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How Cognitive Biases Work · Stuff You Should Know

0:01
Speaker 1: Welcome to Stuff you Should Know, a production of iHeartRadio.
0:11
Speaker 2: Hey, and welcome to the podcast. I'm Josh, and there's
0:14
Speaker 2: Chuck and Jerry's here too, and we are getting down
0:16
Speaker 2: to business, getting right to it here on stuff you
0:19
Speaker 2: should know, because we've got a lot to cover here.
0:22
Speaker 2: That's right. So, Chuck, I got a little bit of
0:26
Speaker 2: an intro.
0:27
Speaker 1: Let's hear it was that it? That wasn't it?
0:32
Speaker 2: Do you remember how homeostasis used to come up a lot? Yes, So,
0:38
Speaker 2: for those of you who haven't been listening that long,
0:40
Speaker 2: homeostasis is what your body, in your mind and your
0:42
Speaker 2: brain wants to return to. Right. You just want everything
0:45
Speaker 2: nice and even, keel and normal and without exerting too
0:49
Speaker 2: much effort and energy. Right, that's homeostasis.
0:52
Speaker 1: That's are you asking me? Sure?
0:54
Speaker 2: Okay? So one of the ways that your brain returns
0:59
Speaker 2: to homeostasis as fast as it can is to use
1:02
Speaker 2: shortcuts in making decisions, right, Because if you're having to
1:07
Speaker 2: decide something, you're actively being challenged, you have to You're
1:10
Speaker 2: not in your homeostatic space. So if you use a shortcut,
1:15
Speaker 2: you can say something like I've had the red apple
1:19
Speaker 2: in the past and it was delicious, I've eaten the
1:22
Speaker 2: brown mushy one before and it was awful. I'm going
1:25
Speaker 2: to eat this red apple, right. Rather than going to
1:28
Speaker 2: the trouble of pulling both apples out and like analyzing
1:31
Speaker 2: them with a microscope and all that, you can just
1:33
Speaker 2: kind of use a little shortcut. That's a heuristic, and
1:36
Speaker 2: it makes a lot of sense because your brain is like, great,
1:38
Speaker 2: I didn't use that much energy. I made the right decision,
1:41
Speaker 2: and we're good to go. The problem that comes about, though,
1:46
Speaker 2: is that with heuristics, you're not always right. You don't
1:49
Speaker 2: always make the right decision, you're not always taking all
1:51
Speaker 2: of the information into account, and when that happens, you
1:55
Speaker 2: start stumbling into cognitive biases.
2:00
Speaker 1: Yeah. Like, this is a frustrating episode because I feel
2:04
Speaker 1: like the title could be cognitive bias is everything you
2:08
Speaker 1: think you know is wrong.
2:09
Speaker 2: Yeah, well that's a great title. Let's go with that.
2:12
Speaker 1: It just it made me feel like a dummy the
2:14
Speaker 1: whole time.
2:15
Speaker 2: Oh don't it's You're not a dummy. All humans are
2:19
Speaker 2: dummies as far as cognitive biases go. It's not just you,
2:22
Speaker 2: and this stuff is hardwired into us because like I
2:25
Speaker 2: just said, we take mental shortcuts and the problem, Chuck,
2:28
Speaker 2: is what we're talking about mostly today are unconscious biases. Right,
2:33
Speaker 2: there's conscious biases. We just usually call those biases, right,
2:37
Speaker 2: those are the active challenges that you need to overcome
2:40
Speaker 2: to be a better version of yourself. These are like unconscious.
2:45
Speaker 2: So there's not a lot you can do about it.
2:48
Speaker 2: Although at the end we're going to kind of give
2:50
Speaker 2: you some tips and pointers, but it's a challenge for
2:53
Speaker 2: absolutely everybody. Doesn't it doesn't make you dumb.
2:56
Speaker 1: Yeah, I mean I think the tips and things can help,
2:59
Speaker 1: for sure, But it's just part of being human, you know,
3:02
Speaker 1: the unconscious bias, and there's not a lot we can
3:05
Speaker 1: do to completely eradicate them. And if it's a you know,
3:10
Speaker 1: if it's a real problem, then I'm sorry.
3:14
Speaker 2: Well. One of the big problems that we all kind
3:17
Speaker 2: of face is that we are were predictably irrational, as
3:24
Speaker 2: was said by Dan Arielli, who was a behavioral economist,
3:30
Speaker 2: And because of that, corporations, marketers, basically everybody who wants
3:35
Speaker 2: to sell you something knows about these things, and they
3:38
Speaker 2: can manipulate those things. They can trick you into making
3:40
Speaker 2: decisions you wouldn't otherwise make.
3:42
Speaker 1: Yeah, for sure, And we wouldn't even be here probably
3:45
Speaker 1: talking about this, but hadn't been for two kind of
3:49
Speaker 1: revolutionary thinkers who ended up being some of the more
3:52
Speaker 1: off cited researchers in the history of research, as we'll learn,
3:56
Speaker 1: especially when it comes to economics. And they were a
4:00
Speaker 1: couple of psychologists, Israeli psychologists named Amos. And I looked
4:05
Speaker 1: up different ways to pronounce this because we always get
4:06
Speaker 1: guff and I've heard everything from hard Tbirski to his
4:12
Speaker 1: colleague Daniel Kahneman doing more of one of those Verski.
4:17
Speaker 2: Oh, I just heard him refer to him as Big T.
4:20
Speaker 1: The Big T because it's TV. But those were the
4:24
Speaker 1: two guys working together. They developed this concept in the
4:26
Speaker 1: seventies at the Hebrew University of Jerusalem and really like
4:33
Speaker 1: got down to it pretty quickly as a result of
4:37
Speaker 1: Connoman I think taking some issue with the Big T's research,
4:41
Speaker 1: and I guess they kind of bonded over that or something.
4:45
Speaker 2: Yeah, it was pretty cool because Tski, basically he was
4:50
Speaker 2: a mathematical psychologist, which anytime you hear mathematical and it's
4:55
Speaker 2: to do with something other than math, what that means
4:57
Speaker 2: is you've taken something and you've set it out in
5:00
Speaker 2: a very standardized way, so you can explore it, you
5:03
Speaker 2: can teach it based on certain facets and the upshot
5:06
Speaker 2: of mathematical psychology as far as human behavior goes. These
5:09
Speaker 2: are the people who came up with the kroc idea
5:12
Speaker 2: that humans behave as rational actors. We're self interested, we
5:17
Speaker 2: take all the best information available to make the best
5:20
Speaker 2: decision for ourselves. And Daniel Kaneman was like, this is
5:25
Speaker 2: not at all true, and he started challenging Amos Tawirski's
5:30
Speaker 2: theories and Tavsky instead of saying like, no, you shut up,
5:34
Speaker 2: he was like, all right, let's go figure out, let's
5:36
Speaker 2: get to the bottom of this. And because of that, Yeah,
5:38
Speaker 2: they formed this partnership that a huge impact on the world. Yeah.
5:42
Speaker 1: I think it's kind of heartening that they, as academics,
5:46
Speaker 1: you know, got together. There were no ruffled feathers or
5:49
Speaker 1: at least it didn't end up that way, and they
5:51
Speaker 1: work together. It's kind of a heartening thing I think
5:53
Speaker 1: these days.
5:54
Speaker 2: Yeah, there's got to be at least one.
5:56
Speaker 1: Yeah, that's right. They came up with a program called
5:59
Speaker 1: the Heroistics and Biases Program to basically, you know, study
6:04
Speaker 1: how human beings make their decisions, how they go through
6:06
Speaker 1: life making choices when they don't have like all the
6:11
Speaker 1: information at hand, all the most perfect information to make
6:14
Speaker 1: that choice, or if they don't have like all the
6:17
Speaker 1: time in the world to look at the information that
6:19
Speaker 1: they do have to make that choice. So, like, how
6:22
Speaker 1: are people making decisions? How are they making mistakes and
6:25
Speaker 1: their decision making? And they ended up coming up with
6:28
Speaker 1: a couple of different systems, one which is super quick,
6:32
Speaker 1: and one which is much more deliberate.
6:35
Speaker 2: Yeah, Daniel Kahman came out with Thinking Fast and Slow,
6:38
Speaker 2: which was one of those super popular airport books.
6:42
Speaker 1: You know, Yeah, thinking Comma faster.
6:45
Speaker 2: Yes, thank you, eat shoots and leaves, that's right. And
6:50
Speaker 2: in it he basically lays out this kind of shorthand models.
6:53
Speaker 2: He's very explicit to say, like this is not this
6:56
Speaker 2: is not how like your brain is actually laid out,
6:59
Speaker 2: but it's a good metaphor for it. And System one
7:01
Speaker 2: is how you think quickly, You think almost unconsciously, you
7:05
Speaker 2: make rapid decisions, and that is kind of how we
7:09
Speaker 2: generally navigate life. System two is much more deliberate. It's
7:13
Speaker 2: where we take into account like different ideas, It's where
7:16
Speaker 2: we really stop and think about something before making a decision,
7:20
Speaker 2: and they're essentially competing. There's something called interference, and system
7:26
Speaker 2: one has a really great tendency to interfere with system two.
