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Documentary, NOVA Wonders 1 Animal Communication
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AnimalsTranscript
00:00What do you wonder about?
00:02The unknown.
00:03What our place in the universe is?
00:05Artificial intelligence.
00:06Hello.
00:07Look at this.
00:08What's this?
00:09Animals.
00:09An egg.
00:10Your brain.
00:12Life on a far away planet.
00:15Nova Wonders investigating the biggest mystery.
00:19We have no idea what's going on there.
00:22These planets in the middle we think are in the habitable zone.
00:25And making incredible discoveries.
00:28Trying to understand their behavior, their life, everything that goes on here.
00:32Building an artificial intelligence is going to be the crowning achievement of humanity.
00:38We're three scientists exploring the frontiers of human knowledge.
00:43I'm a neuroscientist and I study the biology of memory.
00:47I'm a computer scientist and I build technology that can read human emotions.
00:53And I'm a mathematician using big data to understand our modern world.
01:01And we're tackling the biggest questions.
01:04Dark energy.
01:05Dark energy.
01:06Of life.
01:07There's all of these microbes and we just don't know what they are.
01:10And the cosmos.
01:15On this episode.
01:19Animals make all kinds of noise.
01:23But what does it mean?
01:25What they're telling the females.
01:26I'm free of parasites.
01:29Can we crack these mysterious codes?
01:32The gesture means travel with me.
01:34His vocabulary was like a two and a half year old human child.
01:38This is Dr. Doolittle's dream.
01:40Nova wonders what are animals saying right now.
01:44And we're gonna go.
01:49All people along.
02:01Come who on the side of the world.
02:02They đo the bone.
02:03They're gonna die.
02:06If they're not.
02:07The thing is they're gonna die.
02:14Back to this episode.
02:14Our archive.
02:25All around us are alien tongues, and they don't come from space.
02:33From whale songs and wolf howls to birds chirping and dolphins clicking.
02:40The animal world is filled with mysterious conversations.
02:48Could we ever tap in?
02:51We like to think that language sets us apart from the beasts.
02:55But are we really all that special?
02:58Today, scientists are starting to decode those communications.
03:02Discovering that we might not be alone.
03:05I'm Andre Fenton.
03:06I'm Rana El Caliubi.
03:08I'm Talithia Williams.
03:10And in this episode, Nova wonders, what are animals saying?
03:15And what does it say about us?
03:25When I'm working with Zach, it seems like magic.
03:30Zach, that'll do.
03:31Zach, here.
03:33Experiencing that kind of connection with a dog, you're in sync.
03:38It's like any other connection you have with someone.
03:40Lie down.
03:41Where you really get along and you're like, oh wow, that was an amazing conversation.
03:46Robin Queen is a linguist and competitive sheepherder from the University of Michigan.
03:51And like many of us, she likes to think she can talk with her dog.
03:55Walk up.
03:56I think we are, as humans, we're fascinated by the idea, the Dr. Dolittle idea.
04:01We want that to be true in some way.
04:04When I started working with the dogs, I was shocked at what they could do.
04:07I'll lose that.
04:08Slide it.
04:10And for border collies like Zach, herding sheep is just the beginning.
04:15Get spider.
04:15They appear to have a sophisticated understanding of language.
04:19Get spider.
04:20Bring it over here.
04:20Their ability to learn human words are almost unlimited.
04:25It seems to be, you know, every year a new dog comes by with a larger vocabulary.
04:29A glance at YouTube proves the point.
04:32Tessa, get pumpkin.
04:35Tessa can recognize four different toys.
04:38Good girl.
04:38Bring it over here.
04:40Excellent.
04:41Get pig.
04:43And that's puppy's play compared to Gable.
04:45He knows 150.
04:48Good boy.
04:49Chase.
04:50Find meow.
04:51Find meow.
04:52Find meow.
04:52But all of these pooches pale in comparison to Chaser.
04:56There's meow.
04:58Come here.
04:59I said throw that dog.
05:00Who has been proclaimed the world's smartest dog.
05:04Chaser was taught the individual names of over a thousand objects.
05:09And that's really pretty cool because it starts to try and get at that question of how special are humans.
05:15Chaser can understand hundreds of words, but all that she can do is say ruff.
05:21She can't actually say any of those words back.
05:24Now what would be really impressive is when Chaser starts saying, you go get the bunny.
05:28Then I'd be impressed.
05:30Find roach.
05:30Find roach.
05:31But as impressive as Chaser's feats are, do they qualify as?
05:36Language.
05:36Language.
05:36Language.
05:41Since the dawn of history, we've imagined animals to be like us.
05:45I'm a horse, not a guinea pig.
05:47Our stories are filled with talking creatures, but what's the reality?
05:52Well, to answer that question, let's talk about language.
05:57To scientists, it's a learned set of symbols that can be combined into infinite meanings.
06:04Just consider these.
06:06Dog bites man.
06:08Man bites dog.
06:11By just changing the order of a couple of words, the meaning of the message is completely different.
