Stochasticity

SPEAKER_01: Today's rewind of stochasticity is presented by Radialab sponsor BetterHelp. With so many New Year's resolutions this time of year, the emphasis on transformation can get a little tiring. Therapy can help you find your strengths. So if you're thinking of starting therapy, give BetterHelp a try. It's entirely online and suited to your schedule. Celebrate the progress you have already made. Visit betterhelp.com slash Radialab today to get 10% off your first month. That's BetterHelp. H-E-L-P dot com slash Radialab. Hey, it's Lutef. SPEAKER_24: Happy New Year. Look at you. So fresh. It's a new you and a new me and a new page and a new lease on life for all of us. And as we start to chart out our new year, I wanted to play an episode from the archives that asks an important question that I think is helpful to consider, you know, as we make plans and goals and set expectations. So here's the question. Here's the question. How much can we control what happens in our lives? And how much is it just whatever you want to call it luck or fate or just a random and fickle universe having its way with us. This is an episode about that, how that applies to E. coli bacteria, how it applies to dimes and quarters, how it applies to blades of grass on a golf course. And of course, how it applies to you. SPEAKER_24: I hope you enjoy. This is stochasticity. Wait, you're listening. SPEAKER_15: All right. Okay. SPEAKER_15: All right. SPEAKER_21: Listening to Radiolab. SPEAKER_13: Radiolab. From WNYC. SPEAKER_25: Rewind. Okay. SPEAKER_13: I want to start the show today with a truly remarkable story, which at least initially SPEAKER_13: involves this girl right here. SPEAKER_06: Hello, I'm Laura Buxton. SPEAKER_13: Laura Buxton is her name. Remember that name. I should turn my hair back. SPEAKER_13: And Laura, let's do this like a movie, okay? SPEAKER_05: Like a movie. Yeah. SPEAKER_05: Okay. SPEAKER_13: Okay, it's June 2001. Yeah. SPEAKER_05: Where are we? SPEAKER_13: We're in a little town in Northern England called- Stoke-on-Trent. SPEAKER_05: Stoke-on-Trent. SPEAKER_13: Yep. Imagine a little English house in this town and the camera zooms in and there, standing in the front lawn, is little Laura Buxton. She's 10 years old. SPEAKER_05: Well, almost 10. Whatever. SPEAKER_13: She's a tall girl. Pretty tall for my age. SPEAKER_05: Pigtails. SPEAKER_13: And in her hand, she's holding a balloon. A red balloon. You with me so far? Yep. Okay, so earlier that day, Laura had taken a little card and stuck it to the balloon and on one side written- My name. SPEAKER_13: Plus a little message. SPEAKER_05: It just said, please return to Laura Buxton. And then on the other side, it had my address. SPEAKER_13: Okay, so cut back to the outdoor scene. There she is standing on the lawn. SPEAKER_05: It's very windy. SPEAKER_13: She's got this red balloon with her name on it and she holds it up to the sky, to the heavens. SPEAKER_05: And I just let it go. It's in the wind, Tukey. SPEAKER_05: We were laughing and joking because we just thought it'd get stuck in a tree a bit further down the road somewhere. SPEAKER_13: But that's not what happened. The balloon kept going. All right, now I'm looking at a map here of England and Stoke-on-Trent is at the top, so the balloon would have had to go south, like pound down down, past Stratford, past Walsale, past Wolverhampton, then past Birmingham, past Kidderminster, past Worchester, past millions of people, past Chettingham, people with different lives, different names, past Glouchester, Gloucester, Gloucester. And all in all the red balloon goes about 140 miles south. Exactly against the prevailing wind. SPEAKER_06: Oh really? Which is a southwesterly. SPEAKER_13: Okay, so finally when this balloon is all the way on the other side of the country, it begins to descend. Down, down, down. And of all the places it could have landed, you know, in a river, in a factory parking lot, in the sea. Instead, the balloon touches down in the yard of this girl. I live, I live in the countryside in a little village called Milton-Lilbourne. SPEAKER_13: Just so you're not confused, this is a different girl than the first one. They do sound the same, but they live on opposite ends of the country. SPEAKER_06: The balloon got stuck in our hedge, but our next door neighbor found it and he thought it was just a bit of rubbish and he collected it up so the cows wouldn't eat it because he didn't want the cows to like choke on the rubbish. And he was about to put it in the bin, like literally, and then he saw the label saying please send back to Laura Buxton and he was like, oh my god. SPEAKER_16: Why? Why would he say oh my god? SPEAKER_13: Okay, so check this out. Remember how I told you that the first girl who sent the balloon was 10? The second girl who received it? Ten years old. She's 10. Okay. Okay. Wait, wait, there's more, there's more. Better be. Remember how I told you the first girl's name was Laura Buxton? SPEAKER_13: Yeah. Well, girl number two, can you introduce yourself? SPEAKER_05: Okay, um, hi, I'm Laura Buxton. SPEAKER_16: What? They're both Laura Buxton? Yeah. No. Yes. SPEAKER_13: Both named Laura Buxton. Yes. Get out. You heard me right. A 10 year old girl named Laura Buxton lets go of a balloon. That balloon floats 140 miles and lands in the yard of a 10 year old girl named Laura Buxton. This is for real. Yeah. I think it might be the strangest thing I've ever heard in my life. SPEAKER_06: It's pretty weird. SPEAKER_13: Been about eight years since the balloon incident. The Loras see each other a lot and we managed to get them both into a studio. Hello, New York, this is London. SPEAKER_05: Can you hear me? Like, we're going to hear Americans through these. Yeah. SPEAKER_13: Okay, back to the story. SPEAKER_05: Yeah, I got the balloon. SPEAKER_13: That's Laura number two. What did you think at that point? SPEAKER_06: Um, well, I was quite young so I didn't really know what to think. I was just like, I better write the letter because, you know, there's someone else out there called Laura Buxton. I must see them. SPEAKER_13: So Laura number two wrote a letter to Laura number one. SPEAKER_06: Dear Laura, I