760
Speaker 1: which is the quote multiplicity of end points or the

552
00:31:27,040 --> 00:31:30,560
Speaker 1: sort of like the cost of close point. Yeah, because

553
00:31:30,560 --> 00:31:34,080
Speaker 1: if we have already illustrated close counts and coincidence, like

554
00:31:34,120 --> 00:31:36,640
Speaker 1: when we're talking about birthdays, we were looking for the

555
00:31:36,720 --> 00:31:39,600
Speaker 1: same day in the same month, but we settled for sixteen.

556
00:31:39,760 --> 00:31:42,320
Speaker 1: You know, we were looking for the same Tennessee town

557
00:31:42,400 --> 00:31:44,600
Speaker 1: and oh my god, we accidentally went to the same

558
00:31:44,680 --> 00:31:46,720
Speaker 1: high school and didn't realize it. But we'll settle for

559
00:31:46,840 --> 00:31:49,360
Speaker 1: just the same state. And that's what we're doing. We're

560
00:31:49,400 --> 00:31:53,040
Speaker 1: we're constantly looking for these these little coins as to

561
00:31:53,160 --> 00:31:55,240
Speaker 1: line up, and we'll settle for something that's close. And

562
00:31:55,280 --> 00:31:59,520
Speaker 1: if you settle for close, the statistical possibilities just blow up,

563
00:31:59,640 --> 00:32:03,000
Speaker 1: such as of the birthday situation. Um, if you want

564
00:32:03,080 --> 00:32:05,479
Speaker 1: to uh to, uh to, if you want to hit

565
00:32:05,520 --> 00:32:08,080
Speaker 1: a near birthday match with a group of people. So

566
00:32:08,600 --> 00:32:10,880
Speaker 1: you're back on the train car, back on the train car,

567
00:32:11,360 --> 00:32:14,440
Speaker 1: and you're willing to to settle for all right, let's

568
00:32:14,440 --> 00:32:16,880
Speaker 1: see who on this train car has a birthday within

569
00:32:16,920 --> 00:32:18,920
Speaker 1: a day of each other. You know, we'll settle for

570
00:32:19,000 --> 00:32:22,560
Speaker 1: a close match. Then you only seven people are needed

571
00:32:22,640 --> 00:32:28,360
Speaker 1: for that. So yeah, so so coming down from from

572
00:32:28,560 --> 00:32:30,800
Speaker 1: a perfect match to a near match just opens it

573
00:32:30,880 --> 00:32:34,280
Speaker 1: up tremendously. And then, of course, when you think about

574
00:32:34,800 --> 00:32:38,160
Speaker 1: the accumulation effect that we were talking about earlier, it

575
00:32:38,280 --> 00:32:42,920
Speaker 1: makes it much easier. If you are accumulating close matches,

576
00:32:44,000 --> 00:32:46,560
Speaker 1: you keep building up close matches, and over time they

577
00:32:46,600 --> 00:32:50,200
Speaker 1: start to look significant because they just turned into hits

578
00:32:50,240 --> 00:32:52,920
Speaker 1: in your memory. You know, you don't remember, well, that

579
00:32:53,040 --> 00:32:55,640
Speaker 1: was kind of close. You remember, there's a hit, and

580
00:32:55,840 --> 00:32:58,560
Speaker 1: then another hit and then another hit. And some of

581
00:32:58,600 --> 00:33:01,840
Speaker 1: these might be actual hits, of these might be close hits,

582
00:33:02,240 --> 00:33:04,960
Speaker 1: but they all kind of blend together. Yeah, this brings

583
00:33:05,000 --> 00:33:07,760
Speaker 1: to mind like cold readings and uh, you know the

584
00:33:07,920 --> 00:33:10,480
Speaker 1: whole psychic game right where you throw out, oh, i'm

585
00:33:10,520 --> 00:33:13,360
Speaker 1: i'm I think there's somebody named Joe in your life

586
00:33:13,400 --> 00:33:14,959
Speaker 1: and you're like, well, I have an uncle Joseph. There

587
00:33:15,000 --> 00:33:17,600
Speaker 1: you go, close becomes a perfect match and then in

588
00:33:17,640 --> 00:33:19,080
Speaker 1: the blink of an eye, and then that is how

589
00:33:19,160 --> 00:33:23,040
Speaker 1: you reckon your memory. Okay. Then, also when studying coincidences,

590
00:33:23,120 --> 00:33:26,160
Speaker 1: that this is another category of of Diaconis and Mustellar.

591
00:33:26,240 --> 00:33:29,200
Speaker 1: There's the law of truly large numbers. And this is

592
00:33:29,240 --> 00:33:33,880
Speaker 1: a point about context. So let's say somebody encounters of

593
00:33:34,080 --> 00:33:37,520
Speaker 1: an event that is truly incredibly unlikely for a person

594
00:33:37,600 --> 00:33:40,040
Speaker 1: to experience. So it's not one of those things with

595
00:33:40,120 --> 00:33:42,920
Speaker 1: a hidden cause. It's not one of those things where

596
00:33:43,080 --> 00:33:45,800
Speaker 1: the odds are actually, you know, much more probable than

597
00:33:45,840 --> 00:33:50,440
Speaker 1: you realize. It's truly unlikely, you still have to consider context.