7:30
Speaker 2: And there was a psychologist working all the way back
7:32
Speaker 2: in nineteen thirty five named John Ridley's Stroop who basically
7:37
Speaker 2: discovered the Stroop effect that is a way of demonstrating
7:40
Speaker 2: how system one interferes with the slower, more deliberate system too.
7:44
Speaker 1: Yeah, I bet a boy. I bet he patted himself
7:47
Speaker 1: on the back after this one, because it's one of
7:49
Speaker 1: those things that's so simple, But I bet he winked
7:52
Speaker 1: at everyone like watch this. Yeah, this is going to
7:55
Speaker 1: break your brain.
7:55
Speaker 2: It's genius.
7:57
Speaker 1: It really kind of is. So what they did was
7:59
Speaker 1: they simply wrote down the names of colors, but they
8:04
Speaker 1: would write down the name of that color in a
8:06
Speaker 1: different color, and then he would just say, as to
8:10
Speaker 1: the person to read out loud, the color of the
8:13
Speaker 1: word that is written, not the color that it's written in.
8:15
Speaker 1: And it is surprisingly difficult to do that. It's just
8:19
Speaker 1: a little weird brain breaking thing.
8:21
Speaker 2: Yeah. Yeah, so he's showing that your system one just
8:25
Speaker 2: wants to hurry up and read it, yeah, and it's
8:27
Speaker 2: getting it wrong and that's interference, right. So that kind
8:31
Speaker 2: of like started to lay the groundwork for this idea
8:34
Speaker 2: that we do have kind of competing ways of seeing
8:37
Speaker 2: the world and making decisions. And what Knoman was saying
8:43
Speaker 2: is that most of the decisions were walking around making
8:47
Speaker 2: are actually the System one super fast shorthand decisions. But
8:52
Speaker 2: we think that we're using our more rational mind because
8:55
Speaker 2: we make post hoc explanations for why we decided that.
9:00
Speaker 2: And that's not to say we're all walking around with
9:02
Speaker 2: these creepy little secrets that we know. We're like fooling ourselves.
9:05
Speaker 2: We don't realize we're doing this. That's why these biases
9:08
Speaker 2: are unconscious. Even if you stop and think about what
9:11
Speaker 2: you're doing, you may still not come up with the
9:14
Speaker 2: answer like, oh, yeah, I was making up explanations after
9:17
Speaker 2: the fact to explain why I actually used System two
9:20
Speaker 2: when I didn't. It's really hard to do that.
9:23
Speaker 1: Yeah, for sure, Livy gives a pretty good example of that.
9:26
Speaker 1: As far as like hiring somebody, Someone may make an
9:29
Speaker 1: impression in an interview that kind of locks it up
9:33
Speaker 1: from the second they walk in. Maybe they look like
9:36
Speaker 1: their mom or dad, or a relative, or maybe they
9:39
Speaker 1: remind them of themselves, or maybe like who knows what
9:41
Speaker 1: it could be. Then they end up getting that job,
9:44
Speaker 1: and later if you ask the person who hired them,
9:47
Speaker 1: you might say, oh, what it was because of this,
9:49
Speaker 1: this and this and this, when in fact that's really
9:51
Speaker 1: just system too kind of confirming, Like now it's because
9:55
Speaker 1: the guy walked in wearing a New York Giants T shirt.
9:58
Speaker 2: Yeah, and we'll get into some of the problems with
10:01
Speaker 2: the stuff throughout, but this is a good example. Right
10:04
Speaker 2: if the opposite happened, If like you didn't hire somebody
10:07
Speaker 2: because they weren't quite like you, that's an example of
10:11
Speaker 2: a bias too, even if you don't think that that's
10:14
Speaker 2: why you did it. If you're looking at their CV
10:16
Speaker 2: afterward and you're like, oh, they didn't graduate from college,
10:18
Speaker 2: it's why. But really it was not because you're racist,
10:22
Speaker 2: it's not because you're a woman hater. It was because
10:24
Speaker 2: you're preserving your own level of comfort because other groups
10:28
Speaker 2: that are different than you make you uncomfortable. And that's
10:31
Speaker 2: how groups can become entrenched. Right You just once one
10:35
Speaker 2: group kind of dominates an organization, they tend to continue
10:38
Speaker 2: doing that because people hire other people who they're comfortable around,
10:41
Speaker 2: rather than pushing themselves outside of their comfort zone and
10:45
Speaker 2: probably improving their organization. And that's why diversity programs exist
10:49
Speaker 2: in the first place, because of that human tendency.
10:52
Speaker 1: Yeah, or maybe they were just a Jets fan.
10:54
Speaker 2: That's possible. I mean, no Jets is going to hire
10:57
Speaker 2: a Giants fan.
10:58
Speaker 1: Yeah. Well, here's a tip. I don't know a lot
11:00
Speaker 1: about interviewing other than be yourself and try and get
11:02
Speaker 1: someone to like you. But don't go into any interview
11:05
Speaker 1: wearing any sort of branded sports apparel.
11:09
Speaker 2: Yeah, especially a jersey. Yeah, I think that says quite
11:13
Speaker 2: a bit.
11:14
Speaker 1: Yeah, you wear that Giants jersey in there. Well, I
11:17
Speaker 1: guess you're rolling the dice. You've either got that job
11:20
Speaker 1: right or there's no way you're going to get it.
11:21
Speaker 1: So maybe it's not a bad idea. Then I don't
11:24
Speaker 1: even know what I'm I might be wrong.
11:27
Speaker 2: Yeah, I mean, I guess if you dressed it up
11:29
Speaker 2: with a bow tie, maybe you could get away with it.
11:31
Speaker 2: But yes, it is still a gamble regardless.
11:33
Speaker 1: Well, not all jobs you have to wear a suit
11:35
Speaker 1: and tie, you.
11:36
Speaker 2: Realize, I know, But I'm saying, like you dress for
11:39
Speaker 2: the part you want. If you're wearing a giant's jersey
11:41
Speaker 2: with the bow tie, I think you're making a good
11:44
Speaker 2: impression out of the gate.
11:46
Speaker 1: All right, So I guess we can talk about We're
11:50
Speaker 1: going to go through a list of about ten different
11:52
Speaker 1: biases and they're all pretty interesting and I know everyone
11:56
Speaker 1: can identify with probably each of these at some point.
11:58
Speaker 1: But before we do that, we need to point out that, like,
12:02
Speaker 1: these are all mental shortcuts or the result of a
12:05
Speaker 1: mental shortcut, but not all of them work in the
12:07
Speaker 1: same way. And how our brains work, a lot of
12:10
Speaker 1: you know, there could be a lot of things at play.
12:12
Speaker 1: Emotions can come into play, maybe, like we were just
12:16
Speaker 1: talking about, like it's hard to reassess something after you've
12:20
Speaker 1: gotten a first impression. People humans historically through their life
12:24
Speaker 1: tend to make bad guesses at things because if you
12:27
Speaker 1: make great guesses, then things like you know, gambling would
12:31
Speaker 1: be super easy. So all of these things come into play.
12:35
Speaker 1: There's not just like a single way that this it's
12:37
Speaker 1: a broken system.
12:39
Speaker 2: Right yeah, yeah, yeah, But people generally, it seems like
12:44
Speaker 2: universally in a lot of these cases, behave in these
12:47
Speaker 2: ways under the same circumstances.
12:50
Speaker 1: Yeah, like some of their stuff wasn't replicatable, but that's
12:53
Speaker 1: sort of standard for studies in psychology. Like a lot
12:57
Speaker 1: of this stuff, as we'll see, has checked out across cultures.
13:00
Speaker 2: Yeah, which is huge, you know, considering the whole weird
13:03
Speaker 2: problem in psychology in.
13:05
Speaker 1: Particular that weird people.
13:08
Speaker 2: Are Western educated, industrial hich are Yeah, rich democratic, I think.
13:15
Speaker 1: All right, so we'll start. We'll leave the biggest guy
13:18
Speaker 1: for last, I think, which will be after a break probably,
13:20
Speaker 1: but we'll start then with maybe hindsight bias. And this
13:23
Speaker 1: is the idea that after something has occurred and we
13:27
Speaker 1: talked about this one before here and there, that we
13:30
Speaker 1: tend to think like, oh, well, of course that was
13:31
Speaker 1: going to happen. In fact, not only was that should
13:34
Speaker 1: I have seen that coming, It was probably inevitable that
13:37
Speaker 1: that happened. And a lot of a time maybe because
13:40
Speaker 1: you're misremembering your expectation before it even happened, right.
13:45
Speaker 2: Like we can rearrange our memory of how we felt
13:49
Speaker 2: about the event or the outcome of the event afterward
13:52
Speaker 2: to basically match the outcome. Yeah, I guess because we
13:55
Speaker 2: have this number ending need to be right.
13:57
Speaker 1: Yeah, that probably had something to do with it.
13:59
Speaker 2: I knew you were going to say that, so I've
14:05
Speaker 2: got another one for you, Chuck all right, self serving
14:08
Speaker 2: bias combined with a little fundamental attribution error on the side.
