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I'm Manouche Zamorote.

0:55

This is music

0:57

from German composer

1:00

George Philip Telemann.

1:02

Telemann is the

1:04

most prolific Baroque

1:07

composer. He wrote

1:09

more than 3,000

1:11

compositions and in

1:13

the 1700s he

1:16

was incredibly popular.

1:18

But eventually, Baroque music went

1:20

out of style. And

1:22

many of Telemann's scores

1:24

sat collecting dust in

1:26

Germany. Forgotten. Including this

1:28

concerto. And this was

1:30

a piece that had just

1:32

simply existed only one manuscript

1:34

and no one had really

1:37

seen before. This is Gregory

1:39

Hayworth. He's a professor at

1:41

the University of Rochester and

1:43

calls himself a textual scientist.

1:45

will explain what he means

1:47

in a minute. But for

1:49

the last two decades, Gregory

1:51

has been hunting down and

1:53

translating lost manuscripts all over

1:55

the world, including at a

1:57

library in Dresden where many

1:59

of Telemon's works were archived

2:01

alongside a treasure trove of

2:04

other manuscripts. All of them

2:06

badly damaged in World War

2:08

II. Yes, at the end

2:10

of the war, both the

2:12

British and the Americans had

2:14

bombed Dresden, as we all

2:17

know. The manuscripts, which had

2:19

been in the King's Library

2:21

at the time, had been

2:23

stored in an underground room

2:25

near the river, the Elba.

2:27

And with one of the

2:29

bombings, the side of the

2:32

river broke and it flooded

2:34

this underground room. And many

2:36

of the manuscripts lay in

2:38

water for about two weeks.

2:40

And of course there was

2:42

chaos. And then conservatives from

2:44

Berlin came and they dried

2:47

the manuscripts out. So these

2:49

manuscripts went through a lot.

2:51

And when the war ended,

2:53

things didn't get that much

2:55

better. Dresden became part of

2:57

the Eastern Block. And the

3:00

kind of restoration that was

3:02

available to them was limited.

3:04

And so they remained wasting

3:06

away and illegible until 2009.

3:08

That's when Gregory went to

3:10

Dresden to try out a

3:12

new scanning technology. He spent

3:15

the next few years rescuing

3:17

all kinds of documents there,

3:19

including that Telemon Concerto. It

3:21

was one of those badly

3:23

damaged items that the music

3:25

curator knew about and said,

3:27

hey, have a look at

3:30

this. The score was stained

3:32

by mold, the notes nearly

3:34

impossible to read, and for

3:36

two years Gregory and his

3:38

team worked on it. And

3:40

we managed to recover most

3:43

of what was gone. This

3:46

is a 2017 recording of the

3:48

concerto. The first time it was

3:50

performed in hundreds of years. Yes.

3:52

Do you remember listening to the

3:54

concerto? And like, I mean, it's

3:57

like you resuscitated something. that was

3:59

truly dead and buried, and then

4:01

you could hear it come alive.

4:03

Well, what's fascinating about this particular

4:05

piece is that many of the

4:08

objects that we image are esoteric

4:10

there in languages that people don't

4:12

speak anymore, and the public

4:14

has a hard time relating

4:17

to them. But by far

4:19

the most compelling is music,

4:21

because it communicates to the

4:23

general public on an emotional

4:25

level. And so that's really

4:28

exciting to be able to

4:30

take an object from total

4:32

invisibility to sharing with the

4:34

public. And so the moment

4:36

of actually hearing and recovering

4:39

an object is really into

4:41

it. A musical masterpiece revealed.

4:43

Those notes on the page

4:45

would have remained illegible smudges,

4:48

but the right person and

4:50

the right technology came along

4:52

to interpret them. Which brings

4:54

us to our show today.

4:56

found in translation. Ideas about

4:59

making sense of data, biology,

5:01

and language that can change

5:03

the way we understand entire

5:05

economies, diseases, and human interaction.

5:07

So back to Gregory Hayworth.

5:10

His evolution from medieval scholar

5:12

to so-called textual scientists began

5:14

20 years ago when he

5:16

was just a reader of

5:19

texts. What an unsatisfying word

5:21

reader is. Here's Gregory Hayworth

5:23

on the TED stage. For

5:25

me, it counters up images

5:27

of passivity, of someone sitting

5:30

idly in an armchair, waiting

5:32

for knowledge to come to

5:34

him in a neat little

5:36

parcel. How much better to

5:39

be a participant in the

5:41

past? An adventurer in an

5:43

undiscovered country searching for the

5:45

hidden text. I read and

5:47

taught the same classics that

5:50

people had been reading and

5:52

teaching for hundreds of years.

5:54

And with every scholarly article

5:56

that I published, I added

5:58

to human knowledge diminishing slivers

6:01

of insight. What I wanted

6:03

to be was an archaeologist

6:05

of the past, a discoverer of

6:07

literature, an Indiana Jones without the

6:09

whip, or actually with the whip.

6:12

And so I changed the direction

6:14

of my career. Gregory

6:16

changed the direction of his

6:18

career all because of one

6:21

manuscript. In the early 2000s,

6:23

he was working in that

6:25

same Dresden library studying a

6:28

medieval manuscript that was in

6:30

bad shape to begin with,

6:32

made even worse by the Cold

6:34

War. And it was called Lizzishidamu,

6:37

the Chess of Love, and it

6:39

is perhaps the last major... long

6:41

poem of the European Middle

6:43

Ages that has never been,

6:45

well, it's never been transcribed

6:48

and it's never been edited.

6:50

When you first saw the

6:52

manuscript, the poem, what did it

6:54

look like? Well, because it had been

6:56

in water, it looked like a series

6:59

of huge inkblots, and what the

7:01

Soviets had done was they

7:03

had decided to clean up

7:05

the extra ink, and they did

7:07

it using a technique that was...