06:17Well, this is the cornerstone of human language.
06:20It allows us to tell stories, write poetry, negotiate contracts, whisper sweet nothings.
06:28The question is, is this skill unique to us?
06:34There are two chimpanzees in Rome who have brought a new twist in communication between animal and human.
06:41For over half a century, scientists have been working with our closest relatives to answer that question.
06:47Vicki was adopted when her own mother couldn't feed her anymore.
06:51At first, scientists tried teaching language to chimps by raising them like children.
06:56Perhaps one of the most famous of these was Vicki.
07:00She loves all the attention and affection, and she loves everyone.
07:04Do this, kitten.
07:06Do this.
07:06Not only is this approach now considered unethical, it didn't work.
07:11After seven years of intense training, she could barely utter four words.
07:16No, no, do this.
07:24So scientists switched to sign language.
07:27If you watch Coco closely, she's learning to put her fingertips to her mouth to sign eat.
07:34Apes like Coco, the gorilla, hinted that apes have some ability for language.
07:39Coco proved an adept student.
07:41Everyone was amazed at how well the little gorilla was catching on.
07:48Let's do just a little bit more work, and then we'll get a whole bunch of surprises, okay?
07:53But it wasn't until this guy came along that researchers discovered exactly how impressive that ability was.
08:00In the world of ape cognition, Conzi is, you know, Elvis Presley.
08:05All right, Conzi, come on, tell me what this is.
08:07What's this a picture of?
08:10My name.
08:11Very good.
08:14Instead of sign language, Conzi learned these.
08:18They're called lexograms, abstract symbols that represent words.
08:24What's this?
08:25Look at this.
08:25What's this?
08:27An egg.
08:28Very good.
08:29That's an egg.
08:30Good job.
08:32And Conzi has learned over 400 of them.
08:35Good.
08:36Keep going.
08:40Good job, Conz.
08:46Good, Conzi.
08:48Good stuff.
08:50Amazingly, he started teaching himself this skill as a baby over 30 years ago.
08:55I want you to go put the onions in your hot food.
08:59Conzi might have been around 11 or 12 at the time.
09:03His vocabulary, spoken English vocabulary, was assessed in comparison to a two-and-a-half-year-old human child.
09:09Now, I want you to take the spoon and put it on top of the bucket.
09:15Can you do that for me?
09:16Can you put it on top of that bucket?
09:18Watching him today at 37, it would appear his language ability goes well beyond vocabulary.
09:23Can you put it on top of the bucket?
09:26Very good.
09:26That's a good job.
09:28So I can ask Conzi, hey, Conzi, can you put the blanket on your head?
09:32And then I can ask Conzi, can you sit on the blanket?
09:34Can you put it on your head?
09:40Nice job, Conzi.
09:42Very good.
09:43Very, very good.
09:45Can you put the blanket on the cube?
09:48Yeah, now can you sit on top of the blanket?
09:50No, sit with your bottom on top.
09:53Good job, Conz.
09:54That's it.
09:56What he's obviously doing in that context is understanding not only the individual words,
10:01but the order in which they're arranged.
10:03I think that's a big deal because that is one of the foundational elements for human-spoken language.
10:10Conzi is a huge deal.
10:12The studies with Conzi and with the other apes like him allowed us to get a window into what great
10:19apes might be capable of in terms of learning our world and our communication.
10:24Science has gained a whole lot from apes like Conzi, but in all likelihood, Conzi will sort of be the
10:32last of his kind.
10:34Moving forward, I think our approach has shifted to one where we're starting to focus more on what the animals
10:40are doing with one another.
10:42Cat gorilla half visit, Coco love.
10:44Today, the question scientists are asking is not whether animals can learn our language.
10:50Could you take my shoe off, please?
10:52But if we can learn theirs.
10:55It's very interesting that humans who are very caught up in our own intelligence, when they wanted to understand whether
11:02other animals had a language like ours,
11:04the best thing we could think of was, can we teach that other species to speak our language?
11:10What you need to do if you want to understand animal communication is leave our own language behind.
11:15Try as much as you can to become more like an animal and just not think in words and see
11:21what they're seeing and understand what they're feeling, what they're communicating about.
11:27And when you do that, you discover a whole new world hiding in plain sight.
11:35When I first came to the rainforest, this was an alien world for me.
11:39I had no clue what to do, how to be, how to move around in here.
11:46Udongo Forest, Western Uganda.
11:50Cat Hellbaiter is setting off for work.
11:53Trying to understand their communication means understanding their behavior, their life, everything that goes on here.
12:00I am the luckiest person in the world, because I get paid to run around a rainforest with wild chimps.
12:06I love this.
12:10She's spent over 10 years studying these chimps.
12:14It's been a pretty incredible thing to be able to watch some of these chimps from the day they were
12:20born until adulthood.
12:23And I get to see the little detail, the soap opera of their life.
12:27I'm an outside observer, but I've been here for so long, I feel a part of the family sometimes.
