SGU Episode 882

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SGU Episode 882
June 4th 2022
(brief caption for the episode icon)
SGU 881                      SGU 883
Skeptical Rogues
S: Steven Novella
B: Bob Novella
C: Cara Santa Maria
J: Jay Novella
E: Evan Bernstein
Quote of the Week
When I was a kid, people wanted to be an astronaut. Today, kids want to be famous, and that's totally the wrong approach. You have to have authenticity in what you're doing. You have to really care about the core message of what you're saying, and then everything else will fall into place.
David Copperfield, American magician
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Show Notes
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Introduction, Skipping horrible news

Voice-over: You're listening to the Skeptics' Guide to the Universe, your escape to reality.

S: Hello and welcome to the Skeptics' Guide to the Universe. Today is Wednesday, June 1^st 2022, 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: Good evening folks!

S: So here we are. We're trying to figure out what we're going to chat about at the top of the show. And like there's just there's just like horrible news happening in the world, you know what I mean? Like there's really nothing good that we would that we wanted to talk about or that wouldn't sound tone deaf or insensitive. Like you can't talk about something happy and there's only a bunch of sad stuff to talk about. So we decided just not to talk about anything.

C: Get on with it.

J: Let's talk about science.

C: Oh yeah.

S: Let's talk about science. Let's get right so let's, why don't we just get right to our news items and make people feel better about some awesome cool science.

E: Okay.

S: Not to diminish all the bad stuff but this is what we do. All right here we go.

News Items

(At some point in this episode, the Rogues mention the word/term consilience. This is arguably a good word to have tagged for the vocabulary section.)

Exascale Supercomputer (1:05)

• Absurd U.S. Supercomputer Becomes First to Officially Enter Coveted Exascale Status

S: Bob tell us about I know you've been waiting what for years for this Bob, right? An exascale super computer.

B: Okay. So, on SGU Episode 151--

C: --Whoa!

B: --June 9th, 2008--

E: --Oh my gosh!

B: --I announced the first petaflop supercomputer: a quadrillion calculations per second, 10¹⁵. I have been waiting 5105 days to announce this. That an exascale supercomputer has finally been create. Meaning it can do at least one quintillion calculations per second.

C: Wait Bob, why petaflop but exascale?

B: It's an exascale meaning that it has breached the realm of the exascale computing of quadrillion or quintillion calculations the second. So that's an exascale is that scale of─

S: Order of magnitude.

B: ─quintillion or more. The flops is just like you have to have essentially at least one exaflop to be in the exascale.

J: Bob can you give us some perspective on like how much more powerful this is? Like give it on the spectrum where is this.

B: I mean it's hard to put numbers like quintillions in context, right?

C: Yeah.

B: I mean what is a quintillion. I am told that not everyone is obsessed with such large numbers as I am and I of course respond I don't believe you. But let me see if I can put a quintillion into context. It's 10¹⁸. 18 zeros. It's a billion billion. Or this is cool. It's a million million million. Now, those are multiplied. They're not added. When I say a million million million that's not three million. That's a million times a million, times a minute. Just throwing that out there. Okay here's another one. The Milky Way galaxy is one quintillion kilometers wide. Okay, that helps a little bit. One more. Every human, including Jay, doing calculations for four years - the frontier supercomputer can do all those calculations in one second. So it's huge. It's like four times more calculations than number two on this on this TOP500 list of super computers. So yeah it's. It's a milestone. And it's interesting because often if something is ten times bigger, or better, or whatever, an order of magnitude that's dramatic. But for super computers once you have three of those orders of magnitude a thousand times better the number changes from 500-600 petaflops to one exaflop type of deal. At that thousand. And often with it with that three order of magnitude increase in speed you can do dramatically, dramatic new things. Faster things. Many things that you probably couldn't have even thought of with previous computers because it would just be too hard and take too long.

S: Bob there's going to be a new Netflix series called faster things.

J: (laughs) Oh my god.

B: Is that based on the book?

S: It's going to have a whole 80s vibe to it.

B: Oh okay. (laughs)

J: Bob what did they do with this computer?

B: Jay you're throwing it off my flow totally.

J: All right nevermind. Wow Bob. That's this is really awesome man.

B: Okay.

E: Tell us more what you were gonna say next.

B: Okay but I gotta say but listen to this. China already has probably a couple true exascale systems. Exascale super computers. Already have it probably. But they mysteriously, to me anyway, decided not to publish about it and get all those bragging rights. All of them. I mean that would have been all over the news..

E: State secrets man, state secrets.

B: They did of course-- but it hasn't really been that way in the past. They did of course make sure the news was leaked. So it's just kind of weird and but still I don't wanna detract from this accomplishment. Did I say that it's called frontier created by the United States department of energy's famous Oak Ridge National Laboratory.

E: Oh Oak Ridge.

B: Now Frontier. It's an astounding creation. It took more than 10 years of a collaboration between the United States Department of Energy's exascale computing project. But also with national laboratories, private industry, academia. And I think maybe there was a deal with the devil in there as well. So the key thing here, the meat, the meat of this announcement is this. The HPL score was 1.102 exaflops per second. That's it. That's all you need to know. We're done. No we're not. So flop. When I say exaflops a flop is floating point operation. It's just a calculation.

C: I don't like it. I don't like flop.

B: It's yeah. It just─

C: Makes me uncomfortable.

B: ─like yeah. I kind of like exascale as an alternate way to--but exoflop is very specific. And HPL is also critical that stands for High Performance Linpack. It's a benchmark test. It's very important. But it is not this crazy esoteric test to determine how awesome the super computer is. It's really just a dense system of linear equations. That's it. You go through these linear equations and if you do them at a certain in a certain amount of time, bam! You're doing 1.102 exaflops per second. It's a common benchmark and it's it's widespread. That's why they use it because it's used all over the place. And the vast majority of relevant systems can run this test. So that's important because if you had an obscure test that only a very specific type of computer could run it wouldn't be very helpful and it wouldn't be able to put all these computers in context. Remember this is number one on the TOP500 list. So 500 of these super computers need to be able to run this test, this landmark test. So how does it even do this? What's under the hood? You open the hood, what do you see? You don't see a hemi you see Hewlett Packard Enterprises Cray EX platform.

E: Oh the Cray.

