View source for SGU Episode 557

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|episodeNum     = 557
|episodeDate    = March 12<sup>th</sup> 2016  <!-- broadcast date -->
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|qowText        = I have never been converted to or even had much interest in spiritualism, occultism, Swedenborgianism or any particular religion. And I never, except occasionally for a laugh, visit the quacks who call themselves psychics.  <!-- add quote of the week text-->
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== Introduction ==
''You're listening to the Skeptics' Guide to the Universe, your escape to reality.''

S: Hello, and welcome to The Skeptic's Guide to the Universe. Today is Wednesday, March 9th, 2016; and this is your host, Steven Novella! Joining me this week are Bob Novella,

B: Hey, everybody!

S: Cara Santa Maria,

C: Howdy!

S: Jay Novella,

J: Hey, guys.

S: and Evan Bernstein.

E: Hello, everyone!

S: Cara, welcome back! Basically, it's been a month since you've been on the show.

C: I know!

B: Yay!

C: I haven't done three episodes in a row! It's crazy!

S: What have you been up to?

C: I have been traveling all over the country for a TV show – actually the web companion to a TV show I've been working on called, “{{w|America's Greatest Makers}}.” Quick plug, it starts in April on {{w|TBS (U.S. TV channel)|TBS}}. But the web companion show has been really fun! I get to go to a different place each week and visit a maker space, and do something in the maker space. Like, I made a lamp, and I made a table, and I soldered some stuff together, and I used  a big {{w|Laser cutting|laser cutter}}, and a {{w|Plasma cutting|plasma cutter}}; and it's just been awesome! So I was in {{w|Philadelphia|Philly}}, {{w|San Francisco}}, {{w|Chicago}}, {{w|Houston}} ... I've been all over the place.

S: Oh boy, a lot of traveling.

J: That sounds like fun.

S: We're so happy to have you back that we're gonna have you start off with a “What's the Word.”

== What's the Word <small>(1:15)</small> ==
{{w|Thixotropy}}

C: Yay! Oh, I'm so excited about the word this week. Okay, this is one of those words that when I look up the pronunciation – it's so funny. I get so hung up on pronunciations lately. Everybody online says “thix-ot-ropy.” I still like “thixo-tropy.”

B: Ooh!

C: I feel like when something ends in “tropy,” you can go either way.

J: Yeah, it should be “tropy,” right?

C: I like “tropy!” But you know what? I've done this a couple of times where I've said, “The interwebs say it's this way,” and then I'll have everybody within the field that it represents be like, “Nobody says it that way.” ''(Laughs)''

S: Yeah.

C: So I'm like, “Take it or leave it! Thix-ot-ropy, thixo-tropy, it's still a really, really cool word. So, it actually is kind of a chemistry term that represents a property that's exhibited by certain types of liquids or gels that when you move them, when they're stirred, when they're shaken, when energy is put into the system, they actually get thinned out.

And that actually happens over the course of time, also. So, whether you mechanically change them, they have this a {{w|Shear thinning|shear thinning}} property. Or if they're just left under static conditions, these viscous liquids will actually start to flow. They'll become thin and a little bit less viscous.

It was first coined – I love it when I can find words that we can point to the first person who ever said them. That's always really exciting. It was introduced in 1927 by a Mr. A. F. Paturphy. And then it was used after that to talk about {{w|Colloid|colloidal suspensions}}. It was used to talk about clay, and clay that's used in making ceramics. But it was first used in 1927 in the scientific literature. And it seems to have come from an amalgamation of the {{w|Ancient Greek|Greek}} “thixis,” which means “touching;” and “tropy,” which means “turning.” I'm not sure how those two words come together to mean this phenomenon though.

I like that it's spelled, “T-H-I-X,” but I think if I were in chemistry, and I were learning this term for the first time; the fact that it's like “thicks” - like “thick” - that's how I would probably remember it. It's a thick thing that goes thin over time.

B: So it's this the opposite of a {{w|Non-Newtonian fluid|non-Newtonian fluid}} then?

C: I think there are some aspects of these fluids or these gels that are thixotropic, like {{w|Ketchup}}, apparently, is thought to be a thixotropic ''(laughs)'' fluid, which is super-weird. That's an easy one. That do seem to do the opposite of what a non-Newtonian fluid does, kind of like – we called it “{{w|Non-Newtonian_fluid#Oobleck|goo yuck,}}” - did you guys play with this when you were kids? Goo yuck? Corn -

B: Yeah, corn starch. Yeah.

E: Yeah, of course.

B: That was – I just call it a non-Newtonian fluid.

C: Yeah, 'cause you're grown up.

B: ''(Laughs)''

C: But when you're a kid, did you guys learn about it?

B: Oh, when I was ten!

C: Oh, really? No, but we were playing this,

B: No, not at all.

C: with this when we were in kindergarten. Your teacher didn't make a mixture and have you play with it on your desk?

B: Not in school...

C: Ah!

B: At home, we messed around with it. And it was awesome! It's like, “What the hell?”

C: Yeah, that's Goo yuck. 'Cause you pack it up really tightly in your hands, and it's almost like a powdery solid. And then the minute you let it go, it just liquifies, and it just runs all through your fingers.

J: You could run on that, if you have enough of it.

S: Like, walk on a pool of it?

C: Yes! So, a thixotropic substance – like let's say, Ketchup; the more you run on it, the more liquidy it would get.

S: Mm hmm.

B: Right.

S: So this property has been used to explain certain blood relic miracles – alleged miracles

B: Yes!

S: Like the blood ...

E: Right.

S: of Saint {{w|Januarius}}, which is every year they take out the vial of blood, and

B: In January?

S: go through a ritual which involves quite interestingly shaking it! Then after a while, it becomes liquid.

E: ''(Gasp)'' So a miracle!

S: Yeah, so it goes from the coagulated solid, but to liquid with the mechanical action of shaking it; which is as you say, it's a chemical process, interpreted as a miracle, but I think ...

C: Yeah, but it's really just nature.

S: just Thixotropy. Yep.

C: Yep! ''(Laughs)'' It rolls off of your tongue, Steve. Thixotropy. I don't know why, this one really catches me up. Oh, and by the way, this was ... and I do want to mention that this word was recommended by Jenny from {{w|Portland, Oregon}}. Thanks, Jenny!

S: Yeah, it's “Oreg-in,” not “Ora gon.”

C: ''(Snickers)'' Thank you. ''(Laughs)''

S: I have a friend who lives there; it's like, “It's 'Oreg-in,' it's not 'Ore-gon.'”

C: Yeah, it's like, do people still say, “Ore-gon?”

E: Oregon?

S: We used to say that! Every year, in {{w|Connecticut}}.

E: Origami?

S: Ore-gon.

C: Yeah, we say ... I mean, in {{w|Texas}}, you probably say, like, “Organ,” like it's “Oragan.” Oh, and Jenny, I'm looking through your email one more time. It's been a while. Sorry, you sent this in February. You learned this term when you were working I guess in dental school, and you were talking about the different plasters; because those are definitely ...

S: Oh yeah.

C: thixotropic. You stick 'em in your mouth, and then you start to feel it like, gurgle down the back of your throat.

E: Ugh!

C: Oh!

E: Oh god! Bad memories! Bad memories!

C: Yeah. We're done with that. We're not gonna talk about that any more. But thanks, Jenny!

S: Okay.

== News Items ==
=== Overconfidence <small>(6:16)</small> ===
* [http://theness.com/neurologicablog/index.php/what-causes-overconfidence/ Neurologica: What causes overconfidence]

S: So, everyone, do you feel confident? 

C: In what?

J: Sure! About what?

S: Anything. What are you confident in?

J: Lots of things! Like ...

S: Did you know that most people are overconfident, pretty much in anything?

E: Sure!

S: If you ask people to self-assess, they generally are overconfident. They will place themselves greater than any objective measure of whatever skill you're asking them about.

C: Hm!

S: Right, so most people think that they're above average in things like driving cars, when obviously, not everybody can be above average. So psychologists have been very interested in this phenomenon for a while. It's pretty well established that there is an overconfidence effect. People are overconfident. You guys remember the {{w|Dunning–Kruger effect}}.

B: Yeah!

E: Yes, we've...

C: Yep.

E: spoken about it before.

S: Yeah, so that was one – psychologists Dunning and Kruger focused on one aspect of overconfidence, and that is the relationship between the degree of overconfidence, and the actual objective ability. And what they found is that the degree of overconfidence, or the difference between your self assessment of how you did, and your actual performance was greater when performance dropped. The worse you did, the more you overestimated your performance. That has been interpreted as you don't have the competence to assess your own competence.

E: It's the {{w|American Idol}} effect. A bunch of people think they can sing when they have no clue how to sing!

''(Cara laughs)''

S: Yeah, exactly. Exactly. So also the

J: Is that 

S: do you have friends effect.

E: Well that sounds...

C: Aw, geez

S: Is there nobody in your life that could give you a straight answer, that could tell you that you shouldn't be auditioning for American Idol?

''(Cara and Evan laugh)''

S: Yes, Jay

C: That's kind of true.

J: So, the basic point is that we're not good enough at judging our own skill level at something?

S: Right. Because, when you think about it, you need competence in order to assess your own competence. People often misinterpret it as being, “Stupid people don't know they're stupid.” But it's not about stupid people, ''everyone'' has the Dunning-Kruger effect, right? We're all along that curve somewhere for different things, right?

You may be competent at one thing, and not very competent at another; so you'll be at a different place on the curve. So, this should be looked at as just an attribute of people, not quote-unquote, “Stupid people.”

But anyway, there's new research looking at overconfidence with a different approach. They were looking at the association of overconfidence and your thinking about, your theory about intelligence. Specifically, they divided people into two groups: People who had a strong philosophy that intelligence is fixed – which is the so-called entity theorists – and people who believed that intelligence is malleable – that you could essentially learn. You can study, and make yourself more intelligent. They call that the incremental theorists.

Their hypothesis was that people who believed that intelligence was fixed would generally be more overconfident than people who believed that intelligence is malleable. So they gave subjects – it's always university students, right? That's one of the running jokes of psychology studies. {{w|Psychology|Psychologists}} study the behaviour of university students because that's always the available pool of subjects they have to recruit from.

But anyway, they did in fact confirm their hypothesis. They did a series of three studies. The first study did show that. They asked people a series of questions like, “You have a certain amount of intelligence, and you can't really do much to change it.” And they had to agree or disagree with that statement. They used a six-point scale from “strongly agree” to “strongly disagree,” or, “You can always substantially change how intelligent you are.”

