Stochasticity

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Hey, it's Latif. 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.

Wait, you're listening?

Okay.

All right.

Okay.

All right.

You're listening to Radiolab?

Radiolab from.

Rewind.

Okay, I want to start the show today with a truly remarkable story, which at least initially involves this girl right here.

Hello, I'm Laura Buxton.

Laura Buxton is her name. Remember that name?

I'm going to tie my hair back.

And Laura, Let's do this like a movie, okay?

Like a movie? Yeah, okay.

Okay, it's June 2001.

Stoke-on-trent.

Stoke-on-trent.

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.

Yeah, well, almost 10..

Whatever, she's a tall girl.

Pretty tall for my age.

Pigtails, and in her hand, she's holding a balloon, a red balloon. You with me so far, yep.

My name.

Plus a little message.

It just said, Um, please return to Laura Buxton, and then, on the other side, it had my address.

Okay, so cut back to the outdoor scene. There she is standing on the lawn.

It's very windy.

She's got this red balloon with her name on it, and she holds it up to the sky, to the heavens.

And I just let it go and the wind took it.

But that's not what happened. The balloon kept going alright. 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 Walsall.

Gloucester.

Gloucester, and all in all. The red balloon goes about 140 miles south.

Exactly against the pervading wind.

Oh, really.

To the southwesterly.

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-Lilbourn.

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.

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.

Why? what? did he say? Oh my God.

Okay, so check this out. Remember how I told you that the first girl who sent the balloon was ten, yeah, the second girl who received it?

Ten years old, she's ten.

Okay, okay, wait, wait, wait, there's more, there's more. Remember how I told you that the first girl's name was Laura Buxton?

Yeah.

Well, girl number two, can you introduce yourself?

Okay, um hi, I'm Laura Buxton.

What, they're both? LaURA BuXTON Yeah, no.

Yes, get out, you heard me, right? A ten-year-old girl named Laura Buxton lets go of a balloon, phew.

Is this for real? yeah.

I think it might be the strangest thing I've ever heard in my life.

It's pretty weird.

It's been about eight years since the balloon incident. The Lauras see each other a lot and we managed to get them both into a studio. Hello, New York.

This is London.

Can you hear me? So like, we're gonna hear Americans through these, yeah.

Okay, back to the story.

Yeah, I got the balloon.

That's Laura number two and I. What did you think at that point?

Um, well, I. 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.

So Laura number two wrote a letter to Laura number one.

Dear Laura, I think I put, I'm ten 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.

Laura Number one Yep, you get the note.

Got it through the post.

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?

Well, she was trying to tell me that it had come to Laura Buxton and it wasn't from Laura Buxton. She just thought I was confused.

Okay, fast forward. A short while later, the two Lauras meet. 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.

And down the corridor, I saw this girl who looked pretty similar to me.

First thing she notices is, wow, we're the same height, got the same colour hair.

Brownish hair.

We're even wearing the exact same clothes.

Pink jumpers and jeans, yeah.

You both had on pink jumpers and jeans, yeah, and as they started to talk, it just kept getting weirder.

Well, we'd both got a three-year-old black labrador, we'd both got a grey rabbit, we'd both got guinea pigs. Really. 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, Oh my God, they were identical. They were both brown, with a sort of beigey-orange patch on their bum, like, completely the same.

Do you believe in miracles, either of you?

I don't know, would you call this a miracle? 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.

So you don't think that wind that blew the balloon was just wind?

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?

Maybe we were meant to meet, I don't know.

But meant by whom or what?

Who knows, really?

Oh, Chad, I mean, whether you look, what you're.

What did you call me a destiny bully?

Yes, because you.

Sounds like a pop band or something.

No, it's what you're doing to those girls.

No, I wasn't trying to force God on them, if that's what you mean.

Yes, you're the one who says, Oh.

No, no, no. I was trying to get to the question of how should we think about that story? 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 Radiolab. 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 U.S. yes, on Radiolab.

I'm Chad abumrad.

I'm Robert Krulwich.

We're about to get random, so stay with us.

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, Oh God, random. sorry, although it's happened so many times that it's no longer random.

But it does have a very nice kind of lilt to it. Don't you think I'm going to sing with it now? Boom boom, boom, boom boom boom boom, boom boom, boom, boom, boom, boom, boom boom, boom boom. It's a lucky wind. it's a lucky wind.

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.

We found you, so this is Jad. hi Jad. nice to meet you. I'm Debra Nolan.

The reason we'd come to see Deb Nolan at Berkeley is because we'd heard that she plays this game.

