0:00

I'm Kai Wright. On the next Notes from

0:02

America, climate change feels more present tense than

0:04

ever, and it is scary. But can you

0:07

see a light at the end of this burning

0:09

hot tunnel? How hope can be part of the

0:11

solution? Listen wherever you get your podcasts. Researchers

0:19

in Michigan used AI to recreate a

0:21

prehistoric land bridge, complete with

0:24

digital wildlife. She

0:26

described the caribou looked like they were

0:28

roller skating because it didn't exactly walk.

0:31

They say it's Thursday, January 25th. But

0:34

we know it's really Science Friday. I'm

0:42

Sci-fi producer Charles Bergquist. In

0:44

this episode, we'll see how archaeologists are

0:46

using AI to track the paths of

0:49

prehistoric caribou to see where

0:51

artifacts from ancient hunters might be located. But

0:54

first, a conversation about Indigenous art

0:57

and its intersection with spaceflight.

0:59

Here's Ira Flatow. The

1:03

patterns woven in textiles can

1:06

tell a powerful story, and

1:08

Sarah Rosalina knows this well. She's

1:10

a multidisciplinary artist who blends

1:13

ancient mediums and Indigenous knowledge

1:15

with data and new technology.

1:18

She's collaborated with NASA JPL, the

1:21

LA County Museum of Art Tech

1:23

Lab, and her work is currently

1:25

featured at the Columbus Museum of

1:28

Art in Columbus, Ohio, until February

1:30

4th. Sci-fi producer and

1:32

host of our podcast, Universe

1:34

of Art, Dee Peterschmidt sat

1:37

down with Rosalina to talk

1:39

about her collaborations with scientists,

1:41

space colonization, and how she

1:43

views technological advancements through an

1:45

Indigenous lens. Here's Dee.

1:47

When Sarah Rosalina thinks about the loom,

1:50

she thinks about computer programming. It's

1:52

an extension of your body being an algorithm.

1:54

Ada Lovelace, who wrote the first algorithm

1:57

design for a computer, said she'd been

1:59

inspired by the card loom developed in the 1800s,

2:01

which used a binary

2:03

punch card to mass produce intricate textile

2:05

designs. In that approach, blending

2:07

old mediums with new tech sums

2:09

up Rosalina's approach to her own art.

2:11

She's an assistant professor of art at

2:13

UC Santa Barbara based in LA, and

2:16

she's of Waraca descent, indigenous people native

2:18

to what is now parts of Mexico

2:20

and the southwestern United States. She

2:22

works in these old art forms, textiles

2:24

and pottery, but uses AI

2:27

and data visualization as part of the

2:29

creative process. It's a way

2:31

to process her feelings about how modern

2:33

society is progressing. We're at this

2:35

point of the technological frontier, and that's

2:37

actually terrifying for a lot of people,

2:39

especially for people from my background and

2:41

my Waraca background. We're living the

2:44

time of climate change, this possession, the

2:46

rise of AI. And I'm

2:48

always interested in anticipating future forms of

2:50

colonization because it's progress for some, but

2:52

it's not for all. Rosalina,

2:55

who's a fourth generation Waraca weaver,

2:57

was taught indigenous textile work in

2:59

part by her grandmother. It's

3:01

something that really made her feel

3:03

sane. I remember she

3:05

so always encouraged me to weave for mental health,

3:07

but it was also good for exercising your mind.

3:10

Rosalina later found herself in the Bay Area around the

3:12

time of the tech boom of the late aughts and

3:14

learned to code. And there was a

3:16

lot of interesting people that I met at that

3:18

time were very similar to me, a lot of

3:21

BIPOC people working in code, but at the same

3:23

time, tech startups really started to rise and displacing

3:25

a lot of the people that I used to

3:27

enjoy hanging out with. Frustrated, she moved

3:30

back to LA and rediscovered

3:32

her love for textile work. I saw

3:34

so many relationships between the code that

3:36

I was writing and actual designs that

3:39

I was weaving that they couldn't help

3:41

but intersect. It was very

3:43

much like an Aha moment. What

3:45

happens when we bring traditional craft

3:47

or indigenous techniques with emerging technology to

3:49

think about current issues that we are

3:52

facing. Digital technologies are always chasing after

3:54

ways that we could simulate our

3:56

reality, which also produces this way that

3:59

we could reinvigorate. The or reality.