They then gave them a moderate test that was not too easy and not too hard. And they asked them to assess where they thought they fell on a zero percentile to ninety-nine percentile range. Now, by definition, the average that people actually did was fifty percent in each group. But the group that believed intelligence was fixed on average guessed that they performed at the seventy-sixth percentile, and the group that believed that intelligence is malleable on average assessed themselves in the fifty-fifth percentile. So there was still an overconfidence effect in both groups, but it was twenty-six percent in the fixed group, and only five percent in the “intelligence is malleable” group.

So most of the overconfidence effect in this study was in the subgroup that believe intelligence is fixed, which is interesting.

C: Yeah.

S: So, of course, that leads to the question of, well, why? What is it about believing that intelligence is fixed that would make you more overconfident?

So they did two further studies to try to address this. First, they wanted to confirm that there was actually a causal relationship here, right? Right now, we just have an association. Maybe overconfidence makes people feel that intelligence is fixed, you know what I mean? Or maybe they both correlate with some other third thing.

So, they said, “Okay, we'll do another study where instead of asking people what they think, we'll try to influence what they think.” So they gave one group, they told them – they always do the deceptive thing. They say, “We're doing a study of {{w|reading comprehension}}. So read this article, and then we'll ask you some questions about it.”

One group was given an article which essentially was describing research which indicates that intelligence is fixed. The other group was reading about research which indicates that intelligence is malleable. So, allegedly, that would influence their – at least over the short term of the study – that would influence their beliefs about that. And that's a pretty well-established psychological process in psychological studies.

And they found that in fact, the group primed with the fixed scientific research were more overconfident than those who were given the malleable one, although the difference wasn't as big as in the original study. It was sixty-eight percent in the fixed group, and fifty-nine percent in the incremental group.

C: But that was still a significant difference between them?

S: Yeah, so still a significant difference, and it makes sense that it wouldn't be as big as basing it on peoples' long-held philosophical views.

C: Yeah.

S: This was just the immediate effect of reading an article. But because this was an intervention, rather than just asking them what they thought, you're better able to establish cause and effect, right? That when they ''influenced'' their beliefs about intelligence, that influenced their overconfidence. That suggests that that's the arrow of causation.

So then they had a further hypothesis, that maybe this is somehow related – I'm not sure how they came up with this hypothesis, but this is their hypothesis – that people who have a belief that intelligence is fixed will focus more on easy questions that they can do well at. Whereas people who think that intelligence is malleable will focus on more difficult questions.

So they did a third study where they tested that. And they actually had them answer questions – some of which were easy, some of which were hard – on a computer. They could spend as much time as they wanted on any question. They can go back to questions if they wanted to. So essentially, they could spend as much time as they wanted on any of the questions. And the computer tracked how much time they spent on each question.

And they indeed found that the people who were in the “intelligence is fixed” group spent more time looking at – with the easy questions, and less time with the difficult questions. And the people in the “intelligence is malleable” group spent more time with the difficult questions.

Then they did a study where they essentially forced them to spend time on the easy questions, by giving them a task that was time-consuming with the easy questions, but not time-consuming with the difficult questions, like, “Copy all of these questions, but just,” they had to do something very, very quick. Like, just read the other questions, the difficult questions. Or vice versa, right?

And then they had them again, tested their overconfidence. And it turns out that the group that was forced to focus on the easy questions had more overconfidence. The people who were forced to spend time on the difficult questions had less overconfidence. But it was different based upon where they were starting.

So, the group that were forced to spend more time focusing on the easy questions, and who also believed that intelligence was fixed were more overconfident.

C: Gotcha.

S: Right? Than the people who thought that the intelligence was fixed and focused on the difficult questions. But the same effect was not true in the people who believed that intelligence is malleable. Forcing them to focus on one or the other didn't affect their level of overconfidence. There was no statistical difference – fifty-eight versus sixty-one percent.

So, okay, that was a little bit complicated. But this is what it all boils down to: So this is what it shows. These series of studies is yet another confirmation of an overall {{w|overconfidence effect}}. They clearly showed that throughout the study.

E: Sure.

S: The results also suggest that overconfidence is stronger among those who believe that intelligence is fixed, and smaller among those who believe that intelligence is malleable; and that this effect may be mediated by people who believe intelligence is fixed focusing on easy tasks that bolster their confidence, which people who feel that intelligence is malleable spend more time on difficult tasks, which will have a humbling effect on their self-assessment.

B: Ha.

E: Okay.

S: The study did not explore ''why'' that happens, just ''that'' it happens, and that it has an effect on the overconfidence. So it's interesting to speculate – and this would be a good focus of further research. I suspected that if you think that intelligence is fixed, first of all, you are more highly motivated to have an elevated estimation of your own intelligence, 'cause you don't think there is anything you can do about it, you know? Whereas, if you think, “All right, I'm not very smart, but I could become smarter ...

B: Yeah

S: That makes you more comfortable with the notion that maybe you're not that competent in this one area right now, but hey, with some hard work, you could make it better. Also, if you're motivated to pump up your own confidence, you may engage in the {{w|confirmation bias}} of focusing on easy tasks that you do well, that reinforces your overconfidence.

But if you feel that hard work will make you more intelligent, you're more willing to do that hard work by focusing on challenging tasks. And that then reinforces the humility of, “All right, this is really hard; maybe I'm not that great at this. But I'm gonna work at it and become better.”

C: Well, and that's something that I've actually focused on that before when I give talks about {{w|Women in STEM fields|women in STEM}}, and when young girls, when the leaky pipeline really starts getting leaky.

S: Yeah.

C: Because we do find that there's no gender difference in this idea of a fixed or a growth mindset, but for kids who do have a fixed mindset, they're gonna tend to stick to doing things that are easy, so that they feel proud,

S: Yeah

C: when they're finished. They shy away from things that feel hard. And the problem is, boys tend to be more vocally confident than girls.

S: Yeah.

C: So what you have is a mixed gender classroom, where the boys are saying, “This is easy, math is easy.” And the girls are going, “I don't know; this isn't easy for me, but I'm embarrassed to say that out loud.” The ones who have a fixed mindset might be less willing to try.

S: Yeah, yep.

C: And then you have this big problem where the girls start to drop out, 'cause they go, “I'm never gonna get this,”

E: Right.

C: “and everybody else is acting like it's so easy. I don't know why I don't get it.”

B: Oh, wow.

C: Yeah.

S: Yeah, so this research – when the researchers specifically said that, assuming this all pans out. It's one study, right? Or one series of studies. Obviously, especially with psychological research, this needs to be replicated, need to be looked at from different angles. But if it holds up, they said that this would support teaching students that their intelligence is malleable. It's changeable. That they can actually get smarter by studying, because that will motivate them to do so.

B: Yeah, but Steve, shouldn't you be distinguishing {{w|intelligence}} from {{w|knowledge}}?

C: Well, intelligence is broken into crystallized and fluid,

B: Right, right.

C: So there's a huge aspect of even standard, classical {{w|Intelligence quotient|IQ}} tests that are just fixed knowledge, where it's like, “Do you know this thing?” And yeah, if you had read a book, you would know that thing. And if you hadn't read that book, you wouldn't know that thing. That's still a portion of what you get on an IQ test.

S: Yeah, Bob, you can't really answer that question because nobody knows what intelligence is, right?

''(19:15 Cross talk. Very hard to hear)''

B: Well

C: You see!

B: That's exactly it! That's exactly it, I think, is that we throw around this word, “intelligence,” and it's so nebulous. It's hard to define. So just throwing that around I think makes it a little confusing.

J: Steve, you might not know what intelligence is, but I think we know what stupid is.

''(Cara laughs)''

S: Well,  ''(chuckles)'' I know you're being facetious, but not really, because the point is ''(Cara laughs)'', there's so many different aspects to it that it all depends on what you choose to look at, how you choose to measure it. There's no real one generally accepted operational definition of what quote-unquote, “intelligence” is. It's many, many things. And certainly some aspects of intelligence are malleable. You can improve your knowledge, your skills, your thinking ability – all the important things, you can affect. Now, it may take some people longer than other people. This is ...

E: Right

S: something we've talked about on this show before as well, that evidence shows that anybody can – most people. Two {{w|Standard deviation|standard deviations}} let's say. Whatever. Most people can become good at most things, but there's a huge variability in how much time and effort it will take. A talented person will get there quicker.

C: Yeah.

S: Somebody who doesn't have the talents for that particular skill will take a longer time. But they can get there if they work hard enough, you know? It may take twenty thousand hours instead of five thousand hours, but you'll get there.

C: And that's another reinforcement of a lot of the gender biases that we see, again, with STEM education, because a lot of times you'll hear people say, “Oh, but boys are better spatially. Boys are better at reading maps.” And yes, on average, if you look at the two groups as a whole, and you compare their means to one another with no training, you will see that there is bit of what people think might be an innate, or might be a learned improved ability in boys over girls.

But study after study also shows that you can train yourself out of that. The minute that girls sit down and start working on their spatial ability, there's no significant difference any more.

S: Exactly. So, the thing is, there are things we can change, things we can't change, and just don't worry about the things you can't change because you can't change them! Focus on the things that you ''can'' change. What we can change are peoples' attitudes, how hard they work, and the thing is, the bottom line is that the work does pay off, you know?

B: Right.

S: It's not as if we're deceiving them by saying, “Oh, work hard,” when we know it's not gonna make any difference. It ''does'' make a difference. You ''can'' think better, be smarter, know more, improve your skills, be academically better. You can improve all of those things. If you want to be a concert pianist, you can be. It'll just take you however long it will take you depending on where you're starting from. But the work does pay off. That I think is overwhelmingly the result of research in that specific question.

So it's good to emphasize that, especially to young kids. Just to emphasize the fact that, “Hey, you know, you could become good at anything that you work hard enough at,” without being – I do think that ... I don't like the platitudes, like, “You could become anything,” you know.

C: Yeah, you'll be the President one day. ''(Evan laughs)'' It's like, “Maybe ...”

S: Yeah, it's like, unrealistic

E: President of what?

S: If you get too unrealistic, I think that's actually demotivating,

C: Yeah.

S: You know?

E: Right, because you set the goal too high. That it's impossible to achieve.

S: {{w|Richard Wiseman}} spoke about this on our show as well. If people focus on some far off goal, that's actually not motivating. It doesn't help them get there. Like, imagine yourself the CEO of a company. That doesn't help you. ''(Cara laughs)'' What helps you ''(Evan laughs)'' is planning the very next incremental step.

C: Yeah.

S: How are you going to get there? If I study, I will get better at this, I will do well on this test. That's what you need to focus on, is the steps that you need to take. And then just do them one by one.

B: Yeah, but Steve, if you stress the goal, the end goal, wouldn't that help you, or motivate you to plan the next incremental step?

