January 5, 2026 • 15 mins
All at once, it seems as if AI and Music are intertwined: It’s being used for everything from restoring old recordings, to generating entire songs from prompts. For musicians, is AI a tool or a rival? Emmy Award-winning composer and producer, Lucas Cantor Santiago was commissioned by one of the largest technology companies in the world, to collaborate with artificial intelligence in an experiment to finish Franz Schubert’s Unfinished Symphony. The project led him to question his long-standing assumptions about music, technology, and how both evolved together through history. Lucas Cantor Santiago’s book is UNFINISHED: The Role of the Artist in the Age of Artificial Intelligence.
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Episode Transcript
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Speaker 1 (00:01):
Welcome to Get Connected with Nina del Rio, a weekly
conversation about fitness, health and happenings in our community on
one oh six point seven light FM.
Speaker 2 (00:12):
Thanks for listening to Get Connected all at once. It
seems as if AI and music are intertwined. It's being
used from everything from restoring old recordings to generating entire
songs from prompts for musicians. Is AI a tool or
a rival? My guest is Emmy Award winning composer and
producer Lucas Canter Santiago, who was commissioned by one of
(00:33):
the largest technology companies in the world to experiment by
collaborating with AI to finish Franz Schubert's Unfinished Symphony. That
project led him to question his long standing assumptions about
what music is, what technology does, and how the two
have evolved through history. Lucas Canter Santiago's book is Unfinished,
The Role of the Artist in the Age of Artificial Intelligence.
(00:56):
Lucas Canter Santiago, thank you for being on Get Connected.
Speaker 3 (00:59):
Thank you. It's please to be here.
Speaker 2 (01:01):
Lucas Canter Santiago is a composer, producer, multi instrumentalist and
Emmy Award winner. He's collaborated on projects with Lord, the
Wu Tang Clanspike Jones, Warner Music, DreamWorks, Disney, and the
list goes on. So our listeners would know your music,
probably from the super Bowl or from the Olympics. You
have a long history of writing music for TV networks
(01:23):
and also film and TV theme music. For people who
aren't all familiar with that work, I wonder if you
could start by talking about what your work is and
a bit of your workplace. It is very technology dependent.
Speaker 4 (01:34):
Yeah, that's a great question. Thank you for having me on.
What I tell people is that you've heard my music,
but you almost certainly didn't do it on purpose. So
I did score the introduction to last year's super Bowl.
There's were twenty twenty five super Bowl. It was Brad
Pitt talking about America for a few minutes, getting everyone
hyped up for the game. It's really amazing, and about
(01:55):
two hundred and eighty million people saw it. But I
don't think anybody's If you watched some of my work
and you think the music is amazing, I haven't done
my job. My job was to tell the story. So
hopefully you watched that and you were pumped up to
watch the Super Bowl.
Speaker 3 (02:07):
That was the goal.
Speaker 4 (02:08):
I did a similar thing for the Super Bowl two
years ago, and that is a lot of my work
in sports is writing music that cats you pumped up
to watch a sporting event. We have a joke internally
that you know, what is actually happening as grown men
are playing a game, and we try to make it
seem important and heavy, and it is if you're a
fan of the game, but ultimately you know it's it's
adults playing games.
Speaker 3 (02:30):
So the way I.
Speaker 4 (02:30):
Approach that musically is really with a lot of seriousness
and a lot of weight, because you know, these moments
meet a lot of the people who watch them, so
and to me, I know, this isn't a podcast about baseball,
but I could talk about baseball for as long as
you like.
Speaker 3 (02:45):
So yeah, so people would know my work from that.
Speaker 4 (02:49):
The Lord song was on the Hardred Games Catching Virus oundtrack,
so some people may have heard that it was her
cover of Everybody Wants to Rule the World.
Speaker 3 (02:56):
And a lot of a lot.
Speaker 4 (02:58):
Of my music my day obvious to write music for television,
and I write a lot of library music as well,
so some music that is used in the backgrounds of
movie scenes and you would never notice that it was there,
but you would.
Speaker 3 (03:09):
Notice if it was not there.