4:01

And. Rosalina doesn't just reenvisioned reality

4:03

with herself. She. Up and collaborates

4:05

with scientists to make a right. It's

4:07

a big role as an artist to work

4:09

with scientists and engineers because we see the

4:11

world differently and there's a lot of value

4:13

on that. One of those collaboration

4:16

was with Nasa Jpl in Pasadena

4:18

and Rosalina learn that they had

4:20

a mutual interest play. The.

4:22

Space Agency was experimenting with simulated

4:24

Martian soil also called regolith to

4:26

potentially construct a livable human habitats

4:29

on the Red planet without having

4:31

to transport heavy building materials away

4:33

from earth. So. They were doing

4:35

a lot of research on regular

4:37

simulating played actually build some of

4:39

the first cel then set of

4:41

basically adobe which made me giggle

4:43

because again it's like how much

4:45

space colonization is depended on indigenous

4:47

knowledge even on another planet. Rosalina.

4:50

Also teaches coil pot construction at U C

4:52

Santa Barbara and indigenous method of making ceramics

4:55

that's one of the oldest in the world.

4:57

Coil. Pots look like what they sound

4:59

like coils of clay or layer on

5:01

top of each other until you get

5:03

your vessel as she wanted to update

5:05

that with a techie merson twist. With

5:07

the help of Nasa engineers, she was

5:09

able to make her own version of

5:11

Martian clay. They surf soil analyses from

5:13

two pills rovers like curiosity. She

5:16

muddled the vessels and the computer and

5:18

than treaty printed them using her Merson

5:20

Adobe. The. Resulting sculptures like

5:22

both futuristic an instance of ribbed

5:25

rest and just ceramics take a

5:27

few shapes. The. Mouth of a

5:29

black hole along cylinder that looks like

5:31

it's eating itself. A vaguely spherical shape

5:33

that appears as though it was crushed

5:35

by the forces of gravity. And

5:38

Rosalina passion for pottery even rubbed

5:40

off on Jpl Engineers. are

5:42

actually made a lot of friends

5:44

southern guy and she's surroundings at

5:46

the time which is also really

5:48

interesting to have marcin cartographers who

5:50

guiding the rover's suddenly be interested

5:53

in actually the chemical compounds last

5:55

eight and we would talk for

5:57

hours on and on making clay

5:59

signing native in Los

6:01

Angeles. Located just a few miles

6:03

away from JPL is the Mount Wilson Observatory,

6:06

which Rosalina has also partnered with. It was

6:08

an important observatory in the early 1900s. Edwin

6:11

Hubble used the telescope to prove that the

6:13

universe is expanding, but discoveries

6:16

like that couldn't have been made without

6:18

the help of female computers. Women who

6:20

analyzed the raw data from the telescope

6:22

and performed complex math that made those

6:24

discoveries possible. But when I

6:26

got there, I realized that female

6:28

computers were mostly cropped and edited

6:30

out of the history of that

6:32

observatory. Back then, the images from

6:34

the telescope were exposed onto glass plates,

6:37

which the female computers used to make their

6:39

calculations. And I found textile

6:41

was a unique way to approach it

6:43

because it is a feminist or a

6:45

female-based craft. So to shed

6:47

light on these women's work, Rosalina took those

6:49

plates and digitized them into a lower resolution

6:52

where each pixel would become a bead on

6:54

a tapestry, which she then assembled

6:56

by hand. But not all

6:59

of these tapestries are neat rectangles. Some

7:01

of them distort and fray as the

7:03

beads progress downwards, looking like a starry

7:06

cosmic jellyfish. Rosalina

7:08

hopes her art doesn't just serve as a

7:10

form of protest, but also provides an alternative

7:12

way of interpreting the world around us, one

7:15

that places a much larger

7:17

emphasis on indigenous knowledge. It

7:19

is very important because a lot of

7:21

the current crises that we're facing are

7:24

a crisis of humanity in many ways.