598
00:33:50,520 --> 00:33:54,520
Speaker 1: You have to consider this event against the vast number

599
00:33:54,600 --> 00:33:58,640
Speaker 1: of uncounted dice rolls of human experience that it is

600
00:33:58,760 --> 00:34:02,480
Speaker 1: nestled in. So here's an analogy. Let's say you're talking

601
00:34:02,520 --> 00:34:05,800
Speaker 1: to a professional poker player and she tells you one

602
00:34:05,920 --> 00:34:08,520
Speaker 1: time she was playing five card poker and she was

603
00:34:08,640 --> 00:34:11,759
Speaker 1: dealt a royal flush on the opening bet of a hand.

604
00:34:12,320 --> 00:34:14,160
Speaker 1: Then not to trade any cards, she just got a

605
00:34:14,239 --> 00:34:16,839
Speaker 1: royal flush. Now, the odds of being dealt a royal

606
00:34:16,920 --> 00:34:19,960
Speaker 1: flush or about one in six fifty thousand. I think

607
00:34:19,960 --> 00:34:23,080
Speaker 1: it's like sixty nine thousand or something like that, about

608
00:34:23,120 --> 00:34:26,360
Speaker 1: one and six d fifty. But you wouldn't say to

609
00:34:26,440 --> 00:34:29,800
Speaker 1: this poker player he must be lying or like you know,

610
00:34:29,960 --> 00:34:32,800
Speaker 1: or you must have been cheating in this game, because

611
00:34:32,840 --> 00:34:35,399
Speaker 1: you understand that the anecdote is in context. If she's

612
00:34:35,440 --> 00:34:38,640
Speaker 1: a professional poker player, depending on how long she's playing,

613
00:34:38,680 --> 00:34:41,560
Speaker 1: she might have been dealt hundreds of thousands of hands

614
00:34:41,600 --> 00:34:44,080
Speaker 1: in her life. And on top of that, she's one

615
00:34:44,200 --> 00:34:47,040
Speaker 1: player out of many, and maybe not everybody has had

616
00:34:47,120 --> 00:34:52,160
Speaker 1: that experience. So when considered in context, really improbable events

617
00:34:52,239 --> 00:34:54,800
Speaker 1: start looking like, oh okay, well, Yeah, this is the

618
00:34:54,880 --> 00:34:57,200
Speaker 1: one chance in however many. Yeah, this is kind of

619
00:34:57,280 --> 00:35:00,879
Speaker 1: the it'll it's bound to happen eventually, right, Like enough

620
00:35:00,960 --> 00:35:04,120
Speaker 1: people are trying a given thing, it's gonna line up.

621
00:35:04,160 --> 00:35:06,120
Speaker 1: The monkeys are going to compose the complete works of

622
00:35:06,160 --> 00:35:10,040
Speaker 1: Shakespeare than enough time. Yeah, So there are improbable events,

623
00:35:10,120 --> 00:35:12,839
Speaker 1: but there are just a lot of chances to achieve them.

624
00:35:13,480 --> 00:35:16,160
Speaker 1: There are seven point three billion people on Earth today,

625
00:35:16,520 --> 00:35:19,800
Speaker 1: and according to the Population Reference Bureau, there's an estimated

626
00:35:19,840 --> 00:35:22,960
Speaker 1: a hundred and eight billion people who have ever lived.

627
00:35:23,520 --> 00:35:26,080
Speaker 1: So considering that, if there's an event that has a

628
00:35:26,239 --> 00:35:28,680
Speaker 1: one in a million chance per year of occurring in

629
00:35:28,760 --> 00:35:31,320
Speaker 1: somebody's life, let's say it's I don't know what the

630
00:35:31,360 --> 00:35:34,160
Speaker 1: actual chance of this is, but having a baseball bat

631
00:35:34,360 --> 00:35:36,160
Speaker 1: thrown over a wall and it hits you on the

632
00:35:36,200 --> 00:35:40,160
Speaker 1: head or something, Uh, it should still happen to seventy

633
00:35:40,280 --> 00:35:43,759
Speaker 1: three hundred people every year, just given the population of

634
00:35:43,880 --> 00:35:47,960
Speaker 1: the Earth, that that is the probability. If there's a

635
00:35:48,239 --> 00:35:52,480
Speaker 1: one in ten billion chance of something ever occurring in

636
00:35:52,560 --> 00:35:54,960
Speaker 1: a human's life, it should still have happened to at

637
00:35:55,000 --> 00:35:57,680
Speaker 1: least ten people in human history. And it kind of