think I put, I'm 10 years old and I live in Wiltshire and I found your balloon and the thing is that my name is Laura Buxton as well. So lots of love from Laura Buxton. SPEAKER_13: Laura number one. SPEAKER_13: Yeah. SPEAKER_05: You get the note. Got it through the post. SPEAKER_05: You remember reading it? I remember reading it because I sort of opened it up whilst I was in the kitchen and it was really quite confusing actually because it was like to Laura Buxton from Laura Buxton. I took it up to my mum and we stood there arguing about it for quite a while. What did you argue about? SPEAKER_13: Well, she was trying to tell me that it had come to Laura Buxton and it wasn't from Laura SPEAKER_05: Buxton. I just thought I was confused. Okay, fast forward a short while later, the two Loras meet. SPEAKER_13: It was at one of England's most popular TV shows, Richard and Judy. They'd found out about the Laura Laura coincidence, invited them on and here the story gets even stranger because there's Laura number two standing backstage. SPEAKER_06: And down the corridor I saw this girl who looked pretty similar to me. SPEAKER_13: First thing she notices is, wow, we're the same height. SPEAKER_13: Guinea and Tallinn. SPEAKER_13: Got the same color hair. SPEAKER_06: Brownish hair. SPEAKER_13: We're even wearing the exact same clothes. SPEAKER_06: Pink jumpers and jeans. Yeah. SPEAKER_13: And as they started to talk, it just kept getting weirder. SPEAKER_13: Well, we both got a three year old black Labrador. SPEAKER_05: We both got a gray rabbit. We both got Guinea pigs. Really? SPEAKER_13: Yeah, yeah. And they both brought their Guinea pigs with them that day. I remember Laura took hers out of its cage and I had mine on my lap and we were like, SPEAKER_06: oh my God, they were identical. They were both brown with a sort of beigey orange patch on their bum. Like completely the same. SPEAKER_05: I was just like, oh my gosh, how is this happening? SPEAKER_13: Do you believe in miracles? Either of you? I don't know. SPEAKER_05: What do you call this miracle? SPEAKER_05: I'm not sure. I mean, I guess it could be, but I think it's more of a case of fate. Yeah, I'd say it's more fate than a miracle. SPEAKER_13: So you don't think that wind that blew the balloon was just wind? SPEAKER_06: Well, if it was just wind, it was a very, very lucky wind. The chance is just so unlikely. There must be some kind of reason. What kind of reason? SPEAKER_13: Maybe we were meant to meet, I don't know. SPEAKER_06: But meant by whom or what? SPEAKER_13: Who knows really. SPEAKER_05: Only time will tell. It could actually be like preparing us for something else later in life. Maybe when we're all grannies we'll find out. Now we're just young and we're just enjoying life. SPEAKER_06: SPEAKER_16: Oh, Dad. I mean, look what you're... You know what you are? What? You're a destiny bully. What do you call me? SPEAKER_13: A destiny bully? Yes. Sounds like a pop band or something. No, it's what you're doing to those girls. SPEAKER_16: No, I wasn't trying to force God on them, if that's what you mean. SPEAKER_13: Yes, you're the one who says, oh, who's that? No, no, no. I was trying to get to the question of how should we think about that story? SPEAKER_16: SPEAKER_13: Is our world full of magic and meaning and coolness, or is it all just chance? In fact, that's what we're going to do for this whole hour at Radio Lab. SPEAKER_16: We're going to discuss the role that chance, chance plays in so many things. In the lottery, in the flipping of coins, and deepest of all... In us. SPEAKER_13: Yes. On Radio Lab. I'm Chad Abumrad. I'm Robert Krulwich. We're about to get random, so stay with us. SPEAKER_16: So let's start with a very basic question. Let's. Random sounds like it means random. That is, anything can happen at the next turn of the wheel. Like your phone ringing, for example. SPEAKER_13: Oh, God. Random. Although it's happened so many times that it's no longer random. It's completely predictable. But it does have a very nice kind of lilt to it, don't you think? SPEAKER_16: I'm going to sing with it now. SPEAKER_16: And now back to our regularly scheduled program. So let's say that something remarkable happens. Like Dolores. Like Dolores. Can you tell whether this is just the random act of an indifferent universe, or is there something truly miraculous and wonderful about it? Excellent question. Thank you very much. Hello. SPEAKER_17: We found you. So this is Chad. SPEAKER_16: Hi, Chad. This is Robert. I'm Debra Nolan. SPEAKER_25: I'm a professor of statistics at the University of California, Berkeley. The reason we'd come to see Deb Nolan at Berkeley is because we'd heard that she plays this game. SPEAKER_13: I like to incorporate lots of classroom activities and demos. SPEAKER_25: One in particular that has to do with randomness. SPEAKER_13: It's a game that helps her students understand what real randomness actually looks like. I don't know anything about it. And it doesn't look like what you would think. In any case, she takes us into her classroom, us and a few students. SPEAKER_13: Yes. And she sits us down. SPEAKER_16: We all sit down. Should we sit in a semi-circle? SPEAKER_16: That sounds good. SPEAKER_13: And then she explains. Okay, I'm going to divide the group up into two. SPEAKER_25: I'm going to divide it right here. She splits us up so that group one is three of her students. SPEAKER_13: I'm Joe Chang. Richard Liang. Margaret Taub. SPEAKER_13: Group two, Chad Abumrad. Robert Kullwich. Is us. SPEAKER_25: And the group here. She's pointing at us. SPEAKER_13: I'm going to give you a penny. SPEAKER_25: And I'm going to ask you to flip the coin a hundred times. And the three of you. She points to her students. SPEAKER_13: Your job is to pretend to flip a coin. SPEAKER_25: Meaning they just have to flip the coin in their heads. SPEAKER_13: Kind of guess. SPEAKER_25: How do you think that coin might land? We produce a hundred fake coin flips. SPEAKER_16: And then Deb leaves the room. So her students start whipping through their imaginary fake flips. Tails. SPEAKER_15: Heads. SPEAKER_15: Tails. Heads. The tails. Heads. Tell me is that. SPEAKER_15: While we