B: Yes. yes. And Evan you remember that because─

E: I do.

B: ─that to me that was very nostalgic for me because I remember─

E: The 80s my gosh.

B: ─oh dude you nailing it. I remember the Cray-2 in 1985. The first supercomputer that reached the milestone of one gigaflop. Cara. 1 billion operations a second. That was the fastest computer on the planet. I remember that day and it seemed fast. Frontier is a billion times faster. A billion times faster. The phone in your pocket right now is faster than that Cray-2 but it's awesome to see Cray still being used. I'm not sure─

E: Yeah the Cray brand has legs.

B: Yeah I remember, do you remember what the Cray used to look like? It was basically like one tower with a like a seating, a circular seating all around it. It was very compact and very small compared to what we got today. Okay enough of memory lane. So the HP's Cray EX platform. There's 74 cabinets. It's in 74 purpose-built cabinets. If you look inside those cabinets you're gonna find 9 400 CPUs, Central Processing Units, and 37 000 GPUs or Graphical Processing Units. The total core count is 8 730 112. That's a lot of cores.

J: Oh my god.

B: Also you got cables.

J: You know just the idea of them being able to chain that many─

B: Oh my god it's nuts.

J: ─close together. Like there has to be specific hardware and software that goes with that.

B: It's amazing. And don't forget Jay there's 90 miles of networking cables. Oh my god. That's 90 miles. That's crazy. All right so how do you think you'd even cool that. One of the things I remember reading about exascale supercomputers years ago it's like it's going to run so hot it's gonna consume so much power. How are you going to cool this thing. It's gonna be crazy. Well it uses four 350 horsepower pumps.

C: Wow.

B: Four 350 horsepower pumps moving six thousand gallons of water through the cabinets every minute. Every 60 seconds oh man.

E: The water it's still what you use?

B: It's great for carrying away heat man. And I remember it's also works against you Evan. Because I remember when I was scuba diving and you're in the water and that water takes away your heat. You hear your heat the heat being sucked away. It just cools you down so fast. It's too efficient. Enough of that. All right (laughter) also there's other milestones. And this is really cool. Frontier is number one on the GREEN500 list which scores commercial supercomputers for energy use and efficiency. Number one on that list which is really cool. And there was a new category this year called mixed precision computing. This is a brand new category. And that rates performances based on formats commonly used for artificial intelligence. And here the score was 6.88 exaflops. So you see this is even faster it seems. 6.88 exaflops. But it also it depends on the test, right? Because there's so many ways that you could, how do you encapsulate performance overall performance. You can't. You can't get one number for overall performance. There's lots of different ways to do it. So this is great because it's AI. It's based on these AI formats which of course are becoming increasingly common and all over the news. So the next inevitable question you should be asking is well what can it do that's so special? How do you even?

E: Solve Worlde. (Bob laughs)

C: I got Wordle in two today.

B: It would solve Wordle in one attosecond.

S: I almost got it in two but it took me three tries to get the last two letters.

E: This computer will solve Wordle─

B: Boring.

E: ─before the word is even chosen.

B: Exactly. All right now of course the specific impact like this system and similar systems will have because there's gonna be a lot more of these exaflop super computers as in over the next five to ten years. So that the impact is you can't really predict it but you can say things that you can say that exascale supercomputers without question they're going to impact your life in potentially major ways. Precision medicine, climate change models, water use, material science, nuclear physics, national security, pornography (Cara laughs) you name it. It's going to have an impact. How about this: forecasting viruses that leap species. Zoonotic, right? To avoid the next pandemic. These computers can help with that. Here's another way to look at it. I like this one. Now imagine you're at work and you're investigating a promising new pharmaceutical compound. As one does at work I suppose. People do that all over the place and typically you're going to wait weeks weeks for the results. With Frontier you'll be able to know the answer in a few hours. So instead of waiting for almost a month you're going to get it in just a few hours. In between eating your breakfast bagel and your cafeteria lunch you're going to get the answer. Even better here's another way to look at it. Instead of waiting a half hour or more for the number crunching that you do on your project you can get the answer in seconds. In seconds. So you could stay at your desk. You don't have to get up, get a coffee, chat with your friends, do some other weird stuff whatever you do at work. Then you go back and get in seconds you could stay at your desk and then you can go to the next task. So I think it could really speed things up and really help with creativity. Because you're getting the answer right then and there. As you know in our society there's nothing like having immediate feedback.

C: This is starting to sound really like dystopian to me Bob.

B: Oh my god.

C: You can be tethered to your desk all day every day and constantly accomplish things. (laughs)

B: Oh my god. Pharmaceutical compounds!

E: Don't tease Bob.

B: Imagine! Oh look I just found a cure for cancer my day is so boring. (laughter)

J: Cara, Cara─

E: Wow this thing cures cancer.

J: Cara is this the perfect example of don't get Bob started?

C: I was gonna say that.

B: It is. It's weird though because it's like. It's just a tool. It's just a tool. You sure you could use this to do really nasty stuff. But hey man if we follow that down to its logical conclusion you'd say let's ban all cars because so many people died. This is just a tool.

C: To who are you straw manning right now? (laughs)

B: I'm totally straw manning. So if this pattern holds. Which it won't. I will announce on May 23^rd 2036 on SGU episode 1611 that some country, or company, or artificial intelligence perhaps has created a zeta-scale supercomputer with 10²¹ flops. That's a sextillion calculations per second. And you know the jokes are going to be flying when we have this zetaflop supercomputer sometime in the 2030s. Hopefully. Just real quick when we reach that milestone I'm going to be on the show freaking out as I am this show. And it could, people predict that it will be able to do things like for example accurately forecast the global weather for two weeks in the future. Pretty good. That's really good actually. Two weeks? That's pretty amazing because you're up to that hard limit of chaos and so I'm not sure how much how much deeper in the future we're ever going to be able to get in predicting something chaotic like weather. But two weeks and having a fairly accurate forecast using a zeta scale super computer. Pretty sweet. One more thing. They predict they predict that zetascale or yattascale systems─

E: Yes here we go.

B: ─might be able to accurately model the whole human brain. At least according to Kay Kirkpatrick who published as much in 2019. I think we're gonna see some amazing stuff with the zetascale and yattascale super computers but we now have exascale supercomputers and look forward to it. It's gonna do some amazing things. Good and bad Cara.