638
00:35:57,800 --> 00:36:00,480
Speaker 1: comes back around to the idea of think nicity the

639
00:36:00,800 --> 00:36:05,680
Speaker 1: union idea, because even though we're we're talking about about

640
00:36:05,760 --> 00:36:08,080
Speaker 1: real numbers and uh, and just our sort of our

641
00:36:08,080 --> 00:36:12,040
Speaker 1: inability to really make statistical sense of the actual odds

642
00:36:12,120 --> 00:36:15,840
Speaker 1: of things. Uh, those actual odds, the computation of those odds,

643
00:36:16,080 --> 00:36:18,080
Speaker 1: they kind of exist within the wall. They kind of

644
00:36:18,160 --> 00:36:22,520
Speaker 1: exist outside of our perception and our understanding of life

645
00:36:23,080 --> 00:36:27,239
Speaker 1: in the small sense, in the individual sense. So in

646
00:36:27,320 --> 00:36:32,320
Speaker 1: a way, uh, the synchronicity lines up well with with

647
00:36:32,520 --> 00:36:35,960
Speaker 1: it with the statistical likelihood of things happening. We just

648
00:36:36,120 --> 00:36:37,840
Speaker 1: we're just not privy to it. Yeah. I think that

649
00:36:37,880 --> 00:36:40,080
Speaker 1: connects back to the fact that there is a personal

650
00:36:40,160 --> 00:36:44,880
Speaker 1: significance for us even if there is not a statistical significance. Again,

651
00:36:45,360 --> 00:36:48,600
Speaker 1: it's not surprising that somebody won the lottery. It would

652
00:36:48,640 --> 00:36:51,560
Speaker 1: be really surprising if you won the lottery. That's not

653
00:36:51,760 --> 00:36:55,880
Speaker 1: actually objectively surprising, it's just surprising to you, which of

654
00:36:55,960 --> 00:36:58,560
Speaker 1: course brings us to psychology. Yeah, and we save this

655
00:36:58,680 --> 00:37:01,919
Speaker 1: for last because I think this might be the most

656
00:37:02,080 --> 00:37:05,160
Speaker 1: significant of all of these factors. And this is the

657
00:37:05,280 --> 00:37:09,080
Speaker 1: fact that sometimes it's not even the numbers. Sometimes it's

658
00:37:09,120 --> 00:37:12,560
Speaker 1: not even the data. It's just that we are wired

659
00:37:12,960 --> 00:37:16,480
Speaker 1: to bow at the altar of coincidence. It's how our

660
00:37:16,560 --> 00:37:18,960
Speaker 1: brains work, indeed, I mean, that's just how we survive.

661
00:37:19,080 --> 00:37:21,720
Speaker 1: That's how we make sense of the stimuli and our environment.

662
00:37:21,960 --> 00:37:23,920
Speaker 1: That's how we form our memories, and that's how we

663
00:37:24,440 --> 00:37:27,000
Speaker 1: plan for the future. Yeah, So let's look at some

664
00:37:27,160 --> 00:37:30,520
Speaker 1: psychological phenomenon that that are sort of related to our

665
00:37:31,160 --> 00:37:34,800
Speaker 1: tendency to take note of coincidences and maybe attribute to

666
00:37:34,880 --> 00:37:38,799
Speaker 1: them more magical significance than they might actually have. Uh,

667
00:37:39,120 --> 00:37:43,080
Speaker 1: how about even heard of the batter main Hoff phenomenon. Yeah,

668
00:37:43,360 --> 00:37:46,640
Speaker 1: this is the frequency illusion. This is I guess the

669
00:37:46,640 --> 00:37:48,800
Speaker 1: famous example of this would be you just learn a

670
00:37:48,840 --> 00:37:52,319
Speaker 1: new word, you know, you either encounter in a book

671
00:37:52,320 --> 00:37:54,120
Speaker 1: and you're like, WHOA, I don't know that when you

672
00:37:54,160 --> 00:37:56,560
Speaker 1: look it up, and your rather taken with it, and

673
00:37:56,719 --> 00:38:00,160
Speaker 1: then it seems to pop up everywhere you just learned it,

674
00:38:00,239 --> 00:38:02,440
Speaker 1: and it's all around you. So it's like discovering a

675
00:38:02,520 --> 00:38:05,600
Speaker 1: flower exists for the first time you've never seen before,

676
00:38:05,840 --> 00:38:07,600
Speaker 1: and then suddenly it seems to be growing in every

677
00:38:07,680 --> 00:38:11,480
Speaker 1: pot across town. Yeah. Yeah, And so the weird name

678
00:38:11,520 --> 00:38:15,480
Speaker 1: actually comes from a West German terrorist organization doesn't have

679
00:38:15,560 --> 00:38:18,000
Speaker 1: anything to do with them. Really. I I read that

680
00:38:18,120 --> 00:38:21,719
Speaker 1: the origin of this was that the phenomenon supposedly got