12:35In the process, she has unearthed a hidden form of communication.
12:43Those scratches, shaking of trees, to cats, they aren't random motions.
12:48They're part of an elaborate code, a secret language of chimps.
12:53All of these gestures are a part of chimpanzee communication, and they grow up with them.
12:58To humans, it might seem a really subtle, like, tiny little push or a tiny little pull,
13:02and that's really hard for us to see, but I think to the chimps, it's very obvious what's going on.
13:10So she's sitting down, looking up at her daughters, and she's giving a big scratch, so she's ready to go.
13:18That's Harriet, and that scratch, it's not because she has fleas.
13:22It's actually a signal to her daughter, Harmony.
13:26And the little one's coming down now.
13:29Well, that scratch has two meanings.
13:31One of them is groom me, and the other one is let's travel together.
13:37Oh, ho, ho, ho, ho, ho.
13:40Allowed scratch gutter to come down.
13:44They're all going to go down the tree, and that's them leaving together.
13:53To the untrained eye, the gestures don't look like much.
13:57Only after hundreds of days and even more nights, pouring over 4,000 hours of video,
14:03did Kat start to put the pieces together.
14:06So in this case, the gesture is a big, loud scratch, but here it means travel with me, travel together.
14:12The reason she thinks Harriet's scratch means less travel is because she has seen the same action and response dozens
14:20of times before.
14:22So you've got Klaus, the little young male chimp, and his mom, Kalima, and he's ready to go.
14:30He wants to travel, so he gives this big scratch, and then he comes around the back of his mom,
14:35climbs on, and they travel away together.
14:39I sometimes look at this, and I wonder if I'm seeing things, if it's really there, if I'm, you know,
14:45if it's all kind of in my imagination.
14:47And it's not until you're watching the videos over and over and realizing that you see this little movement,
14:53but afterwards, every time you see that little movement, the other chimp does something that you start to think,
14:58Oh, there might be something in there.
15:01Like this one.
15:02If you look carefully, you can see the mother chimp raising her foot.
15:08In this case, the gesture is a foot present, and it means climb on me.
15:12This is a hard one to see.
15:14You've got the mother, Jenny, walking down the transect, and her little boy, James, who she'd like to have climb
15:20on her back.
15:22What she does is, she stops, she lifts her foot up, and she looks back over her shoulder at him,
15:28so you know that she's waiting for him.
15:30She's waiting for him to give the response that she's looking for, and in this case, he climbs on, and
15:34they travel away together.
15:36But it's not enough to just see the same gestures over and over.
15:41She needs to see some evidence of a back and forth, a conversation.
15:45In this case, he wants her to come and be groomed by him, so he's going to give these big
15:50scratches.
15:53And he's waiting for a response, so that didn't work.
15:56She didn't do what he wanted, in fact, she didn't do anything, so he here gives a little object shake,
16:01and he gives the scratch again, so he's combining those two gestures.
16:05But still nothing from her.
16:06She's just not interested at the moment, so he's giving a really exaggerated version.
16:10It's like a back and forth between the two of them.
16:13Big scratch.
16:15Object shake.
16:16Come on, I want to groom you.
16:17Come over here.
16:18That seems to have done the trick, because...
16:21She comes down, and they start grooming.
16:25The reason I know this is an intentional gesture, and not just a chimp shaking a branch in the forest,
16:31is because he gives it, and he waits for that response.
16:35And when he doesn't get what he wants, he gives it again.
16:37He persists.
16:38But once he does get what he wants, then he stops.
16:41And it's the same as human conversations and communications.
16:44After you've passed me the thing I'm asking for, then I don't keep on asking for it.
16:53Kat has come up with over 60 different gestures, with more than 19 different meanings.
16:58Stop.
16:59Stop.
17:02Groom me.
17:03And we're still picking and possibly finding new ones all of the time.
17:08Move closer.
17:09I think in terms of an animal-to-human system of translation...
17:14Stop.
17:15We probably have the most meanings translated here.
17:19Let's go.
17:22Let's be friends.
17:24And that's certainly compared to a lot of other animal systems of communication.
17:28It's much richer, it gives us much more detail than we've been able to find elsewhere.
17:34Let's have sex.
17:42It's easy for us to want to focus in on language.
17:45You know, we're quite self-obsessed as a species.
17:47We want to know what is it that might be special or different about ourselves.
17:52But what the chimps have going on here is their own incredible rich world of communication.
17:57And it would be really easy just to focus in on their vocalizations.
18:02But the real subtlety and texture and all of those rich meanings that we see in the gestures every day
18:08would be lost.
18:13I think as humans we're so language-centered that sometimes it's easy to forget that language is not the only
18:20way we communicate.
18:21Language is just one of the channels of communication that we have as humans.
18:26And also not to think that language is the only model for animal communication.
18:31In fact, we humans communicate with dozens of different expressions and gestures.
18:37When you think about it, animals have all this and so much more.
18:41Everywhere you look, you find elaborate systems of non-vocal communication.