C: If that's a realistic end goal. But if it's so far in the future, you'll give up. You'll feel like, “Ugh! I'm never gonna get there!”

S: Yeah, it's demotivating if it's too far in the future, is if it's too many steps ahead – this is what Richard Wiseman said, the research shows that it actually becomes demotivating, because it's so far away, you'll be like, “Oh, god, why bother?” It's daunting! It's daunting, as opposed to, you know, it's like on {{w|The Martian (film)|The Martian}}, right? It's like he said, “You solve a problem, and then you solve the next problem. You solve enough problems, you live.” You don't worry about where you're gonna be a year from now, two years from now. You just solve the problems that are in front of you. There is something to be said for that approach, you know?

B: Steve, it's funny you mention Watney from The Martian, 'cause you're right. He did say, “You focus on the next problem, and then the one after that. But he also focused on the end game, and he very anally would figure out and extrapolate everything. “I've got two hundred days of food left. I will run out of air ..”

S: Yeah, that's planning though!

B: Yeah.

S: That's fine. That was planning.

C: He's also an astronaut. He's got, like, extra skills.

S: No, but planning like that is fine. And, again, Wiseman said it's not just focusing on the very next step. You could focus on the steps you need to take to get to your goal. Don't focus on the goal; focus on the steps you need ...

B: Yeah

S: to take to get there. And of course, you're gonna do the next one, the next one. It's okay to plan them out, like planning seventeen chess moves ahead. That's fine. But you're not just imagining yourself winning; you're imagining the moves you have to make to win. That's the difference. All right, let's move on. 

=== AI vs Go Champion <small>(24:44)</small> ===
* [http://phys.org/news/2016-03-game-ai-human-smarts.html Phys.org: Game AI a challenge to human smarts]

S: Speaking of playing games, Bob, I understand that another icon of human dominance has fallen

B: In a lot of ways, yeah. I think we are witnessing one of the few of the big milestones of {{w|artificial intelligence}}. And what has happened, an artificial intelligence has beaten the best human {{w|Go (game)|Go}} player in the world. Now, keep in mind, this was game one. As of this recording, we're talking game one of a five game match. But {{w|AlphaGo}} has beaten him in the first game. The human world champion {{w|Lee Sedol}}, as I said, lost game one. And he was beaten by {{w|Google DeepMind|Google's Deep Mind}} AI program, called AlphaGo.

Now, I'm sure most people know about Go, a twenty-five hundred year old game created in {{w|China}}. It's called, “Go,” or “Boudakin.” It's one of the oldest board games played today. Its name means “encircling game.” And that's pretty much exactly what you have to do. You have to surround the largest total area of the nineteen by nineteen board with your playing pieces – they're called “stones.”

Now it seems like a simple game. Black and white stones; you got a board; so it seems simple; the rules seem simple; but that belies a fiendish complexity that far outstrips games like {{w|chess}}. And it's for that reason that Go has been literally one of the outstanding grand challenges for artificial intelligence.

I remember when an AI beat a grand master at chess, that, “Yeah, but it's never gonna beat Go. It's just too complicated.” So, for example then, in terms of complexity, the number of different games of chess has often been listed at ten to the hundred and twenty. And you see that a lot as you Google around. But I dug a little deeper on that one, and actually, it's a little bit controversial. But I'd have to say that the ten to the hundred and twenty different chess games is unrealistic because it includes legal moves that are completely unreasonable, that you would never make; like if you could beat somebody in one move, but you decide to do something else instead of beating him. Why would you include that in the scenario?

So, a better approximation that I came across is ten to the forty, which is still a massive number that's huge. Huge number of people can play for eons, and still be barely scratching the surface in terms of all the different types of games.

Go, on the other hand, of course, has far more possibilities. So, to put it in context, how many atoms are there in the observable universe?

E: Ten to the ... eighty!

B: Aaron – Evan, you are right. Ten to the eighty!

C: Wow!

E: Yeah.

B: Give or take three. Now that's ''(Cara laughs)'', that's a big number. That's – of course I looked this up – ten to the eighty is one thousand quadrillion vigintillion. ''(Cara laughs)''

J: What, now, what's a vengintillion?

B: It's a ...

C: Vengintillion?

B: It's a lot! It's a lot.

E: ''(Laughing)''

B: But I found a better one. It's ten to the eighty is one hundred quinvigintillion. ''(Cara laughs)'' But that's nothing. That's actually nothing. Go has, guess how many possible games Go has? Ten to the...

E: Oh, gosh. Ten to the...

C: Vigivivivillion

E: Five hundred? ''(Jay and Cara laugh)'' Vidvidovigin.

B: Ten to the seven hundred and sixty-first power.

C: ''(Laughing)'' Holy!

B: Seven sixty one! Think about that!

J: What the hell?

B: And of course, did you know, there's a name for that. And that name is one ...

E: Googolplex.

B: No, no. It's [http://www.isthe.com/chongo/tech/math/number/tenpower.html one hundred duocendoquinquaggintillion]. ''(Cara laughs hard)'' Ten to the seven sixty one. I love it! So ...

C: Say that again. Say that again, please.

B: One hundred duocendoquinquaggintillion. So it's this complexity ''(Cara still laughing)'' that prevents modern computers from using a brute force method to look many moves ahead of what a human can do when playing Go. And this is what {{w|IBM|IBM's}} supercomputer {{w|Deep Blue (chess computer)|Deep Blue}} did in 1997 looking many, many moves ahead of chess champion {{w|Garry Kasparov|Kasparov}}, ultimately defeating him. Now that wasn't the only method that it used, but that brute force method was key.

Now, AlphaGo, made by Google's acquisition Deep Mind, has to do things differently. It uses a technique called {{w|Deep learning|deep learning}} on its {{w|Artificial neural network|neural network}}. And that involves massive amounts of data. They took thirty million moves from expert players, and incorporated that into the AI to teach it how to play.

But that was just the first step. Because if you just think about it, that could only bring you so far, because the best case scenario, the system would only be as good as those expert players, right? How could it be better if you use the information from the expert players. So for it to beat the best humans, to take it to that next step, it had to do something called reinforcement learning. This involved the system playing against different iterations of itself, right? So it's just a program. You could just copy it and duplicate it. And you make some tweaks here and there, and you play it against itself, essentially.

So this built up a whole new suite of moves. After the AI learned what moves worked best, and which ones provided the most reward. So it analyzed it. So this allowed it to learn as it played, by analyzing more and more data. And this is very different obviously from learning just how to explore every possible move and counter-move in the brute force technique.

So this reminded me of a comment I came across by a {{w|Gizmodo}} commenter. His or her was Vashieu; and he said ...

E: Guzhunheit

B: “And with all the supercomputing power, it still cannot '''learn''' how to beat a professional Go player.” And he had “learn” in bold. Of course, he was implying that this program was just fed all the rules. But that's not it. Based on what I just said, I think it's obvious that that learning – actual learning – was a very, very important part of the process for Alpha Go to be as good as it is.

So now Lee Sedol, before the match, he was very confident. He predicted a five-oh match, or four-one ...

J: You see that Bob?

B: Four-one at worst. What?

J: He was overconfident!

B: Sure!

''(Cara laughs)''

S: Yeah.

B: ''(Laughs)'' Well, I mean, if you're ten years the grand master at anything, you deserve to be confident as hell.

J: Did he get to wear a cool outfit? 'Cause he was the grand master? That'd be pretty bad ass.

S: You get a cape or something?

E: Grand master class ...

B: He talked to the CEO of Deep Mind though. And after he talked with him about how AlphaGo works, he's like, “You know, I don't think I can win five-oh. I feel that I should be on the edge during the match,” he said. ''(Evan laughs)'' So then he lost the first game. And then he said, “Alpha Go made moves that no human would ever make. It really surprised me.” So that was interesting.

C: It's like when you play {{w|poker}} with people who don't know how to play, and they take your money because they do stupid stuff!

E: That's right!

B: Yes!

C: And you're like, “You should have never been in that hand!”

B: Right

C: “Because you had ''(inaudible 31:43)'' a river!”

''(Cross talk)''

E: Seven-two!

J: I'm not angry at all!

B: That's how, that's exactly how {{w|James T. Kirk|James Kirk}} beat {{w|Spock}} in that {{w|Three-dimensional_chess#Star_Trek_Tri-Dimensional_Chess|tri-D}} chess. He's like, “What? What are you doing? It's so illogical!” So also, he said – this is a weird comment. He said, “He cannot read the feelings or aura of AlphaGo,” which of course is like,

C: Uh oh.

B: Okay, whatever.

J: Whoa!

E: Neither can I, or anyone else!

B: But to prepare for it though, he said he played with himself for one or two hours a day,

J: What!

B: Sorry, he played ''by'' himself for two hours a day to prepare. ''(Evan laughs)'' But you know, at this point, it doesn't even matter. Even if AlphaGo loses the rest of the matches and gets sweeped, it has already proven to be an effective method. It already beat this guy once, and that was actually a big surprise, because even as of less than a year ago, experts would say, “We're ten years away from being able to challenge a Go grand master.” And it looks like they've already, they're pretty much there. Or I guess we'll know in a few days. I think by Monday or Tuesday – the 15th of March, the match will be over. We'll know who has won.

But it has shown to be an effective method already. And one of the most important things is that this could lead to far more than just a one-off AI that's great at the game of Go. It means, so what? If that's all it does, it'd be fascinating, but it really, I think we'll be able to apply this technology to many other fields. And it could be transformative.

For example, {{w|Nick Bostrum}} of {{w|University of Oxford|Oxford University's}} {{w|Future of Humanity Institute}}, he said, “AlphaGo is really more interesting than either Deep Blue or {{w|Watson (computer)|Watson}} because the algorithms it uses are potentially more general purpose. If you remember, Watson was the one that beat the champion at {{w|Jeopardy!|Jeopardy}}

E: Jeopardy!

B: So, Deep Mind...

S: That was more of an expert system,

B: Right.

S: Whereas this is more of a game playing algorithm.

B: Well, exactly my point! Because that's exactly what the point is here is that it's general purpose. It's not an expert system. And that's what they're saying. These are more general purpose, which means we will be able to apply it to lots of different things like robotics. Deep Mind founder {{w|Demis Hassabis}} has said the same thing. He said it's a natural fit for robotics. It could help robots interact with their environment.

S: Or how about things like taking over air traffic control?

C: Ooh!

B: Sure, yeah, exactly. The other things that they say is that it could help scientists zero in on research into areas that are likely to produce results. Or it could suggest or point a human towards a breakthrough. But it's not just science and research and things like that, or robotics. They're saying that this could be applied to digital assistants like {{w|Siri}}, financial investments. I think this guy, Chris Nicholson, he's the founder of Deep Learning startup {{w|SkyMind}}. He had an interesting quote. He said, “You could apply it to any adversarial problem. Anything you can conceive of as a game where strategy matters,” you could potentially apply this to.