actually flip the coin a hundred times. Heads. Heads. Tails. Tails. Tails. Tails. Tails. Heads. Tails. Heads. SPEAKER_16: Tails. That's exhausting. But eventually we did finish. And both groups then put our strings of H and T's up right there on the blackboard. Heads. Heads. Tails. Woo! And then Deb came back. SPEAKER_25: Hello. Here they are, huh? Let's look. SPEAKER_13: Okay, so on the board you've got two sets of H's and T's which look pretty much the same to us. But she looked at their list. SPEAKER_16: The fakers. And then she looked at our list. And right away she says, pointing at our list. This is the real one. SPEAKER_25: We were like, wow! SPEAKER_13: How did she do that? Well, amazingly, the way she knew had to do with one particular moment. Right. We'll roll the tape back. Put it into a moment right at the beginning of our coin flip. SPEAKER_17: Shh. Tails. SPEAKER_13: Tails. Tails. Tails. Three in a row. Shh. Another tails. Shh. I feel like we have way too many tails. SPEAKER_15: SPEAKER_16: Seven tails in a row. It was really spooky. Completely. SPEAKER_16: Like at any moment a unicorn was going to come galloping in. SPEAKER_13: That's how weird it was. But as magical and unrandom as it felt to us. That's how she knew that we were the real flippers. As soon as I saw the seven tails and then I looked over to the other board and there SPEAKER_25: weren't any longer than four, I think. That's how she knew. When we asked one of the guys on the other team, why didn't you put more streaks in your SPEAKER_13: flips? Well, he said, I think we'd all say. I was thinking if we did that too much, maybe she would recognize that we were actually SPEAKER_04: doing it on purpose. In other words, those streaks just feel wrong. SPEAKER_13: And that's the thing about randomness. Real randomness when you see it just doesn't feel random enough. But it says that the truth is. SPEAKER_16: But, says Deb, the truth is. SPEAKER_13: Strange things do happen by chance. SPEAKER_16: But why is it so hard for us to emotionally accept this? Well, it finally made sense to us when we spoke to this guy. Hi, Jed. SPEAKER_16: Hi, Robert. SPEAKER_11: That's Jay Kohler. I'm a professor of finance and professor of law at Arizona State University. So here's how the epiphany happened. We were explaining to Jay the unicorn experience in Deb's classroom. SPEAKER_13: We got one tail, then we got a second, then we got a third, then we got a seventh. SPEAKER_13: And somewhere in the conversation we started to do the math. Okay, what actually are the odds? SPEAKER_13: Let me see, was it heads in a row or tails in a row? SPEAKER_11: Tails. Seven tails in a row, that's one half raised to the seventh power. So we started to do the calculations and at first it looked pretty good. SPEAKER_13: 0.00, a little more than 1%. Just over 1% chance. Yeah. It was at first that what had happened in Deb's class was super unlikely. Right. But then, Soren, our producer, had to go and say this. SPEAKER_24: You know, to be fair, you should tell him that you actually flipped the coin 100 times. SPEAKER_11: Oh, now you, wait, wait, did you, you were holding back on me. Wait, wait, we're too stupid to know that. SPEAKER_16: That's why we have Soren here. Are you saying that somewhere in the 100 flips you got a run of seven? SPEAKER_11: That's what we're saying. That's not a particularly good coincidence. I'm sorry to burst the boat. What do you mean? SPEAKER_13: And then Jay explained it to us. If you're just doing seven flips, then yeah, getting seven in a row is really unlikely. But if you're doing multiple sets of seven, 14 of those sets of seven, which we work, we were doing 100, then the probabilities start to add up. I mean, it starts small, like 1%, but then that one becomes two, which becomes four, which becomes eight, until when it's all said and done, the chances of getting seven tails in a row somewhere in a set of 100 is... Don't hold your breath. About one in six chance. SPEAKER_11: One in six. That's it. SPEAKER_11: That you would have gotten a string of seven. SPEAKER_13: So what felt spooky and almost Twilight Zone-ish in the moment is actually... It's not that improbable. Oh. See, that's why you don't want to know it. It doesn't confirm your goosebumps. SPEAKER_16: No, I think the goosebumps are dead now. Oh, I'm sorry to do that. I still enjoy life. SPEAKER_11: The problem, says Jay, is that we were so focused on those seven flips in a row, SPEAKER_13: that we had forgotten about the other 93 that weren't seven in a row. We'd forgotten about what he calls the background. We were too zoomed in. SPEAKER_11: So you've got to back the camera up and pan around and look at the complete sample space. And when you do that, he says, what you will realize is the thing that felt so special. SPEAKER_13: Suddenly you see that it's not so odd in its real context. SPEAKER_11: And this sad lesson goes way beyond coins. SPEAKER_13: He gave us this example. SPEAKER_11: 1985 and 1986, Evelyn Adams of New Jersey wins the lottery twice. Back to back here is crazily improbable, right? SPEAKER_13: Right. So if you zoom in all the way in... There she is, Evelyn Adams standing outside of a convenience store somewhere in New Jersey. I just won it again! I just won the lottery for a second time! SPEAKER_11: She is completely blown away for good reason. SPEAKER_11: The odds that those two particular tickets would become winning lottery tickets are one in 17.3 trillion. Wow. But, Jay would say, if you pan the camera back, away from Evelyn... SPEAKER_13: Hi, Evelyn! SPEAKER_23: And you look at the whole world of people buying lottery tickets. SPEAKER_13: At this vantage point, you can begin to ask a different question. What are the odds that somebody somewhere... SPEAKER_11: Somebody somewhere... ...will win the lottery twice? And in fact, the answer to that is, it would be very surprising if it didn't happen repeatedly. And it has happened repeatedly. Really? For instance? In Connecticut. Employees of a place called the Shuttle Meadow Country Club, they won twice. A man in Pennsylvania, he won twice a few years later. A California retiree won a Fantasy 5 and the Superlatto in the same day. SPEAKER_17: Wow. SPEAKER_11: The odds of that were calculated at one in 23.5 trillion. That's trillion with a T. SPEAKER_11: One way, I think, to think about this whole thing, I think one example that sort of brings it all home, at least it did for me when I thought about the blade in the grass paradox. A golfer hits the ball down the fairway, and the ball lands on a particular blade of grass. If the blade of grass could talk, you know, the blade of grass would say, wow... Oh my God! What are the odds that that ball, out of all the billions of blades of grass... ...everywhere to the right, left, and right, and me! It lands on me! SPEAKER_11: How did it come to be that it just landed on me? I don't know! It's sort of like a miracle, really. SPEAKER_23: And it is sort of miraculous. SPEAKER_11: But what we know is that it was going to land on some blade of grass somewhere, so it's nearly 100% chance that some blade of grass was going to say, wow, what are the odds that that ball was going to land on me? And if I were that blade of grass, I'd feel so special and chosen. SPEAKER_16: And crushed. SPEAKER_01: And crushed! SPEAKER_13: Soaring. The real lesson here, according to Jay Koehler, and also Deb Noland before him, is that if you don't see past yourself, you fall prey to superstition. SPEAKER_25: Right, or magical thinking. You have to be careful that you're not finding meaning here when it's just coincidence. Just coincidence. But there are some things, like the loras, that will never feel like just coincidence. SPEAKER_13: Well, if it was just wind, it was a very, very lucky wind. SPEAKER_06: So we had to ask Jay. SPEAKER_16: I ask you, sir, is this a miracle? This is not a miracle. It's a good story. SPEAKER_11: But, you know, there are lots of little things I could pick at in the story. Like what? Oh yeah, pick away. SPEAKER_16: Well, I mean, Laura Buxton didn't find the balloon. SPEAKER_11: Somebody else, who knew a Laura Buxton found the balloon? You selected out the features that match. And trust me, somebody checked to see if she was an identical twin and said, no, no, that's not a good one. Skip the twin. Okay, how many brothers and sisters? Oh, not the same number of brothers. Skip that. Ah, they both have a rabbit. Let's put that one in the story. To be totally honest, he's right. SPEAKER_13: What? What do you mean? Well, when I was interviewing the loras, I asked them a bunch of questions, kind of scouting for similarities. What's your favorite color, both of you? Blue, pink. SPEAKER_05: Scrap that. And what do you guys study in school? SPEAKER_13: Biology, chemistry, and geography. SPEAKER_05: Whereas I'm doing English and history and classical civilization. Scrap that. SPEAKER_11: What people do is they try to make the story better by showing more similarities. So you're saying that somebody, I couldn't imagine who, doctored the story? By the way, I don't want to spoil anything. This is a trivial comment, but I believe that one of the girls was actually nine. Well, almost ten. SPEAKER_05: And the other one was ten. SPEAKER_05: Darn it. No. No. SPEAKER_11: Oh, well, that's the story through. Never mind. Yeah, I'm sorry to be your most depressing guest. SPEAKER_13: Nonetheless, I will continue to tell the loras story every chance I get on the air, at parties, wherever, because, you know, damn the statistics. It just makes me feel good. I think Jay would agree with you. SPEAKER_16: Well, first of all, we love stories. SPEAKER_11: It connects us. It gives us insight into our own lives. And I think it also gives us a feeling that life is magical. SPEAKER_13: And maybe we don't have to call it magic to enjoy the experience. In fact, I was talking to the loras and I asked them, what if a statistician were to walk in the room right now and say to you, this was bound to happen. Statistically, this was going to happen. Sometime. To someone. That's fair enough, really, because it just happens to be us in those statistics. SPEAKER_05: Yeah, I mean, if that's what the statistician thinks, I mean, yeah, SPEAKER_06: that came to him. They don't really care. The way they see it, whatever was in that wind, SPEAKER_13: whether it was fate or just wind, doesn't matter. It brought them together. And now they're friends. Radio Lab will continue in a moment. SPEAKER_22: Visit sponsorship.wnyc.org to get in touch and find out more. SPEAKER_24: Hey, it's Lottiff again. Just a quick note before we get back to the episode. The story you're about to hear was reported back in 2009 by journalist Jonah Lehrer, who years after that got in trouble for fabricating quotes in one of his books. We have fact-checked this story, everything in it held up. Just so you know that we know and now you know, you know. Okay, back to Jad and Robert. SPEAKER_19: I'm Ann Kline-Scyber. I live in a small country town where most people, not other people. Ann was a high school English teacher. SPEAKER_14: I taught for 31 years. SPEAKER_19: She now lives in West Virginia. SPEAKER_14: Wait, can you wait this minute? There's someone at my door. SPEAKER_19: I'm sorry. No, no, of course. Of course. SPEAKER_14: Ann was an upstanding citizen, went to church every Sunday, was just one of those people who... Makes the world go round. Makes the world go round. SPEAKER_19: I'm sorry. SPEAKER_14: Not at all. SPEAKER_19: Anyway, in 1991, I would go to the grocery store and on the occasions I wrote a check for my groceries, the woman would say, gosh, you're shaky. SPEAKER_14: And she says she began to notice that her hands would start to tremble. SPEAKER_19: Are you all right? But I just thought maybe it was because of working that hard and trying to get everything done. SPEAKER_14: And it got particularly bad when she said she was just walking in the mall doing some shopping. And I was by myself walking. SPEAKER_19: And it was like I stepped off a step that wasn't there. It was the first full-body tremor. She fell. SPEAKER_14: And then my husband was a doctor. SPEAKER_19: And he sent me to a neurologist who diagnosed me with Parkinson's. How old is she, by the way? SPEAKER_14: She was at that point in her early 50s. What is Parkinson's? Parkinson's is the death of dopamine neurons in