7:09

popular among the Soviets at that

7:12

time, they used urea, which is

7:14

basically made from urine. P? Yes.

7:16

And it's acidic, and it actually

7:18

is quite effective, but in so

7:20

doing it had two effects. First

7:23

of all, it removed ink, but

7:25

it also removed ink from the

7:27

text, so much of it was

7:29

so faded that you couldn't see

7:31

it. although all the inkblots were

7:34

now largely gone. The second thing

7:36

they did is it caused in

7:38

many places the parchment, which of

7:40

course is animal skin, to

7:42

turn translucent, a kind

7:45

of gray translucent quality,

7:48

which is typical of

7:50

urea. And that really

7:52

damaged and destroyed some last

7:54

of it. But I managed to

7:56

transcribe, oh maybe a few

7:58

thousand lines. and a lot of

8:00

effort. And then I ended up

8:03

not being able to go any

8:05

further. And so I went online

8:07

to try to figure out what

8:09

technological means I could use to

8:11

improve the reading. And there

8:13

I learned about how

8:15

multi-spectral imaging had been

8:17

used to recover two

8:19

lost treatises of the

8:22

famed Greek mathematician Archimedes.

8:24

I decided to write to

8:26

the lead imaging scientist, Professor

8:28

Roger Easton. To my surprise,

8:30

he actually wrote back. With his

8:33

help, I was able

8:35

to build a transportable

8:37

multispectral imaging lab. And with

8:40

this lab, I transformed what

8:42

was a charred and faded

8:44

mess into a new medieval

8:46

classic. The

8:49

idea behind multi-spectral imaging is

8:51

something that anyone who's familiar

8:53

with infrared night vision goggles

8:55

will immediately appreciate, that what

8:57

we can see in the

9:00

visible spectrum of light is only a

9:02

tiny fraction of what's actually there.

9:04

The same is true with invisible writing.

9:06

Our system uses 12 wavelengths

9:08

of light between the ultraviolet

9:10

and the infrared. and these

9:12

are shown down onto the

9:14

manuscript from above from banks

9:17

of LEDs, and another multi-spectral

9:19

light source which comes up

9:21

through the individual leaves the

9:23

manuscript. So multi-spectral imaging means

9:25

shining different wavelengths of

9:28

light onto a manuscript

9:30

and taking numerous photographs

9:32

with a very special

9:34

lens. And by taking separate photographs...

9:36

of the same object in multiple

9:38

wavelengths we can reveal or are

9:40

able to see things that the

9:43

naked eye can't see. Computers then

9:45

help refine the photos. You

9:47

know statistical algorithms which help

9:49

enhance the images and starting

9:51

with that we work with

9:53

scholars to try to decipher

9:55

and transcribe the manuscript so

9:57

that we can understand them

9:59

better. Gregory and

10:01

his team have used this

10:03

technology to restore everything from

10:06

biblical Gospels to maps from

10:08

the 1400s. And what they

10:10

discover often helps historians understand

10:12

what the writers were thinking

10:15

at the time. So spectral

10:17

imaging can recover lost texts.

10:19

More subtly, though, it can

10:21

recover a second story behind

10:23

every object, the story of

10:26

how, when, and by whom

10:28

a text was created, and

10:30

sometimes what the author was

10:32

thinking at the time he

10:34

wrote. Take, for example, a

10:37

draft of the Declaration of

10:39

Independence written in Thomas Jefferson's

10:41

own hand, which some colleagues

10:43

of mine imaged a few

10:46

years ago at the Library

10:48

of Congress. Curators had noticed

10:50

that one word throughout had

10:52

been scratched out and overwritten.

10:54

The word overwritten was citizens.

10:57

Perhaps you can guess what

10:59

the word underneath was. Subjects.

11:01

There, ladies and gentlemen, is

11:03

American democracy evolving under the

11:05

hand of Thomas Jefferson. Through

11:08

this lens, we witnessed the

11:10

mistakes, the changes of mind,

11:12

the naivetes, the uncensored thoughts,

11:14

the imperfections of the human

11:17

imagination that allow these hallowed

11:19

objects and their authors to

11:21

become more real, that make

11:23

history closer to us. I'm

11:28

a little embarrassed to admit,

11:30

Gregory, that the images that

11:32

are coming to mind for

11:35

me are Sherlock Holmes, an

11:37

invisible ink, and Nick Cage

11:39

in that movie National Treasure

11:41

trying to hunt down precious

11:43

manuscripts. I mean, it is

11:46

kind of as exciting as

11:48

that, right? Yeah, this is

11:50

a kind of, you know,

11:52

recovery of the past, which

11:54

has, I don't know, maybe

11:56

exaggerated or lurid elements of

11:59

recovery. But... It's something that

12:01

I hope will become much

12:03

more common as students begin

12:05

to learn textual science. It's

12:07

something that we need to

12:10

be able to do because

12:12

otherwise we're going to lose

12:14

forever parts of our past

12:16

in the next 50 years.

12:18

Several years ago I conducted

12:21

a survey of European research

12:23

libraries and discovered that at

12:25

the barest minimum there are

12:27

60,000 manuscripts pre- 1500 that

12:29

are illegible because of water

12:31

damage, fading, mold and chemical

12:34

reagents. Imagine worldwide how a

12:36

trove of hundreds of thousands

12:38

of previously unknown texts could

12:40

radically transform our knowledge the

12:42

past. Imagine what unknown

12:45

classics we would discover,

12:47

which would rewrite the

12:50

canons of literature, history,

12:52

philosophy, music. or

12:55

more provocatively, that could rewrite

12:57

our cultural identities, building new

13:00

bridges between people and culture.

13:02

In a minute, how this

13:04

technology can be used to

13:07

scan documents written now, too.

13:09

Today on the show, Found

13:11

in Translation, I'm Manush Zamorodi,

13:14

and you're listening to the

13:16

Ted Radio Hour from NPR.