Speaker 2 (03:10):
And so much of this is created by technology. It's
really indispensable. The technology you have at your fingertips gives
you access to create tools and almost any sound virtually.
That's kind of the job, is to go out and
find new sounds and put them together in a new way.
What does AI offer you.
Speaker 3 (03:28):
Well, let's let's let's back out.
Speaker 4 (03:29):
I think that I think it's not obvious what you
said to most people that I use a lot of
tools and a lot of technological tools to be a composer.
Speaker 3 (03:37):
I am a composer the same way that fron Schubert
was a composer.
Speaker 4 (03:40):
I'm a composer the same way any one who writes
music for people as a composer. But I write my
music almost entirely on a computer, and so does every
other composer today. Someone who writes music by hand is
a anachronism at best. But every composer that I know
writes music with some form of technology. So that gives
(04:01):
us a unique window.
Speaker 3 (04:03):
Into the world of artificial intelligence.
Speaker 4 (04:06):
Because for a lot of people who have had AI,
you know, maybe ll m's kind of thrust into their workflow.
Speaker 3 (04:13):
Technology has been part of my workflow for.
Speaker 4 (04:15):
Years, decades, and so AI is just kind of an
incremental change. It's a it's a new way of processing data.
It's a different way of processing data. It's I mean,
it's you know, the use case is still kind of
unclear what what AI will be used for.
Speaker 3 (04:29):
In music. I have used it.
Speaker 4 (04:31):
I used it as I detail in the book. I
used it to finish Schubert's on Finnish Sympathy. And this
was someone scholars have finished schuberts On finished symphony before.
This was the first time that AI had been employed
to do it, and it was it was an interesting project,
but you know, it was I don't know if AI
was was is as relevant as the human artistry of
(04:55):
you know, conceiving of the idea and then executing the
idea and you know, and a symphony is you know,
performed by you know, it doesn't happen without about one
hundred people contributing lifetime.
Speaker 2 (05:07):
Of talent, as you talk about in the book. I mean,
the human element is so interesting. For instance, technology, yes,
has been a part of so many things over time.
Technology we're not talking about necessarily computers. Just for instance,
as you detail in the book, I think the oldest
musical instrument found is a bone, right, a bone flute
or something. I think one of the more interesting ones
(05:29):
from the modern era to show us how music has
evolved is the microphone. Can you talk about how just
the invention of the microphone changed performers and performance?
Speaker 4 (05:40):
Sure, that's a that's a very like, yeah, it's a
very live present example that I do this when I
do talks in person, I will sort of sing like
someone would have.
Speaker 3 (05:50):
Saying in the nineteen twenties, and then the way that
Frank Sinatra would sing.
Speaker 4 (05:53):
So if you were, you know, a like a like
Connie Boswell or some you know singer from the era
before or who's performing before microphones, you had to belt
the back row because behind you was an orchestra that
was playing extremely loud, so you had to belt really
loud to be heard. And that's that sort of Broadway style.
Frank Sinatra was able to use a microphone. So you know,
(06:16):
it's it's it's asmr. It's this this feeling that he's
right there next to you, and he's and he's sort
of just kind of telling you these songs in a
very intimate way. That was that was entirely new at
the time. That goes because it was not technologically possible.
So microphones made possible. Like initially we used them to
amplify existing things, but then we very quickly started to
(06:38):
use them as new with new forms of expression. The
way Frank Sinatra sings is completely different than how people
saying before him, and it.
Speaker 3 (06:46):
Is how everybody sings now.
Speaker 4 (06:48):
So there's uh, you know that that is one of
many examples of the technology completely changing the sound of
music and completely changing what we perceive as you know,
interesting and relevant.
Speaker 2 (07:01):
My guest is Lucas Canter Santiago, a composer, producer, multi
instrumentalist and Emmy Award winner. His concert works include the
final two movements of Schubert's Unfinished Symphony Finished with AI.