681
00:38:21,760 --> 00:38:24,399
Speaker 1: its name because a message board user somewhere online told

682
00:38:24,400 --> 00:38:28,160
Speaker 1: the story of encountering information about the batter Mine Hoff

683
00:38:28,200 --> 00:38:31,800
Speaker 1: Gang and then just suddenly seeing that again within like

684
00:38:31,880 --> 00:38:34,920
Speaker 1: twenty four hours. Um, and I'm sure this has happened

685
00:38:34,920 --> 00:38:36,960
Speaker 1: to you. It's happened to me all the time. This

686
00:38:37,080 --> 00:38:40,200
Speaker 1: actually happened to me while I was researching these podcasts

687
00:38:40,200 --> 00:38:44,640
Speaker 1: were recording today. So in the other podcast we're recording today, Uh,

688
00:38:44,800 --> 00:38:47,840
Speaker 1: there's a mention of Prince Chipi island off of the

689
00:38:48,120 --> 00:38:51,200
Speaker 1: west coast of Africa, and I had when I when

690
00:38:51,239 --> 00:38:52,920
Speaker 1: I got to them in the research, I realized I

691
00:38:52,960 --> 00:38:55,560
Speaker 1: had just been reading about that island for the first time,

692
00:38:55,680 --> 00:38:59,960
Speaker 1: like less than twenty four hours before, for completely unrelated read.

693
00:39:00,000 --> 00:39:03,879
Speaker 1: I'm not related to astronomy or anything, but see. Yeah,

694
00:39:03,880 --> 00:39:06,480
Speaker 1: you see those kind of weird littal coincidences pop up

695
00:39:07,000 --> 00:39:10,040
Speaker 1: all the time, and uh, I've often found that to

696
00:39:10,080 --> 00:39:13,120
Speaker 1: be the case to seemingly unrelated episodes, but there'll be

697
00:39:13,239 --> 00:39:16,360
Speaker 1: some little thread that connects them. Um. You know. Another

698
00:39:16,520 --> 00:39:18,919
Speaker 1: example the frequency illusion that I often see is I'll

699
00:39:19,200 --> 00:39:21,640
Speaker 1: I'll come across like a new concept or a concept

700
00:39:21,680 --> 00:39:23,279
Speaker 1: I wasn't that familiar with, and I'll do a deep

701
00:39:23,360 --> 00:39:25,600
Speaker 1: dive in in it for a podcast podcast such as

702
00:39:26,520 --> 00:39:30,319
Speaker 1: super Normal Stimuli. It was a big one, and after

703
00:39:30,520 --> 00:39:32,520
Speaker 1: I researched it, I was just I was just seeing

704
00:39:32,560 --> 00:39:34,840
Speaker 1: it everywhere like it. It kind of a topic like

705
00:39:34,960 --> 00:39:38,200
Speaker 1: that of you know, sufficient depth. It kind of changes

706
00:39:38,239 --> 00:39:40,239
Speaker 1: the way you look at the world and then you

707
00:39:40,400 --> 00:39:44,160
Speaker 1: see reflections of it just all around you. And uh

708
00:39:45,040 --> 00:39:47,680
Speaker 1: and and so it can be something as simple as

709
00:39:47,760 --> 00:39:50,480
Speaker 1: a as a word. It can be something that's you know,

710
00:39:50,640 --> 00:39:53,960
Speaker 1: a particular place, a particular you know, a particular band,

711
00:39:54,040 --> 00:39:57,200
Speaker 1: a particular work of a literature, or it can be uh,

712
00:39:57,320 --> 00:40:01,080
Speaker 1: you know, a philosophical mindset suddenly because you're aware of it,

713
00:40:01,239 --> 00:40:04,000
Speaker 1: you're hyper aware of it, you're excited about it, You're

714
00:40:04,040 --> 00:40:06,279
Speaker 1: going to see it in the rest of the world. Yeah,

715
00:40:06,640 --> 00:40:08,920
Speaker 1: um yeah. And there there could be lots of reasons.

716
00:40:09,239 --> 00:40:12,400
Speaker 1: One could be that hidden causal connection. You know, there

717
00:40:12,440 --> 00:40:16,560
Speaker 1: are actually reasons that you're investigating similar stories around the

718
00:40:16,600 --> 00:40:19,160
Speaker 1: same time, are reading similar material that might use a

719
00:40:19,200 --> 00:40:22,360
Speaker 1: new and unfamiliar word around the same time, because you

720
00:40:22,520 --> 00:40:26,879
Speaker 1: have interests and drives that are sort of unified by time. Uh. Also,

721
00:40:27,040 --> 00:40:29,200
Speaker 1: the authors of the paper we were talking about earlier

722
00:40:29,760 --> 00:40:32,920
Speaker 1: have that they have their own sort of mathematical analysis

723
00:40:33,000 --> 00:40:34,960
Speaker 1: of this, don't they. And they sort of explain how