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14:57

On the show today,

14:59

found in translation. We

15:01

were just talking to

15:03

textual scientist Gregory Hayworths.

15:05

He helped develop technology

15:08

that uses multi-spectral imaging

15:10

to recover manuscripts that

15:12

would otherwise be illegible.

15:14

And he's working on

15:17

more recent documents too,

15:19

including some written by

15:21

prisoners of war in

15:23

Syria. cloth with inscribed names

15:26

in Arabic. And they came

15:28

from an escapee of

15:30

the prisons of Bashar

15:32

al-Assad in Syria. These

15:35

prisoners had found themselves

15:37

in these horrific conditions, and they

15:40

wanted to record at the very

15:42

least a story of who had

15:44

been there. and they agreed that

15:47

if anyone got out, they would

15:49

make multiple lists of this and

15:52

they would be able to contact

15:54

people and tell them their mother,

15:56

their father, had been there. In

16:00

order to make these manuscripts,

16:02

they ripped pieces of linen

16:04

cloth from their shirts, and

16:06

they used chicken bones as

16:08

a stylus, an ink made

16:11

from a mixture of the

16:13

blood from their gums with the

16:15

rust from the bars. Oh my

16:17

gosh. And they inscribed names, and

16:19

then they rolled them up, and

16:22

they sewed them into their

16:24

hems. And one man escaped,

16:26

and he delivered these precious

16:28

lists. to the Holocaust Museum. So

16:30

did they actually take the list

16:33

then? Yes, so we image the

16:35

list and made it more legible

16:37

so that we could read some

16:39

of these names and have a

16:41

real record of them. And the

16:43

images now exist at the Holocaust

16:45

Museum as a testament to who

16:47

had been disappeared. So you are looking

16:50

at things that have been written

16:52

incredibly recently and can help us

16:54

make sense of what is going

16:56

on the world? right now. Yes,

16:58

in fact, many cultural heritage

17:00

objects from the last century

17:03

and a half, for example,

17:05

are in much worse shape

17:07

than objects from a thousand

17:09

years ago. One of the

17:11

things that we're particularly interested

17:14

in are modern objects that

17:16

have been censored by governments,

17:18

beginning with Nazi-censored documents, many

17:20

of them like postcards and

17:22

letters, from the camps. And

17:25

that should, I hope, fill in

17:27

gaps. which otherwise we would never

17:29

be able to know. So we're

17:31

calling this episode found in translation

17:33

and it occurs to me

17:35

that we could use the

17:37

word translation. to describe your

17:39

work on numerous levels. I

17:41

mean there's the literal translation

17:43

from an ancient language to

17:45

languages we speak now. There's

17:47

the translating from what looks

17:49

like absolutely nothing on a

17:51

page to making sense of

17:53

it with the help of

17:55

this technology. There's the translating

17:57

it from the page to

18:00

are ears with the telemon concerto.

18:02

I wonder how you think

18:04

about it. Well, this particular

18:07

telemon piece, it was written

18:09

in the hand of Giovanni

18:11

Vivaldi, who was Antonio Vivaldi's

18:14

father. And Antonio Vivaldi had

18:16

wanted to hear this particular

18:19

concerto. And so he sent

18:21

his father to copy it.

18:24

So what we're hearing is.

18:26

Giovanni Vivaldi's interpretation of some

18:28

of the lines as well.

18:31

So manuscripts are objects that

18:33

evolve. We're used to books

18:35

in which the same text

18:37

is printed in all the

18:39

copies of that same book,

18:41

but a manuscript evolves and

18:43

changes because it's copied by

18:45

hand. One of the things that

18:47

multi-special imaging has taught us

18:50

is that our present is

18:52

changing our past in ways.

18:54

that will really reshape our

18:57

understanding of culture and the

18:59

transmission of that culture and

19:02

at its best, I hope,

19:04

bring people together and eliminate

19:07

or reduce misunderstandings from the

19:09

past. That's textual scientist

19:11

Gregory Hayworth, professor at

19:13

the University of Rochester

19:15

and founder of the

19:17

Lazarus Project. You can

19:20

find his full talk at

19:22

TED. And that 2017

19:24

performance of Telemann's

19:26

concerto was played

19:29

by students from

19:31

the Eastman School of

19:33

Music. Today on the

19:35

show, Found in Translation.

19:37

I'm sitting at the

19:40

edge and suddenly this

19:43

magnificent creature surfaces. And

19:45

I'm thinking, that's a

19:48

blue-white. Ralph Shammy was

19:50

on a boat in Mexico's

19:52

Gulf of California when he

19:54

saw his first whale up

19:57

close. And she's massive.

19:59

Massive! And she comes up

20:01

and to breathe and that breath

20:03

is like a train. She dies

20:06

and she comes up and she

20:08

blows all that air out. I

20:10

mean I had tears in my

20:12

eyes. I'm seeing this incredible mystery

20:15

unfolding in front of me thinking

20:17

where have I been all this

20:19

time? And life has never been

20:22

the same. Ralph

20:26

is an economist who

20:28

recently left the International

20:30

Monetary Fund after 25 years there.

20:33

And within the IMF, I worked

20:35

on all kinds of issues. I'm

20:37

an expert on fragile

20:39

states and conflict-affected countries.

20:42

It was a very stressful

20:44

job. What happened was, after

20:46

you work on fragile states

20:48

and you lead missions, these

20:50

are dangerous missions, really. And

20:53

you become fragile yourself.

20:56

So in 2017, he was on a

20:58

rare break. An old friend who

21:00

knew how much he loved the

21:02

ocean got him a spot on

21:05

an expedition studying whales. The researchers

21:07

told Ralph he had one job.