His website is Lucascantersantiago dot com and his book is
Unfinished The Role of the Artist in the Age of
Artificial Intelligence. You're listening to get Connected on one oh
(07:22):
six point seven light FM. I'mina del Rio. So your
work is about creating music, a lot of it that
sets a specific tone or a mood, scary, powerful, exciting,
music to fit a formula. And as you write in
the book, you have colleagues who perhaps work in the
same realm who feel most threatened by AI because of
the work that you do. So how does AI make music?
(07:44):
When we talk about the microphones and flutes, we're talking
about different sounds and amplification. But what does AI do
that's different?
Speaker 4 (07:51):
Well, I can tell you how AI does anything, which
is it predicts the next likely thing. That's really all
it's doing. So the tokens be musical sounds, or they
can be letters, or they can be words. But what
it does at its core is use sophisticated mathematical analysis
to guess what should come next. And this is why
(08:13):
I don't like to use the term hallucinate, because that
implies some kind of sentience. But this is why they
will sometimes say nonsensical things because the branching tree just
gets lost and so it just goes down a rabbit
hole things that don't make sense. Or it will make
say sentence that does make sense, but it doesn't make
any sense in context, and then we call that I hallucination.
(08:34):
So the way that IT makes music is you can
train it on, you know, spin slices of many, many
millions of pieces of music, and it will learn what
types of things tend to follow other things.
Speaker 3 (08:46):
It's I mean, it sounds simple. I think it sounds simple.
Speaker 4 (08:49):
The results are very robust, and you know, the ability
to predict what will likely come next is is a
very significant power. But it is that's all. It is,
that all, that's all.
Speaker 2 (09:01):
To day I is doing so in the Schubert project.
Just to give a little bit of context for people
from Schubert composed his symphony number eight in eighteen twenty two,
never completed it. There were two movements along with an
outline of a third, and you were commissioned by Huawei
to work with AI to finish that symphony. Yes, what
was your task? Then?
Speaker 4 (09:20):
Huawei was at the time the biggest self film manufacturer
in the world it is today one of the biggest,
and they wanted to use this capability to show off
their new phone.
Speaker 3 (09:31):
And this was for them.
Speaker 4 (09:32):
It was a marketing exercise, and marketing executives don't know
what goes into making a symphony generally, and so they thought, yeah, okay, great,
pressa button will get a symphony. But you know, what
even is a symphony is a symphony the written work,
the music notation is that the sounds in the air
is it? You know, any individual part, And these are
(09:54):
questions that you don't need to know every day with
the questions that you need to answer if you're going
to produce a symphony. And so they had envisioned was
this sort of push button get symphony, but that doesn't
really exist.
Speaker 3 (10:04):
There are too many steps.
Speaker 4 (10:05):
Between an idea and something going on a stage.
Speaker 3 (10:09):
So what I was able to and they had.
Speaker 4 (10:11):
Tried to do it without a human and they got
basically complete nonsense results. I mean not even like I'm
not saying that they've gotten results that were not musically interesting.
They were like cats walking on a piano. And so
they asked me if I could help, and I suggested
that the same way that a Huawei phone is useless
(10:32):
without a human operator, this capability is useless without a
human musician. And so what I suggested was that, like,
why don't I work with it and train it and
figure out how it's training data should be structured, and
then figure out how to prompt it and then get
results that we like, get melodies that make sense, and
then orchestrate those in a context that would make sense
(10:52):
for the time and make sense for Schubert. So we
prompted it. We trained it with every Schubert melody we
can get our hands on. We prompted it with the
two movements that Schubert to finish, and we got back
melodic ideas that would go in the second and third movement.
And then I used my knowledge of nineteenth century symphonies
and use some of the organic unity techniques that they use,
(11:13):
like reprising melodies from the first movement in the third
movement and.
Speaker 3 (11:16):
That kind of thing.
Speaker 4 (11:17):
And the result is a I think, a pretty listenable
and interesting symphony.
Speaker 2 (11:21):
So this was in twenty nineteen, and I know you've
worked on several projects with AI since then. If your
role was to in twenty nineteen to as you more
than just fill the gap, but in part fill the
gap and help interpret for the system what it was
going to come up with, What is the role going forward?