18:46From elephant body language.
18:50To honeybees telling their buddies how far and where to fly.
18:55Even the simplest of creatures seem to have a lot to say.
19:03Just consider these guys.
19:05Habernatus Formosos.
19:07Jumping spiders.
19:09Spiders have some of the most unusual communication systems.
19:13It really is kind of like this fascinating puzzle.
19:16And you use as much imagination as possible to sort of crack this language.
19:24Damian Elias from UC Berkeley spends his life listening to arachnids.
19:29Stay there.
19:30Oh, there you are.
19:31Come on.
19:31Working with spiders is not a normal occupation.
19:35You might be surprised how much this tiny creature has to say.
19:39Especially when it comes to love.
19:43Because these females only mate once in their lifetime.
19:46They need to make that choice count.
19:48That decision better be as informed as possible.
19:53So you want to know what spiders are saying?
19:55You need to be a bit of a voyeur.
19:59Oh my god.
19:59I've probably spent tens of thousands of hours watching spiders have sex.
20:04And hearing spiders have sex.
20:06And thinking about spiders having sex.
20:08So he increases the thumps as it gets closer.
20:10Now he's really inching up close to her.
20:12It's like you're trying to decode some type of alien language.
20:15It's only with technology that we have now that we can even try to really decode what's going on.
20:21So what I'm going to do now is I'm going to make a female decoy.
20:24I take a euthanized female.
20:27And then take a pin that has a small drop of beeswax.
20:30And then I lower that pin onto the female.
20:33And now using this decoy, we can have the male corded.
20:39Here we have our courtship arena.
20:41Which is essentially a needlepoint frame and female pantyhose.
20:44With some pieces of reflective tape on them.
20:47I'm going to place our female decoy into this little rig.
20:53Where it's hooked up to this kind of pulley system.
20:57And with it, we can put her in a lifelike posture.
21:01So she can fool a male.
21:03And so how we record these displays is using a laser vibrometer.
21:07So this is what you see right here.
21:10The laser vibrometer converts vibration into sound.
21:14Spiders don't have ears.
21:17And so they can't detect airborne sound.
21:19Instead, spiders detect vibrations with their feet.
21:23With the stage set, it's showtime.
21:28Think of it as a five act song and dance routine.
21:32Act one.
21:33So he's doing a sideline display there.
21:35They're really exposing a lot of the ornaments that they have on their face.
21:38And those oftentimes are species specific.
21:41Females need to know that it isn't a predator that's trying to eat them.
21:45And so you have this very safe display that starts very far away.
21:49And as soon as he gets close to the female, he'll start to do the introductory display.
21:55Now, the singing kicks in.
22:00There, there, there's the introductory display.
22:03Essentially, it's like, you know, listen to this.
22:05Now I'm going to start to tell you a bunch of information about myself.
22:11And so now he's going to go through a series of different signals.
22:15First, the scrape.
22:16Right there.
22:17That's a scrape.
22:20The parasite load is really tied to how loud the scrapes are.
22:27By counting the parasites on over a hundred spiders, Damien found that the louder the scrape, the fewer the parasites.
22:35So what they're telling the female is that I'm healthy. I'm free of parasites.
22:40Next, the thump.
22:42The thumps are probably to kind of make sure to maintain the female's attention.
22:49And once they've snagged that, time to put on the moves.
22:53So the third leg displays serve to draw attention to these ornaments that are on the third legs and they
22:59kind of like shake them around.
23:01And depending on how bright they are, Damien thinks that these tell the female about his past.
23:08By being able to correlate the brightness of these ornaments and the quality of their food when they were younger,
23:13you can say they're talking about developmental history and their feeding history.
23:18And now for the finale.
23:24And we have buzzes, these long tonal signals that inform the female about the male size.
23:31So the louder it is, the deeper it is, the more the female wants them.
23:39So it gets more and more intense.
23:46You might destroy the female.
23:48Get up.
23:48Get up.
23:49Okay, I'm going to stop.
23:50Get up.
23:51Get up.
23:51Get up.
23:56Enough rehearsal.
23:57Now for the real date.
23:59Now we're going to use two live individuals so we can kind of track what the males are doing and
24:05how the females are responding to them.
24:07To make sure he's right about these signals, Damien has to see how real live lady spiders respond.
24:15You can see that the female now is just like really looking at the male, really looking at what he's
24:20trying to do.
24:21For the guy, the stakes are high.
24:23They aren't just singing for their supper.
24:26They're singing to make sure they don't become supper.
24:30When females are assessing males, they're deciding on whether they're a potential mate or whether a potential meal.
24:39So right now he's buzzing, so he's getting really close.
24:42So he's really going to kind of like ramping up trying to get this female to mate with him.
24:48Now he's really in the dangerous parts of his displace, so it's getting faster and faster.
24:53Now he's going to make a copulation attempt.
24:56The female right there said no way.
25:02It's hard not to sort of feel sorry for that male.