21:09

If you really want to help

21:12

Ralph, Ralph, clock when they were

21:14

reaching when it dives. At night,

21:16

the whole team would go ashore

21:18

to unwind. We'd all cook together,

21:20

and some of us would cooks

21:23

and less with clean. One night

21:25

Ralph joined a dinner table discussion

21:27

that stuck with him. And so

21:29

we're sitting around the table

21:31

and having conversations about the

21:33

whales. And I'm on my

21:35

third class of wine trying

21:37

to get into conversations. And

21:39

I overhear a conversation about

21:42

whale carbon. Whale carbon. The amount

21:44

of carbon dioxide that a whale

21:46

houses in its body away from

21:48

the atmosphere. They said, well, they

21:51

have tremendous amount of carbon.

21:54

Because whales eat massive

21:56

amounts of crill, which

21:58

themselves feed on fights.

22:00

interplankton, single cell plants.

22:02

Now why is phyto important?

22:05

Because phytoplankton is really where

22:07

the biological life of the

22:09

ocean starts. They capture about

22:11

33 gigatons of carbon dioxide

22:14

per year. That's equivalent to

22:16

the work of four Amazon forests. So

22:18

the whales eat krill, the krill

22:20

eats phyto. And then what does

22:22

the phyto need to survive? Well,

22:24

they need phosphorus, nitrogen, and iron.

22:26

And all three factors are in

22:28

the poop of the whale. So

22:30

it's a virtuous cycle. Whale

22:32

feeds on crill, crill feeds

22:34

on fight to fight to needs the poop

22:37

of the whale. So this whale is not

22:39

only grabbing carbonal on its

22:41

body, it's fertilizing the phyto.

22:43

So the whale is a

22:45

great ally in the fight

22:47

against climate change. You see?

22:49

It was the greatest story

22:51

never told. That's what I

22:53

kept saying to myself. So

22:57

you have this wonderful cycle.

22:59

Here's Ralph Shammy on the TED

23:02

stage. The whale feeds on the krill,

23:04

the krill feeds on the phyto,

23:06

and the phyto needs the poop

23:08

of the whale to get more

23:10

active. And when the phyto gets

23:12

more active, it grabs more carbon

23:15

dioxide from the atmosphere.

23:17

Now that's good news, right? Yeah. Except

23:19

that whales are dying. They're

23:21

dying from ship strikes. They're

23:24

dying from pollution.

23:26

than dying from

23:28

entanglements. In fact, they're

23:30

dying because our current

23:33

economic system puts

23:35

a zero value on a

23:37

living wage. But chop a whale,

23:40

sell it for its meat, it

23:42

acquires a value. The value

23:44

of a living whale is

23:46

zero. Zero. Zero dollars. Zero

23:49

in any currency. I'm

23:51

a financial economist.

23:54

And I'm listening to these scientists bemoaning

23:56

what's happening to the waves and I

23:58

wanted to help. I didn't know

24:00

how to help. And I thought,

24:03

wait a minute. Maybe I can

24:05

bring your message to the audiences

24:08

around the world. Maybe I can

24:10

translate all of that value, those

24:12

services they did do for us,

24:15

in a language that we can

24:17

all understand. It's the language of

24:19

dollars and cents. What was going

24:22

through your mind? I mean, it

24:24

sounds like your brain was kind

24:26

of set on fire in some

24:29

ways. Yes, right away my mind

24:31

went to value. value of the

24:34

carbon captured by a whale? Because,

24:36

you know, an economist, I work

24:38

on wages and people's earnings, and

24:41

I said, so, whale carbon, how

24:43

much would I be paying the

24:45

whale for fighting climate change? What

24:48

if I could value the services

24:50

of the whale? I was googling

24:53

and I found nothing on this

24:55

at all. I'm a financially communist,

24:57

so I'm looking at it from

25:00

a market valuation. And I knew

25:02

that a dead whale was worth

25:04

a lot of money in countries

25:07

where they still eat whale meat.

25:09

So that whale had a value,

25:12

40,000 to 80,000 depending on the

25:14

size of the whale, but a

25:16

living whale had no value. So

25:19

I'm thinking, well, how would I

25:21

go about doing it? After all,

25:23

the whale is a living system.

25:26

The whale captures carbon on her

25:28

body. And she gives birth to

25:30

baby whales who also grow up

25:33

to capture carbon on their body

25:35

and they give birth to whales

25:38

and so forth and indirectly through

25:40

the fertilization of phytos. So how

25:42

would you do something like this?

25:45

Well, I looked at it and

25:47

I said, wait a minute, this

25:49

looks like a share of stock

25:52

that pays dividends. Except those dividends

25:54

are live dividends. They give birth

25:57

to more dividends. So if I

25:59

were to track the whale over

26:01

her lifetime... and keep track of

26:04

all these dividends into the future,

26:06

and then multiply that by the

26:08

price of cars. and discount that

26:11

all the way to the present,

26:13

I can't figure out what is

26:16

the present value of the lifetime

26:18

earnings of a single whale. Would

26:20

you like to know how much?

26:23

At least three million dollars. At

26:25

least three million dollars. At least.

26:27

Now that's just an estimate because

26:30

for now there's no standardized way

26:32

for countries and companies to price

26:34

carbon. But Ralph says that needs

26:37

to happen ASAP because companies and

26:39

governments have made a lot of

26:42

promises to go carbon neutral and

26:44

pretty soon they'll need to deliver

26:46

on those promises. So voluntary carbon

26:49

markets, that's what we have right

26:51

now. Uh-huh. But in Europe, the

26:53

regulation is coming. around the idea

26:56

of interest, around the protection of

26:58

nature and its biodiversity, and dealing

27:01

with climate change. And it's no

27:03

longer the privy of just the

27:05

governments. The consumers are asking companies,

27:08

what is your footprint? Investors, I

27:10

mean, billionaires, I know some of

27:12

them, that are saying, now I

27:15

don't want my money to be

27:17

invested in extractive services. I don't

27:20

want to be linked to companies

27:22

that have a huge carbon footprint.