So, yeah. So, Jay, let's say this is coming out on Saturday. So yeah, you could watch the last couple games, the last few games if you're listening to this on Saturday when this is released, and see where it goes. But I guess I'll just end this with a “better start practicing your robot sucking up techniques,” because it's happenin' baby!

C: ''(Quiet laugh)''

''(Commercial Break: 35:09)''

=== Minority Report <small>(36:33)</small> ===
* [http://www.dailymail.co.uk/sciencetech/article-3483859/Minority-Report-style-machines-solving-crimes-happen-AI-successfully-identify-likelihood-domestic-violence-90-cases.html?ITO=applenews Daily Mail: AI identifies likely repeat offenders]

S: Well, Jay, you have another related item; another AI item. I wanted to do these two in tandem. This time, they're predicting peoples' behavior!

J: Yeah, this is where I think it starts to get a little creepy, right? So, first of all, this is interesting because the news item that I found, of course, invokes the {{w|Tom Cruise}} movie about ... what was the name of that movie?

S: {{w|Minority Report (film)|Minority Report.}}

E: Legend!

J: Yeah, and they always pull out Minority Report whenever they have anything like this, ''(Cara and Evan laugh)'', telling the future type of predictive behaviour type of news item. So, to be clear, this is actually not about predicting crimes done by those who have not committed crimes previously. They're using records from people that have already committed crimes, and specifically about people who've committed a violent type of crime against another person.

So a team of scientists that are working at the {{w|University of Pennsylvania}}, and they have their software that they created, examined twenty-eight thousand cases of domestic violence. And out of all the cases, the offender was actually charged with a crime, and then later released. And the researchers were able to identify the people on that list, out of the twenty-eight thousand, that were the least likely to commit an act of domestic violence in ninety percent of the cases studied using this software.

It seems like a good thing, right? The predictive behavior technology could also easily turn into a big brother type of technology, right? More of that in a minute. But I first off want to get your opinion. What do you guys think about using software to try to predict whether or not a criminal will be engaging in criminal activity in the future?

C: I mean, it's probably better than just a cop going, “Yeah, he's probably gonna do it again!”

S: It's basically using a computer to use big data. You're just using lots of data points to make statistical projections. It's fine!

J: I like this and I don't like it. And I'll tell you why. Because the first thing I thought about when I read this was, “Well, what are they gonna do with it? What are they gonna do with this software?” Right? So they have a piece of software running, and it says, “Okay, out of these twenty-eight thousand people, here are the people that we know aren't gonna be violent. But here's a list of people that we think will be violent.” Let's say ten years from now. The software's more tricked out, and it can actually predict whether or not someone's gonna be violent.

So what do you do? What do you do with that information? Let me tell you what is happening today. The Chinese government is actually working on a version of this predictive software called, “predictive policing,” and their system will combine machine learning, like Bob was talking about, and using big data like Steve was talking about. And they use facial recognition. So they use it on surveillance cameras, and they're going to assign people a threat score.

And they plan to include information from bank transactions, and emails that the person sends, and video footage of the person's behavior from the past to try to figure out if they're showing behavior that indicates that the individual is probably going to commit a crime.

So now, they're taking this concept of predicting peoples' behavior, and they're spying on people. And then they're gonna use that information again, to do what? Because at some point, they're gonna do an intervention, right? They're not waiting for the crime to be committed. It doesn't seem like it. I think that that kind of breaches privacy; it breaches ...

C: Well, what's the part you're concerned about though? The spying part? Because that's a separate issue that's already happening. Like, it's one thing to be kind of naive and say, “Oh, the idea that they have security cameras everywhere, and they can watch over us,” - that exists! And not just in China. Every street corner in {{w|Los Angeles}}, almost, goes to the traffic control center.

J: That's a slippery slope! It's starting to get to a point where there really are cameras almost everywhere, especially in public places.

C: Yeah.

J: You know, there's cameras in parking lots, inside stores, outside stores, things like that. But then, Cara, the thing that kind of bothers me here is, what's the actionable item with the information? So let's say the computer gives them a threat score that hits a threshold. What do they do? What do they do at that point?

E: I guess they monitor the subject?

C: Yeah, at that point, it's a civil rights question. So are we talking about ... it's probably very different in China than it is here, but the same thing here. What happens when somebody is arrested, but there isn't good cause? What happens if they're detained and then they're let go later? How are they treated during the time when they're in custody? Are they being questioned? Are they being treated aggressively? But that has so much I think less to do with predictive policing, and more to do with having well-trained forces.

J: But I think it turns things into more of a {{w|police state}}, right? Where you have, it's like, “Stay in line or else.” And then the “else” could be whatever the government wants to do. I think it's moving in a direction that could be easily abused.

C: I feel very strongly, and I'd be interested to see what people think about this, that the mentality is already there. We're not talking about the technology allowing us and changing our mentality to be more of a police state. I think that we are already living in a police state, and the technology is finally allowing these institutions to do what they've always been doing, just more effectively and more efficiently.

So, yes, I am concerned about more of the existential questions that you're concerned about. I recommend reading {{w|Radley Balko}}; he's so good. He writes about this, the militarization of American police. But I think the technology's not what's making us more of a police state. We already ''are'' that way. The technology is just allowing it to be more efficient.

J: Yeah, I hear what you're saying. It's almost like the desire has been there for a long time, and now the technology's kind of catching up. But either way ...

C: So it's not a slippery slope; it's just an eventuality.

J: Right, and I have to say, after researching this and really thinking about it, like, wow. The technology is here, or it's very, very soon to be here. I don't agree with it. I think, yeah, I want to do what we can to protect people. Of course I'm against {{w|domestic violence}} – horrible! Of course! And I would love to be able to stop people from having to experience that and go through any kind of thing like that.

But at the same time, though, you know, it's one of those deals. I agree with both sides of the coin in a sense. But it could get to the point where this becomes incredibly repressive. And we can't let ...

C: Yep. Well, it's unconstitutional.

J: Yeah.

C: You cannot detain somebody for something they haven't done yet.

J: Right.

C: Because they ''might'' do it. That's {{w|Internment|internment camps}}, ''(chuckles)'' you know what I mean? We have a history of that; and it's not good.

J: Yeah, so what do you think, Steve?

S: I think both views are reasonable. It all depends on how it gets executed, right? The devil's always in the details. Obviously, we need police. And there are gonna be criminals, and we need to handle them in some way. And we already use psychology to try to evaluate criminal behavior, and try to predict their probability of {{w|recidivism}}. Are they gonna commit crimes again? You try to get inside the head of criminals. And it's all very subjective, and not very accurate.

So I think any tool that we use to try to give us some more predictive power rather than subjective feelings ... it's like the {{w|sabermetrics}} of crime, right? Instead of going with your gut feeling about whether or not this is a good baseball player, you're gonna use statistics and number crunching with a computer to predict the effect that they're gonna have on your team's performance.

And this is the same thing! I think this is fine. It's the sabermetrics of crime. It's just using computers and big data to have better predictive value than just a subjective evaluation.

E: Are you saying ...

C: And that's already happening

E: sacrificing?

S: Yeah.

C: Privacy.

E: Wait, what's the ... yeah, privacy.

C: That sacrifices privacy.

E: Right.

C: But the truth is that is ... we've already moved past that.

S: I don't think ...

C: It's already happened.

S: I wouldn't be blasé about the sacrifice of privacy, but that's a separate issue.

C: It's a separate issue that ...

S: It's a separate issue. How you gather the information is separate from what you do with it once you have it, in a way.

C: Yeah, and I think that's an important .. we tend to mix those things up in our minds. But like you said, the devil's in the details. It's so true. We covered this last season on the {{w|Al Jazeera}} show – tear - that I used to work on when Al Jazeera existed.

S: Yeah.

C: And – sads – but I didn't. {{w|Lindsay Moran}}, one of our reporters covered it, and she went to – ooh – don't quote me, she went to the bay area. And they were talking about {{w|predictive policing}}, where they would look at all this big data, and they would know where these hot spots of crime happen, and at what time of day.

So they could send more police to these areas that statistically have higher crime rates. So that they were more reinforced. And it seemed to be working.

E: And that ...

S: Yeah, the effect is very weak, if I remember.

C: It was, it was.

S: It was there, but it was very weak.

C: Yeah, it was there, but it was weak. But it was still better than, like you were saying, the “feely” effect. That corner ... ugh! I always see the bad element on that corner! Looking at data is definitely ... takes the emotion out of it!

S: Right.

== Who's That Noisy <small>(45:55)</small> ==
* Answer to last week - modem sound

S: All right, Jay, it's Who's That Noisy time!

J: Last week, I played this sound: 

''(Something that sounds like chimes, then wind, an electric vibration sound, more windy chimes, turning into a static sound.)''

J: Now tell me, anything familiar about that sound?

E: Hmm... gee...

C: It's an exorcism!

S: Sounds a little {{w|The War of the Worlds|War of the Worlds}}

E: {{w|Darth Vader|Darth Vaderish}}

C: It's a demon! Is it a demon?

J: All right, this ''(Evan laughs)'' Keep that sound in mind. Now listen to this:

''(Phone beeps and boops)''

''(Evan laughs)''

C: Ah! Dial up! It hurts! ''(Modem dial up sound)''

J: ''(Laughs)'' It's the old dial up sound slowed way down.''(Rogues laugh)''

B: Oh god!

E: So, the slow just got slower?

J: Yeah, but what I thought was really clever about slowing that down is it still kind of sounds like it if you listen to it again, you'll definitely be able to hear it this time. But it takes on almost a mean vibe to it.

C: Yeah, it's demonic!

J: Yeah, and it has for those of us who were using dial up, we'll never forget that sound. It is one of the unique sounds of our lives.

''(Several rogues cross talk indistinguishably)''

E: Half our audience has no clue.

C: Well, that's what I was gonna say. I bet you if we stay on for ten more years, you could just play the dial up sound.

S: Yeah, right.

C: ''(Laughing)'' And people will be like, “I don't know what it is.”

J: That's right. So, I had a couple of funny guesses. So, I told everyone to use their gut last week, because I wanted people ... because when I first heard it, and I didn't know what it was, I felt like I knew the sound. And I was hoping that some one would guess it. And you know what? Somebody did guess it actually.

B: No shit!