C: Are your-- (laughs) I didn't say it was going to do bad things. I don't want to not be able to get up from my desk. That's all I said.

B: You just harshing oh I get you, all right.

S: You can get up from your desk you just don't have to to waste your time.

C: Exactly. Like those breaks are actually healthy. No what I was wondering Bob based on Steve's news item last week. Your estimation of when we're gonna hit this next milestone. Is that utilizing a linearity bias?

B: Oh yeah absolutely that. And that's specifically why I said─

S: If the trend continues which it probably won't.

B: ─no I didn't say trend. I said if this pattern holds. Which it won't. So I just absolutely this may take there are some predictions that say this could happen you know even before 2030. I doubt that. A lot some people are predicting in the 2030s. They could be, they could hit some fundamental problems that are going to prevent this and delay it for even more. Maybe 2040s. But I think it's you're pretty safe to say sometime in the 2030s. That's a pretty big net. 20-2030s

E: Bob when did China come up with their exascale computer?

B: It's I think it was─

E: Years ago?

B: ─like--oh no no. Earlier this year, late last year.

E: Okay so it's been months.

B: Relatively recently but it's just. And kudos to them if it just I know so little about it because they just didn't publish it. And they didn't submit it for this.

S: They're not transparent so it doesn't count.

E: Well. Yeah, that part of it.

B: Yeah. In a sense. In a real sense it doesn't count. But I mean it if it truly existed─

S: That's the thing.

B: ─and it seemed like it really did. Some reliable sources say that this thing does exist. And it did pass the landmark with over one exaflop. So but if it did exist it does and there's no taking that away from them but I mean sorry. You're not in the limelight because you chose not to be in the limelight and we got to give the Oak Ridge National Laboratory all the kudos it deserves for this.

S: All right thanks Bob.

Dinosaurs Warm or Cold Blooded (16:17)

• Were Dinosaurs Warm or Cold-Blooded?

S: Jay.

J: Steve.

S: Are we finally going to end this long-standing debate where dinosaurs, were dinosaurs warm-blooded or cold-blooded?

J: Steve. I don't think I could bring as much enthusiasm as Bob. (Cara laughs)

S: Yeah.

J: I'm gonna just say that now to get that weirdness out of the way.

S: To lower that bar for yourself right out of the gate.

E: Let's dial this back.

J: All right so the long term question for scientists is could dinosaurs actually sing? Nope that's not the question. The question is that would be interesting though like I want to hear a real dinosaur vocalization, right? Were dinosaurs warm-blooded or cold-blooded? People always assumed or whatever. Whenever we were kids everybody thought that they were cold-blooded. They're lizards. They were big lizards. They were slow.

C: But they're birds.

E: Birdies.

J: But the truth is Cara scientists were never sure. At least the the smart people in the room were not sure and they weren't just assigning it like we were. Paleontologists have tried to figure this out for a long time. And in fact it's one of the earliest questions that paleontologists ask themselves about dinosaurs. Were these creatures warm or cold-blooded? So warm-blooded creatures are called endothermic animals and these are animals that can regulate their body temperature. Their metabolism creates plenty of heat as most of you know after hearing Bob talk. (Cara laughs) This heat is a byproduct of their metabolism and these types of creatures have developed many different things that can handle retaining that heat. Like fat and shedding the heat using sweat glands and feathers and fur as insulation. All of these things regulate body heat. This is called thermoregulation. Endothermic animals metabolize oxygen efficiently and this means that their bodies can absorb and use oxygen fast. These types of creatures also need a lot of calories because of how hot and fast their metabolism is. And this in turn generates more than enough body heat thank god. And of course mammals are warm-blooded. We are all warm-blooded creatures and we're using a lot of calories and oxygen every single day.

E: 98.6.

J: That's a weird average number I guess but the I'm─

S: That's not the real number.

E: No.

J: I'm a degree cooler than that.

S: Yeah there's a range and we actually use a hundred as like the cutoff for saying you have a "fever". 98.6 is a myth basically but go ahead.

J: Ectothermic animals, Steve Novella, these creatures metabolize oxygen more slowly causing them to generate less heat, right Bob? From their metabolism. Their body temperature is dictated by the environment. This allows them to eat less. They don't have to breathe as much. But in hand of course they're less active. And ectothermic animals don't need to eat as often for example. Some of them they might eat once a month. You ever have a pet snake? You don't feed it every day. You feed it one mouse every once in a while. Every week or so. And let's not forget birds. Birds happen to be more warm blooded than mammals. So they're not just warm blooded, they're very warm-blooded. And this trait goes way back into the bird lineage before they could even fly. And this fact makes the question about dinosaurs being hot or cold-blooded even more interesting. So the question is were dinosaurs warm blooded like birds or cold blooded like lizards.

E: Yes.

J: Researchers at the California Institute of Technology with lead study author Jasmina Wiemann they found a new way to determine if dinosaurs are warm or cold-blooded. They look at waste products that form the amount of these waste molecules found in the bones directly relates to the amount of oxygen taken in by the animal. And this shows that the animal was warm or cold blooded. So these waste molecules are luckily preserved during fossilization and that's key to this whole thing. The researchers studied the femurs of 55 different creatures. This included 30 extinct and 25 modern animals. So they had a collection of bone samples that had dinosaurs, pterosaurus, plesiosaurus, modern lizards, birds and other random mammals. A very large spectrum you know that's what they're trying to do. The researchers used a technology called infrared spectroscopy. And this is a tool that measures the interactions between molecules and light. So they shine a laser light at something and that laser light. Some of it is reflected back and they'll be able to read the colors of those reflected lights back and it'll tell them what material they're actually the lasers hitting which very interesting. Very very important technology that is used in lots of different sciences. Using this process they're able to qualify the number of waste molecules in the fossils. In the bones that they were studying. Then they compared their findings with the metabolic rates of modern animals that exist today. This gave them a clear picture of what the ancient fossils metabolic rates were. This is freaking genius what they figured out here. So guess what they found?

E: Warm-blooded.

J: Dinosaurs could actually sing. (Cara laughs) Just kidding. They found out that they were both. They were both warm-blooded and cold-blooded.

E: Both! Of course.