27:25

For the last six years, Ralph

27:27

has been working to envision a

27:30

new kind of marketplace, one that

27:32

doesn't extract from nature, but puts

27:34

a value on it. He calls

27:37

his solution science-based finance, and he's

27:39

not just applying it to whales,

27:41

but to elephants, wildebeast, seagrass. Right

27:43

now he's working with the Bahamas

27:46

on one pilot project. So they

27:48

mapped the sea floor of the

27:50

Bahamas and discovered that the Bahamas

27:53

is sitting on 30 percent. of

27:55

the total mass of sea grass

27:57

in the world. In the world?

28:00

Yeah, according to my... calculations and

28:02

my colleagues that is worth about

28:04

a hundred and fifty billion dollars.

28:06

So I am sitting on seagrass

28:09

and you Microsoft you need to

28:11

offset your carbon footprint you made

28:13

a commitment to go carbon negative

28:16

so here's what we do how

28:18

much carbon do you need and

28:20

Microsoft says well for this year

28:23

I need a hundred tons for

28:25

next year a hundred and fifty

28:27

I'll say okay I'll sell you

28:29

these from my seagrass you pay

28:32

me that money Because remember, in

28:34

order for the seagrass to do

28:36

its work, it has to stay

28:39

alive and well. Which means you

28:41

also have to look after the

28:43

sea turtles and the apex predator,

28:46

the tiger sharks, the tiger sharks,

28:48

the tiger sharks died, the sea

28:50

turtles would completely destroy the seagrass.

28:53

So when you're investing in seagrass,

28:55

you're impacting food security. When you're

28:57

investing in seagrass, you're looking after

28:59

the people, the communities. You're alleviating

29:02

poverty, you're creating employment, you're bringing

29:04

new businesses. So suddenly for Microsoft,

29:06

they can put on their website,

29:09

look, we are purchasing the carbon

29:11

of the seagrass, we're ensuring that

29:13

seagrass lives forever, we're investing in

29:16

nature and perpetuity by creating resilience

29:18

in nature, we create resilience in

29:20

the people. Not to be cynical,

29:22

though, Ralph, but who is going

29:25

to keep track of all this?

29:27

Who's going to make sure that

29:29

the people who say they're going

29:32

to grow more seagrass actually grow

29:34

it? Who's going to make sure

29:36

that the companies actually spend the

29:39

money to buy the carbon offsets

29:41

from the seagrass growers? How do

29:43

we keep track of all this?

29:45

Exactly. Who verifies the verifier? Who

29:48

certifies the certifier who's watching the

29:50

watch person? That's what you're asking.

29:52

I've worked on financial development for

29:55

30 years. Every nascent market is

29:57

subject to gold rush behavior, double

29:59

counting. counting, cheating, and for Pete's

30:02

sake, even mature markets, how many

30:04

times do we hear about all

30:06

kinds of insider trading on Wall

30:08

Street? So, especially nascent markets are

30:11

subject to these things, but if

30:13

the market is to take off,

30:15

we need to solve these issues.

30:18

Some of them, the market themselves

30:20

would solve, some of it would

30:22

need a policy, because I'm now

30:25

telling people conservation is not a

30:27

cost proposition. Conservation, now we've turned

30:29

it upside down, is a profit-making

30:31

proposition. Just think about it. What

30:34

this paradigm does, it turns it

30:36

upside down and says, no, you

30:38

are conserving what is now an

30:41

asset. And that asset has value.

30:43

It's producing cash rules for you.

30:45

So of course you need to

30:48

protect it. Part of me feels

30:50

very sad that we humans don't

30:52

know how to value nature in

30:54

and of itself, that we need

30:57

to translate it into monetary value.

30:59

Is money the only language we

31:01

really speak? You know, with this

31:04

calling, I've met so many people,

31:06

I remember being at the International

31:08

Labor Organization, and right before I

31:11

spoke a woman, she said to

31:13

me, I'm appalled that you're putting

31:15

the price on nature. And I

31:18

said, do you work for free?

31:20

And she said, no. I said,

31:22

why should the elephant work for

31:24

free? Yeah. Why do I allow

31:27

for myself what I would not

31:29

allow for nature? I find that

31:31

the epitome of arrogance, that humans

31:34

prefer to sing songs about nature

31:36

and write poetry as they watch

31:38

it die, taking its less breath

31:41

in front of us. You see,

31:43

if we were not in the

31:45

eleventh hour, if all people appreciated

31:47

nature for its intrinsic value, you

31:50

wouldn't be interviewing me. But we

31:52

are at a point in time

31:54

where despite our best efforts, nature

31:57

is dying as we speak as

31:59

we speak. And we're dying because

32:01

the language that we have chosen

32:04

for ourselves is the... language of

32:06

dollars and cents. Leave the tree

32:08

where it is and make money.

32:10

Leave the whale for itself and

32:13

make money. So I'm really not

32:15

about nature, I'm really about changing

32:17

people's behavior. You're like the lorax,

32:20

you speak for the trees. I

32:22

would love to. I would be

32:24

honored if I'm thought that way.

32:27

But I'm trying my best to

32:29

take what the scientists are saying

32:31

and translate it into the language

32:33

that we have chosen. If we

32:36

choose a different language, it's a

32:38

translation. Now all translations suffer, right?

32:40

But let's not wait till we

32:43

get it perfect. Because if we

32:45

want to make it perfect, there'll

32:47

be nothing left. That's economist Ralph

32:50

Shammy. He recently retired from the

32:52

International Monetary Fund after 25 years.

32:54

You can find him at Blue

32:56

Green future.org to see his full

32:59

talk. Go to Ted. on the

33:01

show today found in translation. I'm

33:03

Anish Zamorote and you're listening to

33:06

the Ted Radio Hour from NPR.