J: James – yes, James Coultass, one of our listeners guessed. I also got a couple of really funny, horrible guesses. So one person said, this is Tobeeas or Toe-bias (Tobias) Korell.  He said, “You said go with your gut, so I'm guessing that this week's Who's That Noisy is the sound of a stomach rumbling that has been audio-processed, time-stretched in the software Apollostrich.” <!-- I could not find any clue of what this software is, or if I spelled it right --> ''(Chuckles)'' Nope! And Karstin guessed, “The first recording of the Tibet Monk chant.” ''(Laughs)''

C: Yeah

J:Not even close, man. That's a funny guess. So let's move on to this week's Noisy. What is this sound?

''(High pitch pulsing vibration sound with a static electricity element to it. Gets slightly louder at the end)''

J: So, send in your guess, or send me a Noisy you heard this week at wtn@theskepticsguide.org.

''(Commercial at 48:45)''

== Questions and Emails ==
=== Question #1: Piloting and Valsalva <small>(50:24)</small> ===

S: We have a couple of interesting questions this week. These are both follow ups to previous discussions. First one comes from Brad from {{w|Seattle}}. And Brad writes: 

<blockquote>The first five minutes of [[SGU Episode 556|episode 556]] were difficult to listen to. It was quite astounding and embarrassing to hear Steve claim competence as a pilot after a brief experience in {{w|NASA|NASA’s}} fixed based simulator. To begin with, he was totally oblivious that landing an airplane is the culmination of the previous twenty minutes or so of energy management (airspeed and altitude modifications) and navigation decisions to place the airplane in the ideal position to even be able to attempt a landing. The landing itself is a basic maneuver which can be learned fairly quickly, but equating completing the final touchdown with being even remotely capable of flying the airplane to a successful landing is very naïve.</blockquote>

He goes on with some more details there, but then he has a second point to make. He writes:

<Blockquote> Even all of this buffoonery this would be forgivable, but the one area related to human physiology was the most shocking of all coming from a medical professional, i.e. confusing the {{w|Valsalva maneuver}} with G-resistance straining. Even when {{w|George Hrab|Mr. Hrab}} correctly suggested the contrary that the Valsalva is to clear the ears and sinuses, Steve bulldozed his way right on through it, disregarding input to the contrary. This was a great example of a little bit of knowledge being a dangerous thing.</Blockquote>

Again, he goes on a little bit further, but that's the crux of it. So, I thought this would be an interesting email to discuss. I did email back Brad, and we had a little bit of a discussion. The interesting thing is that Brad is completely wrong on both points.

C: ''(Laughs)'' Shit! ''(Evan laughs)'' I was like ''ugh!'' when you started reading this.

S: Yeah, so actually, he said, “I'm sure I'm not the only pilot to respond.” Actually, you ''were'' the only pilot to respond. But here's the thing: I never, ever suggested that I can fly a plane. He got that completely backwards, which is interesting because I was actually very conscious not to do that during the discussion, and when I was listening back during the editing, because I didn't want to give the impression that I was in any way suggesting that I thought that I could pilot a plane after a half an hour in a simulator.

So that's why I found his take on it interesting. And he's a pilot. This is his career, so I think this is an example of somebody hearing something through a very particular filter because they have an emotional investment. I specifically said that they had me all lined up to the runway, and that they did all the complicated stuff in the cockpit. And all I had to do was basically steer the plane down to the runway, which he admits, that's the easy part. Yes, that's why that's what they let me do, because that's the easy part.

E: ''(Laughing)'' Yeah, because otherwise you'll crash.

S: Right. So I don't know how he got this impression from what I said. That's what I think is what's interesting here, is how ... and this is not an isolated incident. This is an every week thing.

B: Oh my god! At least!

S: We get emails from people who hear segments completely different than what we said, what we intended, what our impression of it is. And it's interesting, this is I think a general phenomenon, that we all have filters in our head. This is why you can have a conversation with somebody – especially if it's a heated conversation – and then you both have completely different memories of the conversation you both just had, right? You've all had that experience.

B: Oh my god! Or ...

C: Yeah, have you ever had a significant other?

S: Yeah, yeah, exactly.

C: Right.

B: Or how about this one? Somebody is relating to you a story of what happened, and you happened to be there, perhaps unbeknownst to them. So you're listening to their take on the scenario, and you were right there, and you're like, “Wow! That's what your takeaway was from that? I was right there!” You know? So it's fascinating.

S: Well, but your takeaway is just as unreliable-

B: Exactly!

S: as theirs. But we all have a narrative-

E: That's the point. That's the point.

S: We pay attention to bits and pieces filtered through our narrative. And also, it's in the loop of what we're thinking at the time. So we come out the other end, again, with a sort of impression of what was said, and somebody else could listen to the same exact thing and come away with a completely different impression.

J: I know, that's true, Steve. But I'll tell you what. That happens. My wife and I will get into an argument, but she's always right.

S: ''(Laughs)'' Yeah, when she's convinced you, huh Jay? ''(Bob laughs)''

E: Do you think Brad was referring to the part of that discussion in which it was brought up that if there were an emergency, and you had to go and assume control, with aid, you might be able to survive some sort of ...

S: Yeah...

E: half-assed crash landing or something.

''(Cara laughs)''

S: George asked me if in an emergency, could I be of help. Not, could I fly the plane, or would I feel comfortable landing on a plane. And I said, “Yeah, I think if there were favorable conditions, and somebody was talking me through it, it would not be pretty, but we might survive. That was, you know...

B: Right, Steve. And you also brought up the point, Steve, that this has happened many times in real life!

E: There was a movie about it called, “{{w|Airplane!|Airplane}}.”

S: That is, I actually looked it up. I looked it up because I was interested in that. It's happened in private planes. It's never happened in a commercial airliner.

C: Well, that's comforting. I have to say.

S: Because there's always two, three people who can fly in a plane, you know what I mean?

B: Right, right.

S: It could be an unusual circumstance for it to happen in a {{w|Boeing 757|seven-fifty-seven}}, which I was training in. Yeah, but he interpreted me saying that I couldn't land in a cross wind, which to me, that's the caveat. That's me being self-deprecating. Like, yeah, this is hard. I could do it if there's no wind. ''(Cara laughs)'' And he said, “Oh, how could you consider yourself competent if you can't even land in a cross wind?”

B: ''(Groaning)'' Oh...

S: He completely interpreted the opposite of what I meant! Isn't that interesting?

J: It is, and I think part of it is like you were saying, from a pilot's perspective, first of all, there is no wriggle room here. You're either trained to fly ...

S: Yeah

J: these million dollar airplanes with two to three hundred people on it, or you're not, and you shouldn't even be suggesting that thirty minutes in a simulator takes you anywhere.

S: Yeah

J: And I get his perspective. He's probably just being ultra-protective about the sanctity of sitting in that chair, you know?

S: Yeah. I mean, let me be absolutely clear ''(laughs)''. I have absolutely zero competence to fly a plane. But the {{w|MythBusters|Myth Busters}} did this themselves. They asked the same question, right? They did a show where they said, “Could somebody talk a novice down to the ground?” And they found out that yeah, you could! They went into a simulator, and with no previous experience, had the tower talk them through the process of just putting the plane on the ground, and they did it without crashing.

So what's interesting is just that the steering of the plane down to the ground is like a video game. That part – as he admits – that's the easy part. It's all the complicated stuff, putting the flaps in the right thing, and getting to the right air speed, and lining yourself up, and all that stuff, putting the gears down, they did all that. I didn't have to do navigating. Forget about that! That's what all the complexity is!

But any way, I thought that was interesting. But here now, the second thing, Cara, you're gonna be especially interested in this. So he said that I was wrong about this Valsalva maneuver, and that he was shocked that a medical professional would get that wrong. So this, we're gonna do an impromptu Name That Logical Fallacy – or it's actually a bias. He's committing a very, very, very common bias in his interpretation of this.

So, he has a certain understanding of what the Valsalva maneuver is; and it differed from what I said. So he assumed that I was being arrogant. He was assuming that the disconnect was because of my personality – an internal cause – rather than questioning whether or not there might be an external cause. So that's the {{w|fundamental attribution error}}, right? We're very willing and will very easily assume that other people do things for purely internal personality reasons, or motivational reasons, rather than considering, “Okay, is there an external thing here I'm not aware of?”

So, I do this all the time, but I've really, really made an effort to train myself, like, whenever I think that somebody else is wrong, or that they disagree with what I think I know, my first instinct is, “Okay, am I wrong? Let me first make sure that I'm absolutely correct.” And then if I'm correct, then I think ,”What, are there any situation that might explain this?” And then, resorting to internal personality explanations, that's the very, very last thing I will reluctantly go to only if I've exhausted everything else.

I think that's a good process to go through. If Brad had gone through that process, he might not have written this email ''(Cara laughs)'' because what's interesting is that he was taught wrong. Now I'm taking him at his word here. He says that thirty years of training as a pilot, and this is what everyone in aviation thinks the Valsalva maneuver is. Well, if that's true, then everyone in aviation is wrong.

C: So what did he say it was, and what did you say it was?

S: So he says the Valsalva maneuver is blowing out your nose to clear your ears, or clear your sinuses. That's what George thought it was.

E: Right.

S: And that, what I was describing, what George was describing is what he calls G-resistance straining. So, now, of course, I learned about the Valsalva maneuver in medical school; and it wasn't just in passing. This is a classic physiological concept. I know it inside and out. There's many, many, many papers written about the Valsalva maneuver and its implications. In fact, I remember this funny story from medical school. Do you know how {{w|Elvis Presley}} died?

B: Straining.

E: On the toilet.

C: He was straining!

S: On the toilet. He had a {{w|pulmonary embolism}} because of the Valsalva maneuver. Because when you bear down to have a bowel movement, that causes the Valsalva maneuver. And then when you release, it sucks basically the blood up from the veins in your legs, and that dislodged a blood clot, and caused a pulmonary embolism.

J: So he was actually trying to clear his ears?

S: No, ''(Steven and Bob laugh)'' So, but it's -

C: It's – we use our own internal airway to impart pressure on other parts of our body.

S: So, let me give you the precise definition of the ...

C: Okay

S: Valsalva maneuver – the intention any way. The effect is to increase pressure within the thorax – within your chest. And by increasing the pressure inside your thorax, you increase your {{w|Blood pressure|systolic pressure}} – which is good for {{w|perfusion}} – but you also decrease venous blood return from the lower extremities because now the pressure gradient is going the other way, right? The pressure's greater around your heart than it is in the veins in your legs. So you reduce that venous return. So if you hold the Valsalva maneuver for twenty, thirty seconds, a minute, and then you release it, you could actually pass out.

C: Oh yeah.

S: Because your blood pressure drops, and you don't have the venous blood return to keep it up, you know.