14:13
Speaker 1: Yeah, that's a good one. It's a good side dish.
14:15
Speaker 2: So these things basically go hand in hand. It's basically
14:19
Speaker 2: how we see ourselves in a great light and how
14:22
Speaker 2: we see other people in a more negative light. Self
14:24
Speaker 2: serving bias is basically saying, if something good happens to you,
14:28
Speaker 2: it's because you are good, like you earned it. It's
14:31
Speaker 2: because of you doing something right. Something bad happens to you,
14:35
Speaker 2: it's external forces that made that happen, right. Fundamental attribution
14:41
Speaker 2: error is the exact opposite with other people, If they
14:43
Speaker 2: do something right, it was just luck. If something bad
14:46
Speaker 2: happens to them, it's their own fault. So good example
14:49
Speaker 2: of this is like if a coworker comes in late
14:52
Speaker 2: one day, you're like, they're just lazy and slack, but
14:55
Speaker 2: then you come in late the next day and you're
14:57
Speaker 2: like it was traffic.
14:58
Speaker 1: Right.
14:59
Speaker 2: That's basically the two things going hand in hand, and
15:01
Speaker 2: those are those are both biases.
15:04
Speaker 1: Yeah, and I hope people understand that, Like all of
15:07
Speaker 1: those things can also be true. You know. Sure, so
15:11
Speaker 1: if you're if you're thinking like, well, no, but some
15:14
Speaker 1: you know, sometimes I did deserve the thing, and sometimes
15:17
Speaker 1: it was someone's fault. Yeah, sure, that can't happen. That's
15:20
Speaker 1: we're not These aren't absolutes.
15:22
Speaker 2: No, it's more just yeah, your your your tendency to
15:27
Speaker 2: think in certain ways. Yeah, sometimes you're going to be right.
15:30
Speaker 2: Sometimes you're going to be wrong for.
15:31
Speaker 1: Like humanities tendency. Yeah, you got to take a big
15:34
Speaker 1: broad view here.
15:35
Speaker 2: Yeah, but also you specifically right you James Kirkland listening
15:41
Speaker 2: in Baltimore.
15:42
Speaker 1: There's one. Oh, man, James Kirkland is going to pull
15:44
Speaker 1: over to the side of the road right now and really
15:47
Speaker 1: freak out.
15:48
Speaker 2: I hope, man, I hope I nailed it.
15:50
Speaker 1: Yeah, I think you picked a common enough name.
15:52
Speaker 2: We'll see, all right.
15:54
Speaker 1: So anchoring bias is another one. This one I've fallen
15:58
Speaker 1: prey too. I'm gonna say that probably about all these,
16:00
Speaker 1: but that is the first piece of info that you
16:02
Speaker 1: get about something can really affect and even in a
16:06
Speaker 1: very disproportional way, things that happen after that, Like, once
16:10
Speaker 1: something is kind of locked in, it's hard to unwind that.
16:14
Speaker 2: Yeah, that first piece of information, it's like, oh, okay,
16:17
Speaker 2: this is going to basically prime you in your answer
16:21
Speaker 2: your decision. Right. So a good example I saw is
16:24
Speaker 2: there was a study that says, like, Okay, the Mississippi
16:27
Speaker 2: River is less than two miles long, how long is it?
16:31
Speaker 2: And those people would say something like fifteen hundred miles.
16:34
Speaker 2: And then other people would say, okay, the Mississippi River
16:37
Speaker 2: is less than five hundred miles long, and people would
16:40
Speaker 2: say like, it's like three hundred miles. And then another
16:42
Speaker 2: group was the Mississippi River is less than eighty miles long.
16:45
Speaker 2: Those people would answer like sixty. It's the same thing,
16:49
Speaker 2: the length of the Mississippi River. But they were presented
16:52
Speaker 2: with this basically this priming number, a large one, a
16:55
Speaker 2: middle number, or a smaller number, and their answers were
16:59
Speaker 2: related to that first piece of information that they got,
17:02
Speaker 2: and that's anchoring bias.
17:04
Speaker 1: Yeah, And Livia pointed out another little side this year,
17:07
Speaker 1: which is called the decoy effect, and that's when you
17:10
Speaker 1: will go into a restaurant and they might and this
17:12
Speaker 1: is how just kind of one way this can affect economics,
17:16
Speaker 1: which will come up a lot. But you'll go into
17:17
Speaker 1: a restaurant and they might have one super expensive bottle
17:21
Speaker 1: of wine on the menu, and maybe it's even placed
17:24
Speaker 1: at the top so you see it first, and then
17:26
Speaker 1: the other bottles of wine might seem like a decent
17:29
Speaker 1: deal after that, even if they're also overpriced.
17:31
Speaker 2: Yeah, exploitation, but.
17:34
Speaker 1: All wine and restaurants is overpriced. I hope everyone realizes that.
17:37
Speaker 2: I mean buy a lot, right, Yeah, I think that
17:39
Speaker 2: most of their margin on that.
17:41
Speaker 1: Oh, totally. It's it's frustrating, but it's that's that's the business.
17:45
Speaker 2: Well, that's also I think, chuck. This anchoring bias is
17:48
Speaker 2: why they say you should never lead in a negotiation
17:50
Speaker 2: with your actual price that you want to go high
17:53
Speaker 2: or lower depending on your position.
17:56
Speaker 1: Oh like if they ask what you want to get paid?
17:58
Speaker 2: Yeah, or like you're trying question or something like that.
18:01
Speaker 1: You know, yeah, I hate all that stuff.
18:04
Speaker 2: Yeah. Yeah. If somebody it's like, well, what do you
18:07
Speaker 2: think I should get paid?
18:08
Speaker 1: You know, what are you looking to make at this job?
18:10
Speaker 1: But that's what I'm saying, what you make is should
18:12
Speaker 1: always be the answer.
18:14
Speaker 2: Exactly. You just want to add I don't know, fifty
18:17
Speaker 2: percent to what you actually want, and then you're away
18:19
Speaker 2: for negotiation. There's the one other thing that's related to
18:22
Speaker 2: this framing bias, and that's basically the same thing, but
18:25
Speaker 2: rather than the first piece of information guiding you, this
18:28
Speaker 2: is more directly guiding you. So for example, some drug
18:35
Speaker 2: maker says ten percent of patients die, You're like, oh god,
18:38
Speaker 2: that's a lot, right. You could say at the opposite weight,
18:41
Speaker 2: ninety percent of patients live and you're like, oh that's great,
18:44
Speaker 2: the same amount of people dying. It's just framed differently
18:47
Speaker 2: to exploit your your response.
18:51
Speaker 1: To exploit your aversion to dying.
18:55
Speaker 2: And that's a human thing, isn't it?
18:57
Speaker 1: For sure? Shall we take a break? Yeah, all right,
19:01
Speaker 1: Josh said human things. So it's time for a break
19:03
Speaker 1: and we're going to come back with more biases right
19:04
Speaker 1: after this.
19:34
Speaker 2: All right, chuck up to bat is number twenty three
19:38
Speaker 2: availability heuristic?
19:40
Speaker 1: Can we put like a stadium echo effect on that?
19:44
Speaker 2: Next to bat? Many motos?
19:47
Speaker 1: Very nice?
19:49
Speaker 2: So what is that availability heuristic? And I'm sure this
19:53
Speaker 2: has happened to you before.
19:54
Speaker 1: Right, Yeah, none of these have ever happened to you,
19:58
Speaker 1: which is a funny thing about us doing this episode.
20:00
Speaker 1: But the availability heuristic is what you have available to
20:06
Speaker 1: call up in your brain at any given moment, So
20:08
Speaker 1: you're you're going to rely more on what you can
20:12
Speaker 1: immediately think of in the moment, and chances are what
20:16
Speaker 1: you're immediately able to think of in the moment as
20:18
Speaker 1: something that probably aligns with your worldview or something like that,
20:22
Speaker 1: which is a sort of a well, we won't talk
20:24
Speaker 1: about the sea bias because that's coming up.
20:27
Speaker 2: Well, yeah, or something that like really kind of goosed
20:30
Speaker 2: you emotionally, like that's that's very available because it's wow,
20:34
Speaker 2: you know, loud and scary in your mind kind of
20:38
Speaker 2: you know, like if you saw something about a plane
20:42
Speaker 2: crash in the last like day or so, right when
20:44
Speaker 2: somebody asks you how frequent plane crashes are, you're probably
20:47
Speaker 2: going to give a much higher estimate than you would
20:49
Speaker 2: have before that, you know, maybe based on the number
20:52
Speaker 2: of times you've flown and nothing bad happened.
20:54
Speaker 1: Yeah, that's a good one.
20:57
Speaker 2: There's also an attentional blindness. And before anybody, before we
21:01
Speaker 2: talk about this, because we're gonna spoil it. Yeah, yeah,
21:04
Speaker 2: I want to send everybody, if you have the means
21:06
Speaker 2: to do this, go onto YouTube and search for selective
21:10
Speaker 2: attention test. And this is Daniel Simon's YouTube channel, and
21:15
Speaker 2: then watch the test where the people are passing the
21:18
Speaker 2: basketball back and forth. We'll wait a second.