25:05And this is especially the case if a male is really trying his heart out and he gets eaten, then
25:09I just feel absolutely terrible.
25:14So where do all these complex signals come from?
25:17It turns out what spiders are doing with all those thumps and buzzes is completely innate.
25:23They're born knowing a fixed set of sounds.
25:26What might we find if we look further up the food chain?
25:29For starters, it's clear what we humans do is very different.
25:34We aren't born knowing language.
25:35Our brains learn it by listening to others.
25:38This skill is called vocal learning.
25:40And only a few other animals have it.
25:44Whales and dolphins, elephants and seals, some birds and bats.
25:51Like us, these animals have a flexible communication system.
25:55Scientists think that if we're ever going to find a communication system like ours, it's going to be in one
26:01of these.
26:05If you enter a bat cave, you hear a cacophony.
26:09Thousands of individuals simultaneously shouting at each other.
26:13And you ask yourself, are they just shouting at each other or is there more to it?
26:21You see, the bat is a bat biologist from Tel Aviv University.
26:22Yossi Yovell is a bat biologist from Tel Aviv University.
26:28Bats are probably one of the most vocal and most social mammals on Earth.
26:33Since the moment we're here, they haven't shut up for a second.
26:37What exactly is the purpose?
26:39Maybe we can say something about what exactly they're saying.
26:43To understand how difficult a quest this is, watch what happens when Yossi's team records wild bats.
26:52So this is a very sensitive ultrasonic microphone.
26:56Here on the screen, you can see the vocalizations already in real time.
27:02Trouble is, there's just too much noise.
27:06Looking at this screen like this and trying to interpret what you see would be just like standing, you know,
27:12in the middle of a crowd of 500 people shouting at each other.
27:18So back at the lab, Yossi's team has created a tightly controlled mini bat colony.
27:27Welcome to my bat cave.
27:31This is a male.
27:33As you can see, bats are extremely cute.
27:37Some people will describe them as small puppies or small flying dog.
27:45So this is our control environment.
27:47If the cave we visited was like a stadium full of thousands of individuals,
27:51this is like your living room with a few friends and I can put a camera there and monitor the
27:57full situation.
28:01I put them on this wall and they'll probably fly to the dark.
28:03But placing bats in a controlled environment is just the first step.
28:07To crack the code of bats, or any animal for that matter, requires making a connection between action and sound.
28:16And that, as it turns out, is a real pain in the you-know-what.
28:22Unfortunately, the only way to go about it is to go over a million hours of videos and just annotate.
28:28First, the action. What are the bats doing?
28:31Generally, they're annoying. They're really squabbling, kinda. No personal space.
28:37Because bats live in close quarters, they fight a lot.
28:41So making a database of what's the fuss about is key.
28:45This is a fight over food, basically.
28:48So the first bat is holding a food item in its mouth, and the second bat is coming to try
28:53and steal it.
28:54In this case, I would enter a context which is fighting over food.
28:59We see a female protesting a mating attempt by a male, and it's a failed mating attempt.
29:05So in this case, they're sleeping, one bat wakes up, he shifts a bit, and he annoys the other bat
29:12by him.
29:13It's a painstaking process.
29:15But one by one, Yossi's team creates a database of over 100,000 bat spats.
29:21We did this for several months, around the clock, not missing a single vocalization.
29:28When you listen to these vocalizations, they all sound the same.
29:32But that's because you have a human brain and not a bat brain.
29:35So they turned to the next best thing, a brain of the silicon variety.
29:41We fed this huge data set into a machine learning classifier.
29:45And if there are differences, the computer algorithm will learn these differences.
29:51That is, if there is, in fact, any connection between the sounds the bats are making,
29:56and what they're talking about, the computer will find it.
30:00And after months of work...
30:04We have essentially built a simple bat translator.
30:08One that can translate four different bat calls, even ones it hasn't heard before.
30:15This one is a fight over food.
30:19This one is a female saying something like,
30:22Not tonight, big fella.
30:25And this one, trying to sleep over here. Knock it off.
30:29You can now take a new vocalization, a vocalization that I've just now recorded, for example, in my colony.
30:37You can feed it into this algorithm and the classifier now will tell you what was the argument about without
30:44observing it.
30:48It's fantastic. This is Dr. Doolittle's dream, you know, come true.
30:52When you've cracked the system and you can tell that these calls have these very distinct meanings.
30:57And though they've only decoded a few bat calls, it's a start.
31:06Is it possible other animals are communicating something bigger?
31:11Much bigger.
31:30I think everybody is used to hearing these beautiful, melodic, lovely songs from humpback whales.
31:35But it's not always nice to listen to.
31:38When anyone asks me how pretty their songs are, I'm like, ha ha.
31:48Ellen Garland is a humpback whale expert from the University of St. Andrews.
31:53I've always loved being by the sea and on the sea.
31:57Apparently when I was six years old, I declared that I was going to be working with whales.
32:03Whales, like bats, are vocal learners.