C: Little kids do it when they throw fits. Like, 

S: Yeah

C: you see them, and their face is turning red. And you're like, “You need to breathe; you need to stop.”

S: Yeah

C: 'Cause they're pushing, pushing, pushing.

S: So, the way to increase pressure in your thorax is to contract your thorastic muscles, right? Your breathing muscles, or your abdominal muscles, 'cause that pressure gets translated right into your thorax through the {{w|Thoracic diaphragm|diaphragm}}, right? So one way you can – and if you read the text, it says you could breathe out against a closed airway. That was misinterpreted as blowing out against your nose, right?

C: Which is one way to ...

S: Which puts the pressure ... yeah, but it depends on where the pressure goes. You could all do this right now. Take a deep breath, and then bear down. Breathe out, but close your throat off, and breathe out. And you can feel that pressure's all in your chest, right?

J: Yeah

C: Yeah

S: Now, hold your nose and blow out through your nose. Where does the pressure go?

B and C: Your ears!

J: It went right in my mouth.

S: Your ears!

E: Yeah, the ears.

S: It equalizes the pressure in your inner ears – these are two totally different things. They're only superficially similar in that you're blowing out against a closed airway. But in the Valsalva maneuver, the pressure's going to your thorax. And when you're clearing your sinuses, you're equalizing pressure in your inner ear to the throat, really, is what you're doing. The pressure's all going in your head, right? It's all going to your ears. Two totally different things.

But the Valsalva maneuver was misinterpreted as clearing your ears in this non-medical context of aviation -

B: Oh!

S: at least according to Brad ...

C: Yeah, and so when you ...

S: and it was wrong!

C: reading {{w|Wikipedia}}, it's funny. It's on Wikipedia, it lists it as both of those things.

S: But it's not. The Valsalva maneuver is increasing intrathorastic pressure, period.

C: Yeah, that's so weird. Its variations can be used in either for a medical examination as a test of cardiac function, and on autonomic nervous control of the heart; or to clear the ears and sinuses.

E: So what's the other maneuver?

S: Not true! That's not true.

B: So, Steve, what is the medical term then?

S: I actually don't know what the medical term is for clearing, you're equalizing the pressure in your ears. I never heard it. Okay, so here's the thing: I looked up G-resistance straining; and G-resistance straining is actually a modified Valsalva maneuver. So you bear down like George said – you bear down like you're having a bowel movement; and that will give you a Valsalva effect, right? It will increase your pressure in your chest. But you also contract your legs as much as possible as well. And that makes perfect sense.

C: Oh yeah!

S: Because when you contract ...

C: To keep the blood in your brain.

S: Yeah, so you contract – you do a Valsalva maneuver to increase your systolic blood pressure, which is your perfusion pressure, but you contract your legs to increase the venous return up from your legs so you don't lose your venous return. If you do both simultaneously, you get the benefits without the downside ...

B: Cool!

S: and that's how pilots keep from passing out. You can actually add three G ...

C: Wow!

S: to your tolerance if you do that G-resistance straining ...

J: Wow!

S: maneuver ...

J: That is awesome!

C: And this is why training is so important.

B: What about {{w|g-suit|G-suits}}? Does that include ... is that the same as G-suits?

S: G-suits help as well! They do the same thing. They squeeze out everything so you ...

B: So it adds to it? So you can get maybe four or five G's?

S: Yeah!

C: Maybe.

S: I don't know what the exact number is there, but I read specifically the G-resistance straining can add three G's to your tolerance. Okay, let's move on.

== Name That Logical Fallacy <small>(1:04:44)</small> ==


S: We have a Name That Logical Fallacy this week. We haven't had one in a while. This one comes from Tristan. Tristan writes:

<blockquote>Hello happy people – I am finally getting around to watching the original {{w|Cosmos: A Personal Voyage|Cosmos}} and I've had a nagging question about one of the opening sequences. {{w|Carl Sagan}} says that with the number of stars and planets out there there must be other life out there. I've had this feeling before, but I can't help thinking there is a logical fallacy buried in there somewhere. However, with my limited exposure to these concepts I'm hard pressed to determine what it is. I'd be excited to hear a short chat.</blockquote>

So what do you guys think? Did Carl Sagan commit a logical fallacy when he made the observation that with so many stars and planets in the galaxy and the universe, there's gotta be other life out there. What do you think about it?

E: I would argue that because I'm familiar with the Cosmos series, that he brought that up as one possibility; but he also said that there are other formulas out there that say there are not other life out there. So he kind of presented both of them, if you look at it in the larger context.

S: He did, but let's stick to that statement, though. What do you think about that statement.

C: The {{w|Gambler's fallacy}}?

B: No, there's – it's pure probability! I don't think there's a logical fallacy in there. It's pure probability. Chances are overwhelming with the numbers of stars and planets, and galaxies. It's such a huge place, and so much opportunity. If it can happen on Earth, even if it was a quadrillion to one, then there's thousands of other life forms out there.

E: {{w|Law of large numbers|Law of very large numbers}}?

B: It's pure probability!

J: I agree with Bob. I don't think it's a fallacy at all.

S: I agree that, I don't think there's any logical fallacy in there. What I do think is in there, and I think this is maybe what's nagging at Tristan is that there's an unstated major premise, right? So, just, Sagan is not spelling out all of the premises of ... his logic is valid, but what are his premises?

So, one of the premises is that the {{w|Earth}} is ordinary, that there is nothing extraordinary about the Earth. We do not live in a privileged place in the universe or in a privileged condition. And that is a general assumption of {{w|cosmology}}, that the laws of physics are the same everywhere. That by chance alone, we live in an ordinary planet around an ordinary star in an ordinary galaxy, you know what I mean?

That we can essentially say that Earth is typical, and not remarkably unusual. Now, Sagan does say, Evan, at some point, we could be the first life in the universe. Some one's gotta be the first. But what are the odds of that? You know, it's ''possible'', but just statistically – as Bob and Jay say, it's very unlikely. But that's based upon the premise that the Earth is not extraordinary. There's a name for that, like, the mediocre principle<ref>Steve seems to be referring to the [https://en.wikipedia.org/wiki/Cosmological_principle Cosmological principle]</ref> or whatever. We are non-extraordinary.

Which is a reasonable premise. It's a reasonable premise, although it ''is'' an assumption. It is quite possible that life is extremely rare in the universe. And if that were true, any intelligent being – it's like winning the lottery. You would think, well, what are the odds of winning by chance alone? But, you know.

C: But it does happen.

S: It does happen. Anybody, with a big universe.

E: It should happen!

S: Yeah, you can look at it this way: With such a huge universe, with so many stars and planets, very, very rare things are gonna happen. Well, what if we're one of those really rare things?

B: Yeah, Steve, I'm not sure how much bearing that has, because even if we are incredibly, incredibly rare, just the fact of life arising, I don't – the numbers we're talking about are so gargantuan that it doesn't even matter! It doesn't matter!

S: Well, it does matter. It just means you would have to be ''really'' rare. The bigger you're talking about, the rarer it would be. So that's again, I think that's what Sagan is talking about when you put it into that context of that premise, that the more opportunities for life there are, then the only – to say that there's no life out there, the only alternative is that the Earth is an exceptionally rare event. It becomes so rare that that becomes a fantastically extraordinary claim in and of itself.

So I think Sagan's logic is valid. There's just an unstated premise there, which is perfectly reasonable; that life on Earth is not a one-off in the universe, or not extremely, extremely unlikely event.

C: I think that that's what often nags at people is when it's like, “Because of this, there ''must'' or there's ''bound to''”; or instead of saying, “it's highly likely that.”

E: Yeah

C: That would be for me,

E: definitive statement

C: that would be my trigger because it almost feels emotional. So that's, if I would go, “Is that a fallacy that's being committed?” Like, “Oh,” because to me, that could be on the verge of the gambler's fallacy. I know it's not, but if this keeps happening, “Eventually, this ''must'' happen!” It almost feels like it's more in the wording than in the meaning of what he was saying.

S: Yeah, although, you could just write that off as a bit of poetic hyperbole.

C: Which is how Sagan talked.

S: It's a little short hand.

C: And that's what was effective, exactly. I mean, it's beautiful, and it's meaningful; but for somebody who it's like, really putting on their skeptic hat and trying to cut through all the BS. That might be where that nagging feeling came from.

S: Yeah, but you know, but if we say, “Oh! There's gotta be life out there,”

C: Yeah

S: I don't literally mean that there ''has'' to be. ''(Cara laughs)'' I mean that it's so overwhelmingly ...

E: Statistically

S: Yeah.

C: Totally.

S: That's just shorthand.

E: If Carl Sagan had said, “I ''know'' that there is life out there,” then you could really take issue with him in that way.

S: Yeah.

E: But he doesn't say that.

S: He always says “if” – he does say “if there is intelligent life out there,”

E: He qualifies it.

S: Yeah

E: He qualifies it

C: Which is important.

''(Commercial 1:10:25)''

== Science or Fiction <small>(1:11:37)</small> ==

''(Science or Fiction music)''
''It's time for Science or Fiction''

S: Each week I come up with three science news items or facts – two genuine and one fictitious – then I challenge my panel of skeptics to tell me which one is the fake! Cara, you gotta get back into the swing of things.

C: I know!

S: Are you ready?

C: ''(Hesitant moan)'' Yes.

S: Okay, you're ready. ''(Cara laughs)'' Here we go. [https://news.osu.edu/news/2016/03/09/product-placement/ Item #1]: Researchers find that gamers were better able to notice and remember branded product placement in video games the more violent the action. 

[http://www.sciencedaily.com/releases/2016/03/160309082804.htm Item #2]: A new study finds that gender stereotyping is not very different today in the US than when it was thirty years ago.

And [http://www.sciencenewsline.com/news/2016030918520036.html Item #3]: New research finds that voters prefer to be represented in negotiations by people who resort to extortion.

All right, Cara, go first.

C: Gamers were better able to notice and remember branded product placement in video games the more violent the action. I feel like that could go one of two ways. That could either be really, really, true because we do tend to see this more {{w|flashbulb memory}} experience, and this {{w|Posttraumatic stress disorder|PTSD}} experience when linked to things that are violent or aggressive.

The problem is unless the branded product placement is like, on the sword that's being wielded, or the bullet going into the guy's brain spills some brain matter on the wall, “{{w|Doritos}}!” I'm not sure. If it's just in the background, ''(Evan laughs)'' I'm not even sure if it would be focusing on it because they'd be so into the violent part of it.

E: Oh my god!

C: So, I'm torn on that one. A new study finds that gender stereotyping is not very different today in the {{w|United States|US}}. This is one of those ones that's so obvious that it has to be true, because it's like, “Of course that's not the case! Thirty years ago people were calling me, 'Toots!'” But I don't know ''(Rogues laugh)'', if we actually ...