7:26

And I feel like artists really shine

7:28

that light and also can see the

7:30

world differently than what a scientist or

7:32

engineer does. And we can learn quite

7:34

a bit from one another. For

7:36

Science Friday, I'm Dee Petersmith. Thanks,

7:39

Dee. You can check out

7:41

photos of Rosalina's work at sciencefriday.com/textile

7:43

art. And like I said before,

7:46

her art is on view

7:48

at the Columbus Museum of

7:50

Art in Columbus, Ohio until

7:52

February 4th. There was

7:54

a time when people did not question

7:56

the authority of doctors, but HIV and

7:59

AIDS helped change that. People

8:01

were dying. Attention was demanding.

8:03

We literally had to convince

8:06

the government that there were women

8:08

getting HIV. It was hard to

8:10

fight and it was activists.

8:13

We changed the world. Join

8:15

us for Blind Spot, The Plague and

8:18

the Shadows, a series from the History

8:20

Channel and WNYC Studios. Listen wherever you

8:22

get podcasts. Artificial

8:28

Intelligence is great at detecting

8:30

patterns, which means its calculations

8:32

can help predict the future.

8:35

But AI can also be used to take

8:37

a look back into the past. That's

8:40

exactly what one research team in Michigan

8:42

is doing. Using AI

8:44

to track the paths of

8:46

prehistoric caribou. Why? To

8:49

see where artifacts from ancient hunters

8:52

may be located. Joining me

8:54

to talk about this is my guest,

8:56

Morgan Springer, editor of the Points North

8:58

podcast at Interloc & Public Radio in

9:00

Interloc in Michigan. Welcome to

9:02

Science Friday. Thank you so much for having me.