the back of your brain and the part of your brain that controls bodily movement. And so when these neurons die, the end result is first the shaking hand and the loss of feeling and the loss of movement. And then, of course, the tremors get worse and worse. SPEAKER_19: But anyway. SPEAKER_14: Well, the doctor diagnosed her with Parkinson's and he gives her a drug called Requep. Requep was a new medicine in 1992. SPEAKER_19: It's a pseudo-dopamine. SPEAKER_14: It basically mimics dopamine in the synapse of the cells. SPEAKER_19: And it was like a miracle drug for me. SPEAKER_14: Her tremors disappear. Her symptoms disappear. So she's cured or? If you looked at her on Requep, years after she had Parkinson's, SPEAKER_14: you wouldn't notice anything. She would seem symptom-free. The So about seven or eight years go by. All the while, they're upping the doses to compensate for the cell loss that's still taking place. And in the early years of 2000, something sort of unusual happened to Ann. SPEAKER_19: Some friends of mine had gone to Las Vegas every year for the basketball tournament, the Final Four type thing. And they asked would I like to go with them. And I said yes, I would. So she went to watch basketball, but as often happens in Vegas, SPEAKER_14: one afternoon she and her friends found themselves in a casino. Had you ever gambled before this trip to Las Vegas? No. I was raised in a household that was fairly religious SPEAKER_19: and we considered gambling a sin. But as she stood there in the casino in Vegas, SPEAKER_14: she had this inexplicable urge to go to the slot machines. They had frogs and princesses and cars and cherries and lemon. SPEAKER_19: Push a button, wheels spin, and see what the pictures did. I've never taken any drug sight or anything to compare it to, SPEAKER_19: but it was like a high. SPEAKER_00: SPEAKER_19: That was sort of the beginning of it. And then when she comes back to West Virginia. SPEAKER_14: I couldn't wait to get to a machine I really wanted to play. SPEAKER_19: She discovers the dog racing track. SPEAKER_19: About 15 miles away from her house. SPEAKER_14: I'd go to 730B there when they opened. SPEAKER_14: And that's where she would go, and they had a wide assortment of slot machines. SPEAKER_19: Hi, how are you? If I had the money, I'd play all day. SPEAKER_14: From 7 to 3.30 in the morning. Whoa. And then she would go home and play slots. On the computer. SPEAKER_19: On her computer. Not even for money. SPEAKER_14: Just for the sheer, visceral thrill. SPEAKER_19: I would play that the rest of the night. 7.30 the next morning, I'd be back at the joint. Hi, how are you? SPEAKER_14: Was that any sleep at all? No sleep, and she could keep that up for several days in a row. SPEAKER_19: At the beginning of my gambling, I'd wake up in the night and just scream out, Oh God, what am I doing? Help me, save me. But eventually I became too hardhearted, I guess, to even pay attention to that. Her credit cards are all maxed out. SPEAKER_14: I sold my mother's silver. SPEAKER_19: I sold my silverware. Things that should have been my son's heirlooms. Sold from the safety deposit box. She steals quarters from her grandkids. SPEAKER_14: Steals quarters from her grandkids? Yeah. SPEAKER_19: Anything I looked at around the house, I thought I could get money out of. SPEAKER_14: Everyone who knows her is watching her life fall apart. My house was filthy dirty, a mess. SPEAKER_19: I wouldn't take time to even wash dishes. She lives on peanut butter. SPEAKER_19: Didn't have any crackers or bread or anything. I just had peanut butter. SPEAKER_14: Because that's all she can afford and still leave as much money as possible for the slots. Even when I'd be at church, I'd think, SPEAKER_19: I've got so many more minutes or so many more hours I can get a gamble. Her husband eventually leaves her. SPEAKER_19: I mean, I loved my husband, but... They got divorced. There's just no decision. Everything is gambling. One of the neat things about gambling is that you can do it by yourself. SPEAKER_14: How much money did you lose during those years, if you don't mind me asking? I lost at least $300,000. SPEAKER_19: $300,000. SPEAKER_18: Which to her is? SPEAKER_14: Is all her life savings. And it's one quarter at a time. Yeah, that's the surreal part. I tried several things. SPEAKER_19: I went to a rehab facility. My father, I told you I was raised in a religious home. SPEAKER_12: Sometimes I would say my dad watched me from heaven and he wouldn't approve of this. He wouldn't be so disappointed in me. But seemingly I just couldn't stop. SPEAKER_16: Let me pause here for a second, Jad. I want to just take a moment to try to figure out what exactly is happening to Ann. Yeah, why can't she stop? Yeah. It turns out there may be an explanation if you look into her brain. Remember earlier we talked about a little chemical called dopamine and how she didn't have enough dopamine in her brain, so that was giving her some kind of movement trouble, the Parkinson's. It also turns out to be the case that any time you do something that makes you feel good, your brain spurts out dopamine. For years, that's how scientists saw dopamine as the neurotransmitter of pleasure, SPEAKER_14: the neurotransmitter of sex, drugs, and rock and roll. SPEAKER_13: But you said earlier that dopamine has to do with movement. Well, what is the ultimate purpose of movement from the perspective of evolution? SPEAKER_14: It's to get you to food. It's to get you to sex. It's to get you to a reward. So that's why the same circuits, the same chemical that controls motivation, that controls what you want, also controls movement. But it turned out it was a little more complicated than that. SPEAKER_16: In the mid-1970s, a guy named Wolfram Schultz decided to take a much closer look and his subject was a monkey. SPEAKER_14: So he would put these very thin needles that can record the activity of individual dopamine neurons in the monkey brain. And they'd put the monkey in a room, and then every day they would walk down the hall to the room where the monkey was. SPEAKER_16: They'd open the door. Hello, monkey. They'd flip on the light. They'd give the monkey some juice. Here