S: Weren't you like, five, thirty years ago?

C: Yes, I was. But, no, thirty years ago, I was actually only two. ''(Laughs)'' But in the eighties, I'm assuming that this is one of those situations where outwardly it seems to be the case, and anecdotally it's the case that stereotyping was so much worse thirty years ago – fifty years ago is different – but thirty years ago? But if you looked at psychological evaluations, and how people actually saw each other, probably stereotypes persist for a reason, and they do have a lot of staying power, unfortunately. So I wouldn't be surprised if that is fiction.

And then, new research finds that voters prefer to be represented in negotiations by people who resort to {{w|extortion}}. ''(Cracks up)'' What? I don't even understand this one! ''(Evan laughs)'' Voters prefer to be represented in negotiations? What? What are they voting on?

S: So, if they're voting for who's gonna represent them in negotiations, they'll take the person who's like, “Yes, I'm gonna use extortion in order to represent our interests”

C: Okay! I thought you meant, like, voters for public office. ''(Laughs)'' I was so confused!

E: So it's more like a sports athlete and their agent maybe.

J: Yeah. Yeah, yeah.

C: Okay, I'll filter it that way, because I have an agent. So, I want my agent – oh! Yeah. My agent does that – well, maybe not extortion – but ultimatums, ''(Evan laughs)'' intense demands, that kind of stuff's important. Like, “You're gonna come to this number or we walk,” that's really important in negotiation. So I'm gonna say that that is science. The middle one I said was probably science. Okay, I'm gonna go, because I was fifty-fifty on the top one. I'm gonna say the top one's the fiction.

S: The gamers.

C: Mm-hmm

S: Okay. Bob?

B: I'm gonna start from the last one – the negotiations. Yeah, I could totally buy that. I mean, extortion sounds pretty nasty, but, use blackmail or force – it doesn't have to be so nasty as EXTORTION type of thing. But yeah, I totally agree with that, for a lot of reasons that Cara said. You want somebody – you probably – a lot of people assume that this stuff is done any way. So if it's gonna be done, I might as well have my guy be willing to do it as well. I mean, I can totally buy that one.

The gender stereotyping, sure. I think we've come a descent distance in that; but I think there's still this undercurrent in a lot of people in the country. So, yeah. So I'm totally buying that as well. 

And I also agree with Cara on the first one, about the branded product in the violent games. Sure. I'm not buying it, because I know for a lot of games, especially violent ones, you're focused on what's moving? What do I need to kill? You know what I mean? ''(Cara laughs)'' Sure, there's some down times, but I don't think you're gonna notice a lot of, like, a {{w|Pepsi}} can on the corner there. I really don't think you're gonna notice it, especially when the action gets intense. It doesn't make sense to me that the violent games would have that more recognizable. I'm not buying it.

Maybe if it was more of a sedate game where you have to really scope out the environment more so than even in a violent game. Perhaps looking for clues ... I don't know! I don't see the correlation with the more violence, so I would say that's fiction.

S: Okay. Jay?

J: The one about extortion, I really like what Bob said. Like, if everybody's doing it; my guy better do it, you know? Cara's reaction is similar to mine. I just think it's a weird idea, but yeah. Okay, if you're gonna get involved in some type of negotiation, you want some one that'll use any technique they can to win – even though extortion seems like a horribly dirty word. But I can't disagree with what Bob and Cara said.

So, this one about gender stereotyping has not changed in the past thirty years – really? I don't know; I feel like the people in my generation and the following two generations have a quite different attitude about gender stereotyping. So I would need more information on this. This is a tough one to call for one sentence. Specifically what hasn't changed? It certainly has ... the society has changed. What's okay in society has definitely changed. It's not like the seventies any more, the sixties or whatever. It's – the world is different. I don't know, but does this mean peoples' sentiments haven't changed? I don't know. I hate to think that that one is science.

But I do have a very strong opinion about the first news item here about the video games. I've played lots of video games historically. I've played a lot of violent video games. And I don't remember any product placement at all! Ever! ''(Cara laughs)'' Not one example of a cereal box or a soda can or a – no! No branding. I don't remember any branding at all, whatsoever! So, I don't know. What do you think about that? And Bob and Cara both picked that. I'm just gonna go with them and say, yeah, this is hoo-how.

S: Okay. And Evan.

E: Yeah, my fellow rogues pretty much covered this one with a blanket. I don't think the subliminal effect here – which is I guess what the branded product placement thing is about - or that concept of a subliminal sort of message holds water here. I'd say that one's the fiction.

S: Okay, so I'll take this in reverse order like you guys did. We'll start with the third one. New research finds that voters prefer to represented in negotiations by people who resort to extortion. You all think this one is science; and this one is ... science!

C: ''(Whispering)'' Yes!

J: Extortion!

B: Yeah, baby.

S: So this is an interesting psychological study. What they did was they divided people into groups; and they gave them a certain amount of money – like eighty Euros. This was done in Europe. Gave 'em eighty Euros, and they said, “Okay. As a group, the entire cohort, you have to reduce {{w|global warming}}.” And it was like a game. So you could – they broke them up into groups of three, which were like countries. And they said, “You can spend your money in order to reduce global warming. And if everybody spends enough money, then to reduce global warming to a certain target level, then you all get to keep whatever money you have left.” Like, you actually get to keep the money, right?

E: Um-hmm!

C: Yeah.

S: So, think about that. So, everyone needs to spend a certain amount of money so that everybody gets to keep what they have left. But you want to spend less than everybody else. They played multiple rounds. And what they found is that some people were more willing to spend their money, and other people were trying to free load, right? They were trying to let other people spend money, but spend less themselves so that they would have more money to keep for themselves at the end of the game.

But they still had to get to the goal. But the thing is, you know that other people also need to get to the goal, so you could kind of force other people into spending more money by spending less yourself. Because if they don't spend enough, then nobody gets any money. And at least in the short term people were not willing to screw themselves over just for spite, right? Or just for justice.

In the long run, people do do that. People will take a hit themselves in order to punish bad behavior. But at least in this study, in the short run, people would generally, like, “Ah, okay. I'll spend an extra ten Euros in order to have thirty left over, which is better than nothing.” So that's the extortion. You're basically saying, “I'm holding out 'cause I know you'll be forced to spend more money so that you get some money back.” So you have them over a barrel, right?

So then when they played in subsequent rounds, the players would vote for one member of their three member team to be their representative, to make the decisions, to spend the money. And they tended to elect and ...

B: Wow!

S: stick with people who extorted the other players. And they tended to replace – basically fire – people who gave away a lot of money.

C: Yeah, 'cause they were effective. ''(Laughs)''

S: Yes, in the short term, because they were effective! Exactly right. So that was, selfishly, wanting an effective representative who would extort other people was more important than everyone playing fair was basically the conclusion of the study – at least, again, I have to say, at least in the short term. There's other evidence that would suggest that people do punish extorters in the long run, and it's not a good long term strategy. But if you have the opportunity to do that, Any way I thought that was interesting.

C: Yeah, it's different if it's you, yourself. But if somebody's affecting on your behalf ...

S: Exactly!

C: you could break some rules.

S: And they said that! They said that!

B: Yes!

S: They gave ...

B: I was thinking that too.

S: people the distance. Now, people were less willing to extort themselves. But if somebody else were extorting on their behalf, that gave them a layer of insulation, and they were more willing to do that. Like, “Yeah, I want the bad guy to do the stuff I don't want to have to do myself.”

C: I've always wondered that. We talk about murderers. And we're always like, men murder more often than women. But if you added up all the women who have paid somebody to murder for them ...

S: Yeah.

C: I wonder how much closer those numbers ''(Bob laughs)'' would be.

E: That's interesting, isn't it.

C: Yeah, because they want to be distant from that.

S: Cara, that's a gender stereotype.

C: It's such a gender stereotype. But it's true! Men murder at a way higher level than women.

S: Well, let's go on to number two: ''(Cara laughs)'' A new study finds that gender stereotyping is not very different today in the US than it was thirty years ago. You all think this one is science; and this one is ... the science!

B: Yeah baby!

C: That's a bummer. I mean, yay! But no...

B: Yeah. I'm happy and sad.

E: So much for progress.

C: Yeah.

S: So this is stereotyping. This is not sexism, and stuff like that. This is stereotyping.

B: Right, true.

S: So the authors had ...

E: Women are bad drivers.

S: a data set of a hundred and ninety five college students, right? It's always college students. In 1983. So they said, “Okay, let's do an update. We'll do the same survey in 2014.” They did a hundred niney-one adults. I don't know if that's a factor, college students versus adults, but whatever. And they just asked them a series of questions about gender.

And what they found was that actually things have not changed very much in those thirty years for those two data sets. They found that despite the fact that there's greater diversity in 2014, sampled people continued to strongly stereotype men and women on personality traits like kindness and competitiveness. Gender role behaviors, tending the house, upholding more religious values. Occupations like nurse or engineer. And physical characteristics like delicate or deep voiced.

Here are some other findings: They found that the 2014 sample, men and women were largely similar in their gender stereotyping. They showed similar stereotyping on psycho-social traits and occupations for both genders on the physical characteristics for males. So, men and women stereotype equally ...

B: Interesting.

S: in the 2014 data set.

E: So, is that indicative of a hard-wiring of the brain?

S: You can't say that, because it could one hundred percent be culture.

E: I just did!

C: Also...

S: You can't ''conclude'' that, because from this data, this doesn't explore whether it's innate or learned.

C: Yeah, I bet you if you looked at a data set from sixty years ago, it would be different. It would be much more stringent. You know, in the eighties, there was a lot – like, we had gone through huge ...

S: Yeah

C: cultural revolutions. I think that...

S: You're right.

C: in the sixties, men and women were viewed – or the fifties – men and women were viewed very differently ...

B: Yeah

C: then they are today. But is it a stereotype to say that men have deeper voices than women? Or is that just true?

E: Not ''all'' men...

S: It's one of those “on average” things, but not necessarily for every individual.

C: Yeah, I'm a little worried about the way that they did their study, because I feel like they picked things that more stereotypically fit into the stereotype.

S: Nurse versus engineer.

C: Nurse versus engineer for sure. But then, in the same breath, you said ...

S: Or tending the house ...

C: No, of course! There are great examples in there. But then I feel like there's some examples ...

S: Yeah

C: that, like, is that even a stereotype?

S: Yeah, I agree.

C: It's weird.

S: All right, a couple more things they found. Women and men were believed to be more equally engaged in financial roles in 2014 than in 1982. So that was one different. Men and women are now perceived of as being more equally involved in finances.