I like to incorporate lots of classroom activities and demos.

One, in particular, has to do with randomness. It's a game that helps her students understand what real randomness actually looks like. It doesn't look like what you would think in any case. She takes us into her classroom, us and a few students.

And she sits us down, Yeah, have a seat, we all sit down. should we sit in a semi-circle?

That sounds good.

And then, she explains.

Okay, I'm going to divide the group up into two, I'm going to divide it right here.

She splits us up so that group one is three of her students. I'm Joe Cheng.

I'm Richard Liang.

I'm Margaret Taub.

And group two Jad Abumrad.

I'm Robert Krulwich.

Is us.

And the group here?

She's pointing at us.

I'm going to give you a penny and I'm going to ask you to flip the coin a hundred times and the three of you.

She points to her students.

Your job is to pretend to flip a coin.

Meaning they just have to flip the coin in their heads. Kind of guess.

How do you think that coin might land produce a hundred fake coin flips?

And then Deb leaves the room.

Tails.

Tails.

Tails.

How many is that?

While we actually flip the coin a hundred times.

Heads.

Heads.

Tails.

Tails, tails, tails.

Tails, heads, heads, tails. That's exhausting.

But eventually we did finish and both groups then put our strings of H's and T's up right there, like boys heads, tails.

Hello, here they are, huh? Let's have a look.

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, the Fakers, and then she looked at our list, and right away, she says, pointing at our list.

This is the real one.

We were like, Wow, how did she do that? well, amazingly, the way she knew had to do with one particular moment.

Right, roll the tape back to a moment, right at the beginning of our coin flip.

Tails.

Another tails.

I feel like we have way too many tails.

It was really spooky, completely, like at any moment a unicorn was going to come galloping in. 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 weren't any longer than four, I think.

That's how she knew. And when we asked one of the guys on the other team, why didn't you put more streaks in your flips?

Um.

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 doing that on purpose.

In other words.

But.

Those streaks just feel wrong, and that's the thing about randomness, real randomness when you see it just doesn't feel random enough.

But, says Deb, the truth is.

Strange things do happen by chance.

Chance.

Chance, chance.

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, hi Robert.

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.

We got one tail, then we got a second, then we got a third, yeah, and then we got a seventh.

And somewhere in the conversation, we started to do the math, like, Okay, what actually are the odds?

Let me see was it heads in a row or tails in a row? 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.

Point zero, zero, a little more than one percent.

Just over one percent chance, yeah. So it seemed at first that what had happened in Deb's class was super unlikely, right? But then Soren, my producer, had to go and say this.

Oh ho ho, now you wait, wait. did you? you were holding back on me?

Wait, wait.

Because we're too stupid to know that. That's why we have soren here.

Are you saying that somewhere in the hundred flips, you got a run of seven?

That's what we're saying.

That's not a particularly good coincidence. I'm sorry to burst the bubble.

What do you mean? And then Jay explained it to us.

Fourteen of those sets of seven.

Which we were because we were doing a hundred. Then the probabilities start to add up, it starts small, like one percent, 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 a hundred is don't hold your breath.

About one in six chance.

One in six, that's it.

That you would have gotten a string of seven.

So what felt spooky and almost twilight zone-ish in the moment is actually.

It's not improbable.

Oh.

See, that's why you don't want to know it. It doesn't confirm your goosebumps.

No, I think the goosebumps are dead now.

Oh, I'm sorry to do that, I still enjoy life.

The problem, says Jay, is that we were so focused on those seven flips in a row 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.

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 that the thing that felt so special.

Suddenly, you see that it's not so odd in its real context.

And this sad lesson goes way beyond coins. He gave us this example.

1985 and 1986 Evelyn Adams of New Jersey wins the lottery twice.

Back-to-back years, crazily improbable, right 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 the second time.

She is completely blown away, for good reason.

The odds that those two particular tickets would become winning lottery tickets are 1 in 17.

Wow, but Jay would say if you pan the camera back away from Evelyn.

Bye, Evelyn.

And you look at the whole world of people buying lottery tickets. At this vantage point, you can begin to ask a different question.

What are the odds that somebody somewhere?

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.

Wow.

The odds of that were calculated at 1 in 23.

That's trillion with a t.

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 me, it lands on me.

How did it come to be that it just landed on me?

I don't know, it's sort of like a miracle, really.

And it is sort of miraculous. 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.

And crushed and crushed sore hand. The real lesson here, according to Jay Kohler and also Deb Nolan before him, is that if you don't see past yourself, you fall prey to, you know, superstition.