33:08

We'll be right back. This

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servicenow.com/AI dash agents. It's

35:23

the Ted Radio Hour from

35:25

NPR, I'm Anouche Zamorote, on

35:27

the show today, found in

35:29

translation. One thing we've all

35:31

gotten used to over the

35:33

past couple years is testing

35:35

ourselves at home for the

35:37

COVID virus, translating an infection

35:39

into a thin pink line

35:41

that tells us to stay

35:44

home or go about our

35:46

day. But let's say you

35:48

test negative and still have

35:50

a fever that just won't

35:52

go away. One day, you

35:54

might be able to take

35:56

another test at home, so

35:58

you could know immediately... if

36:00

you have a bacterial infection

36:02

and need antibiotics stat. Oh,

36:04

it would be amazing. It

36:06

would be amazing just to know

36:09

that at least as a patient

36:11

you don't need to go somewhere

36:13

and deliver your sample in a

36:15

place where you could get an

36:17

even worse infection. It's a long road

36:19

to making research in the

36:21

lab so user-friendly. And one

36:23

of the people leading the way is

36:26

this woman. My name is Fatima

36:28

Alsara Alatracti. I'm a researcher

36:30

within the intersection of molecular

36:33

biology, micro nanotechnology, and medicine.

36:35

I'm also a founder of

36:38

a company called Prediagnose, where

36:40

we create the sensors for

36:42

the detection of bacteria.

36:45

In the future, you may

36:47

have a version of Fatima's

36:49

invention in your own home.

36:51

For nearly a decade, she's

36:53

been using her expertise in

36:56

highly complex nanotechnology. to watch

36:58

and listen as bacteria cells

37:00

communicate. Yes, bacteria talk to

37:02

each other in their own

37:04

microbial language. Yeah, bacteria speak

37:07

to each other. They can

37:09

communicate, they send out

37:11

signals to these signals,

37:13

and they are able

37:16

to coordinate their activities

37:18

based on their communication.

37:20

But instead of words,

37:22

the tiniest organisms on

37:25

our planet communicate

37:27

with signaling

37:29

molecules. They're all

37:32

ways around. Whispering,

37:34

making secret plans,

37:36

building armies with

37:38

millions of soldiers.

37:40

And when they decide to attack,

37:42

they all attack at the same

37:45

time. Here's Fatima on the TED

37:47

stage. To coordinate all the functions

37:49

bacteria have, they have to be

37:52

able to organize, and they

37:54

do that just like us humans

37:56

by communicating. But instead of using

37:58

words, they use signaling... molecules

38:00

to communicate with each other. When

38:03

bacteria are few, the signaling molecules

38:05

just flow away, like the screams

38:07

of a man alone in the

38:09

desert. But when there are many

38:11

bacteria, the signaling molecules accumulate, and

38:13

the bacteria starts sensing that they're

38:16

not alone. They listen to each

38:18

other. In this way, they keep

38:20

track of how many they are,

38:22

and when they are many enough

38:24

to initiate a new action. And

38:27

when the signaling molecules have reached

38:29

a certain threshold, all the bacteria

38:32

sends at once that they need

38:34

to act with the same action.

38:37

So bacteria use different messages to

38:39

rally each other, to say, band

38:41

together or build a colony or

38:44

start a mutiny. They are really

38:46

smart. But we are trying to

38:48

decode what their conversations mean. Hmm.

38:51

So, okay, let's say that they

38:53

do decide to attack, that they've

38:55

been hanging out, they've been multiplying,

38:58

and now they're thinking, you know

39:00

what, we're bad, we're mean, we're

39:02

nasty bacteria, and we're going to

39:05

show off a little bit. How

39:07

would that work? Then they would

39:09

all at once start producing something

39:12

that that will be harmful for

39:14

for the host or for other

39:17

bacteria that they would like to

39:19

get rid of because they would

39:21

also Sometimes they they are really

39:24

dominating they would really like to

39:26

dominate the space they are in

39:28

and that would be Secreating something

39:31

that would kill the other bacteria

39:33

and this is where Fatima's sensor

39:35

comes in She uses it to

39:38

interpret these molecular conversations between bacterial

39:40

cells and possibly predict what they're

39:42

up to. In one trial, she

39:45

listened in on the signals they

39:47

were starting to send each other

39:49

and used those early whispers to

39:52

diagnose infections before they spread. I

39:54

followed 62 patients in an experiment

39:57

where I tested the patient samples

39:59

for one particular infection without knowing

40:01

the results of the traditional diagnostic

40:04

test. Now in bacterial diagnostics a

40:06

sample is smeared out on a

40:08

plate and if the bacteria grow

40:11

within five days the patient is

40:13

diagnosed as infected. When I finished

40:15

the study and I compared the

40:18

tool results to the traditional diagnostic

40:20

test and the validation test I

40:22

was shocked. It was far more

40:25

astonishing than I had ever anticipated.

40:29

My device cut bacterial conversations

40:31

in more than half of

40:33

the patient samples that were

40:35

diagnosed as negative by traditional

40:37

methods. In other words, more

40:39

than half of these patients

40:41

went home thinking they were

40:43

free from infection, although they

40:45

actually carried dangerous bacteria. Inside

40:47

these wrongly diagnosed patients, bacteria

40:49

were coordinating a synchronized attack.

40:51

They were whispering to each

40:53

other. What I call whispering

40:55

bacteria are bacteria that traditional

40:57

methods cannot diagnose. So far,

40:59

it's only the translation tool

41:01

that can catch those whispers.

41:03

I believe that the time

41:05

frame in which bacteria are

41:07

still whispering is a window

41:09

of opportunity for targeted treatment.