21:21
Speaker 1: Dude, Okay, that's enough.
21:26
Speaker 2: All right, great, so hopefully you press pause and you
21:29
Speaker 2: didn't just try to watch it while we were while
21:31
Speaker 2: Chuck was doing the Jeopardy theme.
21:33
Speaker 1: It is short, but it's not that short.
21:35
Speaker 2: It's like a minute and a half or something, right, Yeah,
21:37
Speaker 2: So tell them about this video, Chuck, because it's pretty great.
21:40
Speaker 1: That's right. In the video, they have a group of
21:44
Speaker 1: what was it like six people, probably six on the nose,
21:49
Speaker 1: six college students I guess, Three are wearing white shirts,
21:52
Speaker 1: three are not wearing white shirts, and they're in a
21:55
Speaker 1: very tight, small circle. It looks very awkward. They have
21:59
Speaker 1: a I think was it two basketballs. There's two groups, yeah,
22:03
Speaker 1: two groups, two basketballs, and you're what you're told is
22:07
Speaker 1: the tasket hand is to count the number of times
22:09
Speaker 1: that people in white the white team are passing the basketball.
22:14
Speaker 1: So you're counting, right, one, two, three, four, four, five, six, seven,
22:19
Speaker 1: and that's all you're supposed to do. And at the
22:21
Speaker 1: end you're supposed to say, you know how many times
22:23
Speaker 1: they pass a basketball?
22:24
Speaker 2: Right?
22:24
Speaker 1: And now, now, hit them with the good stuff.
22:27
Speaker 2: So apparently half of the people who do this, which
22:32
Speaker 2: is astounding to me, half of the people who watch
22:35
Speaker 2: this video and take this test don't notice that in
22:38
Speaker 2: the middle of it, a person in a gorilla suit
22:41
Speaker 2: walks into frame and turns to the camera and I
22:44
Speaker 2: think beats on their chest and then walks out of frame.
22:48
Speaker 2: Like in the middle of these people throwing these basketballs
22:50
Speaker 2: around the gorilla, half of the people are paying such
22:54
Speaker 2: close attention to counting how many times the people wearing
22:58
Speaker 2: white T shirts are passing the basket well that they
23:00
Speaker 2: do not notice the gorilla until the end of the
23:03
Speaker 2: video when it's pointed out.
23:05
Speaker 1: Yeah, and we're assuming it's a person in a gorilla costume.
23:09
Speaker 2: I'm hoping, first of all.
23:10
Speaker 1: That might be a bias at play, that it's not
23:11
Speaker 1: a real gorilla.
23:13
Speaker 2: Well, I guess it depends on the amount of funding
23:15
Speaker 2: they had.
23:15
Speaker 1: Yeah, it looks actually like the gorilla from trading places.
23:19
Speaker 2: Totally, which is like, were they even trying? No, Okay, kid,
23:24
Speaker 2: I just wanted to make sure.
23:25
Speaker 1: Uh, did you watch this video Before you knew about this.
23:28
Speaker 2: I had heard it from some friends who were who
23:32
Speaker 2: do magic, and they were basically talking about this on
23:34
Speaker 2: a little podcast that they made.
23:36
Speaker 1: Who Bo Bobo, You are friends who do magic?
23:41
Speaker 2: So you know our friend Toby. Oh, yeah, he has
23:44
Speaker 2: very good friends that do magic.
23:46
Speaker 1: Wow.
23:46
Speaker 2: I became Yes, I became kind of friends with him.
23:50
Speaker 2: So yeah, I guess I do. I have friends that
23:52
Speaker 2: do magic.
23:53
Speaker 1: Well, buddy, next time we are in Los Angeles at
23:55
Speaker 1: the same time, our good friend and friend of the show,
23:58
Speaker 1: Adam Pranica, Yeah, is a member of the Magic Castle
24:03
Speaker 1: and it's one of his and his wife Elaine's favorite
24:05
Speaker 1: thing to do is to take friends to the Magic Castle.
24:08
Speaker 1: So have you ever been?
24:09
Speaker 2: No?
24:10
Speaker 1: And it is great fun.
24:11
Speaker 2: Adam Pranika just keeps getting better and better, doesn't he.
24:15
Speaker 1: Yeah. I haven't been with him, but I've been a
24:17
Speaker 1: couple of times, once many many years ago, then another
24:19
Speaker 1: probably ten years ago. But it's a lot of fun.
24:21
Speaker 1: I'm a big fan of magic. Yeah, And it's pretty magical.
24:25
Speaker 1: When people don't see that gorilla in a very tight frame,
24:28
Speaker 1: it's not like it's on a big basketball court and
24:31
Speaker 1: the gorilla sneaks in there like there's six people and
24:33
Speaker 1: then there's a seventh. Very clearly it is.
24:36
Speaker 2: It is very obvious so I mean, what this is
24:38
Speaker 2: showing is that our attention is limited, right, and we're
24:41
Speaker 2: really focused on a task. You you saw that gorilla.
24:46
Speaker 2: Those half of the people who didn't notice the gorilla,
24:48
Speaker 2: you still saw it, but you're still focused on the task.
24:51
Speaker 2: That your brain was just getting rid of information that
24:53
Speaker 2: was unrelated to the task because it's not pertinent. It
24:57
Speaker 2: can become pertinent though, when that gorilla decide to attack you.
25:01
Speaker 2: And so this is a cognitive bias we have where
25:04
Speaker 2: we're ignoring potentially unimportant information to take in the stuff
25:10
Speaker 2: that's related to the task at hand. Yeah.
25:12
Speaker 1: Well, you know where they could really get away with
25:14
Speaker 1: this because where you have great concentration. Is it a
25:17
Speaker 1: professional sports game on the jumbo tron when they have
25:20
Speaker 1: the baseball under the helmet or whatever, uh huh, and
25:23
Speaker 1: then they're moving them around and you got to find
25:25
Speaker 1: you know, it's like three card money, yep, Because you're
25:27
Speaker 1: concentrating so hard on that, they could they could put
25:30
Speaker 1: whatever they wanted on that screen while that's going on,
25:32
Speaker 1: And I bet you most people would not or maybe
25:35
Speaker 1: I guess it's half if that's what they found.
25:37
Speaker 2: Yeah, I'll bet you're right. I'll bet you're right, man.
25:40
Speaker 1: I was just trying to think of something where you're
25:41
Speaker 1: super trying to follow because I was happy I came
25:44
Speaker 1: up with the correct amount of passes at the end.
25:46
Speaker 2: You did. You said, what does it mean if I
25:49
Speaker 2: noticed the gorilla and got the correct number of passes?
25:52
Speaker 2: And I said, it means you're a perfect human.
25:53
Speaker 1: That's right, which we all know is not true.
25:57
Speaker 2: None of us are, Chuck, None of us are.
25:59
Speaker 1: Yeah, I know.
26:00
Speaker 2: So there's another one that you may have heard of before,
26:02
Speaker 2: even if you've not heard of any of these other ones,
26:04
Speaker 2: called the Dunning Kruger effect. It became kind of viral
26:07
Speaker 2: because if you take it through the pop culture meat grinder,
26:11
Speaker 2: it becomes much more simplified and kind of loses some
26:14
Speaker 2: of its actuality. But yeah, people still like it because
26:18
Speaker 2: it's a good way to put other people down.
26:20
Speaker 1: Yeah, it is. This is the idea that the correct
26:23
Speaker 1: idea is that people with a little understanding in an
26:27
Speaker 1: area tend to overestimate their ability and their knowledge about something,
26:31
Speaker 1: right because they don't They know so little they don't
26:34
Speaker 1: even know what they don't know. Kind of right exactly,
26:37
Speaker 1: But what you were talking about, it's kind of been
26:39
Speaker 1: transformed into like morons have them are the most like braggadocious,
26:44
Speaker 1: which can be true.
26:47
Speaker 2: It can be you know. I think that's one of
26:49
Speaker 2: the things. Like you said, you can be right with
26:51
Speaker 2: cognitive biases, you're not wrong with them all the time.
26:53
Speaker 2: So yeah, that kind of supports that, But that's not
26:56
Speaker 2: what the Dunning Kruger effect actually says. You said it.
26:59
Speaker 2: And then there's the opposite way too, where the more
27:02
Speaker 2: experience you have, the more expert you are in a field,
27:06
Speaker 2: the more you assume that it should be easier for
27:10
Speaker 2: you than it is.
27:12
Speaker 1: Yeah. That's a very valuable thing to understand, I think,
27:15
Speaker 1: and you get much further in life if people are like, well,
27:19
Speaker 1: you're the expert, and the experts usually the one going yeah,
27:22
Speaker 1: but I don't know, maybe we should hold off because
27:25
Speaker 1: you know X, Y and Z.
27:27
Speaker 2: Right. Yeah, So that's the actual Dunning Kruger effect, and
27:30
Speaker 2: I saw that it's it's being assailed right now. People
27:33
Speaker 2: are showing a question even the basic version of it,
27:36
Speaker 2: like the actually academic version of it. Yeah, so we'll
27:39
Speaker 2: see what happens with that.