724
00:40:35,320 --> 00:40:38,480
Speaker 1: it's not that unusual that you should, you know, at

725
00:40:38,480 --> 00:40:41,960
Speaker 1: a certain point, after acquiring a word for the first time,

726
00:40:42,000 --> 00:40:46,000
Speaker 1: see it again. Yeah, that's just sort of expected to happen. Yeah,

727
00:40:46,040 --> 00:40:48,000
Speaker 1: they're just there. There's a finite number of words that

728
00:40:48,239 --> 00:40:50,879
Speaker 1: you're going to see them again. Um. And of course

729
00:40:50,920 --> 00:40:55,920
Speaker 1: this plays into apothenia. Uh. This is uh, this is

730
00:40:55,960 --> 00:40:58,400
Speaker 1: a term comes to us from German science. Is Claus

731
00:40:58,480 --> 00:41:01,760
Speaker 1: Konrad who coined api finia from the Greek appo away

732
00:41:01,960 --> 00:41:06,279
Speaker 1: and uh uh and finea to show in nine and

733
00:41:06,320 --> 00:41:10,440
Speaker 1: he was studying acute schizophrenia, during which connections and meanings

734
00:41:10,520 --> 00:41:14,320
Speaker 1: seem to web together around unrelated details. So this is

735
00:41:14,480 --> 00:41:17,400
Speaker 1: the basic idea here is we're always looking for patterns

736
00:41:17,440 --> 00:41:19,879
Speaker 1: and signals from our environment. I mean, that's how we think,

737
00:41:19,960 --> 00:41:22,880
Speaker 1: that's how we live, that's how we survive, particularly when

738
00:41:22,920 --> 00:41:27,120
Speaker 1: it comes to assessing threats. Okay um, And so we

739
00:41:27,200 --> 00:41:29,880
Speaker 1: have we often have this tendency to perceive patterns and

740
00:41:29,920 --> 00:41:35,480
Speaker 1: connections in random or meaningless data. Um. For instance. Uh.

741
00:41:36,239 --> 00:41:37,840
Speaker 1: One example that comes to mind here is you have

742
00:41:37,920 --> 00:41:40,279
Speaker 1: some sort of silly police drama on right, They're looking

743
00:41:40,320 --> 00:41:42,120
Speaker 1: at a map of the city, and they have little

744
00:41:42,160 --> 00:41:44,400
Speaker 1: pins showing where the crimes are at. And then what

745
00:41:44,480 --> 00:41:46,399
Speaker 1: do they see. They see like a pentagram, Right, there's

746
00:41:46,800 --> 00:41:49,040
Speaker 1: some sort of order, And of course in the show

747
00:41:49,080 --> 00:41:51,879
Speaker 1: it always makes sense, right, like the the Satanic killer

748
00:41:51,960 --> 00:41:54,600
Speaker 1: actually is trying to kill people so that his crimes

749
00:41:54,600 --> 00:41:57,000
Speaker 1: look like a pentagram in a map. But you can

750
00:41:57,040 --> 00:41:59,719
Speaker 1: see that pentagram without any planning at all, or some

751
00:41:59,800 --> 00:42:01,279
Speaker 1: other or symbol. Yeah, if you want to see that

752
00:42:01,400 --> 00:42:03,759
Speaker 1: pentagram in the planning, you can see that pentagram in

753
00:42:03,800 --> 00:42:06,600
Speaker 1: the planning of just about anything. Um. But what this

754
00:42:06,719 --> 00:42:10,759
Speaker 1: basically breaks down to is a false positive in statistics,

755
00:42:11,560 --> 00:42:14,680
Speaker 1: a type one error in cognition. And this is something

756
00:42:14,719 --> 00:42:18,799
Speaker 1: that plays into religion, gambling, conspiracy theory, and just are

757
00:42:19,239 --> 00:42:21,920
Speaker 1: and also our need to see faces everywhere. Right. It's

758
00:42:21,920 --> 00:42:24,800
Speaker 1: the reason we see uh, figures in the constellations in

759
00:42:24,840 --> 00:42:27,200
Speaker 1: the sky, right. I mean it's a very few people

760
00:42:27,320 --> 00:42:30,800
Speaker 1: these days actually think that the stars were arranged to

761
00:42:31,000 --> 00:42:33,360
Speaker 1: look like a figure from Greek myth. Yeah, because you

762
00:42:33,440 --> 00:42:35,359
Speaker 1: think whoever was doing it would do a better job, right,

763
00:42:35,560 --> 00:42:38,480
Speaker 1: I mean, yeah, it's it's not very good. It's kind

764
00:42:38,480 --> 00:42:44,080
Speaker 1: of a crappy portrait. But you know people saw it. Yeah, yeah,

765
00:42:44,120 --> 00:42:46,040
Speaker 1: they saw the pattern and we just can't help. But see,

766
00:42:46,080 --> 00:42:49,960
Speaker 1: patterns were pattern recognition engines, as we've mentioned before here.