C: As in different ones were warm blooded?

J: Yes. Yes. Not the same ones.

C: Okay. Not like within the same organism.

J: I'm gonna be warm blooded today. No, no. It was different. Different ones. They were able to look at different dinosaur groups and create a timeline of what animals were warm or cold-blooded. Along this very long timeline. It seems that all dinosaurs were warm-blooded in the beginning when we go far enough back. But then in the Triassic period which was between 251.9 million and 201.3 million years ago dinosaurs split into two major groups. So one of the groups is the cervicians and these are considered lizard-hipped creatures. These include the velociraptor the T-Rex. And these are warm-blooded creatures. Warm-blooded dinosaurs were common and modern birds came from this group. Now we move on to the ornithischians. These are the bird-hipped group. Now Steve right out of the gate. And I'm asking you directly about this. Why did birds come from the lizard hipped group and not the bird hip group?

C: Because these were named in 1888.

S: Yeah.

J: Okay. All right.

S: Ten years old when I first asked that question. Because you would think that intuitively you think birds evolved from the bird hip dinosaurs. But yeah it's more, it's has to do with the way the bones are pointing. And it was in fact I'm gonna be talking about this in my news item in a little bit. They were going by morphology and there's a lot of convergent evolution. And if you just base it on superficial morphology you make incorrect designations and this is an example of that.

J: Okay so but they're still using it. So the ornithischians, which I said are the bird-hip group, this includes the triceratops, the stegosaurus. And these are the animals that ended up being cold-blooded. So another question they were able to answer was that about 65 million years ago the Earth's atmosphere had a higher oxygen content. And they wanted to know if the higher level of oxygen meant that animals had a higher metabolism because of the extra oxygen that was available. And they ended up finding out because of this study that there was no connection between higher oxygen levels and metabolism. Jasmina Weimann said: "Birds inherited their exceptionally high metabolic rates from their dinosaur ancestors which is pretty cool." and she actually said that "which is pretty cool" which I liked. Here now Steve you told me about something that I thought was incredibly interesting. This gigantothermic. Could you? Can you explain that?

S: Yeah so one of the ideas was that so the sauropods, these are the really big long-necked Brontosaurus type dinosaurs. They're in the saurischian groups. And they are also warm-blooded. But the question was perhaps they're cold-blooded. But because they're so big they can retain enough heat to be functionally warm-blooded, right? Even the little heat they're making builds up in their large body and because the bigger you are the greater your volume to surface area ratio. Surface area pretty much determines how quickly you will lose heat and your volume will determine how much heat you generate. That's why creatures become larger to adapt to cold environments. They hold on to their heat more. These things were massive. So the idea was oh man they're just so massive they're even if they're cold-blooded they could still generate their own heat and we'll call that gigantothermia. But this study pierced. It said nope they were actually warm-blooded. They were metabolizing as as warm-blooded creatures not as cold-blooded creatures which is interesting.You think those are the big lumbering dinosaurs that we think of. But they were warm-blooded as well.

J: This is really fascinating to know now the answer is really here. Science basically knocked another pin down. And I think that this will lead to more understanding about each individual type of dinosaurs. Where they lived? We know that. When they lived? We know that. But how they lived? There's a lot to be learned there and this is a huge piece to that puzzle.

S: Yeah this I mean this seems like the most direct evidence we have so far because they're measuring the direct metabolic products of oxygen metabolism in the bone. And across many─

E: And that doesn't get contaminated in any way? That's a pure measurement? It's never a contaminated thing?

S: These are highly stable molecules they're looking for. So what would they have to what are they being contaminated with?

E: I don't know.

S: Yeah they're looking for, it's spectroscopy. So it's looking at specific molecules. And but they did have to select for fossils that have retained a lot of organic material. Some fossils don't have a lot of organic material in them and they wouldn't be useful for this study. But if the conditions under which they fossilized from and were preserved allowed them to retain a lot of organic material these molecules are very stable and would last. So at least you know they can compare apples to apples, right? Like if they say these two dinosaurs are relatively the same preserved. This one has a high content of oxygen waste products the other one has a very low content. So you could directly compare their metabolisms there. But I like the fact Jay. You touched upon this but just to zero in on it a little bit. Before going into this study we obviously know that birds are hot blooded. They're even more warm-blooded than mammals. And so the really the question was, and birds are dinosaurs, right? So we already know that some dinosaurs are warm-blooded. So the real question was when did they evolve warm-bloodedness not if they evolved warm-bloodedness. And the thinking was it was when they evolved flight because flight is very metabolically demanding. So birds evolved flight. Then they as an adaptation to flight they became more and more higher metabolism warm blooded.

J: But the warm blooded came first.

S: But the warm blooded came first. This study shows it was there─

E: Interesting.

S: ─throughout all the not only all the theropod dinosaurs but all the saurissians. And maybe even farther back there with the ornithischians in fact sort of slowing down their metabolism over time becoming more cold-blooded. Which is very very interesting. So the conditions for flight were there before birds evolved. They had feathers and they were warm-blooded. The theropod dinosaurs. And birds evolved out of that group.

C: Yeah it speaks to that sort of evolutionary bias that we often have when we're looking backward when we want to ask why instead of how.

S: Yeah.

C: It's like there's no why in evolution. It just happened because of pressures. But they had the equipment necessary.

S: Yeah. We tend to think of evolution as creating the features necessary to adapt. But actually evolution is much more opportunistic. That strategy evolved because the pieces were already there and they were just doing the just following the low-hanging fruit, you know what I mean?

C: Yeah of course. What we see now as an end point is not a goal. It's not even an end point. It's just where we see it as being, yeah.

S: It's just what happened.

C: Yeah exactly.

J: Another cool thing about this news item. In general when you think about what the scientists did here. This is a moment to really marvel at how unbelievably powerful and awesome science is. This information that they're that they have found a way to interpret has always been there─

S: It's always been there, right.

J: ─every paleontologists, right? Every paleontologist that ever dug up a bone and all the time that they spend removing the rock away from these from the fossils. And the information was there and nobody knew it was there. And scientists, science is relentless. They keep trying to find more information out of the material that we have in front of us.