32:06And their songs are among the most complex forms of animal communication.
32:11A single song typically is anywhere from five minutes to half an hour just for one song.
32:19So these guys sing for hours and hours on end.
32:23Like human music, whale songs consist of repeated phrases and themes made up of individual units.
32:32On average, it's about 34 to probably 36 different sound types that we recognise within the humpback song repertoire.
32:42And we name them how they sound.
32:44So moans, groans, grunts, whoops.
32:48So we call that a trumpet.
32:50We have a lot of low frequency, very grunty sound.
32:55And sort of a sending shrieks.
32:57So yeek!
33:07I feel like that one is definitely going to come back to haunt me.
33:12Which begs the question, why?
33:14Why are whales making such complex songs?
33:21One clue might be that only the males do the singing.
33:25A humpback song is really an acoustic peacock tale.
33:28It's extremely showy and complex.
33:31They're obviously communicating with each other.
33:34You sort of want to understand why they're doing that, what they're trying to say.
33:38To find out, Ellen embarked on the world's first mapping mission of whale song.
33:46I was to analyse song across the South Pacific region to try and understand what the songs were in multiple
33:53populations through multiple years.
33:57Across the South Pacific, there are tens of thousands of whales living in separate groups.
34:02Until Ellen came along, no one had ever compared their songs.
34:07There were so many songs, I couldn't keep them straight in my head, so I started to draw them.
34:12And then from there, I could actually lay them down on the floor by population, by year.
34:18Next, she colour-coded the songs.
34:21You can absolutely tell the difference between these song types because they have lots of different sounds in them and
34:27it's the particular arrangement of these sounds.
34:29So this is the blue song type.
34:40Now, if we listen to the Dark Red song.
34:51As you can see, this is completely different.
34:55Scientists thought that, at any given moment, each group only sang its own tune.
35:00Well, we thought for a long time that all the males in an area sing the same song, but that
35:05it's different when you go to different areas.
35:06It's different in whatever Hawaii from Tahiti.
35:10So we expected to find that all the songs within a year would be the same.
35:16So I started analysing and I started with the easterly population of French Polynesia.
35:21And there was some interesting irregularities in there, shall we say.
35:26And I was like, hmm, this seems strange.
35:28Strange, because in French Polynesia in 2006, not all the males were singing the same song.
35:35Sometimes the whales were singing the red song.
35:40Sometimes the blue.
35:45And then I went to the next population over, the Cook Islands.
35:48And then I got to Tonga.
35:49And then I got to New Caledonia.
35:51And of course, finally to East Australia.
35:54There was sort of a disconnect.
35:56The same songs kept turning up, but in different places.
36:00I talked with other researchers and they were like, wow, I've seen that song type.
36:04What is it doing over there in that year?
36:08What was going on?
36:09It wasn't until Ellen mapped everything out over time that a picture began to emerge.
36:17Consider the blue song.
36:19In 2002, it enters the charts in East Australia.
36:23In 2003, it's all the rage in Tonga.
36:272004, it's a hit in Samoa.
36:29And by 2005, it's number one in the Cook Islands.
36:34Meanwhile, back in East Australia, those trendsetters had picked up a brand new tune.
36:41All of the males threw their current blue song out the window and started singing this dark red song type.
36:47And then once they were singing it, it was then passed to the next population over, which is New Caledonia.
36:52And all those males learnt this brand new song type.
36:55And again and again across the South Pacific.
36:57So to Tonga, American Samoa, the Cook Islands, and finally to French Polynesia.
37:02It's almost a game of telephone across the South Pacific.
37:06It was kind of like Beatlemania when the British invasion came over and transformed American music.
37:13And this didn't just happen once.
37:15As Ellen dug deeper, she found that this same thing happened year after year.
37:22And that was the really big eureka moment.
37:25The fact that we see repertoires of song shifting from one population to another across the Pacific and humpback whales
37:34shows that humpback whales have cultural transmission.
37:39That's a big deal because culture was once thought to be uniquely human.
37:47No one knows how these songs start, but why would male whales put so much effort into switching them?
37:54We think that it's something to do with novelty.
37:57A novel song makes you stand out against the background of singers around you.
38:02You want to be able to stand out to that female and maybe you'll get more matings.
38:06But are they just sexy tunes? Could there be any lyrics?
38:12So, exact content in them, what their message is, that's still unknown.
38:19Could we ever know if any information is being exchanged?
38:28It's the same problem faced by scientists at SETI, who listen to signals from space, hoping to find signs of
38:35intelligent life.
38:37SETI's really interested in knowing whether or not there are other beings in the universe that are intelligent.
38:42And one of the ways to do that is to quantify and understand communication.
38:47So why not start by trying to decode the alien tongues right here on Earth?
38:52Looking at the stars and saying, are we alone, I don't think is as useful as looking at the millions
38:58of other communication systems that are non-human on Earth.
39:01And studying them so that if and when the extraterrestrial signal is received, we'll have a feel for non-human
39:09communication.