767
00:42:50,480 --> 00:42:53,600
Speaker 1: And there's the thing is there's an evolutionary advantage for

768
00:42:53,760 --> 00:42:57,399
Speaker 1: us pattern recognition apes in making that type one error

769
00:42:57,480 --> 00:42:59,400
Speaker 1: because essentially you have you have a you have a

770
00:42:59,440 --> 00:43:02,560
Speaker 1: type one air or any other type two right, false positive,

771
00:43:02,600 --> 00:43:06,520
Speaker 1: false negative. And the classic example is that of you know,

772
00:43:06,680 --> 00:43:10,200
Speaker 1: rustling in the bushes on the on the prehistoric savannah, right,

773
00:43:10,920 --> 00:43:14,160
Speaker 1: because there's a possibility that a big cat is about

774
00:43:14,200 --> 00:43:16,719
Speaker 1: to spring out of those rustling bushes and kill us,

775
00:43:16,920 --> 00:43:19,960
Speaker 1: or it could be the statistical noise of wind. Exactly.

776
00:43:20,560 --> 00:43:23,440
Speaker 1: A false positive just gets you hot and bothered over

777
00:43:23,520 --> 00:43:25,320
Speaker 1: nothing and maybe a good laugh. I thought it was

778
00:43:25,360 --> 00:43:28,120
Speaker 1: a tiger and it was just wind. But a false

779
00:43:28,200 --> 00:43:32,120
Speaker 1: negative that gets you killed. Yeah, so obvious, there's obviously

780
00:43:32,160 --> 00:43:36,400
Speaker 1: a selection pressure to favor false positives. Yeah, exactly. So

781
00:43:36,640 --> 00:43:39,279
Speaker 1: I mean so that just plays into how we think

782
00:43:39,360 --> 00:43:42,800
Speaker 1: and how we behave as humans and are overwhelming tendency

783
00:43:43,239 --> 00:43:45,439
Speaker 1: to see the pattern when there isn't one, to see

784
00:43:45,520 --> 00:43:48,080
Speaker 1: the connective tissue between events in this case, when there

785
00:43:48,160 --> 00:43:50,239
Speaker 1: isn't any right, So, yeah, and so in that way

786
00:43:50,320 --> 00:43:53,320
Speaker 1: a coincidence can represent a pattern to us, we start

787
00:43:53,520 --> 00:43:57,080
Speaker 1: thinking what does it mean? I mean, and there's likely

788
00:43:57,080 --> 00:44:00,399
Speaker 1: a connection between apophenia and creativity. This is a theory

789
00:44:00,440 --> 00:44:03,520
Speaker 1: that was put put forth by Swiss neurologist Peter Bruger

790
00:44:04,040 --> 00:44:06,640
Speaker 1: Uh in a two thousand one book, Hauntings and Poulter

791
00:44:06,719 --> 00:44:11,360
Speaker 1: Guy's Multidisiplinary Perspectives. And he was studying Apophanian patients suffering

792
00:44:11,400 --> 00:44:14,879
Speaker 1: from psychotic episodes UH that were beginning to find spontaneous

793
00:44:14,960 --> 00:44:17,680
Speaker 1: meaning and random aspects of their life. And his research

794
00:44:17,760 --> 00:44:21,480
Speaker 1: revealed that high levels of dopamine H disposes his patients

795
00:44:21,520 --> 00:44:25,080
Speaker 1: to find meetings, patterns, significance where there was there was none.

796
00:44:25,560 --> 00:44:31,200
Speaker 1: So creativity apophenia, Uh, you know, it's what is creativity.

797
00:44:31,280 --> 00:44:34,160
Speaker 1: But ultimately, you know, finding new patterns, new connections, new

798
00:44:34,239 --> 00:44:39,080
Speaker 1: ways to arrange existing ideas and motifs uh into something new, right,

799
00:44:39,719 --> 00:44:42,520
Speaker 1: of course, Yeah, I mean we often see that as

800
00:44:42,560 --> 00:44:45,239
Speaker 1: sort of the core of the creative principle. It's you know,

801
00:44:45,760 --> 00:44:48,799
Speaker 1: understanding like, oh, this is connected to this other thing.

802
00:44:49,160 --> 00:44:52,560
Speaker 1: And very often the connections you see between events or

803
00:44:52,640 --> 00:44:56,200
Speaker 1: objects or ideas and say a literature class or something

804
00:44:56,320 --> 00:45:00,960
Speaker 1: like that, are they are still psychic phenomenon. It's something

805
00:45:01,120 --> 00:45:04,120
Speaker 1: that we are putting together out of our need defined meaning.

806
00:45:04,880 --> 00:45:07,160
Speaker 1: That's right, and a lot of times that meaning that

807
00:45:07,280 --> 00:45:09,680
Speaker 1: we need to find. You know, we we already have

808
00:45:09,719 --> 00:45:12,160
Speaker 1: our our minds made up about what that meaning is.