C: Yeah, makes sense.

S: Beliefs about male gender roles such as that males repair and maintain the car did not change from 1983 to 2014. There was an increase, actually, a worsening, an increase in female gender role stereotyping, which they said was the result of men being perceived as less likely than women to engage in female gender roles, like taking care of children, or tending the house. That's surprising.

C: That surprises me too. There are plenty of stay at home dads now that don't think existed in the eighties.

S: My father, right, our father never changed a diaper.

C: ''(Laughs)'' That's crazy!

S: We were five kids, never changed a diaper. Whereas we all I think are equal participants in that level – feeding and changing the diaper and all ...

B: Oh my god! Yeah!

S: that stuff. Yeah. But any way, again, that might be going back fifty years, not thirty years. And then five other, in 2014, data also showed that men were more likely to believe gender stereotypes about male gender role behavior, while women were more likely to believe stereotypes about female gender role behaviors. Isn't that interesting? The self-stereotyping was more prevalent.

All of this means that researchers find that gamers were better able to notice and remember branded product placement in video games the more violent the action is the fiction because the study found the opposite.

C: Yay!

S: Yeah. But I didn't want to use it as the science, because I don't think it's a very good study. ''(Cara laughs)'' So if it's the fiction, I don't have to worry if I actually believe the study or not. ''(Rogues laugh)''

B: Ah, nice!

S: So, what the study did was they compared ... they had branded product placement in video games. One game they looked at was {{w|Grand Theft Auto (series)|Grand Theft Auto}}. And they had people drive around killing people, versus just driving around town. And in that game, they had a third person view, so you were looking at the car you were driving in. And the car itself had brands on the doors, and on the bumper. So it was in their view the whole time.

But still, if the players were focused on killing people, they were able to remember and identify a significantly fewer percentage of those brands than the people who were just driving around town. The other game was {{w|The Getaway (video game)|The Getaway}}. Anybody familiar with The Getaway?

E: The ghetto-way?

S: The getaway, getaway.

E: Oh, ''get'' away.

C: The getaway!

S: And again, they were instructed to kill as many people as you could versus not to try to drive as fast as you could, but not kill anybody. And the people who were instructed to kill as many people as you can were able to notice and remembered far fewer of the product placements within the world they were driving around.

Now the reason why I think that this is not a great study is because, at least in the press release, they're concluding that the violence was the key. But I don't think this study establishes that because in condition A, they had a goal in mind. They were looking for targets, and trying to kill them. Whereas in condition B, they were just kind of driving around.

C: Yeah, they weren't even playing the game.

S: Yes, so this, I think, {{w|inattentional blindness}} completely explains this.

B: Yes!

S: Without...

B: Exactly.

S: invoking violence at all!

C: And it would be hard for them to set up two different simulations where you're doing something that requires equal focus, but one's violent, one's not.

S: Exactly.

C: How do you weed out all of those confabulating factors.

S: I know, you're right. But they didn't even attempt to do that in this study.

C: Yeah.

S: And until I see that comparison, I don't buy the violence angle. That's the bottom line. Unless they're driving around town trying to pick up coins or something where they're ...

C: Yeah.

S: looking for something. So they needed some way to control for inattentional blindness; and I don't think they did. So I didn't buy the conclusion of the study, which is why I just made it the fiction, so I didn't have to worry about whether or not I believed it. But yeah. I think this is to me, the simpler and more well-established explanation is attention, not this new phenomenon of violence having an effect. I think that they did not establish that in this study in my opinion.

C: It's a bummer too, 'cause that's probably how they got their – well I shouldn't say that. But it seems like there's so much interest in violence ...

S: Yeah

C: in video games. Like, there's probably so much funding available for that.

S: No, that was the headline. “Gamers don't notice the ads when they're busy killing.” ''(Cara tsks)'' It couldn't have been when they're busy doing stuff.

E: Focused on any topic.

S: Focused on anything, ''(Bob laughs)'' they didn't know that.

J: I just don't remember any of it though.

S: Yeah, interesting. So, good job guys! You guys all got it right; very good.

E: Yeah.

C: Yay! She's back!

''(Rogues laugh)''

=== NECSS 2016 <small>(1:30:10)</small> ===
J: {{w|Northeast Conference on Science and Skepticism|NECSS}} 2016, guys, May 12th to the 15th in New York city. It's gonna be a awesome conference this year. We have Richard Wiseman as our keynote. We also have {{w|Bill Nye}} coming back. He was there last year. He's coming back again this year. Like I said, last week, Bill is going to be doing the [http://necss.org/necss-2016/sgu-skeptical-extravaganza/ Skeptical Extravaganza] with us. That is on Friday night. And Cara will be joining us for the first time as well!

C: So excited!

S: It's so much fun, Cara. You're gonna love it.

B: Oh my god. Yes.

C: Yay!

J: Also, just having Bill do random things like walk on and off the stage whenever he wants to is a lot of fun. ''(Rogues laugh)'' Steve, who else do we have coming?

S: Well, you remember that Entremont, the [http://www.scibabe.com/about-me/ SciBabe], she was on our show not too long ago. She is going to be at NECSS. Go to NECSS.org – N-E-C-S-S dot org to see our full list of speakers. I also want to point out {{w|Michael E. Mann|Michael Mann}}, who was the climate scientist who was the first to point out the {{w|Hockey stick graph|hockey stick}}, right? The ...

B: Yeah!

S: increase in temperatures recently. He is gonna be there! He is literally the Mann when it comes to climate change. ''(Evan laughs)'' We've interviewed him before as well. Brilliant, brilliant guy. Just one of those people who just have so many facts crammed in their head that it's just a pleasure to talk to.

We're having a whole day of [https://www.sciencebasedmedicine.org/ Science Based Medicine] on Friday with new speakers. It's gonna be a lot of fun. New topics. I'm not gonna just cover stuff we've covered previously. It's all gonna be new. So, yeah. We're all really looking forward to it. 

J: Yeah. A couple more things; so George Hrab will be doing his Broad Street Score. Which is an interpretation of some of his best songs with a four-piece stringed instrument band backing him up, which we'll be doing on Thursday night. We have workshops as well, which are really fun. We have a couple of cool ones, like Steve and I are gonna be sitting on a workshop that is gonna talk about Star Trek's {{w|Prime Directive}} and the {{w|Jedi}} and {{w|Sith}} philosophies, and are they any good? What do we think about those philosophies?

E: Bring your {{w|lightsaber}}.

J: We also have, Steve, what's {{w|Baba Brinkman}} doing on Sunday?

C: Is he rapping?

S: He's rapping.

J: Yeah.

C: Yes!

S: He's doing the rapper's guide to religion.

J: That's gonna be cool.

''(Rogues laugh)''

E: That's gonna be fun.

J: So, go to N-E-C-S-S dot org. You can sign up; you can take a look at our other events that we have; you can come for some of it, one day, two days, the whole thing. Just go to the workshops, whatever you want. But don't miss the Extravaganza.

S: All right. Thanks Jay.

== Skeptical Quote of the Week <small>(1:32:34)</small> ==

S: Evan, give us a quote.

E: All right. Here we go!

<blockquote>'I have never been converted to or even had much interest in {{w|spiritualism}}, {{w|Occult|occultism}}, {{w|The New Church|Swedenborgianism}} or any particular religion. And I never, except occasionally for a laugh, visit the quacks who call themselves psychics.' </blockquote>

And that was written by {{w|Dick Cavett}}!

S: Dick Cavett!

B: Ah! Nice!

E: Dick Cavett. Good old, Dick Cavett, former television show host for many, many years . In the article, which is called “Ghost Stories,” he basically asks the question, “Why are people afraid of ghosts?” And among the the things that he writes about or talks about in the article is the incident, or the famous incident I should say, in which {{w|Groucho Marx}} attended a {{w|Séance|séance}}.

And we've talked about it before, perhaps maybe not on the show, but I know it's kind of a common story in skeptical circles. But here's what Dick Cavett wrote about it. It's just a paragraph long.

<Blockquote>The seance was held in the darkened parlor of some wealthy believer's apartment. Groucho reported a heavy air of sanctity about the place, and not entirely from the incense.</blockquote>

That part's in quotes.

<Blockquote>Lights were low, and the faithful conversed in hushed tones. The medium began to chant unintelligibly. And then to emit a strange humming sound, eventually achieving her trance state. She says, “Am I in touch? Am I touch with the other side? Does anyone have a question?” Groucho arose, and asked, “What is the capital of {{w|North Dakota}}?” He recalled being chased for several blocks, but escaped injury.</blockquote>

''(Rogues chuckle)''

E: Which is fantastic. I love that story about Groucho Marx.

B: Awesome!

E: Showing his skeptical side. And that reminded me of this Cavett article, and I pulled that quote out. So, Dick Cavett, skeptic among us.

S: Thank you Evan.

E: Thank you.

S: Well, thank you all for joining me this week.

B: You got it man!

C: Thank you!

S: Cara, it was great having you back.

E: Yeah!

C: I'm so glad to be back.

S: And until next week, this is your Skeptic's Guide to the Universe.

{{Outro404}}

== Today I Learned ==
*There are one hundred duocendoquinquaggintillion possible games in Go (That's 10^761)<ref>[http://www.cctv-america.com/2016/04/29/go-like-a-pro-how-to-play-this-ancient-chinese-game CCTV America: Go like a pro: How to play this ancient Chinese game]</ref>
*Cara has a personal agent<ref>[http://carasantamaria.com/representation/ Cara's Agent] according to her website</ref> 

== References ==
<references/>

{{Navigation}} <!-- inserts images that link to the previous and next episode pages -->

{{Page categories
|History                    = y <!-- Groucho Marx at a seance (557) -->
|Logic & Philosophy         = y <!-- Logical Fallacy: Unstated premise (557) -->
|Myths & Misconceptions     = y <!-- Gender stereotypes unchanged in 30 years (557 SoF)-->
|Neuroscience & Psychology  = y <!-- Overconfidence (557) --> <!-- Violence and product placement (557 SoF) -->
|Paranormal                 = y <!-- Groucho Marx at a seance (557) -->
|Physics & Mechanics        = y <!-- Thixotrophy (557) -->
|Politics                   = y <!-- AI predicting crime (557) -->
|Science & Medicine         = y <!-- Valsalva maneuver (557) -->
|SGU                        = y <!-- NECSS 2016 (557) -->
|Technology                 = y <!-- AI vs Go champion (557) --> <!-- AI predicting crime (557) -->
|Other                      = y <!-- Who's That Noisy – Dial up modem (557) --> <!-- Piloting (557) --> <!-- Negotiation and extortion (557 SoF) -->
}}