39:10Easier said than done.
39:12We're faced with a big problem, which is we don't have any idea what the meanings of the sounds are.
39:17So we can't translate them, we've got no Rosetta Stone, we can't say this sound means fish and that means
39:23dog.
39:29Think about it for a second.
39:31Imagine you were an alien, peering down on Earth, trying to decipher what these odd creatures had to say.
39:41How would you know what to listen to?
39:45This music stuff?
39:48Laughter?
39:52Crying?
39:54When you think about it, we humans are making lots of noise.
40:03And only a fraction of it contains information we call language.
40:08How would you be able to pick out the right parts?
40:12Well, this is where the math comes in.
40:15We're really looking for a statistical fingerprint for language.
40:20Is there something about the way that the sounds have been put together into a sequence that is characteristic of
40:26language?
40:27Consider hours for a moment.
40:30In 1945, linguist George Ziff asked his students to plot out the frequency of each of the 264,430 words
40:39used in James Joyce's Ulysses.
40:42He drew a straight line through it and it had a 45 degree minus one slope.
40:47Oddly, the most frequent word occurred exactly twice as often as the second most frequent word.
40:55Three times as often as the third most frequent word.
40:59And so on down the line.
41:01In the logarithmic scale that mathematicians use, it looks like this.
41:05So he thought, that's interesting. What if I take another book?
41:09Darwin's Origin of Species.
41:11Same thing.
41:12What if I take Chinese book?
41:15Same thing.
41:16Turns out, every human language on the planet follows this rule.
41:21From Swahili to Arabic to Eskimo.
41:24It's called Ziff's Law.
41:27It's suggested that the structure of language is fundamentally the same across different languages.
41:32So what about animals?
41:34Brenda McGowan at UC Davis and Lawrence Doyle at SETI.
41:39Yes, the search for extraterrestrial intelligence wanted to find out.
41:44So they decided to analyze one of the most intelligent animals we know.
41:49Dolphins.
41:51They communicate with an elaborate repertoire of whistles.
41:55By categorizing whistles into what we would call words, if you will.
41:58I mean, and I don't mean that literally, but the idea is to categorize signals into types.
42:04Brenda McGowan had collected a bunch of signals and gotten their frequency of occurrence.
42:09And one morning I got up and decided, well, I wonder if this obeys Ziff's Law.
42:14And wouldn't you know?
42:15It obeyed Ziff's Law.
42:17So I went and had a cup of tea.
42:19And then I went back and did it again.
42:22And it obeys Ziff's Law.
42:24I was pretty excited because, I mean, it could have been anything.
42:27I mean, what's the probability that you're going to find something that's a negative one slope in another species?
42:33Um, is, is, you know, not only exciting, but seems highly improbable.
42:39Some of those moments in science where you're going, wait a second.
42:44Dolphins have a communication system with potential complexity as complex as humans.
42:49It doesn't measure meaning, but it does measure what they could be saying.
42:55It doesn't necessarily mean that dolphins have language.
42:58It just means that they may have a complex communication system that functions like language.
43:05Which brings us to the question, do any animals have language?
43:11People have set up language as being really the only remaining trait that separates us from all other animals.
43:19The trouble is that language cannot be simply binary.
43:22It cannot be the case that we have language and no one else has even a part of a language.
43:28That goes against everything we know about how evolution works.
43:31So there must be a spectrum of linguistic ability among animals.
43:36And in fact, all the research today is telling us how much we share with animals.
43:42But a huge mystery remains.
43:45Where does language come from?
43:48Unlike our other features, like opposable thumbs or walking upright, there are no fossils for speech.
43:55The only way to answer this question is to dive deep into the biology, into our brains, our cells, and
44:02the very genes that make up you and me and every creature on earth.
44:07Could it be that we're not as special as we think?
44:14Many people have been assuming that we're much more different than animals when it comes to language.
44:21When we start to realize the similarities, then we start to learn how we could get at this mystery of
44:27where language came from.
44:28This is the question that drives Eric Jarvis at Rockefeller University.
44:34A formally trained dancer from the Bronx, he's long been fascinated by language.
44:39I felt like being trained as a dancer trained me to become a scientist because both require a lot of
44:44discipline, hard work, creativity, lots of failure before you get success.
44:50And in the past 29 years, Eric has had a lot of success.
44:55But the path to get there was not easy.
45:01I guess my story begins being born here in New York City.
45:04We had what one might consider a broken family.
45:07My father, he eventually became homeless, and he was later killed by a gang who were killing homeless people.
45:13So I grew up with a single mother. We were not a wealthy family.
45:18Culturally, we were wealthy.
45:20I followed my mother's wisdom of trying to do something that has a positive impact on society.
45:24So I decided I'm going to become a scientist.
45:29I had to learn that it is more difficult for me because I didn't have much to compare to.
45:35There wasn't anybody in my family, anybody in my friend circle, anybody in my neighborhood that I knew was a
45:41scientist.