Right, or magical thinking? You have to be careful that you're not finding meaning here when it's just coincidence, just coincidence, just coincidence, just coincidence.

But there are some things, like the Loras, that will never feel like just coincidence.

Well, if it was just wind, it was a very, very lucky wind.

So we had to ask, Jay, I ask you, Sir, is this a miracle?

This is not a miracle. It's a good story, but you know, there are lots of little things I could pick at in the story, like, what?

Oh yeah, pick away.

Well, I mean, you know, Laura Buxton didn't find the balloon? 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. It said, No, no, that's not a good one.

To be totally honest, he's right.

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.

Scrap that. And what do you guys study in school?

Biology, chemistry and geography, whereas I'm doing English and history and classical civilization, hmm.

Scrap that. 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 and this is a trivial comment, but I believe that one of the girls was actually nine.

Well, almost ten.

And the other one was ten.

No.

Oh well, that's the story through, never mind.

Yeah, I'm sorry to be your most depressing guest.

Nonetheless, I will continue to tell the Lora 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.

Well, first of all, we love stories. It connects us, it gives us insight into our own lives, and I think it also gives us a feeling that life is magical.

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.

Fair enough, really, because it just happens to be us in those statistics. So yeah, I mean, if that's what the statistician thinks, I mean, yeah, fair game to him.

They don't really care the way they see it. Whatever was in that wind, 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.

Hey, it's Lotsef 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.

Hey, I'm Jad Abumrad.

And I'm Robert Krulwich and we are talking on Radio Lab about things stochastic.

Like coin flips and lottery tickets.

But let's just push this whole argument another step forward, if we may.

Which mean?

Let's talk about human beings.

I'm Ann Kleinschneider, I live in a small country town where most people know other people.

Ann was a high school English teacher.

I taught for 31 years.

She now lives in West Virginia.

Wait, Can you wait? Just a minute? There's someone at my door, I'm sorry.

No, no, of course.

Of course.

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.

I'm sorry.

Not at all.

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.

And she says she began to notice that her hands would start to tremble.

Are you all right? But I just thought maybe it was because of working hard and trying to get everything done.

And it got particularly bad when she said she was just walking in the mall doing some shopping.

And I was by myself, walking, and it was like I stepped off a step that wasn't there.

It was the first full-body tremor she fell.

And then my husband was a doctor, and he sent me to a neurologist who diagnosed me with Parkinson's.

How old is she, by the way?

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, in 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.

But anyway?

Well, the doctor diagnosed her with Parkinson's, and he gives her a drug called Requep.

Requep was the new medicine in 1992.

It's a pseudodopamine, it basically mimics dopamine in the synapse of the cells.

And it was like a miracle drug for me.

Her tremors disappear, her symptoms disappear.

So she's cured, or?

If you looked at her on requep years after she had Parkinson's, you wouldn't notice anything she would seem symptom-free.

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, 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, and we considered gambling a sin.

But as she stood there in the casino in Vegas, she had this inexplicable urge to go to the slot machines.

They had frogs and princes and cars and cherries and lemons. Push a button, wheels spin and see what the pictures did. I've never taken any drugs, so I don't know anything to compare it to, but it was like a high.

And then when she comes back to West Virginia.

I couldn't wait to get to a machine, I really wanted to play.

She discovers the dog racing track.

I'd go at 7.

And that's where she would go. And they had a wide assortment of slot machines.

Hi, how are you?

If I had the money, I'd play all day.

From 7 to 3.

Whoa?

And then she would go home and play slots.

On the computer.

On her computer, not even for money, just for the sheer visceral thrill.

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?

Without any sleep at all.

No sleep, and she could keep that up for several days in a row.

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 hard-hearted, I guess, to even pay attention to that.

Her credit cards are all maxed out.

I sold my mother's silver, I sold my silverware, things that should have been my son's heirlooms stole from the safety deposit box.

She steals quarters from her grandkids.

Steals quarters from her grandkids.

Yeah.

Anything I looked at around the house I thought I could get money out of.

Everyone who knows her is watching her life fall apart.

My house was filthy, dirty, a mess, I wouldn't take time to even wash dishes.

She lives on peanut butter.

Didn't have any crackers or bread or anything, just had peanut butter.

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, Well, so many more minutes or so many more hours, I can go gamble.

Her husband eventually leaves her.

I mean, I loved my husband, but.

They got divorced.

There's just no decision and everything is gambling. One of the neat things about gambling is you can do it by yourself.

$300,000.

Which to her is.

Is all your life savings?