you go, monkey. And then when the monkey sipped the juice, dopamine. Happy monkey. Right. But then comes a surprise. SPEAKER_14: He soon discovered something very odd about these neurons. As they juiced this monkey day after day after day after day after day, SPEAKER_20: the squirt of dopamine, which they were always measuring in the monkey's brain, seemed to move forward in time. SPEAKER_16: What do you mean? Well, at first the dopamine hit when the monkey took the sip of juice. But after a while, the monkey got the dopamine hit when they entered the room and switched on the light. Hello, monkey. And then after a few more times, the dopamine hit when the researcher's feet could be heard walking down the hall. You see what's happening here? Hello, monkey. Um, not really. You're going to have to bring it home for me. SPEAKER_16: I'll do it again then. What the monkey is trying to do is piece together the sequence of events that inevitably lead to juice. Exactly. That's what these cells do. They try to predict rewards. SPEAKER_13: Oh, so this isn't just about movement or about feeling good. It's about finding the pattern of the thing that makes you feel good. Yeah. It's pattern finding. SPEAKER_14: Oh, this is pure pattern recognition. This is essentially how your brain makes sense of reality in some very primitive sense. It parses reality in terms of rewards. This is how you get more food in the wild is you can see the reward before anyone else can. So we're talking about basic survival stuff here. SPEAKER_13: Mm-hmm. SPEAKER_14: There's one other wrinkle, though, about the dopamine system that makes casinos and slot machines so tantalizing, which is that these cells are also programmed to be very sensitive to surprising rewards. So this seems to be, most scientists speculate that this seems to be your brain's way of telling you, pay attention, you just got something for free. This must be good. Sit here in this nice, comfy velvet chair and try to figure out this reward. So now imagine Anne sitting there at the slot machine. SPEAKER_16: She pushes the button on the machine, slot machine, and oh my God. SPEAKER_16: And sirens and bells go off, coins clang. SPEAKER_16: And inside her head, her dopamine neurons, they're saying, whoa, this is wonderful. But now how did this happen? Where did this big reward come from? SPEAKER_14: What did you do this time? Why are you so happy all of a sudden? And it starts searching for something. SPEAKER_16: Bedfalls and princesses and... SPEAKER_19: Was it the number of cherries that she had just before? SPEAKER_16: Was it that this machine had 13 hits and this was the 14th? I thought I could tell. SPEAKER_16: It has all kinds of pattern-like things. It has bells, it has lights. But the problem is, is that there is no pattern to find. SPEAKER_14: There is no pattern. It's inherently random. It's inherently unpredictable. And while the rest of us might just, you know, give up and walk away, God, I just wasted a hundred bucks on this stupid machine. SPEAKER_16: I should go get lunch. Ann can't go to lunch. Her dopamine system is too powerful, too potent. Oh, because of that drug she's taking. Right. It keeps surging and surging, forcing her neurons to fight, to fight hard, to find a pattern. That's what's gripping her. Her brain is intoxicated at the possibility that it will learn how to succeed, that it will crack an uncrackable code. SPEAKER_19: I thought I was good at softening machines, in fact. She told me a story about she would go to buy milk and then spend the next 12 hours SPEAKER_14: with the milk rotting next to her as she puts quarter after quarter after quarter into this machine. Were you surprised when you learned that the medication might be responsible for your gambling addiction? I mean, someone said to me, this medicine will cause compulsive gambling. SPEAKER_19: I would have thought they were crazy. SPEAKER_14: It's just at that time where the first studies come out showing that this is actually a common side effect of Requip. Really? So there were other Anns appearing in other places? Same deal? Absolutely. Basically, after my neurologist sent me off the Requip, SPEAKER_14: Her compulsion disappeared instantaneously. Almost immediately. SPEAKER_19: That fast. SPEAKER_14: Well, within a week, I'd say. SPEAKER_19: Wow. SPEAKER_16: It was gone. SPEAKER_19: I haven't gambled for nearly three years. Did her Parkinson's return? SPEAKER_16: Yeah. SPEAKER_19: After dreamers a lot worse. I've recently gotten a cane. After a walk in, he's a walker. So the price of not being a gambling addict is living with debilitating Parkinsonian symptoms. SPEAKER_19: But my son, let me finish about my son. When I told him, after I had a quick gambling, I said, Son, I have some things that belong to you that you should have. SPEAKER_12: And he said, Mom, those are just things. It's just really great to have you back. SPEAKER_13: Radio Lab will continue in a moment. SPEAKER_13: Or to take things deeper when you breathe. Crow, would you think about the air that's flowing around your head right now? It's full of atoms and molecules that are flying about and smashing into each other and colliding and shooting off at different trajectories that can't be predicted. It's totally chaotic, right? Until you breathe it all in. When you do, things get predictable. SPEAKER_16: Can I release? SPEAKER_13: Nope, nope. Okay. The point is when you breathe in, all of those chaotic, fluxy molecules come in and become a part of the machinery that is you. They go into your blood. They go into your cells, which are themselves these little factories. Factories full of even tinier factories like mitochondria. What are mitochondria? I'm not really sure. But I do know that's Jonah Lara again, himself a factory of insight. A factory is full of these intricate things which work and you can understand, you know, this gene makes this protein, which makes this organelle, which does this thing for the cell. SPEAKER_13: This process, says Jonah, of taking in flux and giving it a shape. Giving it an order. That is what life does. In fact, you might say it is the definition of life. SPEAKER_14: The closer you get, the more you kind