Is that gap something that is going to be Is
(11:42):
it going to be filled? What is the role of
the artist going forward?
Speaker 4 (11:46):
So I think the role of the artist is it
hasn't really changed. And that's the conclusion I came to
in the book. I don't know if it's a conclusion,
But this is my feeling, is that the role of
the artist is to understand what it is we do,
how it is meaningful to our audience, and how it
is meaningful to us to and what it means for
(12:07):
the world broadly, and then to understand how tools have
helped to create that in the past and how they
can help to create those feelings in the future.
Speaker 3 (12:16):
There no, there's no new.
Speaker 4 (12:19):
I mean, it makes for a good copy to talk
about artificial intelligence doing things, but technology helping to create
art is not news. It is something that has existed
for every listener's entire lifetime, and hundreds of years before that,
and thousands and tens of thousands of years before that.
You know, the history of technology and the history of
(12:39):
music specifically are intertwined, and there is no factor that
affects the way music sounds more than the technology that
it's used to make it.
Speaker 2 (12:48):
You also came to the conclusion, I don't know if
this was when you were younger, or it's just been
sort of underlined through your work in the last few years,
that the emotion that someone feels for music is more
about the listener perhaps the composition itself.
Speaker 4 (13:02):
Yeah, the I mean, the composer's intent is almost irrelevant
frankly too, how a piece of music is perceived, and
you can find examples of that without looking too far.
One of them that I write about in my book
is that Leonard Cohen's idea for Hallelujah was very, very
far away from how.
Speaker 3 (13:23):
The song is perceived today.
Speaker 4 (13:24):
And I picked that one because it's a famous example,
but you could find almost anything.
Speaker 3 (13:31):
I love to think about.
Speaker 4 (13:32):
Gun Non Style, which you know, the hit of fifteen
years ago, which I don't know what he was thinking
when he wrote that, and I don't know what we're
thinking when we listen to it, but they're definitely not
the same thing. You don't decide, like you know, all
art is the audience has to meet you halfway.
Speaker 3 (13:47):
You know, as an artist, you can create it and you.
Speaker 4 (13:49):
Can put it out there in the world, but you
really can't predict how it's going to affect your audience.
Speaker 3 (13:55):
That's marketing, and marketing you can predict.
Speaker 4 (13:57):
But in art, you're trying to say something that is
true for you and sort of see if it's true
for anybody else, and you learn that the answer is
sometimes yes and sometimes no, and both.
Speaker 3 (14:07):
Can be beautiful.
Speaker 2 (14:07):
It's the difference between looking at a painting and crying
and looking at a painting and walking to the next one.
Speaker 4 (14:13):
Yeah, or I guess the opposite of looking at a
painting and crying would be looking at a painting and laughing,
which I think is also the great.
Speaker 2 (14:19):
Response Lucas Canter Santiago's book is Unfinished, The Role of
the Artist in the Age of Artificial Intelligence. Thank you
for being on to Get Connected.
Speaker 3 (14:28):
It was my pleasure. Thank you so much for having me.
Speaker 1 (14:32):
This has been Get Connected with Nina del Rio on
one oh six point seven light Fm. The views and
opinions of our guests do not necessarily reflect the views
of the station. If you missed any part of our
show or want to share it, visit our website for
downloads and podcasts at one oh six to seven lightfm
dot com. Thanks for listening.
Welcome to Get Connected with Nina del Rio, a weekly
conversation about fitness, health and happenings in our community on
one oh six point seven light FM.
Speaker 2 (00:12):
Thanks for listening to Get Connected all at once. It
seems as if AI and music are intertwined. It's being
used from everything from restoring old recordings to generating entire
songs from prompts for musicians. Is AI a tool or
a rival? My guest is Emmy Award winning composer and
producer Lucas Canter Santiago, who was commissioned by one of
(00:33):
the largest technology companies in the world to experiment by
collaborating with AI to finish Franz Schubert's Unfinished Symphony. That
project led him to question his long standing assumptions about
what music is, what technology does, and how the two
have evolved through history. Lucas Canter Santiago's book is Unfinished,
The Role of the Artist in the Age of Artificial Intelligence.