27:40
Speaker 1: Oh interesting. We've got the gambler's fallacy next, and that
27:44
Speaker 1: is oh boy, if you have ever gambled anywhere. But
27:49
Speaker 1: if you like go to casinos and stuff like that,
27:52
Speaker 1: you're going to see this all over the place. You're
27:54
Speaker 1: going to hear it spoken out loud. And this is
27:56
Speaker 1: the idea that you find patterns where there are no patterns.
28:01
Speaker 2: Yeah.
28:01
Speaker 1: So if you're at the blackjack table and you hear
28:04
Speaker 1: the person next to you like, well, oh, man, see,
28:08
Speaker 1: I've lost four in a row, so I'm gonna bet, like,
28:10
Speaker 1: I'm gonna go all in on this because I'm bound
28:13
Speaker 1: to win because I've lost four in a row. There's
28:14
Speaker 1: no way I'm gonna lose five in a row.
28:16
Speaker 2: Right. The problem is is those each of those hands
28:19
Speaker 2: of blackjack are unrelated to one another. They don't form
28:22
Speaker 2: a pattern. But you are predicting a pattern that just
28:26
Speaker 2: doesn't exist. Yeah, that means you're a fallacious gambler.
28:29
Speaker 1: I can get you in real trouble. I mean it's
28:33
Speaker 1: you can do the same thing on the playground with
28:35
Speaker 1: coin tosses. In fact, coin tosses, I think is a
28:37
Speaker 1: lot of a lot of times the way they sort
28:39
Speaker 1: of try and prove.
28:41
Speaker 2: This, Yeah, because each coin toss, considering like you're playing
28:45
Speaker 2: with a perfect unflogged coin that has no bias whatsoever.
28:49
Speaker 2: Each coin toss is totally unrelated to the last. So
28:52
Speaker 2: you could get one hundred heads in a row and
28:54
Speaker 2: that doesn't mean anything. It doesn't mean a tail is coming,
28:57
Speaker 2: because that each of those hundred heads in each of
29:00
Speaker 2: those coin tosses had nothing to do with the last
29:03
Speaker 2: one or the next one.
29:05
Speaker 1: I know. That's hard to break out of, though, because
29:07
Speaker 1: it seems very human to think like they've flipped foreheads
29:10
Speaker 1: in a row. There's no way there's going to be
29:11
Speaker 1: a fit.
29:12
Speaker 2: Well, that's another reason why this is so hard. We're
29:14
Speaker 2: hardwired to find patterns and stuff. It's a way to
29:17
Speaker 2: navigate the world. The way we navigate the world is
29:20
Speaker 2: by finding patterns so that we can recognize things in
29:22
Speaker 2: the future and thus spend less energy getting back to homeostasis.
29:26
Speaker 1: That's right, This is all so interesting to me.
29:29
Speaker 2: I love this stuff.
29:30
Speaker 1: I knew that you loved it. This is Josh Clark Central.
29:33
Speaker 2: I love observing it because I can't grasp what it
29:36
Speaker 2: feels like to suffer any of these, So just to
29:39
Speaker 2: discuss it and in this way is really fascinating to me.
29:42
Speaker 1: All right, let's talk about the base rate fallacy That
29:45
Speaker 1: means you put more weight on just like one very
29:49
Speaker 1: specific piece of information instead of looking at all the
29:52
Speaker 1: pieces of information that have come your way.
29:54
Speaker 2: Yeah, and usually it's individuated information, meaning like say some
29:59
Speaker 2: quality or careacteristic of one person, and then you're ignoring
30:03
Speaker 2: the base rate, which is like pure statistical information about
30:06
Speaker 2: what you're trying to figure out. And a really good
30:09
Speaker 2: example of this is like, let's say that you are
30:12
Speaker 2: looking at somebody who is super fit, a woman who's
30:14
Speaker 2: very fit and athletic, and you're asked, do you think
30:18
Speaker 2: that woman is a personal trainer or a teacher, Because
30:21
Speaker 2: the basically the only evidence you have there is that
30:24
Speaker 2: this woman is very athletic and fit. You might say
30:28
Speaker 2: personal trainer. But if you took all the base rate
30:31
Speaker 2: information into account, you would know that even the very say,
30:36
Speaker 2: very small portion of teachers who are very fit and
30:40
Speaker 2: athletic may be small compared to the total number of teachers,
30:44
Speaker 2: it's still much larger than the total number of personal
30:48
Speaker 2: trainers in the world. So statistically speaking, it's much likelier
30:52
Speaker 2: that that very fit athletic woman is a teacher and
30:55
Speaker 2: not a personal trainer. You don't do that because you
30:58
Speaker 2: think personal trainer athletic fit must be a personal trainer.
31:02
Speaker 2: You've just fallen prey to the base rate fallacy.
31:05
Speaker 1: My friend, Yeah, but she has on yoga pants and
31:08
Speaker 1: hokuhs exactly. That doesn't narrow down anything these days.
31:13
Speaker 2: You know, how about the mere exposure effect, Chuck, and like,
31:18
Speaker 2: mirror is part of it. I'm not making a judgment
31:20
Speaker 2: about it.
31:21
Speaker 1: That's right. That means just merely being exposed to something
31:26
Speaker 1: has a vast impact. So the more we experience something,
31:31
Speaker 1: the more you like it, which is why you see
31:33
Speaker 1: that commercial for the thing over and over and over,
31:36
Speaker 1: that burger king ad over and over and over. Although
31:40
Speaker 1: I wouldn't say that you might like that one the
31:42
Speaker 1: more you heard it.
31:44
Speaker 2: That's the outlier for me too.
31:46
Speaker 1: But that's the idea. Though there's just just mere exposure,
31:51
Speaker 1: we'll get you there.
31:52
Speaker 2: And then there's a related thing called the illusory truth effect,
31:54
Speaker 2: which is basically that repeated exposure to a lie causes
32:00
Speaker 2: you to eventually believe in it if you hear it
32:02
Speaker 2: enough times, even if you initially knew that it wasn't true.
32:07
Speaker 2: So that makes me wonder if like it just wears
32:10
Speaker 2: you down over time, like your brain is tired of
32:12
Speaker 2: defending itself against being assailed with a lie. And it's
32:15
Speaker 2: just like, fine, that's true. I don't I don't care.
32:18
Speaker 1: Yeah, I mean sure, politics certainly comes to mind. Repeat
32:22
Speaker 1: the lie, repeat the lie, repeat the lie.
32:23
Speaker 2: Yeah, And I mean like it's a viable way to
32:26
Speaker 2: exploit people's cognitive biases in that In that respect.
32:30
Speaker 1: Should we end up should we close out with the
32:33
Speaker 1: big daddy of them all, the big c the big
32:35
Speaker 1: confirmation bias?
32:36
Speaker 2: Yeah, let's do it, baby.
32:38
Speaker 1: All right, why don't you start this one?
32:41
Speaker 2: Okay, So there's a guy named Peter Wasason back in
32:43
Speaker 2: the sixties. He coined the term confirmation bias, and he
32:48
Speaker 2: basically had an experiment that's really clever. It's hard to
32:51
Speaker 2: understand at first, but it's very clever. He basically said, hey,
32:55
Speaker 2: here is a sequence of numbers two, four, and six.
32:59
Speaker 2: Figure out what the pattern is. Just to be clear,
33:02
Speaker 2: this is really hard to explain. If if you find
33:07
Speaker 2: somebody who can explain this, well you'll get it. But
33:10
Speaker 2: I don't think I'm a candidate for that. I think
33:13
Speaker 2: we all know that I'm not going to explain this
33:15
Speaker 2: very well.
33:16
Speaker 1: Oh I don't think that's true.
33:17
Speaker 2: Do you want to take a crack?
33:19
Speaker 1: Okay, The original numbers were two four six, and people
33:23
Speaker 1: might tend to go with, like, all right, eight ten twelve,
33:26
Speaker 1: and they thinking it might be all right, it's even
33:29
Speaker 1: number sequence ascending even number, right, and they would say, no,
33:33
Speaker 1: that's not correct. And you said, well, maybe it's four
33:35
Speaker 1: eight twelve and it's like doubled or something, and they
33:38
Speaker 1: would say, well, that's also incorrect. And then you're at
33:43
Speaker 1: WIT's end because what you haven't done is just done
33:46
Speaker 1: any ascending order. You didn't go one seventy nine, three hundred.
33:50
Speaker 2: All right, let me take a crack at it. You ready?
33:54
Speaker 1: Sure?
33:55
Speaker 2: So the original numbers two four six, and the participants
33:58
Speaker 2: would try to come up with the explanation of why,
34:01
Speaker 2: like what are the what pattern are those numbers following?
34:05
Speaker 1: Right?
34:05
Speaker 2: So you might say the like does eight ten twelve
34:11
Speaker 2: work and they would say yes, and you'd say, okay,
34:14
Speaker 2: well then you're just looking at even numbers and they
34:16
Speaker 2: would say, no, you still got this right, This still
34:20
Speaker 2: fits the pattern, but your your hypothesis for it is wrong.
34:23
Speaker 1: Right, that's yeah, that's the key.