41:11

Together with doctors, I'm already

41:13

working on implementing this tool

41:15

in clinics to diagnose early

41:17

infections. Fatima,

41:21

I just read that in 2019,

41:24

7.7 million people died of bacterial

41:26

pathogens. I mean, that is over

41:28

13% of all global deaths that

41:30

year. And then you found that

41:32

using normal diagnosing methods, half of

41:35

the patients in the study went

41:37

home thinking that they were fine,

41:39

but actually carrying dangerous bacteria. So,

41:41

so if we can diagnose people

41:43

early... Would that change the way

41:45

that we treat them? Yes, so

41:48

one of the big questions was

41:50

if we are able to detect

41:52

that early what? it mean for

41:54

the patients? Do we then treat

41:56

with antibiotics when we are in

41:59

all other fashion not able to

42:01

see the bacteria? So when we're

42:03

not able to detect the bacteria

42:05

with our routine techniques, what do

42:07

we do then? Do we treat

42:10

them? Is it okay to treat

42:12

patients that early? What would happen

42:14

to the patients if we do

42:16

that? Would we develop resistance? All

42:18

sort of questions started popping up

42:20

just by the scenario of being

42:23

able to detect early. If we

42:25

understand their communication, maybe we're also

42:27

able to diagnose better, diagnose earlier,

42:29

and set in with alternative treatments

42:31

that enables us to use way

42:34

less antibiotics than we're doing today.

42:36

I wonder if you could just

42:38

describe to me what your vision

42:40

is for this technology, maybe five,

42:42

ten, twenty years from now. Our

42:45

vision is that in the short

42:47

term, the tools that we create

42:49

can be used at clinics. So

42:51

they can be operated by the

42:53

healthcare professionals. For example, when the

42:55

patients come in during initial screenings,

42:58

then they can use these tools

43:00

to quickly get an overview of

43:02

how the patient is doing. On

43:04

the long term, we hope that

43:06

it's possible for the patients to

43:09

administrate this themselves. We really hope

43:11

that if we can identify a

43:13

group of really problematic infections and

43:15

then work on a tool that

43:17

only can detect them, then we're

43:19

able to say, okay, if you

43:22

have a surgery, if you're susceptible,

43:24

then stay at home, measure at

43:26

home, and then the results will

43:28

go to your doctor. And then

43:30

your doctor can take action from

43:33

there, but at least you don't

43:35

need to get in somewhere and

43:37

be exposed to having an infection

43:39

from the hospital or from another

43:41

side where a lot of sick

43:44

people come in. And it all

43:46

starts with decoding the language of

43:48

bacteria. Exactly. If we are able

43:50

to understand them, then maybe we

43:52

are better treating them, better diagnosing

43:54

them. That's the whole concept. That's

43:57

why we do this basic research.

43:59

That was Inventor, Microbiologist, and Nanotechnologist

44:01

Fatima Auzara Alatractic. You can see

44:03

her full talk at TED. As

44:05

we come to the close of

44:08

our show found in translation, we

44:10

want to acknowledge that people usually

44:12

say lost in translation to refer

44:14

to all the nuances that get

44:16

missed when you try to express

44:18

yourself in a language not your

44:21

own. Because learning a new language

44:23

can be daunting. And even though

44:25

you can just download an app

44:27

these days to translate things for

44:29

you, Lydia Makova says there are

44:32

good reasons to keep learning new

44:34

languages. And it's actually not that

44:36

hard if you discover the method

44:38

that works best for you. Lydia

44:40

herself speaks nine languages. Here she

44:43

is on the TED stage in

44:45

2019. I love learning foreign languages.

44:47

In fact, I love it so

44:49

much that I like to learn

44:51

a new language every two years.

44:53

When people find it out about

44:56

me, they always ask me, how

44:58

do you do that? What's your

45:00

secret? And to be honest, for

45:02

many years, my answer would be,

45:04

I don't know, I simply love

45:07

learning languages. But people were never

45:09

happy with that answer. They wanted

45:11

to know why they are spending

45:13

years trying to learn even one

45:15

language, never achieving fluency. And here

45:17

I come, learning one language after

45:20

another. They wanted to know the

45:22

secret of polyglots, people who speak

45:24

a lot of languages. And that

45:26

made me wonder too, how do

45:28

actually other polyglots do it? What

45:31

do we have in common? And

45:33

what is it that enables us

45:35

to learn languages so much? much

45:37

faster than other people. I decided

45:39

to meet other people like me

45:42

and find it out. The best

45:44

place to meet a lot of

45:46

polyglots is an event where hundreds

45:48

of language lovers meet in one

45:50

place to practice their languages. There's

45:52

several of such polyglot events organized

45:55

all around the world, and so

45:57

I decided to go there and

45:59

ask polyglots about the methods that

46:01

they use. And so I met

46:03

Benny from Ireland, who told me

46:06

that his method is to start

46:08

speaking from day one. He learns

46:10

a few phrases from a travel

46:12

phrasebook and goes to meet native

46:14

speakers and starts having conversations with

46:17

them right away He doesn't mind

46:19

making even 200 mistakes a day

46:21

because that's how he learns based

46:23

on the feedback And the best

46:25

thing is he doesn't even need

46:27

to travel a lot today because

46:30

you can easily have conversations with

46:32

native speakers from the comfort of

46:34

your living room using websites I

46:36

also met polyglots who always start

46:38

by imitating sounds of the language

46:41

and others who always learn the

46:43

500 most frequent words of the

46:45

language, and yet others who always

46:47

start by reading about the grammar.

46:49

If I asked a hundred different

46:51

polyglots, I heard a hundred different

46:54

approaches to learning languages. Everybody seems

46:56

to have a unique way how

46:58

they learn a language, and yet

47:00

we all come to the same

47:02

result of speaking several languages fluently.

47:05

And as I was listening to

47:07

these polyglots, telling me about their

47:09

methods, it suddenly dawned on me.

47:11

The one thing we all have

47:13

in common is that we simply

47:16

found ways how to enjoy the

47:18

language learning process. All of these

47:20

polyglots were talking about language learning

47:22

as if it was great fun.