(00:56):
Lucas Canter Santiago, thank you for being on Get Connected.
Speaker 3 (00:59):
Thank you. It's please to be here.
Speaker 2 (01:01):
Lucas Canter Santiago is a composer, producer, multi instrumentalist and
Emmy Award winner. He's collaborated on projects with Lord, the
Wu Tang Clanspike Jones, Warner Music, DreamWorks, Disney, and the
list goes on. So our listeners would know your music,
probably from the super Bowl or from the Olympics. You
have a long history of writing music for TV networks
(01:23):
and also film and TV theme music. For people who
aren't all familiar with that work, I wonder if you
could start by talking about what your work is and
a bit of your workplace. It is very technology dependent.
Speaker 4 (01:34):
Yeah, that's a great question. Thank you for having me on.
What I tell people is that you've heard my music,
but you almost certainly didn't do it on purpose. So
I did score the introduction to last year's super Bowl.
There's were twenty twenty five super Bowl. It was Brad
Pitt talking about America for a few minutes, getting everyone
hyped up for the game. It's really amazing, and about
(01:55):
two hundred and eighty million people saw it. But I
don't think anybody's If you watched some of my work
and you think the music is amazing, I haven't done
my job. My job was to tell the story. So
hopefully you watched that and you were pumped up to
watch the Super Bowl.
Speaker 3 (02:07):
That was the goal.
Speaker 4 (02:08):
I did a similar thing for the Super Bowl two
years ago, and that is a lot of my work
in sports is writing music that cats you pumped up
to watch a sporting event. We have a joke internally
that you know, what is actually happening as grown men
are playing a game, and we try to make it
seem important and heavy, and it is if you're a
fan of the game, but ultimately you know it's it's
adults playing games.
Speaker 3 (02:30):
So the way I.
Speaker 4 (02:30):
Approach that musically is really with a lot of seriousness
and a lot of weight, because you know, these moments
meet a lot of the people who watch them, so
and to me, I know, this isn't a podcast about baseball,
but I could talk about baseball for as long as
you like.
Speaker 3 (02:45):
So yeah, so people would know my work from that.
Speaker 4 (02:49):
The Lord song was on the Hardred Games Catching Virus oundtrack,
so some people may have heard that it was her
cover of Everybody Wants to Rule the World.
Speaker 3 (02:56):
And a lot of a lot.
Speaker 4 (02:58):
Of my music my day obvious to write music for television,
and I write a lot of library music as well,
so some music that is used in the backgrounds of
movie scenes and you would never notice that it was there,
but you would.
Speaker 3 (03:09):
Notice if it was not there.
Speaker 2 (03:10):
And so much of this is created by technology. It's
really indispensable. The technology you have at your fingertips gives
you access to create tools and almost any sound virtually.
That's kind of the job, is to go out and
find new sounds and put them together in a new way.
What does AI offer you.
Speaker 3 (03:28):
Well, let's let's let's back out.
Speaker 4 (03:29):
I think that I think it's not obvious what you
said to most people that I use a lot of
tools and a lot of technological tools to be a composer.
Speaker 3 (03:37):
I am a composer the same way that fron Schubert
was a composer.
Speaker 4 (03:40):
I'm a composer the same way any one who writes
music for people as a composer. But I write my
music almost entirely on a computer, and so does every
other composer today. Someone who writes music by hand is
a anachronism at best. But every composer that I know
writes music with some form of technology. So that gives
(04:01):
us a unique window.
Speaker 3 (04:03):
Into the world of artificial intelligence.
Speaker 4 (04:06):
Because for a lot of people who have had AI,
you know, maybe ll m's kind of thrust into their workflow.
Speaker 3 (04:13):
Technology has been part of my workflow for.
Speaker 4 (04:15):
Years, decades, and so AI is just kind of an
incremental change. It's a it's a new way of processing data.
It's a different way of processing data. It's I mean,
it's you know, the use case is still kind of
unclear what what AI will be used for.
Speaker 3 (04:29):
In music. I have used it.