34:25
Speaker 2: Right. Here's where the confirmation bias came in. People would
34:28
Speaker 2: then go back and continue trying to find versions that
34:32
Speaker 2: fit their hypothesis to explain this even though it was wrong. Yeah,
34:36
Speaker 2: rather than take their hypothesis and say, Okay, this is right,
34:40
Speaker 2: this fits the pattern, but it's still not correct and
34:42
Speaker 2: start trying to break their original hypothesis by coming up
34:47
Speaker 2: with like just completely random stuff that doesn't fit their
34:50
Speaker 2: original hypothesis, in which case they might have said something
34:54
Speaker 2: like does one, six or twenty seven work and they
34:57
Speaker 2: would say no, that's that doesn't fit, and then that
35:00
Speaker 2: might lead the person to see that actually, the only
35:03
Speaker 2: the only thing that has to be correct to be
35:06
Speaker 2: part of the model is that the numbers have to
35:08
Speaker 2: ascend in order. That was it. But people, people, man,
35:14
Speaker 2: just you.
35:14
Speaker 1: Might even try, you might even try and break it
35:16
Speaker 1: by saying three, five, seven, but you're still using that
35:20
Speaker 1: original a version of that original hypothesis.
35:25
Speaker 2: Exactly that that there's yes, say like that you think
35:27
Speaker 2: it goes up by two or something like that. Yes,
35:30
Speaker 2: You're like very few people go back and try to
35:33
Speaker 2: break their own hypothesis, And that's the point of confirmation bias.
35:37
Speaker 2: Let's move on from that experiment. The point of confirmation
35:40
Speaker 2: bias that this shows if you actually can understand it
35:43
Speaker 2: from other people than us, is that we tend to
35:47
Speaker 2: take our initial ideas, our beliefs in a lot of cases,
35:51
Speaker 2: and look for information that supports those and discard information
35:55
Speaker 2: that doesn't support it.
35:57
Speaker 1: Right, And that's of course you know mentioned politics a
35:59
Speaker 1: minute ago. That where you most firmly see that these
36:01
Speaker 1: days is you are in a media bubble. Probably, I
36:06
Speaker 1: don't know a ton of people that get their news
36:09
Speaker 1: sources from completely disparate points of view, and news these
36:14
Speaker 1: days that you're getting is so a lot of it
36:17
Speaker 1: is so slanted to begin with. It's probably not even
36:19
Speaker 1: the best example anymore to use, but you're probably a
36:23
Speaker 1: long way of saying, you're probably going to be seeking
36:26
Speaker 1: out news that confirms your beliefs because you don't want
36:28
Speaker 1: your beliefs challenged.
36:29
Speaker 2: Yes, I mean, I, like everybody else, I have trouble
36:32
Speaker 2: with that as well. But I have to boast you
36:34
Speaker 2: me is actually really good about getting news from different sources.
36:38
Speaker 1: Yeah.
36:39
Speaker 2: And one reason that I find it difficult to do
36:41
Speaker 2: is because I have like physical reactions sometimes. Yeah, And
36:45
Speaker 2: that is a thing that's one of the reasons why
36:47
Speaker 2: they think we have we use confirmation biases because it
36:50
Speaker 2: sucks to be to have your beliefs challenged, right, It's
36:53
Speaker 2: really difficult to overcome that. And there's this thing called
36:56
Speaker 2: belief perseverance, which is, even when you're beliefs are challenged with,
37:01
Speaker 2: say like an indisputable fact, you can still use confirmation
37:06
Speaker 2: bias to preserve that belief because we usually attach our identity,
37:12
Speaker 2: or build our identity around our beliefs. That's who we are.
37:15
Speaker 2: So it's like we're being personally attacked. And then even
37:18
Speaker 2: more than that, there's the backfire effect. Right did you
37:20
Speaker 2: see that?
37:21
Speaker 1: I did not.
37:22
Speaker 2: So the backfire effect says that in the in the
37:26
Speaker 2: face of being presented with information that is that basically
37:30
Speaker 2: counters your own beliefs, it can make you actually solidify
37:34
Speaker 2: your original incorrect belief in the first place. Right, You'll
37:39
Speaker 2: you'll you'll believe it even more strongly, even though you've
37:42
Speaker 2: just been given facts that contradict it. So we really
37:46
Speaker 2: really hang on to our beliefs as much as possible.
37:51
Speaker 2: And that is a huge, huge thing that humans trip over.
37:54
Speaker 2: That confirmation bias is probably the grandaddy of all biases.
37:58
Speaker 1: I think, Yeah, that's why I saved it for last Yeah,
38:03
Speaker 1: and you know, a lot of reasons people do this.
38:04
Speaker 1: You might be protecting your yourself, like your self esteem,
38:08
Speaker 1: because otherwise you can you're admitting that you're may have
38:11
Speaker 1: been wrong about something, and it, you know, takes a
38:14
Speaker 1: big person to do that. You want to believe that
38:17
Speaker 1: you're right about stuff. And it also might just be
38:21
Speaker 1: difficult to process more than one hypothesis at once. It
38:25
Speaker 1: might just be a little too brain breaking.
38:27
Speaker 2: Yeah, because once you lock into an explanation, your brain
38:30
Speaker 2: just it's like, I know, we've got it. We don't
38:32
Speaker 2: have to figure this other thing out. Homeostasis, homeostasis. You know.
38:36
Speaker 2: It's it is very hard to entertain something that is
38:40
Speaker 2: counter to what we already think is true.
38:42
Speaker 1: That's right, all right everyone. As you can tell by
38:45
Speaker 1: the clock, we are taking our second break, this is
38:48
Speaker 1: a long one, and we're going to come back and
38:49
Speaker 1: talk about behavioral economics right after that.
38:52
Speaker 2: Well, wait, before we do that, let's try to explain
38:54
Speaker 2: this confirmation by a study again.
38:56
Speaker 1: Yeah, we should all right, we'll be right back, Okay,
39:29
Speaker 1: I promised talk about behavioral economics. A lot of the
39:33
Speaker 1: work that Spirsky and Konoman did was super applicable and
39:38
Speaker 1: kind of revolutionary in a lot of ways for the
39:40
Speaker 1: world of economics and how people buying behavior is affected.
39:45
Speaker 1: They didn't invent it, like Adam Smith wrote about stuff
39:47
Speaker 1: like this, and starting about World War two is when
39:51
Speaker 1: they started really kind of homing in on stuff like this,
39:54
Speaker 1: like using mathematical models, and it all kind of started
39:58
Speaker 1: with the assumption that people and companies and organizations are
40:03
Speaker 1: really just trying to pursue their self interest at the end.
40:06
Speaker 2: Of the day. Yeah, and they're going to make the
40:08
Speaker 2: most rational decision. Yeah, and that's just they And they
40:12
Speaker 2: were like, yes, we know people make irrational decisions, but
40:15
Speaker 2: these are outliers. Like if you take all of the
40:17
Speaker 2: information and their data and aggregate, you will see that
40:21
Speaker 2: humans generally try to make the most rational decision. That's
40:24
Speaker 2: just not true. People don't do that. We make all
40:28
Speaker 2: sorts of irrational decisions that very frequently run counter to
40:32
Speaker 2: our own best interests. And again we'll even reject stuff
40:37
Speaker 2: like information that would help us make decisions to our
40:40
Speaker 2: own best interests if they counter our beliefs. So there's
40:44
Speaker 2: a guy named Richard Thaler who ended up becoming a
40:47
Speaker 2: colleague of Diversky and Konnoment, and he took some of
40:50
Speaker 2: their papers, and he realized that these mistakes, these cognitive biases,
40:56
Speaker 2: they can be predictable. Right, you can actually map how
41:01
Speaker 2: somebody's going to make a bad decision. And this became
41:04
Speaker 2: the basis of behavioral economics.
41:07
Speaker 1: Yeah, he well, let's talk about this this prospect theory,
41:12
Speaker 1: because this was from Tversky and Konomon. It was an
41:16
Speaker 1: article from nineteen seventy nine from this idea of prospect
41:21
Speaker 1: theory colon an Analysis of Decision under Risk, and Livia
41:25
Speaker 1: says it's probably the most cited economics paper of all time.
41:28
Speaker 1: Like this was a revolutionary, landmark paper and they didn't
41:31
Speaker 1: write a ton of papers for researchers. They did like
41:33
Speaker 1: eight totalah, which just shows what an outsize impact they had.
41:38
Speaker 1: But they talk about in this paper a lot of
41:41
Speaker 1: attitudes about risk. One is loss a version, which is
41:46
Speaker 1: the idea that you're going to experience more emotional suffering
41:49
Speaker 1: when you lose money, then you will gain happiness if
41:53
Speaker 1: you gain something, So you may pass up an offer
41:58
Speaker 1: that gives you equal odds of winning twenty five or
42:00
Speaker 1: losing twenty. There was another example I think kind of
42:04
Speaker 1: gets it across more is there was an experiment in
42:06
Speaker 1: nineteen ninety six where they gave participants a lottery ticket
42:10
Speaker 1: and before you scratched it off or whatever, let's say
42:12
Speaker 1: it was a scratch off. They said, all right, well,
42:14
Speaker 1: hold on, before you do that, I'll give you another
42:17
Speaker 1: lottery ticket plus ten dollars in cash. And for no
42:22
Speaker 1: logical reason at all, people tended to think that that
42:26
Speaker 1: first ticket was the one, even though there was no
42:29
Speaker 1: it was a lottery ticket, there was no difference at all.