809
00:45:12,480 --> 00:45:15,320
Speaker 1: This brings us to confirmation bias, which of course is

810
00:45:15,360 --> 00:45:17,960
Speaker 1: always a big one. This, of course is the idea

811
00:45:18,320 --> 00:45:20,840
Speaker 1: that we have a tendency to search for or interpret

812
00:45:20,920 --> 00:45:25,400
Speaker 1: information in a way that confirms your preconceptions about life,

813
00:45:25,560 --> 00:45:30,480
Speaker 1: about about basically anything, which leads to statistical errors that

814
00:45:30,600 --> 00:45:34,239
Speaker 1: cloud your decision and problem decision making, a problem solving ability. Yeah,

815
00:45:34,280 --> 00:45:36,640
Speaker 1: so this would come into play if say you are

816
00:45:36,760 --> 00:45:40,919
Speaker 1: already looking for a pattern of coincidences, say you've had

817
00:45:41,239 --> 00:45:45,120
Speaker 1: to like to sort of synchronous strange events happen in

818
00:45:45,280 --> 00:45:48,920
Speaker 1: one day, You're looking for a third and that's going

819
00:45:49,040 --> 00:45:52,280
Speaker 1: to bias the way that you sample data. It's probably

820
00:45:52,320 --> 00:45:54,239
Speaker 1: going to make you look for things that are sort

821
00:45:54,280 --> 00:45:57,400
Speaker 1: of a close hit something you might have ignored otherwise

822
00:45:57,520 --> 00:46:02,000
Speaker 1: to confirm your pattern. Hypoth assists that there's gonna be

823
00:46:02,080 --> 00:46:04,560
Speaker 1: something in line with this second thing. You know, it's

824
00:46:04,640 --> 00:46:07,560
Speaker 1: the same like people dye in threes. I was just

825
00:46:07,640 --> 00:46:10,080
Speaker 1: thinking of that. Yeah, like you, if you're lucky, you'll

826
00:46:10,120 --> 00:46:13,399
Speaker 1: get like to a list celebrities dying at the same time.

827
00:46:13,440 --> 00:46:15,239
Speaker 1: But then often like the third one has to be

828
00:46:15,760 --> 00:46:17,759
Speaker 1: like a radio star for the whole days. You know,

829
00:46:17,800 --> 00:46:19,840
Speaker 1: it's something that doesn't really match up, but you'll take it.

830
00:46:20,000 --> 00:46:23,480
Speaker 1: It's totally fleets the prophecy exactly right. It's confirmation by us.

831
00:46:23,520 --> 00:46:25,560
Speaker 1: You're you're bringing it in because you've got to make

832
00:46:25,640 --> 00:46:28,879
Speaker 1: it fit the pattern. Yeah, it's kind of like when

833
00:46:28,880 --> 00:46:31,320
Speaker 1: you listen to an episode of This American Life and

834
00:46:31,640 --> 00:46:33,400
Speaker 1: like that they have the theme for the show, and

835
00:46:33,480 --> 00:46:35,719
Speaker 1: like the intro hits the theme, the second segment really

836
00:46:35,800 --> 00:46:39,320
Speaker 1: hits the theme, the third segment, the second third segment,

837
00:46:39,360 --> 00:46:41,160
Speaker 1: you know they mostly hit this theme, and that last

838
00:46:41,239 --> 00:46:43,719
Speaker 1: one you're kind of like, I don't know, close enough,

839
00:46:43,880 --> 00:46:46,279
Speaker 1: close enough to close out the show, but you're really

840
00:46:46,360 --> 00:46:49,640
Speaker 1: kind of strayed from the overall theme. Um. But then

841
00:46:49,680 --> 00:46:53,520
Speaker 1: that's pretty much how we approach life in general, whether

842
00:46:53,560 --> 00:46:58,480
Speaker 1: you're talking about belief in UFOs, ancient Egyptians and alien tech, bigfoot,

843
00:46:59,040 --> 00:47:03,080
Speaker 1: or or office conspiracies, well, whatever it happens to be.

844
00:47:03,520 --> 00:47:06,080
Speaker 1: If you're looking for something to be true, uh, you

845
00:47:06,200 --> 00:47:10,120
Speaker 1: can find it. So if it plays into scientific analysis,

846
00:47:10,280 --> 00:47:12,360
Speaker 1: you have a you know, a theory you want and

847
00:47:12,480 --> 00:47:14,759
Speaker 1: you want to see it proven out, and you subconsciously

848
00:47:14,800 --> 00:47:18,040
Speaker 1: scow your the results of the experimentation in your favor.