of stand in awe at the exquisite engineering. There is a sense that life is to be the world's most elegant clock. SPEAKER_13: Nicely put. Now, if life is a machine, you would think that the most clock-like, most machine-y part of life would be all the way down at the bottom. I would think so. Which for our purposes is when a gene makes a protein. Gene, protein. Gene, protein. This is the basis of life. So you would think it's got to be orderly, it's got to be predictable. Otherwise, none of us would be alive. SPEAKER_16: It is a very predictable, orderly system, so we all believe. SPEAKER_13: Pretty amazing. But then we spoke to this guy. Am I talking? Have I been talking to him? SPEAKER_09: Yeah, you are. Okay. SPEAKER_13: And he mucked things up a bit. Well, what's your name? My name is Carl Zimmer. He's a science writer like Jonah. SPEAKER_09: I write a lot for the New York Times and Scientific American and Discover. I blog. And he told us that this whole genes-making-protein situation, as tick-tocky and unfair as we've always assumed it to be, SPEAKER_13: in fact, scientists have never actually seen it. SPEAKER_16: Well, I mean, it's very small. But finally, scientists have figured out a way to turn on a light when it happens so they now can see a gene turning on a protein. SPEAKER_13: SPEAKER_16: Literally see it with their own eyes. SPEAKER_13: Yeah. And what they saw was astonishingly un-clock-like. SPEAKER_09: At the fundamental level, it's just sloppy. Sloppy. And that's the best word for it. SPEAKER_13: In fact, in our interview, he used that word like 42 times. SPEAKER_09: Sloppy, sloppy, sloppiness. Sloppiness. Sometimes he used this word. Random. Or this. Fluctuating. In this one. SPEAKER_13: Noise. Chaos. SPEAKER_09: Noise. Definitely used that one a lot. Jumble. Noise. Noise. Noisy. Accident. Noisy. Noise. Noise. Noise. Noise. Noise. Noise. SPEAKER_13: Noisy. Sloppy. Chaotic noise. Sloppiness. In this one, involving a little, tiny bacteria called E. coli, which is Carl's favorite. SPEAKER_09: Indeed. Yeah, so these are E. coli. These are harmless residents of our gut. And they're also- Would you call them creatures? SPEAKER_09: They're creatures, sure. They sense their world. They make decisions. They feed. They reproduce. They have genes like us. They've got 4,000 genes. I think they're earned the title creature. And these creatures are actually very similar to our own cells. SPEAKER_13: Their genes make proteins just like ours. So what these scientists did was they took some E. coli that were exactly the same, clones, in every single way. They're genetically identical. And then they put the whole batch in a dish and they said, okay everyone, we're going to turn on your genes, start making proteins. Now. And they watched. Because like you said earlier, they had found this new way of getting the E. coli to glow. Every time it's genes, made a protein. SPEAKER_09: It seems like it ought to be like just flicking a switch. Yeah, you turn on the genes, click. SPEAKER_13: Protein, protein, protein, protein, protein, protein, turn it off. SPEAKER_13: Turn it on. SPEAKER_16: Protein, protein, protein, protein, protein, protein, turn it off. SPEAKER_09: Couldn't get simpler. SPEAKER_16: This is like a basic function of biology. Yeah, this is biology 101. SPEAKER_09: And again, these are genetically identical E. coli. Meaning they've got the same genes, they're making the same proteins, so they should glow SPEAKER_13: the same. SPEAKER_09: Right. You just expect a steady glow. In all of them. SPEAKER_09: Nice and steady. And that's not what happened. You could start with like an individual E. coli and say, okay, well what happened with that one? Um, it didn't start to glow. It started to flicker. SPEAKER_09: There'd be a little bit of light. No light. Little bit more light. Then maybe a sudden flash. Then dark again. Then a little bit of light. SPEAKER_13: Hmm. So they were expecting... Yeah. And what they got in his tongue was... SPEAKER_13: Swoop swoop swoop swoop. SPEAKER_10: It was completely defective. SPEAKER_13: Like a car with no muffler going... SPEAKER_13: More troubling still, when they looked at E. coli number 2, it too was defective. Except in its own unique way. Two had his own thing going. Same with number 3. He had his own thing going. SPEAKER_09: I mean they're genetically identical. Same with number 4. This is essentially the same creature in many different copies. And 5. 6, 2. But... And 7. Each one was flickering in its own... Number 8. Pattern. 9. Chaos. 10. Fluctuating. 11. SPEAKER_08: Sloppyness. Noise. SPEAKER_08: Chaos. Jumble. Chaos. Floppyness. Jumble. Floppyness. Noise. Random noise. Kno... Accident. Noise. Floppyness. Noise.. Noise. Noise. Noise. SPEAKER_13: Noise. Noise. Now this noise... would not be a problem if it's just a bacteria we're talking about. But according to Carl... It's everywhere. Everywhere. In. We are built, he says, on a foundation of chaos. SPEAKER_16: This is very puzzling to me because if, down at the deep level of our DNA, there's just this random mayhem, Bedlam, how do you go from Bedlam up to the organization that I think I represent? I wake up in the morning, I go to sleep at night, I get hungry, I eat, I breathe in, I breathe out. Listen to my heart. I am very, very orderly. I don't know how you get from this to this. SPEAKER_09: That's right. I mean, so somehow all of this sloppiness has got to be somehow tamed because we're alive. I mean, it's not total chaos in our bodies, but... SPEAKER_16: But you keep this sentence, never seems to quite finish. But we don't know how that happens, is that what... SPEAKER_09: We have some ideas of how it happens. As scientists start to understand how genes work with other genes, they can see ways in which you can filter out the noise and keep the good signal, keep the music. SPEAKER_13: Okay, so do you want to sit? Sure. Anywhere, really. Now this I find really cool. The research on this stuff is really new, but Carl says one of the ways that the body may do this... Testing, hello, hello. May go from like... Is by doing something that I actually do on the show all the time, which is use a noise filter. SPEAKER_13: The body may