C: Well and also for a long time it was anathema to destroy bones in order to look for evidence within. It really like is a much more modern use of paleontology to say let's look at this microscopically, let's look at this from a chemical perspective because it really was looked at like oh gosh this is such a precious piece of data and now I have to like grind it down or I have to cut it in half in order to get this information out of it. That was a scary prospect.

S: Yeah and ironically Cara one of our archaeologist friends said in archaeology 50 years ago when you found stuff, you found tools or anything the first thing you did was clean it. And now you would never do that (Cara laughs) because you're destroying the DNA evidence. Now it's like you want all the dirt and grime and everything. It's just the techniques adapt to the technology.

Preventing Violent Crime (30:17)

• A study gave cash and therapy to men at risk of criminal behavior. 10 years later, the results are in.

S: All right Cara tell us about this kind of unusual way to prevent violent crime. Or we see it as unusual.

C: Yeah I was really excited when I came across this research study that was just recently published. The write-up from Vox was actually just published yesterday as of this recording. It takes an interesting approach. It takes a preventive approach. And it takes a very in my mind a duh kind of evidence-based approach. But I think against a backdrop of what we are all kind of struggling with right now. The vicarious trauma that we're struggling with against the backdrop here in the US at least of these kind of terrible reports of gun violence across the country. It's important to sort of take a new look at this. Basically there was a researcher who is friends with a man who lived in Liberia and this man who is living in this west African country runs a program and had been running it for about 15 years called the Sustainable Transformation of Youth in Liberia. And that program was a violence prevention program. And when this researcher who is friends with the man in Liberia. The man in Liberia is named Borh, Johnson Borh. When this researcher, Blatman from the University of Chicago saw the impact of this man's youth program he was like I think I want to study this. This looks kind of too good to be true and I wanna understand it. So he set out along with some colleagues on a pretty inclusive and long-term experiment. So he looked at at 10 years of data across I think it was 999 people in Liberia. And they specifically wanted to look at who they described as the most dangerous men in a city called Monrovia where the crime rate was very very high. So they look at these 999 dangerous men and they randomized them into four different groups. One group received cognitive behavioral therapy and it was an adapted form of cognitive behavioral therapy that specifically focused on crime and violence. It was given in an eight-week time period and it was given in a group format. So I think it's something like 20 men to every one therapist. Or maybe it's just, I'm actually not sure how many therapists were present but it's 20 men per group. So that was one group. Another group was given cash. A third group was given CBT plus cash and the fourth group was the control so they weren't given any intervention at all. And then they looked at the crimes that were associated with each individual at the one year mark and at the 10-year mark. And if I were to ask you guys to guess, I probably should have done this at the top, if I were to ask you guys to guess per crime how much do you think it costs in this paradigm to prevent crime? What would you?

J: Oh my god.

C: Yeah.

J: That's very hard.

E: Put a cost on it?

C: Per yeah. A dollar cost per crime. Not per person just per crime.

B: 100 bucks.

E: I don't. I have no idea.

C: 100 bucks a crime? Okay. You think that would be a good deal for the government? 100 bucks of investment in preventive measures per crime?

E: Sure that sounds like a good deal.

J: Yeah I can't figure this out.

C: Right so because we often talk about─

B: How many crimes are we talking about?

C: ─we often talk about punitive measures. We talk about punishment. We talk about policing. We talk about sort of after the fact crime. I'm putting interventions in quotes because as we know they don't really work very well. That often results sadly in aggressive policing, incarceration, kind of a recapitulation, that's not the right word I'm looking for but an exacerbation of poverty. And of inequality, income inequality so if we're talking about peer prevention and you think about the amount of money we spend on policing in this country and jailing and incarceration. The justice system as a whole. If we're talking about prevention. Bob you said about a hundred bucks a crime would probably be a good investment.

B: That's my wild ass guess yes.

C: In this paradigm it cost a dollar fifty per crime.

B: Yeah I was thinking of going low.

C: That was the calculation that they were able to work out. So as you may have guessed the group with the both the CBT and the money fared the best. They had a significant difference in outcomes. A significant reduction in crime compared to all the other groups. And so the question here is why not just CBT. Why not just a cash infusion. Why is it CBT plus a cash infusion. So let's look at the actual specifics here. I told you the specifics about the the CBT paradigm. The Cognitive Behavioral Therapy paradigm. Which is of course an evidence-based intervention. The cash infusion was only 200 bucks a person. And so the total cost of the group that got CBT plus cash was I think 500 plus or minus per person. Because that included the cost of delivering the therapy. So just CBT alone did reduce violent crime but it didn't really have the staying power that we would hope for. And this is borne out by other literature. We know that evidence-based therapeutic interventions can have a preventive approach. Or they can have a preventive outcome to crime like if we offer therapy to at-risk youth or at-risk individuals we can see reductions in antisocial behaviors. We also know that in some instances cash can help as well. But the question here is why is cash plus CBT not only so effective but so lasting. Because here's the kicker, after 10 years they found that the outcomes held and nobody expected that. Everybody except─

S: Yeah, it's a long time.

C: ─it's a really long time. Everybody expected that the outcomes would have kind of dissolved or petered out. And that does seem to be the case a little bit with just therapy. That's, so that's not to say that therapy doesn't work, right? Like and I think it's important that we think about this not just from a purely scientific perspective but also from a face validity. Like what's the word I'm looking for? From a purely rational perspective. If you want to prevent hunger you will give somebody food. Now they're gonna be hungry again in a few days you have to keep giving them food. That's how that works. And sadly therapy is often similar. Like we can have targeted interventions at very particular pinch points in somebody's life but one dose of therapy is not always going to be sort of like preventive for their entire lives. But the weird thing is the cash infusion which by the way was two hundred dollars one time. Really did work synergistically with the therapy. And so the researchers are hypothesizing that it sort of was a almost like a behavioral activation. So behavioral activation is an important part of cognitive behavioral therapy. It's one of the things that you're often teaching is how do we get motivated and actually start the process. And then once we start the process we can usually keep going. The 200 cash infusion seems to have sort of aided in that. So the idea here was training individuals through the use of therapy to see themselves in a new light to kind of try on a post criminal identity. And sometimes it would involve things like buying new clothes, changing their appearance, trying out new job skills. And it seems as though they needed the money right at the top to be able to maintain the therapeutic skills that they were learning. The economic assistance really did help them utilize these new skills and actually see what it felt like to make money legitimately and get that positive feedback to be able to continue doing that. And so it's really fascinating to see that in this clearly small example which does have some caveats although to be fair the researchers I think did address a lot of the caveats really well. Like for example they looked at 999 different people. A 160 of them iI think by the end the 10-year period had died. And so the question is this like a survivor bias. Like did the individuals who are most likely to be involved in violent crime die because of violent crime. So it looked like the non-violent individuals did better. But the truth of the matter is they were able to use some sort of forensic capabilities to interview friends and family of those who had died and look at medical paperwork. And it turns out that something like two-thirds of the individuals who died died of disease or other associations─

S: Just medical [inaudible].