849
00:47:18,840 --> 00:47:21,400
Speaker 1: You want to love that new movie that just hit

850
00:47:21,440 --> 00:47:23,920
Speaker 1: the theaters, so you wind up looking for reasons to

851
00:47:24,000 --> 00:47:26,359
Speaker 1: love it and focusing more on that and and being

852
00:47:26,440 --> 00:47:28,920
Speaker 1: perhaps a little less critical than you normally will. And then,

853
00:47:28,920 --> 00:47:31,800
Speaker 1: of course there's a racial aspect too, right you You,

854
00:47:31,920 --> 00:47:34,560
Speaker 1: if you happen to distrust members of another racial group,

855
00:47:34,600 --> 00:47:37,160
Speaker 1: you wind up focusing on the evidence that supports your

856
00:47:37,200 --> 00:47:41,040
Speaker 1: existing distrust rather than evidence that challenges it. Oh yeah,

857
00:47:41,080 --> 00:47:45,799
Speaker 1: people are definitely likely to oversample stuff that confirms their

858
00:47:45,840 --> 00:47:48,480
Speaker 1: bigotry or biases. So if yeah, if if you have

859
00:47:48,560 --> 00:47:52,880
Speaker 1: a preconceived stereotype, you're looking to make things fit evidence

860
00:47:52,960 --> 00:47:55,280
Speaker 1: that doesn't fit it, you just kind of like that's noise,

861
00:47:55,360 --> 00:47:56,880
Speaker 1: It doesn't matter. Yeah, I mean, for the most part,

862
00:47:56,920 --> 00:47:59,920
Speaker 1: you're kind of maintaining the castle of you know, fortress

863
00:48:00,080 --> 00:48:03,719
Speaker 1: sanity and fortress worldview and uh and and so you

864
00:48:03,800 --> 00:48:06,040
Speaker 1: want to to focus as much on the stuff that

865
00:48:06,120 --> 00:48:08,960
Speaker 1: keeps the walls up as possible. Yeah, of course this

866
00:48:09,040 --> 00:48:11,960
Speaker 1: all works perfectly because post addiction is largely a result

867
00:48:12,360 --> 00:48:16,400
Speaker 1: of the brain's task of continually integrating sensory stimuli and

868
00:48:16,560 --> 00:48:22,200
Speaker 1: reconciling conflicting information into a unified vision of reality, a

869
00:48:22,320 --> 00:48:25,960
Speaker 1: unified story again in which we are the central character. Yeah,

870
00:48:26,080 --> 00:48:28,040
Speaker 1: I mean, that's just simply how our memory. Yeah, I mean,

871
00:48:28,120 --> 00:48:31,040
Speaker 1: you you always see the pattern of clue is left

872
00:48:31,080 --> 00:48:33,560
Speaker 1: by the mystery writer once you've had the ending revealed.

873
00:48:34,160 --> 00:48:36,759
Speaker 1: You might not notice it while you're going through the

874
00:48:36,840 --> 00:48:42,600
Speaker 1: novel to the first time. All right, So there you

875
00:48:42,680 --> 00:48:45,160
Speaker 1: have it, the science of coincidence. Hope you enjoyed the

876
00:48:45,200 --> 00:48:48,279
Speaker 1: rerun or the first run if you had not heard

877
00:48:48,320 --> 00:48:50,359
Speaker 1: the previous one. Yeah, So I hope you will take

878
00:48:50,480 --> 00:48:52,359
Speaker 1: something away from this that you can apply to your

879
00:48:52,400 --> 00:48:55,280
Speaker 1: everyday life when you think about all those strange coincidences

880
00:48:55,360 --> 00:48:58,640
Speaker 1: you encounter day in and day out, and do they

881
00:48:58,760 --> 00:49:01,200
Speaker 1: really mean something. Indeed, now, in the meantime, if you

882
00:49:01,239 --> 00:49:03,359
Speaker 1: want to explore more episodes of Stuff to Blow your Mind,

883
00:49:03,600 --> 00:49:05,399
Speaker 1: head on over to stuff to Blow your Mind dot com.

884
00:49:05,480 --> 00:49:08,320
Speaker 1: After you will find all the podcast episodes. You'll find videos,

885
00:49:08,400 --> 00:49:10,279
Speaker 1: you'll find blog posts, you'll find link out to our

886
00:49:10,280 --> 00:49:13,040
Speaker 1: social media accounts such as Facebook and Twitter. We'll blow

887
00:49:13,080 --> 00:49:14,640
Speaker 1: the mind on both of those who also find us

888
00:49:14,680 --> 00:49:17,560
Speaker 1: on Instagram and Tumbler. And if you want to get

889
00:49:17,560 --> 00:49:20,000
Speaker 1: in touch with us with feedback on this episode or

890
00:49:20,000 --> 00:49:22,160
Speaker 1: any others, you can always email us at blow the

891
00:49:22,239 --> 00:49:34,120
Speaker 1: Mind at how stuff works dot com. Well more on

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00:49:34,200 --> 00:49:36,680
Speaker 1: this and batands of other topics. Is that how stuff

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00:49:36,719 --> 00:50:00,040
Speaker 1: Works dot com. It