9:05

Help me imagine what we're talking

9:07

about here before we get to

9:09

the AI caribou. Where is

9:11

this land bridge that researchers are so

9:14

interested in? Yeah, so it's at

9:16

the bottom of Lake Huron, which for listeners that

9:18

don't know, it's one of the Great Lakes. It's

9:20

on the east side of Michigan and

9:23

the official name of the land

9:25

bridge is the Alpena-Amberly Ridge. And

9:27

it goes from northern Michigan to

9:29

southern Ontario, kind of cutting the lake

9:31

at a diagonal. And what's

9:33

the significance of this bridge? Yeah,

9:36

so what I'm going to say, it's going to sound

9:38

obvious once I say it, but the

9:40

Great Lakes didn't always look the way that

9:42

they do now. If we go back to

9:45

the ice age, the glaciers

9:47

are receding. And about 10,000 years

9:50

ago, lake levels were lower than they

9:52

are today. So that

9:54

means land that's now underwater, it was

9:56

above water then, including this ridge, this

9:59

land bridge. And it

10:01

was continuous. It was this causeway

10:03

where people and animals could move

10:05

and migrate back and forth and

10:07

leave artifacts, presumably. And so then

10:10

the water levels rise, it comes

10:12

up, and these artifacts

10:14

are submerged and remarkably preserved

10:16

and protected from development. And

10:19

you know, archaeologists were skeptical

10:21

that they'd find anything, that

10:24

this was going to be an opportunity to find

10:26

artifacts, but they wanted to look anyway. And

10:29

let's get into the details of this. Why

10:31

would someone want to research how

10:34

animals crossed this long-gone path? Yeah,

10:36

so John O'Shea, he's an anthropological

10:38

archaeologist and he's based at the

10:40

University of Michigan, and he wanted

10:43

to find something. And so basically he came up

10:45

with an idea for something he thought

10:48

he could find, something that would have

10:50

survived being inundated with water about 9,000

10:52

years ago. And so

10:54

one of the things they knew about that time

10:56

period was that caribou were the main source of

10:58

food. And they also

11:01

knew that prehistoric hunters made these

11:03

really cool hunting structures, they're

11:06

called drive lanes, and they would guide

11:08

the caribou to these kill

11:10

sites. And so John

11:12

O'Shea, his collaborator, they thought if they

11:14

were made of stone back then, maybe

11:17

we could find them underwater. So it's

11:19

all these hypotheticals, but it

11:22

helps to know where the caribou would

11:24

go so that they can know where

11:26

to look for sites. So

11:29

the idea is if the caribou follow a

11:31

certain path, then humans probably aren't

11:33

far behind, and then it's the

11:35

humans who are leaving these artifacts. Exactly.

11:38

And why couldn't researchers just find

11:41

these artifacts the old-fashioned

11:43

way? Yeah, so technically they did

11:45

find the first one the old-fashioned

11:48

way, kind of. I mean,

11:50

they used side-scan sonar. I think they had

11:52

an underwater robot at the time, but there

11:54

wasn't any AI. But

11:56

regardless, the challenge was that Lake Huron

11:58

is... huge and even

12:00

though the land bridge offers this concentrated

12:04

place, this corridor to look,

12:06

it's still really long. It's about 90 miles

12:09

long. It's about nine miles

12:11

wide and then on top of that you got to

12:13

go 100 feet underwater. And

12:16

here's John O'Shea talking about

12:19

this process. Underwater research

12:21

is always like a needle in a haystack. So

12:24

any clues you can get that help you

12:26

narrow down and focus the kind of places

12:28

you might look at is a real help

12:30

to us. And you

12:32

know, John happened to know the

12:35

premier, one of the premier

12:37

people doing archaeological computer

12:39

simulation. His name's Bob Reynolds.

12:41

He's based at Wayne State

12:43

University. And so their

12:45

idea was they'll create a

12:47

computer model of the land bridge and

12:50

then use AI to help predict sites. And

12:54

how does this AI actually work? What

12:56

kind of information were the researchers plugging

12:58

into the model? Great question.

13:00

Okay, so the first step is you've got

13:02

to actually build the virtual

13:04

land bridge, the Alpina-Amberley Ridge, and

13:07

they use the actual topography. And

13:09

then they start populating it with

13:11

digital caribou. And that's the piece

13:14

that has the artificial intelligence. So

13:16

they create these caribou and they

13:18

give them instructions, their computer algorithms,

13:21

and the instructions basically tell them how to

13:23

behave. A really simple one

13:25

is caribou walk. Okay,

13:28

so the caribou start walking. And then

13:30

another simple one is be aware of

13:32

obstacles and move around them like don't

13:34

bump into rocks or each other. Another

13:36

one is move in groups and break

13:39

apart. And they just they keep refining

13:41

and refining it until the caribou start

13:43

behaving more and more like real

13:45

caribou. And what did

13:47

it look like to watch the

13:49

AI model in action? I'm picturing

13:51

a sort of animated video of

13:53

caribou walking around. But is

13:55

that what the early models really looked like? They

13:58

had some glitches. One

14:03

of the researchers I talked to, she

14:05

described that the caribou looked

14:07

like they were roller skating

14:09

because they didn't exactly walk.

14:11

But they've kept developing it

14:13

and that's really a whole

14:15

other story. Now they have

14:17

an amazing virtual reality where

14:19

they really look like caribou.

14:23

But another glitch was Bob Reynolds,

14:25

the computer scientist at Wayne State

14:27

that I mentioned. He

14:30

talked about this other one glitch that was

14:32

funny. Literally the first model. We

14:34

let the herd run across the land bridge

14:37

and they did not have edge perception and

14:39

so they kept dropping off the size of

14:41

the bridge like lemmings. Oh

14:43

no! RIP to the

14:46

AI caribou I guess. I

14:49

know. And so that's a perfect example of

14:51

where they have to introduce a new algorithm

14:53

and they basically give the caribou a new

14:55

instruction which says, hey you gotta perceive

14:57

edges. So it's a lot of

14:59

trial and error and refining. And

15:02

how well is the AI working today?