C: ─yeah medical things and just associations with poverty. This is a very poor city and so tuberculosis is rampant, malaria is rampant and sadly there's an Ebola outbreak around the time when they were collecting this data. So a fair amount of these people did die from disease and other medical things. And then about 20 something ended up dying of actually violent deaths. But they were pretty evenly spread across all four groups. So there really wasn't a good argument to be made that any particular group reduced impacts of violence on the individual. But there is a very good argument to be made that the individuals were engaging less in criminal behavior which includes violent activity. So the researcher who led this study who's actually in Chicago has decided to implement a similar program in Chicago. It's called READI. R-E-A-D-I. And for 18 months they are identifying men in violent districts of the city and offering therapy sessions and job training. So instead of direct cash they're actually giving them sort of access to the economic market. They believe that obviously we can't always compare apples to apples in when we're looking across cultures and across countries with different economic development. And so they're hoping that in Chicago actually getting access to the job market is going to have that kind of staying power that the cash infusion had in Liberia. But they don't have outcomes from this study yet because it's actively going on. But we have seen some really interesting examples like in Ecuador for example in 2007 and this is described in the Vox article. There was basically a lot of gang violence and so the country did something that seems kind of counterintuitive. It's that they actually legalized gangs. They said okay let's actually legitimize these groups and you can register them with the government, you can call yourself a cultural association which opened them up to qualify for things like grants and different social service benefits. And the rate of violence significantly plummeted after that. And so there's this I think and we see this a lot when it comes to gun violence especially in our country. We have these entrenched ideologies that prevent us from looking at evidence-based practices when those evidence-based practices seem to bump up against our sacred cows. And so I think what's so important about this kind of research and being open-minded to this kind of research is that even if it feels counterintuitive. Even if it bumps up against maybe your personal ideology your personal value systems. Really give it a good look. Look at the outcome measures and see how evidence-based approaches can actually be really really transformative. Doing something the way we always did it just because that's the way we feel we should is not good public policy. Looking at the evidence and taking a science-based approach is one of the best ways to move forward. And I think that we can see a lot of parallels between this great study in Liberia, the study that's going on now in Chicago and some of the direct action that we could be taking across our country.

S: Yeah this is an interesting study obviously and whenever you're dealing with human behavior no one study is going to be definitive. You got to look at it as many different ways as you could think try to─

C: Yeah but the sad thing is we don't have that many studies like this.

S: I know.

C: Because there's so much resistance.

S: We need more. We need more. But my reaction to this was for a couple of things. One is that it really does seem that when it comes to changing behavior our instincts are completely wrong. Over and over again like we think that punishment is going to work. It really is not. It's not really effective. Or scared straight. It really doesn't work.

C: And we've known this since like Pavlov. (laughs) It's amazing.

S: No but we keep going back to these things. It's intuitive for some reason and it feels like it should work but the evidence is pretty clear that our our our instincts are wrong. They just don't work. And doing things that seem very counterintuitive. I think because there's multiple different intuitions going on here. And we have our intuition of justice and when you do things that doesn't feel just then it rubs you the wrong way. You wanna do something that feels like justice and then you argue well and it will have the desired outcome that I want. I'm going to punish this guy and it's going to keep other people from doing this bad thing. It's like okay you really just want the punishment. The other thing is just a justification for it. But when you look at the data. The things that work are the things that aren't emotionally gratifying. Like we're gonna pay people to not be criminals. It just doesn't feel right. But if you just say forget about what it feels like. Just forget about that. Do the money ball, right? It's the other idea. Like the money ball approach is just whatever outcome works. Forget about your intuition or your instincts or whatever what feels right. Let's just look at outcomes. And if you just do like how much money are we spending. How much quiet crime are we preventing. Let's do that and forget about how it feels.

C: We saw this in Utah of all places where there was that interesting kind of social experiment to say how much is it costing the state to use all these social services around homelessness. And they say well how much does it cost to just build these people homes. To just like literally put them in homes and it was significantly cheaper. And all these other variables were affected by this. Crime rates went down. So many positive outcomes came from this. But you're right it's this twisting of motivation. And I think it's also a fundamental misunderstanding of human behavior. This links back to a study we covered years ago on the show about belief in pure evil. And the idea that people commit crimes because they are intrinsically evil versus the truth which is that people commit crimes because they are desperate.

S: Yeah it's a fundamental attribution error.

C: Yeah. And if we can create a system in which people don't have the desperate need to engage in gang activity, they don't have the desperate need to steal at gunpoint, to rob, to whatever because of these entrenched social problems like poverty and racism. If we can start working on correcting these things preventively we don't have to rely on punitive responses which don't work. And actually entrench the problems more.

S: And you don't have to keep too many people out of jail to pay for a lot of prevention because keeping people in jail is expensive.

C: It's very expensive.

S: For the state. It's very expensive.

C: But sadly it also makes a lot of money for privatized─

S: Yeah yeah.

C: ─industry. That's a whole other conversion.

S: Separate issue.

Revising Evolutionary Trees (46:29)

• Molecular phylogenies map to biogeography better than morphological ones

S: All right guys as promised I'm going to talk a little bit about evolutionary trees. Phylogeny. Phylogeny is basically like a diagram of when different species branched off from which other species when. It's mapping out the evolutionary history of how life evolved and all the interrelatedness. The question is how do we come up with those diagrams? How do we determine the phylogenies or the evolutionary relationship among all of the species? Actually it goes this goes back to before evolutionary theory. Because even though we didn't have an evolutionary understanding of nature back in the day we still had a desire to categorize life. And there was the this idea of a tree of life actually predates evolutionary theory. Pre-evolution this is the mind of god. This is the god's plan for life. Everything's organized. We still decide─

E: Here's the map.