42:31
Speaker 1: They would turn down that extra ten bucks. I think
42:33
Speaker 1: less than fifty percent of them took that deal.
42:35
Speaker 2: Yeah, because in giving away or trading that first ticket,
42:38
Speaker 2: they risked a loss even though the gain was right there.
42:42
Speaker 2: Just trading the ticket, you got an extra ten bucks, right, Yeah,
42:45
Speaker 2: that's fairly irrational. We also have a lot of trouble
42:51
Speaker 2: with rare events. Yeah, we tend to overestimate them. It
42:56
Speaker 2: can be a positive event and it can be a
42:57
Speaker 2: negative event. But we're really bad at probabilities and statistics.
43:02
Speaker 2: And this is essentially it's like you won't let your
43:10
Speaker 2: kid walk to school because you're afraid of your kid
43:12
Speaker 2: being kidnapped, even though the chance of your kid being
43:15
Speaker 2: kidnapped is just ridiculously low. It's technically irrational, even though
43:21
Speaker 2: very few people would fault you for that, but it's
43:24
Speaker 2: still an irrational decision.
43:26
Speaker 1: Yeah, for sure. We talked about that in the.
43:31
Speaker 2: Well was it free range kids?
43:33
Speaker 1: Maybe I can't remember, tied in with a satanic panic
43:36
Speaker 1: and stuff like that I think definitely did back in
43:38
Speaker 1: the day. Relative rather than absolute terms. That is a theory,
43:43
Speaker 1: monetary theory where and there's a great example. You might
43:48
Speaker 1: drive an extra ten minutes in a car to buy
43:50
Speaker 1: a shirt that you know is selling the shirt for
43:52
Speaker 1: twenty bucks rather than the one closer to you that
43:55
Speaker 1: sells it for thirty. But you're not going to do
43:57
Speaker 1: that because that saves you ten bucks. You won't s
44:00
Speaker 1: twenty dollars on a car even though you may even
44:04
Speaker 1: have to drive five minutes down the road, because you're like, oh,
44:07
Speaker 1: it's twenty dollars, the car is twenty thousand. But it's
44:10
Speaker 1: really a relative, you know, absolute thing, as you're saving
44:13
Speaker 1: twice as much money as you did on that T
44:15
Speaker 1: shirt purchase.
44:16
Speaker 2: Right, But it's like you said, it's all relative again,
44:20
Speaker 2: totally irrational. But all this stuff relates to economics, and
44:25
Speaker 2: like you said, this stuff can be replicated. There's a
44:27
Speaker 2: twenty twenty study that looked at the prospect theory in particular,
44:33
Speaker 2: and this major study was conducted in nineteen countries and
44:37
Speaker 2: thirteen different languages and held up not bad. No, that's
44:41
Speaker 2: not bad at all. And so it's not just economics.
44:44
Speaker 2: It's not just being exploited by the wine list or
44:49
Speaker 2: you know, Kentucky Fried Chicken or something like that to
44:53
Speaker 2: make you buy their stuff. This actually this can have
44:58
Speaker 2: like life and death consequences too, although I guess so
45:01
Speaker 2: can wine. In Kentucky Fried chicken.
45:04
Speaker 1: You know what you're gonna get a Kentucky fried chicken?
45:07
Speaker 1: What PEPSI?
45:08
Speaker 2: That's right, you will get some pepsi. You know how
45:11
Speaker 2: I know that cause you just had Kentucky fried Chicken.
45:14
Speaker 1: I did. After our tour. I was a little tired
45:16
Speaker 1: and needed just some fried chicken. So I got fried chicken.
45:19
Speaker 2: What do you get just the original or extra crispy?
45:21
Speaker 2: Because you're crazy if you don't get extra crispy.
45:23
Speaker 1: I get extra crispy. But they were out they could satisfy.
45:28
Speaker 1: I got the three piece. They had two more pieces
45:30
Speaker 1: of extra crispy, and they asked if one piece of
45:33
Speaker 1: O R was available, and I was like, yeah, sure,
45:36
Speaker 1: I'm not gonna not eat a piece of chicken.
45:40
Speaker 2: It is good. They do chicken, right, Yeah they do.
45:43
Speaker 2: Did you get the mashed potatoes and gravy?
45:45
Speaker 1: You know it? Buddy times too, and extra biscuit. I
45:48
Speaker 1: went all in. It was a rare treat eating frenzy.
45:52
Speaker 2: Did you drink a PEPSI?
45:54
Speaker 1: I did?
45:54
Speaker 2: Awesome. Well that all fits somehow. I don't know how,
45:58
Speaker 2: but it somehow fits this this episode so where I
46:03
Speaker 2: was saying that this can be life and death, as
46:05
Speaker 2: with medicine, because although doctors have God complexes and like
46:08
Speaker 2: to present themselves as infallible, they are quite fallible. They're
46:11
Speaker 2: humans and they can suffer the same cognitive biases as us.
46:15
Speaker 2: But they have your life in their hands. We rarely
46:19
Speaker 2: have others' lives in our hands.
46:21
Speaker 1: Yeah. Do you watch the show the Pit?
46:24
Speaker 2: I tried and I just did not grab me. I
46:26
Speaker 2: gave it like ten minutes, but I hear nothing but
46:29
Speaker 2: good things.
46:30
Speaker 1: Yeah, I mean, I really like it. I've never been
46:31
Speaker 1: a hospital show guy, so this is kind of one
46:33
Speaker 1: of my first forays into it, but I like it
46:36
Speaker 1: a lot. I haven't started season two, but I noticed
46:38
Speaker 1: when reading through these bias like medical biases that they do,
46:43
Speaker 1: or at least Noah Wiley does a really good job
46:45
Speaker 1: on the show with these younger residents trying to bust
46:49
Speaker 1: through and a lot of this stuff comes up. He
46:51
Speaker 1: doesn't say, hey, that's affect heuristic. He just will talk
46:57
Speaker 1: about what that is. And now that I know the definitions,
46:59
Speaker 1: I'm like, oh, he's talking about as an outcome bias
47:02
Speaker 1: or an anchoring bias. It's fairly interesting.
47:05
Speaker 2: Yeah. Rather than say, like being presented with a really
47:08
Speaker 2: high price for a bottle of wine to make the
47:10
Speaker 2: other overpriced wine seem like a bargain, this can be
47:14
Speaker 2: like your first lab work comes back and that forms
47:17
Speaker 2: the anchoring biased impression of your condition. And even as
47:23
Speaker 2: new lab work comes back, that doctor may fail to
47:27
Speaker 2: adjust their view of your condition because they're not taking
47:31
Speaker 2: into account this new stuff. They're giving more weight to
47:34
Speaker 2: that original, that original number. So yeah, and that's just
47:37
Speaker 2: the anchoring bias. The way that it can affect there's,
47:40
Speaker 2: like you said, there's all sorts of other ways for
47:41
Speaker 2: it to happen, and all of it can result in
47:44
Speaker 2: poorer outcomes for patients just because their doctors are humans,
47:49
Speaker 2: and we don't really approach cognitive biases in a really
47:53
Speaker 2: methodical or deliberate way.
47:56
Speaker 1: Yeah. They In fact, now that I'm thinking about it,
47:58
Speaker 1: they do this so much on the show. The show
48:00
Speaker 1: could be called medical confirmation bias the show because you
48:05
Speaker 1: see it all the time. Outcome bias is when a
48:08
Speaker 1: shift in the patient's health you're convinced is the result
48:10
Speaker 1: of a treatment, like it's because of that thing I did,
48:13
Speaker 1: or affect heuristic that I mentioned, an emotional reaction to
48:17
Speaker 1: a patient, you know, kind of overrunning you know, deliberating
48:21
Speaker 1: on this thing in a logical way. This happens all
48:24
Speaker 1: the time on the show.
48:25
Speaker 2: Yeah. Well, another field that it happens with this forensic science,
48:28
Speaker 2: which we've gone to great links to kind of point out,
48:31
Speaker 2: is junks in the most in most cases, and a
48:35
Speaker 2: lot of that junk is just based on cognitive biases.
48:38
Speaker 1: Yeah, for sure. I mean certainly the way they do
48:41
Speaker 1: lineups is flawed. I mean the way they I feel like,
48:45
Speaker 1: you're right, we've done this a lot on the on
48:46
Speaker 1: the show. The way they have done a lot of
48:49
Speaker 1: this is super flawed. And I think maybe they're looking
48:53
Speaker 1: at it some but not a lot.
48:55
Speaker 2: No, So if you want to fight cognitive bias in
49:00
Speaker 2: your own mind, Chuck, what do you do? What do
49:04
Speaker 2: you do?