have engineered its own noise filters. I'll just give you an example from my world. SPEAKER_13: This is the honest to God's truth. I have a friend named Little Wing Lee. Hey, Little Wing. SPEAKER_03: Hello, Dad. SPEAKER_13: Tell me what you're holding in your hands there. SPEAKER_03: In my hands I have two audio tapes. SPEAKER_13: Little Wing just recently called me up. She said, I've got these two cassette tapes. They're really old. SPEAKER_03: I think they were made in the 70s. SPEAKER_13: My mom found them in her attic and they're of my grandmother. SPEAKER_03: One's labeled Mima Sings. Singing. SPEAKER_13: Singing old slave songs and old hymns. Now Little Wing's grandmother died last year. She was 99 years old. SPEAKER_13: Wow. And they were really close. SPEAKER_03: Yeah, very close. They used to call me Little Mima when I was a kid. SPEAKER_13: So she's got these tapes. She wants to hear them. The problem is if you put it on for more than three minutes, you get annoyed. SPEAKER_03: And there was that weird like, sss... SPEAKER_13: It's too noisy. I was kinda over-pounding there. SPEAKER_13: She wanted to know if I could do something about it. So real quick, here's what I did. I put it into a computer, launched an EQ program, found the base noisiness which was around 600 hertz, dialed that down. SPEAKER_13: Like so. Then I found the high hiss frequencies which are around 2,000 hertz, dialed that down. Ah, now as a final step, I just kind of located the voice around a thousand hertz and dialed it up. SPEAKER_17: Okay, so it's not a flawless process, I mean now she sounds like she's coming out of a well, but SPEAKER_13: for the first time you can hear her voice. I don't know. This is the first time I'm hearing this song. SPEAKER_03: But it seems like she's describing the night that my grandfather passed away talking about the doctors telling her that my grandfather's passed SPEAKER_03: and then she's describing putting a fern in his hand and she said it should be a rose. SPEAKER_13: The thing that's applicable here is that we started with this and then just by bringing certain frequencies down and others up, we ended up with this. SPEAKER_13: This might be how it is in the body that you've got this noise all the way in the bottom, these genetic circuits which are spitting out messiness, but somehow just on top of that are other genetic circuits which are cleaning it all up, giving it a shape. SPEAKER_13: Wait, what? Is that not right? SPEAKER_09: Not quite. Damn it! Science! What's wrong with it? Well, in our cells there's no grandma. What do you mean there's no grandma? SPEAKER_13: SPEAKER_09: You don't start off with some very clear signal that gets masked by noise. The noise is there from the start. It's noise and then all of a sudden you have this beautiful song. Carl went on to explain and it took like an hour for us to finally get this. SPEAKER_13: There's nothing but noise down there at the bottom and yet somehow the song emerges like a phantom because it seems like the noise is somehow filtering itself into music. SPEAKER_16: So if we were to get the analogy right, Little Wing would hand-jat a tape with just fragmented sound. Little bits of me-ma. Little bits of me-ma in all kinds of random ways. SPEAKER_13: SPEAKER_09: Maybe she gave you eight or nine tapes. SPEAKER_13: And somehow he says it all starts to kind of get into a network where this one filters that one and that one filters the other one and the other one filters that ninth one. And out of all of that comes grandma. SPEAKER_16: Comes a song. SPEAKER_16: The song of a living regular organism. SPEAKER_16: Nima literally. I mean, grandmas are made from chaos. I love that. You say, mm-hmm, like it's almost like it seems like a miracle. I don't even think it stands up and walks. SPEAKER_09: But see, the thing is, you've hit, I mean, we are talking about something that scientists don't understand yet. So I don't have, so there's not a, if you want to have a part of this show where you're SPEAKER_09: saying, and this people is how it all works. SPEAKER_13: Can't do that. No. SPEAKER_13: But here's the thing. If you want to get fruity about this, you could say, and I put this to Carl, that if all the way down at the bottom of us there is this fuzz, it cannot be predicted, then in some sense, we're free to be whatever we want. SPEAKER_09: Well, you know, I mean, look, I can sit here and concentrate and I can think any thought SPEAKER_13: I want to write now. Any thought? SPEAKER_09: Sure. But you can't think about a poem from second century China. Do you think that, do you think that could you make an equivalence between loose mechanics SPEAKER_16: and sense of freedom? SPEAKER_09: Well, you know, I mean, does the sloppiness and the floppiness of a protein clamping onto your DNA scale up to what you're going to be when you grow up? SPEAKER_13: On radio, yes. Okay. All right. SPEAKER_09: Well, here we are. SPEAKER_13: SPEAKER_10: Hello, this is Carl Zimmer. SPEAKER_07: This stochasticity theme song was created by Josh Kurtz and Shane Winter. Special thanks to Lil Wingley and Nima. SPEAKER_02: Visit Radiolab online at radiolab.org where you can comment on the show, ask random questions and hear the entire Frostasity theme song. Anyways, this is Lil Wing. SPEAKER_21: Thank you. Bye. Hi, I'm Hazel and I'm from Silver Spring. Radiolab was created by Chad Bohmak and is edited by Soren Wheeler. Lulu Miller and Latif Nasr are co-hosts. Dylan Keith is our director of sound design. Our staff includes Simon Adler, Jeremy Bloom, Becca Bressler, Eketi Foster-Kees, W. Harry Fortuna, David Gable, Maria Paz-Gutillas, Sindhu Nainesam-Bhadhan, Matt Kielty, Annie McEwen, Alex Neeson, Sara Khari, Alyssa Jung Perry, Sarah Sandback, Arianne Wack, Pat Walters and Molly Webster. Our fact checkers are Diane Kelly, Emily Krueger and Natalie Middleton. Thank you. SPEAKER_00: Hi, this is Tamara from Pasadena, California. Leadership support for Radiolab science programming is provided by the Gordon and Betty Moore Foundation, Science Sandbox, Assignments Foundation Initiative and the John Templeton Foundation. Foundational support for Radiolab was provided by the Alfred P. Sloan Foundation.