15:04

I mean, have the researchers actually found

15:06

any real world evidence based on these

15:08

computer generated paths? Yes,

15:11

absolutely. They've found

15:14

prehistoric hunting sites, they've found

15:16

artifacts. Ashley Lemke,

15:18

she's an anthropological archaeologist also

15:20

on the team and she's

15:22

currently a professor at the

15:24

University of Wisconsin-Milwaukee and

15:27

here she is. We

15:29

could ask this archaeologist, how did you find a site? Or

15:31

how did you know where to dig? And

15:33

for me I can be like, oh well artificial

15:35

intelligence told me. So how

15:38

it works is the caribou developed these optimal

15:40

routes over time. They're going back and forth

15:42

and back and forth. And

15:44

there were a few spots that they went nearly

15:46

every time and they called these choke points. And

15:50

so this is a really obvious place for archaeologists

15:52

to go and look. And this

15:54

is just one example of how AI

15:56

helped. But this one particular choke

15:58

point led them to the site, they

16:00

call it Drop 45. It's

16:02

the most complex hunting structure found in

16:05

the Great Lakes to date. And

16:07

there's a number of things there. There's a

16:09

line of stones guiding caribou to a kill site.

16:12

There was a fireplace with burnt

16:14

earth, incredible 9,000 years old. And

16:17

then there were also these really

16:19

unusual small tools that were unprecedented

16:21

for the season. And you know,

16:24

that's AI. AI helped them find

16:26

that and it saved them time

16:28

and money. And

16:30

now that these amazing artifacts

16:33

are being, little and large, I guess

16:35

artifacts are being found, what's

16:38

next for the team? Yes.

16:40

So keep looking.

16:43

Yes, they found some

16:45

artifacts, but they've just

16:48

scratched the surface. And with

16:51

what they found, they've started to build an

16:53

understanding about what the environment might have looked

16:55

like and how people might have lived. But

16:58

they've also found some totally new

17:00

and, as I mentioned, unprecedented artifacts.

17:02

Here's Ashley Lemke again. None

17:05

of this matches the models we had

17:07

about peoples in this region, which is really, you know,

17:10

it's really fascinating because then you have to go back

17:12

and be like, all right, well, now we have this

17:14

new data, you know, what does that mean for

17:16

what we thought about peoples that were living in

17:18

the Great Lakes? You know, you kind of have to rewrite the

17:20

story. So they keep looking, they

17:23

keep researching and they keep rewriting

17:25

the story. And now that

17:28

it's been proven that this sort of

17:30

application for AI works, do you think

17:32

it'll gain traction in the larger scientific

17:34

community? You know, I don't

17:36

know. I think it should for

17:38

sure. But Bob

17:41

Reynolds, he's the main computer scientist. This

17:43

is not the only project he's worked

17:45

on. So it's definitely something he's working

17:48

on with other archaeologists,

17:50

other scientists. But it

17:52

requires a lot of strong collaboration

17:54

between completely different fields. And

17:57

I know that Bob specifically, he

17:59

leans heavily on students at Wayne

18:01

State to really help make the

18:03

simulation and the virtual reality come

18:06

to life. That's all the time

18:08

we have for now. I'd like to

18:10

thank my guest, Morgan Springer, editor of

18:12

the Points North podcast at Interlochen Public

18:14

Radio in Interlochen, Michigan. Thank you for

18:17

joining me. Thank you so

18:19

much, Sophie. That's it

18:21

for today. Lots of folks helped make

18:23

the show, including Ariel Zich,

18:26

Jordan Smudgick, Diana Plasker,

18:28

and many more. Tomorrow, we'll check

18:31

in on the top stories from the week

18:33

in science. I'm Sci-fi producer Charles Bergquist. Thanks

18:35

for listening. We'll see you soon.