49:05
Speaker 1: Well, there's a list of good tips here, and I
49:07
Speaker 1: think these are pretty good tips. The first one is
49:10
Speaker 1: just being aware that you have these, which is something
49:12
Speaker 1: that we've already kind of kind of worked through on
49:14
Speaker 1: this episode, except for you, of course, because you don't
49:16
Speaker 1: have these. Sure, but studies show that like just being aware,
49:22
Speaker 1: it's not one of those things where like, well, being
49:24
Speaker 1: aware is have the problem. It's like being aware seems
49:26
Speaker 1: like two percent of the problem.
49:27
Speaker 2: Yeah, it's like you're aware that you have an unconscious bias.
49:32
Speaker 2: It doesn't make you understand the bias. You just know
49:35
Speaker 2: that they're there, Right, that's the problem with is unconscious.
49:40
Speaker 1: What else?
49:40
Speaker 2: There are some like actual things you can do like
49:43
Speaker 2: delay decision making. Yeah, don't don't come to snap judgments.
49:48
Speaker 2: Go get more information, Go get information from a contradictory
49:52
Speaker 2: source or different source or something like that. And then
49:55
Speaker 2: it like kind of tied into that. You can have
49:57
Speaker 2: like personal like rule like if there's a big decision,
50:02
Speaker 2: you will not make that decision until you've slept on it. Yeah,
50:06
Speaker 2: for example, don't buy a TV unless your friend says, yeah,
50:11
Speaker 2: good idea.
50:12
Speaker 1: Try and consider your past experience for sure, because optimism
50:17
Speaker 1: biased could come into play, like hey, worked out last time, yeah,
50:21
Speaker 1: Like why would I why would I take more time
50:24
Speaker 1: this time?
50:24
Speaker 2: Yeah? And that's another way that you can kind of
50:27
Speaker 2: do that. An exercise you can do is write down
50:29
Speaker 2: your expectations for an outcome and then go back and
50:33
Speaker 2: look at it afterward and see if you were right
50:35
Speaker 2: or not. Can kind of help you realize like, uh,
50:38
Speaker 2: I do kind of tend toward the optimism bias.
50:41
Speaker 1: Yeah, because I believe that was one of the other biases.
50:43
Speaker 1: Is even like it is hard to recognize because you're
50:46
Speaker 1: biased and that you misremember what you thought going into it.
50:49
Speaker 1: So writing it down is a good that's a good.
50:51
Speaker 2: One, right, But if you're super super unconsciously biased, you
50:54
Speaker 2: might be like someone else wrote this in my handwriting, Right,
50:58
Speaker 2: I've never been this wrong.
51:00
Speaker 1: What about Thomas Bayes and Baysian reasoning.
51:03
Speaker 2: So he was a minister from the eighteenth century, and
51:06
Speaker 2: he basically came up with a standardized formula for taking
51:10
Speaker 2: into account the probability of an outcome, right that things
51:14
Speaker 2: aren't essentially so I saw this on less wrong dot
51:18
Speaker 2: org founded by one of the guys who wrote, if
51:21
Speaker 2: anyone builds it, everyone dies about Ai Eliotz or Yukowski.
51:25
Speaker 2: The whole point of less wrong dot org is to
51:27
Speaker 2: overcome your biases in a methodical way. And they love
51:31
Speaker 2: Baysian reasoning, and it basically says, there's no such thing
51:34
Speaker 2: as something is just true. Everything is just a probability,
51:39
Speaker 2: and you can kind of try to determine how probable
51:42
Speaker 2: something is based on whatever evidence you can gather about it.
51:46
Speaker 2: Just basically going through life like that.
51:49
Speaker 1: You know, who hates that website? Who l E s
51:53
Speaker 1: R O NNG That dude who started his own personal
51:57
Speaker 1: comedy website right, less wrong dot God. That's right, he's
52:01
Speaker 1: just getting smashed.
52:03
Speaker 2: What else, Chuck?
52:06
Speaker 1: What else is I cultivate a growth mindset?
52:09
Speaker 2: That's a big one.
52:10
Speaker 1: Hey, I make mistakes. I screw things up, and like
52:13
Speaker 1: I need to recognize that and try and grow from
52:16
Speaker 1: that rather than you know, just being confirmed with my
52:21
Speaker 1: own biases constantly.
52:22
Speaker 2: Yeah, maybe like looking around at some of the ways
52:25
Speaker 2: that you're commonly exploited, say like by advertisers, Like scarcity
52:29
Speaker 2: is one when somebody says act now supplies are limited.
52:31
Speaker 2: They're creating a scarcity mindset in you social proof basically
52:37
Speaker 2: like these people like this, so you probably should too,
52:40
Speaker 2: and you're like, oh, I should like that too.
52:42
Speaker 1: Yeah.
52:42
Speaker 2: And then two other things I saw. There's something called
52:46
Speaker 2: cognitive bias mod modification I think is what it is. Okay,
52:54
Speaker 2: you can use this for like treating anxiety, right, Like
52:57
Speaker 2: people like tend to seek out negative facial expressions. Oh yeah,
53:02
Speaker 2: and this treatment is like like here's a thousand frownie faces.
53:07
Speaker 2: Find the smiley face in there, and just screen after screen,
53:10
Speaker 2: you're looking for the smiley face, and you're training your
53:13
Speaker 2: brain to stop putting as much weight on negative facial expressions,
53:19
Speaker 2: just using like basically exploiting your cognitive bias to get
53:23
Speaker 2: over your cognitive bias.
53:25
Speaker 1: Oh wow.
53:26
Speaker 2: And then the last thing, Chuck is apparently AI are
53:30
Speaker 2: starting to show signs of emergent cognitive biases because they
53:35
Speaker 2: use heuristics too, so they're starting to make cognitive they're
53:40
Speaker 2: starting to make errors in judgment in predictable ways, which
53:44
Speaker 2: are cognitive biases, just like humans.
53:47
Speaker 1: Rob Zombie more human than human.
53:49
Speaker 2: That's right, you got anything else?
53:51
Speaker 1: I got nothing else.
53:52
Speaker 2: This is a good one. This is fun. Chuck, I'm going, well,
53:56
Speaker 2: since Chuck and I both liked this episode, that means
53:59
Speaker 2: we have no choice but for listener mail to be triggered.
54:02
Speaker 1: Right now, I'm going to call this follow up on
54:07
Speaker 1: a Sebastopol because I wondered what the connection there was, Hey, guys,
54:12
Speaker 1: because if you didn't listen Sebastopol, California, and we were
54:15
Speaker 1: talking about the Sebastopold in the Crimean War, and I
54:20
Speaker 1: was like, there's no way that's a coincidence. And it's not. Hey, guys,
54:22
Speaker 1: listening to the podcast on the Light Brigade from Sonoma County.
54:26
Speaker 1: Our Sebastopol was named after Sebastopod. And here's a little information.
54:31
Speaker 1: The settlement was apparently originally named pine Grove, and the
54:35
Speaker 1: name changed to Sebastopol was attributed to a bar fight
54:40
Speaker 1: in the eighteen fifties which allegedly compared by a bystander
54:45
Speaker 1: to the long siege of the seaport of Sebastopol during
54:49
Speaker 1: the Crimean War. Wow, so the original name survives in
54:53
Speaker 1: the name of the Pine Grove General Store downtown only,
54:57
Speaker 1: and that is it. There's also the rush there Russian
55:00
Speaker 1: River Valley, so apparently there are some Russian influence in
55:04
Speaker 1: that area which I didn't know about. And that is
55:05
Speaker 1: from Marsha Ford.
55:06
Speaker 2: Yeah. Also, we want to apologize to all of our
55:10
Speaker 2: Iron Maiden fans who wrote in to be like, yeah,
55:14
Speaker 2: that song of the Trooper is about that whole battle.
55:18
Speaker 1: Yeah, I didn't know. I am not. I like Iron Maiden,
55:21
Speaker 1: but I didn't have as much shame upon my head
55:23
Speaker 1: as you. But you didn't reading the lyrics, it doesn't
55:26
Speaker 1: say you know crimean war in charge of the light Brigade,
55:31
Speaker 1: does it?
55:32
Speaker 2: I don't know. I haven't heard it in a while.
55:35
Speaker 2: I'm a big fan of the poster. I love the
55:37
Speaker 2: poster a lot.
55:38
Speaker 1: Yeah, me too.
55:39
Speaker 2: Well, sorry all of you Iron Maiden fans out there.
55:42
Speaker 2: We'll try to do better next time.
55:44
Speaker 1: Yeah, missed opportunity.
55:45
Speaker 2: Who is that that wrote in about Sebastopol?
55:48
Speaker 1: That was Marcia, I believe.
55:49
Speaker 2: Thanks Marcia, Marcia, Marsha Marsha. We really appreciate you, and
55:53
Speaker 2: if you want to be like Marcia, you can email
55:55
Speaker 2: us as well. Send it off to Stuff podcast at
55:58
Speaker 2: iHeartRadio dot com.
56:03
Speaker 1: Stuff you Should Know is a production of iHeartRadio. For
56:06
Speaker 1: more podcasts Myheart Radio, visit the iHeartRadio, app, Apple podcasts,
56:10
Speaker 1: or wherever you listen to your favorite shows.