And that's one quarter at a time.

Yeah, that's the surreal part.

I tried several things, I went to a rehab facility.

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, yeah.

For years, that's how scientists saw dopamine as the neurotransmitter of pleasure, the neurotransmitter of sex, drugs and rock and roll.

But you said earlier that dopamine has to do with movement.

Well, what is the ultimate purpose of movement from the perspective of evolution? 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 that turned out it was a little more complicated than that. In the mid-1970s, a guy named Wolfram Schultz decided to take a much closer look, and his subject was a monkey.

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, 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.

He soon discovered something very odd about these neurons.

As they juiced this monkey day after day.

Hello Monkey.

Day after day.

Hello Monkey.

The squirt of dopamine, which they were always measuring in the monkey's brain, seemed to move forward in time.

What do you mean?

Well, at first, the dopamine hit when the monkey took the sip of juice.

Hello Monkey.

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.

Not really, you're going to have to bring it home for me.

Well, 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.

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.

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, like, basic survival stuff here.

Mm-hmm. There's one other wrinkle, though, methadopine 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. she pushes the button on the machine, slot machine, and oh my God.

And sirens and bells go off. Coins clang.

And inside her head, her dopamine neurons, they're saying.

This is wonderful.

But now, how did this happen?

Where did this big reward come from?

What did you do this time?

Why are you so happy all of a sudden?

And start searching for something.

They had frogs and princesses.

Was it the number of cherries that she had just before? Was it that this machine had 13 hits and this was the 14th?

I thought I could tell.

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.

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 100 bucks on this stupid machine. I should go get lunch.

Anne 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, 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.

I thought I was good at stopping the machines, in fact.

She told me a story about she would go to buy milk and then spend the next 12 hours with the milk rotting next to her. 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, if someone had said to me this medicine will cause compulsive gambling, I would have thought they were crazy.

It's just at that time where the first studies come out, showing that this is actually a common side effect of RecREp.

Really, so there were other Annes appearing in other places. Same deal.

Absolutely.

Basically, after my neurologist took me off the Recrep.

Her compulsion disappeared instantaneously.

Almost immediately.

That fast.

Well, within a week, I'd say, wow.

It was gone.

I haven't gambled for nearly three years.

Did her Parkinson's return?

Yeah, I have tremors a lot worse, I've recently gotten a cane, I have trouble walking, I use a walker.

So the price of not being a gambling addict is living with debilitating Parkinsonian symptoms.

But my son let me finish about my son when I told him after I quit gambling. I said, Son, I sold things that belong to you that you should have. And he said, Mom, those are just things. It's just really great to have you back.

Radio lab will continue in a moment.

The voice was their guide to life from people who cared about what they were covering. With such intensity that there were fistfights and brawls inside the paper. That's gone.

The End of an Era? On this week's On the Media from WNYC Find on the Media wherever you get your podcasts.

And I'm Robert Krulwich.

This is radio lab, and our topic today is You want to say the word?

Stochasticity.

Stochasticity, which is a wonderful and fancy word that essentially means randomness. Chance, like the kind that's built into flipping a coin or playing the lottery. Or to take things deeper, when you breathe Krulwich, 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 in different trajectories. That can't be predicted. It's totally chaotic, right until you breathe it all in.

Factories full of even tinier factories, like mitochondria.

What are mitochondria? I'm not really sure, but I do know that's Joan O'Leary again himself. A factory of insight.

Factories 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.

This process is Joan of taking in flux and giving it a shape, giving it order. That is what life does. In fact, you might say it is the definition of life.

The closer you get, the more you kind of stand in awe at the exquisite engineering.

Nicely put.

Now, if life is a machine, you would think that the most clock-like, most machiny 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.

It is a very predictable, orderly system, so we all believe.

Pretty amazing. But then we spoke to this guy.

Am I talking? Have I been talking?

Yeah, you are.

And he mucked things up a bit.

Well, what's your name?

My name is Carl Zimmer.

He's a science writer like Jonah.

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 proteins situation as Tiktokian affairs we've always assumed it to be. In fact, scientists have never actually seen it happen.

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.

Literally see it with their own eyes.

Yeah.

And what they saw, well was astonishingly unclock-like.

At the fundamental level, it's just sloppy, sloppy, and that's the best word for it.

In fact, in our interview, he used that word like 42 times.

Sloppy, sloppy, sloppiness, sloppiness.

Sometimes use this word.

Or this fluctuating?

In this one.

Noise, chaos, noise.

Definitely use that one a lot.

Jumble noise noisy, accident noisy.