47:24

You should have seen their faces

47:26

when they were showing me their

47:29

colorful grammar charts and their carefully

47:31

handmade flashcards and their statistics about

47:33

learning vocabulary using apps or even

47:35

how they love to cook based

47:37

on recipes in a foreign language.

47:40

All of them use different methods,

47:42

but they always make sure it's

47:44

something that they personally enjoy. I

47:46

realize that this is actually how

47:48

island languages... myself. When I was

47:50

learning Spanish, I was bored with

47:53

the text in the textbook. I

47:55

wanted to read Harry Potter instead.

47:57

So I got the Spanish translation

47:59

of Harry Potter and started reading.

48:01

And sure enough, I didn't understand

48:04

almost anything at the beginning. But

48:06

I kept on reading because I

48:08

loved the book. And by the

48:10

end of the book, I was

48:12

able to follow it almost without

48:15

any problems. And the same thing

48:17

happened when I was learning German.

48:19

I decided to watch France, my

48:21

favorite sitcom in German. Monica, should

48:23

I stay the telephone up and

48:25

hold the flash away? At the

48:28

beginning it was all just gibberish.

48:30

I didn't know where one word

48:32

finished and another one started. But

48:34

I kept on watching every day

48:36

because it's friends, I can watch

48:39

it in any language, I love

48:41

it so much. And after the

48:43

second or third season, seriously the

48:45

dialogue started to make sense. And

48:47

we have no shortcut to learning

48:49

languages. We simply found ways how

48:52

to enjoy the process, how to

48:54

turn language learning from a boring

48:56

school subject into a pleasant activity

48:58

which you don't mind doing every

49:00

day. So meeting other polyglots helped

49:03

me realize that it is really

49:05

crucial to find enjoyment in the

49:07

process of learning languages, but also

49:09

that joy in itself is not

49:11

enough. If you want to achieve

49:14

fluency in a foreign language, you'll

49:16

also need to apply three more

49:18

principles. First of all, you'll need

49:20

effective methods. If you try to

49:22

memorize a list of words for

49:24

a test tomorrow, the words will

49:27

be stored in your short-term memory,

49:29

and you'll forget them after a

49:31

few days. If you, however, want

49:33

to keep works long-term, you need

49:35

to revise them in the course

49:38

of a few days repeatedly using

49:40

the so-called space repetition. We're all

49:42

very busy, and no one really

49:44

has time to learn a language

49:46

today. But we can create that

49:48

time if we just plan a

49:51

bit ahead. There are so many

49:53

things we can do without even

49:55

planning that extra time, such as

49:57

listening to podcasts on our way

49:59

to work or doing our household

50:02

chores. The important thing is to

50:04

create a plan in the learning.

50:06

I will listen to a YouTube

50:08

video while having breakfast. If you

50:10

create a system in your learning,

50:13

you don't need to find that

50:15

extra time because it will become

50:17

a part of your everyday life.

50:19

And finally, if you want to

50:21

learn a language fluently, you need

50:23

also a bit of patience. It's

50:26

not possible to learn a language

50:28

within two months. But it's definitely

50:30

possible to make a visible improvement

50:32

in two months, if you learn

50:34

in small chunks every day in

50:37

a way that you enjoy. And

50:39

there is nothing that motivates us

50:41

more than our own success. I

50:43

vividly remember the moment when I

50:45

understood the first joke in German

50:48

when watching France. I had more

50:50

and more of those moments of

50:52

understanding these little victories. And step

50:54

by step, I got to a

50:56

level where I could use the

50:58

language freely and fluently to express

51:01

anything. I can't get enough of

51:03

that feeling and that's why I

51:05

learned a language every two years.

51:07

Now some of you may be

51:09

thinking, that's all very nice to

51:12

enjoy language learning, but isn't the

51:14

real secret that you polyglots are

51:16

just super talented and most of

51:18

us aren't? Well there's one thing

51:20

I haven't told you about Benny.

51:22

Benny. had 11 years of Irish

51:25

Gaelic and 5 years of German

51:27

at school, couldn't speak them at

51:29

all when graduating. Up to the

51:31

age of 21, he thought he

51:33

didn't have the language gene, and

51:36

he could not speak another language.

51:38

Then he started to look for

51:40

his way of learning languages, and

51:42

today, Benny can easily have a

51:44

conversation in 10 languages. Does that

51:47

sound like a miracle? Well, I

51:49

see such miracles every single day.

51:51

So if you've also tried to

51:53

learn a language and you gave

51:55

up thinking it's too difficult or

51:57

you don't have the language talent.

52:00

give it another try. Maybe you're

52:02

also just one enjoyable

52:04

method away from learning

52:06

that language fluently. Maybe

52:08

you're just one method

52:11

away from becoming a

52:13

polyglot. That was translator and

52:15

polyglot Lydia Makova. You can

52:17

watch her full talk, The

52:19

Secrets of Learning a New

52:22

Language, at ted.com. Thank

52:24

you so much for listening

52:26

to our show this week

52:28

found in translation. This episode

52:30

was produced by Hirscha Nahata,

52:32

Andrea Gutierrez, Lane, Kaplan, Levinson,

52:35

and Fiona Guiren. It was

52:37

edited by Sanna's Meshkipur, and

52:39

me. Our production staff at

52:41

NPR also includes James Delahousi,

52:43

Rachel Faulkner-white, Matthew Cloutier, and

52:45

Katie Montelion. Beth Donovan is

52:48

our executive producer. Our audio

52:50

engineers were Patrick Murray, Josh

52:52

Neuel, Hannah Glovna. Trey Watson.

52:54

Our theme music was written

52:56

by Romteen Arablui. Our partners

52:59

at TED are Chris Anderson,

53:01

Colin Helms, Michelle Quint, Alejandro,

53:03

Salazar, and Daniela Balarazzo. I'm

53:06

Manouche Zamorote and you've been

53:08

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