45:42Nonetheless, Eric forged ahead, delving for answers about the origin of language in the brains of songbirds.
45:50This mystery of where language came from 10 years ago, we had very little clue.
45:55But now we're at the point where we're starting to understand how language brain pathways evolved and the underlying genes
46:03that control it.
46:06Little did he know, a huge clue would come from a single family.
46:12When we first heard about the family, it was the first time that anybody had found any genetic change that
46:19causes something specific for speech.
46:21Three generations of the Kearney family had difficulty speaking.
46:26Analysis of the family's DNA led to a gene called FOXP2.
46:31Humans with a mutation in the FOXP2 gene, who are otherwise normal, have trouble making complex sounds.
46:40And they can do ca, ca, ca, ca, ca, but they have trouble producing complex syllables, like condition.
46:49Songbirds also have the FOXP2 gene.
46:52And when Eric inserted the same mutation into them, they too had trouble.
46:57Then the birds can't imitate properly, just like in humans.
47:00Even though we're separated by 300 million years from a common ancestor, a gene became used for a similar purpose
47:06in humans and vocal learning birds.
47:08Turns out, all animals have a FOXP2 gene, but it was assumed that it only affected communication in vocal learners.
47:18But if this were true, why would all animals have the gene?
47:22Eric wondered if its effect on communication could be more profound.
47:28So, he decided to try the same experiment in a species that doesn't learn its vocalizations.
47:35Mice.
47:36They don't just squeak.
47:38They sing.
47:39When pitched down to the human hearing range, actually sound like songbird songs.
47:44It's amazing.
47:47And like many songbirds, the males seem to impress the ladies.
47:52Usually when you put female with the male, he produces these complex, very modulated syllables.
47:58We call them the sexy songs.
47:59But unlike songbirds, mice are born knowing their songs.
48:04Our assumption was that mice are vocal non-learners, so putting this human mutation that causes a speech deficit shouldn't
48:10do anything to their vocal behavior.
48:13If the FOXP2 mutation does affect mice, that would mean the roots of human language spread well beyond a handful
48:21of vocal learners.
48:22So, above the cage here is a microphone that detects in the ultrasonic range.
48:30To find out, you need to take twin mice like these, identical in every way except the mutation.
48:38First, the normal mouse.
48:42I'm going to go ahead and put him in the cage now and see how it responds to this female.
48:46And I'm going to expect, since he doesn't have the mutation, that he's going to produce more complex songs to
48:52her.
48:53So here we go.
49:01There we go.
49:02So that's a complex syllable type.
49:03There we go.
49:04You see?
49:05So like we have these pitch jumps here from here to here, here to here.
49:08And then these long syllables like this, followed by a short one.
49:11This is what a normal animal should be singing.
49:16Now for his brother, the mouse carrying the same mutant version of the gene that affects speech in humans and
49:22songbirds.
49:24Okay, so now I'm going to take his brother, who has the FOXP2 mutation, and I'm going to put him
49:29in the cage.
49:30So our question is, will his mutation affect his ability to produce song, and if so, how?
49:38Ah, here he goes.
49:40Here he goes.
49:41These are more simple syllables.
49:47Simple.
49:48Here we go.
49:51He's singing.
49:53So this guy, he's behaving normally, but he doesn't seem to want to produce these more complex sequences, as we've
50:00seen in his brother.
50:02This female, she's like, eh.
50:09So what you see here is sonograms of the sounds that these mice are producing, and what kind of almost
50:15looks obvious here, this is the complex song that the wild-type mice sing to a female.
50:24You take the FOXP2 mice out of the mutation, instead of doing this, they do this, this simple song, where
50:31they have these simple syllables, not the same as what you're seeing in the wild-type mice.
50:39So I'm actually even struck more about the stark contrast that I'm seeing in these two brothers, one that doesn't
50:45have the mutation and one that does.
50:47Everything else about them is the same.
50:51What it means, according to Eric, is that the roots of human language run deeper than we previously thought.
50:59Even in a species that's born knowing its vocal repertoire, FOXP2 appears to affect the ability to make complex sounds.
51:09And it suggests that it's not a black or white world of the haves and the have-nots. It's a
51:15continuum. And it brings us closer to these other animals in our abilities, in our cognition, in our speech.
51:22I'm not saying we're the same. Mice and humans aren't the same. We're more advanced, but we're closer than what
51:28people realize.
51:35Language is like the last barrier that we seem to hold as being truly unique. So we really have to
51:41sort of change our way of thinking about what I would call a continuum between other animals and humans.
51:46If we only think about human language, and we're only focusing on what might be shared between human language and
51:53communication and other species, we could be missing so much of what other species do.
51:59I think we've discovered enough and had enough surprises to be absolutely sure that we've just scratched the surface, and
52:06that there's an amazingly complex and wonderful world to explore, which should keep generations of biologists and psychologists busy into
52:13the future.
52:57We'll see you next time.
53:09We'll see you next time.
53:40We'll see you next time.
54:02We'll see you next time.
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