S: ─yeah wanted to map out life in this and that would reveal sort of god's design or whatever. But people also could just see that yeah birds are a thing, right? Birds are an identifiable group with bird-like characteristics that we can put them in into one category. But that was famously a very inexact way to group living creatures because morphology could be very deceptive. And sometimes we did like one of the biggest fails. Like with the linnaean system of categorization of taxonomy was with flowers right. Linnaeus just decided to split up the flowers by how many stamen they had. Which had like nothing to do with their revolutionary relationships with each other. It was just like he picked one superficial characteristic and made that the primary criterion for how to to split them up into groups. This by the way gets is repeated in many different situations where we've categorized things based on very superficial characteristics initially and then as our scientific understanding evolves and progresses we figure out more and more precise and meaningful ways to categorize them. This happens a lot with diseases and medicine for example. Okay so post-evolution there was the idea that we should be categorizing species based upon, grouping them, based upon their actual evolutionary relationships. That idea is called cladistics. And that's why we talk about clades. Clade is an evolutionary group not one that's determined by morphology or anything else but by strictly by evolutionary relationships. So given that goal to develop a strictly cladistic evolutionary map of the relationship of life, how do we do it now? There are two─

B: Genes, duh.

S: ─yeah there are two main. Two main methods. We still use morphology just how they look we still use that.

B: Why?

S: And I'll tell you why. And we use molecular methods. Genes, genetic data. And not just genetics but also proteins and amino acids, whatever. We use that level of data. Now why don't we do that all the time Bob? Because we don't always have that data, right? We don't have a full genome of T-rex for example. So if we don't have the molecular data we don't really have much of a choice but to go on morphology.

B: That's true.

S: But the morphology and we've talked about this concept before. Morphology can be tricky because of convergent evolution. There's, remember homologous and analogous traits? Analogous traits look similar because of similar function. Homologous traits look similar because of evolutionary relatedness. And how do we tell the difference? Well it's tricky. And sometimes we get it wrong. But not only that. So even when we know like these are homologous traits and these creatures are closely related to each other it's still hard to tease apart the branching relationship. So if we're thinking about apes for example it's like okay we know that chimpanzees or humans are closest. But who's next? Is it the orangutans or is it the gorillas? And how do you arrange those. And sometimes even when we're doing, even when we have good molecular data. Even with extant species. We have good molecular data. There's multiple ways that you can fit to the data. You could fit a tree to the data. And so you might have like three or four fits that are all pretty much equal, statistically equal, in terms of fitting the molecular evidence that we have. So then what do you do? So we have a couple of other sort of ancillary methods to help us break the tie as it were. If we have multiple options among, based upon morphological or molecular evidence we might and there are other things we can turn to. What do you think those are? There's basically two there as well. I'm oversimplifying a very complicated field but we'll start with these sort of basic concepts. What do you think?

B: Prayer? (laughter)

S: No.

C: So you said okay so not morphological and not genetic.

S: Yeah those are the two primary things. So there are some two secondary methods that we use to help break the tie. To see what correlates best and then we find─

B: Geographic location?

S: Absolutely. Geographic location. And I'll give you a hint. For fossil species specifically. Things that are in the ground.

C: Rocks? Geology.

E: Depth? Depth.

B: Strata.

S: Stratigraphy. Yeah, strata. Stratigraphic correlation. So where do they, how long ago were they in the past. Obviously things can only evolve from things that are older than they are. You can't evolve from a species that appears later in the fossil record. So yes we use those two methods. Okay now this gets to the study that is triggering this discussion. They wanted to know all things considered. Again not just based on our gut feeling or because it's newer or sexier. From an evidence-based perspective which maps are more accurate. Morphological maps or molecular maps based on genes and proteins and whatnot.

B: Is that a trick question? It's got to be molecular.

E: Yeah I would think molecular.

S: That, so that's your instinct, right? It's got to be molecular. But they didn't want to go by that. They wanted to really prove mathematically which one was better. So what the researchers did this is in Communications Biology, Jack Oyston et. al. And they looked at different phylogenetic maps. Morphological and molecular and they they said which one which ones fit a geological map more consistently. So if you also take a sort of a geographical map of the species it's basically an independent line of evidence that you can use to also map out relatedness. The idea being that creatures that are related to each other are more likely to live close to each other.

C: Right it's like, what do you call it? Convergent? Not convergent evolution but convergent validity. Looking at another type yeah it's like consilience there.

S: Exactly. So like for example with the geographic like there's a lot of marsupials in Australia. The marsupials are not evenly distributed around the world they sort of cluster in the southern continents. That's geographic data. So they did a statistical analysis where they compared various morphological and molecular maps, phylogenys. Said which ones match the geographic and the stratigraphic maps more and the answer was the molecular phylogenys.

C: Of course.

S: Which is not surprising it confirmed what we all would have guessed. But it did put a hard number on it which is good. All right so here are the actual numbers. Not as high as you might think. So they write in the discussion: "The observation that biogeographic congruence is significantly greater than expected by chance alone for most of our clades was 69%." So 69% of the claydes they looked at had bio geographical congruence greater than chance alone. So that's still that's pretty good but it's not as high as you might think. But for the morphological trees it was only 50% congruence with the biogeographic data. The biogeographic congruence. So big picture if you look at biogeographic maps, molecular maps, morphological maps, stratigraphic maps they all agree with each other pretty well. But it depends on what level you are digging down to. I mean there aren't like crazy inconsistencies. Like they all overlap pretty well. But when you when you dig down to like the real fine details. And you're asking questions about the exact order in which different species branched off. That's where you see the differences. At that really high resolution level. And that's where they were asking so when we have multiple potential branching patterns that fit the data should we listen to the phylogen the molecular data or the morphological data when they conflict. And this you know it was making a strong argument that we really should go with the molecular data when it conflicts with the morphological data. Which again I think kind of we all would have guessed. Kind of makes sense.

C: But also to be fair the morphological data in this study is modern morphological data. So that's why the consilience is so high. It's not as good but it's pretty good. That's because we're not talking about like in linnaeus's day, we're talking about modern morphological data.

S: Oh yeah that's so here's the other thing they found. Thank you for bringing that up Cara. The other thing they found was that the morphological and the molecular maps get more and more accurate over time.

C: Right. Yeah I'm not surprised by that.

S: So yeah so if you look at the ones we had 100 years ago, they were they didn't do so well. And then over the longer we've been sort of gathering data. So they got like all science it's imperfect but it makes progress. I see it as like a picture coming into focus. And it's getting more and more into focus over time which tells you that these methods are working. If they weren't working then there would be no relationship with, you know, be random. You wouldn't expect it to progress over time to get more accurate as we gather more data. But because the methods are working we get higher and higher resolution. Basically models phylogenetic trees as we go over time. And again I thought it was a fun sort of way to point out also that this is what's happening. Is that we developed this molecular tool. Being able to to sequence genes even from fossils. Sequence protein structures. Amino acid sequences. And with this data it's we're sort of revolutionizing our phylogenetic trees. And we didn't get rid of the older method like the morphology that going all the way back to even pre-evolutionary days. It's still there. It's still important. It's still data. But it just is very tricky to interpret but sometimes that's all we have. There are sometimes we have a skull and that's it. That's the other thing the morphological data is often incomplete. If we had perfect data, if we had the whole genome sequence and protein sequence and a 100% of the skeleton of every species then the maps would completely overlap each other. There would be no discussion here but it's when we have incomplete data the different methods are gonna have different strengths and weaknesses and they may not exactly agree. It's a good example of how science is messy but it works and it trudges forward. And it's good to have kind of a nuanced understanding of how the evolutionary biologists do this. I also like, it's good for people to understand this. Another reason is that creationists exploit people's misunderstanding of this. They will argue that there's like no correlation among different phylogenetic trees because evolution is not real. And that's of course just bullshit. They're just lying. But if you understand how this works and what the data actually is it's a lot easier to refute misinformed creationists. They play with the word correlation, right? What does that mean? If again you could always zoom in to an arbitrary level of detail. Like what's precise, what's accurate, what's correct. It's always within this certain error bars. And you can if you can always deny a scientific finding by just arbitrarily requiring and a higher level of precision or focus.

E: It's like moving the goalpost.

S: Yeah it's moving the goal post absolutely.

C: It's like when they say well there's no transitional fossil between those transitionals, oh god.

E: Oh we found one! But now you got two transitional fossils.

S: Just keep zooming in, keep zooming in.

J: Steve at some point wouldn't it be great if we could tell the creationists like actually that is as granular as it gets.

C: (laughs) Yeah.

S: I think about what we're doing. We're reconstructing a billion years of evolutionary history involving billions of species based upon fragments of evidence. It's amazing what we can do. As you were saying before Jay. We've always had this data now we know which dinosaurs are warming cold-blooded based upon this trace evidence that we have fantastic tools that can pull out the most amazing. I often think of shifting like to astronomy. When you think about it, right now we are being bathed with a tremendous amount of information about the universe we just don't know how to look at it yet. We're just increasing our ability to detect, to analyze and to infer the universe from the data but this information is there. It's hitting us at all times and if we just had the instruments or had the knowledge or the ability. There's so much more we could learn about the universe. And it's the same way when we're looking into the past. We have the fossils are there. The evidence is here it's all around us. We're just increasing our ability to get at it, to analyze it, to infer what's going on with greater and greater detail.

C: And of course Jay like when you said wouldn't it be great if we could actually say that's as granular as you get. We're doing that now. We can do it with covid. We're like look here's a new variant it directly evolved from the last variant. There is no in between.

[commercial brake]

New Optical Illusion (1:02:39)

• This illusion, new to science, is strong enough to trick our reflexes

Quickie with Bob (1:11:44)

• Gato AI

Who's That Noisy? (1:14:18)

Answer to previous Noisy:

All vocalizations from Smooth Criminal by Michael Jackson

_hearme_put_text_about_answer_here_

New Noisy (1:17:04)

[high pitched whoops and grunting, squeaking calls]

J: The more information you give me, the better. If you think you have an answer, or you want to send me in something cool, just like that Noisy--somebody just sent that in to me--you can email me at WTN@theskepticsguide.org

Questions/Emails/Corrections/Follow-ups (1:18:59)

_consider_using_block_quotes_for_emails_read_aloud_in_this_segment_
with_reduced_spacing_for_long_chunks –

Science or Fiction (1:28:40)

Item #1: A new analysis finds that the Cueva de Ardales in Spain, famous for its many cave paintings, was likely occupied by human ancestors for as long as 500,000 years. Item #2: In a prospective study, dogs were able to detect asymptomatic SARS-CoV-2 infection with higher sensitivity than nasopharyngeal antigen testing, 97% vs 84%. Item #3: Scientists have developed a molecular drill that is activated by visible light and rotates at 2-3 million times per second, which can drill through bacterial membranes and can be used as a broad-spectrum, rapid-acting antibiotic for skin infections.

Answer	Item
Fiction	500,000-year occupation
Science	Dogs better than antigen test
Science	Molecular drill

Host	Result
Steve	sweep

Rogue	Guess
Bob	Molecular drill
Cara	Molecular drill
Evan	Molecular drill
Jay	Dogs better than antigen test

Voice-over: It's time for Science or Fiction.

Cara's Response

... [in Cockney accent, as in The Rain in Spain] "the kive in Spine falls minely..."

Skeptical Quote of the Week (1:46:35)

When I was a kid, people wanted to be an astronaut. Today, kids want to be famous, and that's totally the wrong approach. You have to have authenticity in what you're doing. You have to really care about the core message of what you're saying, and then everything else will fall into place.
– David Copperfield, American magician

Signoff/Announcements (1:51:16)

S: —and until next week, this is your Skeptics' Guide to the Universe.

S: Skeptics' Guide to the Universe is produced by SGU Productions, dedicated to promoting science and critical thinking. For more information, visit us at theskepticsguide.org. Send your questions to info@theskepticsguide.org. And, if you would like to support the show and all the work that we do, go to patreon.com/SkepticsGuide and consider becoming a patron and becoming part of the SGU community. Our listeners and supporters are what make SGU possible.

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Today I Learned

• Fact/Description, possibly with an article reference
• Fact/Description
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References

Vocabulary