Speaker 4 (04:31):
I used it as I detail in the book. I
used it to finish Schubert's on Finnish Sympathy. And this
was someone scholars have finished schuberts On finished symphony before.
This was the first time that AI had been employed
to do it, and it was it was an interesting project,
but you know, it was I don't know if AI
was was is as relevant as the human artistry of
(04:55):
you know, conceiving of the idea and then executing the
idea and you know, and a symphony is you know,
performed by you know, it doesn't happen without about one
hundred people contributing lifetime.
Speaker 2 (05:07):
Of talent, as you talk about in the book. I mean,
the human element is so interesting. For instance, technology, yes,
has been a part of so many things over time.
Technology we're not talking about necessarily computers. Just for instance,
as you detail in the book, I think the oldest
musical instrument found is a bone, right, a bone flute
or something. I think one of the more interesting ones
(05:29):
from the modern era to show us how music has
evolved is the microphone. Can you talk about how just
the invention of the microphone changed performers and performance?
Speaker 4 (05:40):
Sure, that's a that's a very like, yeah, it's a
very live present example that I do this when I
do talks in person, I will sort of sing like
someone would have.
Speaker 3 (05:50):
Saying in the nineteen twenties, and then the way that
Frank Sinatra would sing.
Speaker 4 (05:53):
So if you were, you know, a like a like
Connie Boswell or some you know singer from the era
before or who's performing before microphones, you had to belt
the back row because behind you was an orchestra that
was playing extremely loud, so you had to belt really
loud to be heard. And that's that sort of Broadway style.
Frank Sinatra was able to use a microphone. So you know,
(06:16):
it's it's it's asmr. It's this this feeling that he's
right there next to you, and he's and he's sort
of just kind of telling you these songs in a
very intimate way. That was that was entirely new at
the time. That goes because it was not technologically possible.
So microphones made possible. Like initially we used them to
amplify existing things, but then we very quickly started to
(06:38):
use them as new with new forms of expression. The
way Frank Sinatra sings is completely different than how people
saying before him, and it.
Speaker 3 (06:46):
Is how everybody sings now.
Speaker 4 (06:48):
So there's uh, you know that that is one of
many examples of the technology completely changing the sound of
music and completely changing what we perceive as you know,
interesting and relevant.
Speaker 2 (07:01):
My guest is Lucas Canter Santiago, a composer, producer, multi
instrumentalist and Emmy Award winner. His concert works include the
final two movements of Schubert's Unfinished Symphony Finished with AI.
His website is Lucascantersantiago dot com and his book is
Unfinished The Role of the Artist in the Age of
Artificial Intelligence. You're listening to get Connected on one oh
(07:22):
six point seven light FM. I'mina del Rio. So your
work is about creating music, a lot of it that
sets a specific tone or a mood, scary, powerful, exciting,
music to fit a formula. And as you write in
the book, you have colleagues who perhaps work in the
same realm who feel most threatened by AI because of
the work that you do. So how does AI make music?
(07:44):
When we talk about the microphones and flutes, we're talking
about different sounds and amplification. But what does AI do
that's different?
Speaker 4 (07:51):
Well, I can tell you how AI does anything, which
is it predicts the next likely thing. That's really all
it's doing. So the tokens be musical sounds, or they
can be letters, or they can be words. But what
it does at its core is use sophisticated mathematical analysis
to guess what should come next. And this is why
(08:13):
I don't like to use the term hallucinate, because that
implies some kind of sentience. But this is why they
will sometimes say nonsensical things because the branching tree just
gets lost and so it just goes down a rabbit
hole things that don't make sense. Or it will make
say sentence that does make sense, but it doesn't make
any sense in context, and then we call that I hallucination.
(08:34):
So the way that IT makes music is you can
train it on, you know, spin slices of many, many
millions of pieces of music, and it will learn what
types of things tend to follow other things.
Speaker 3 (08:46):
It's I mean, it sounds simple. I think it sounds simple.
Speaker 4 (08:49):
The results are very robust, and you know, the ability
to predict what will likely come next is is a
very significant power. But it is that's all. It is,
that all, that's all.
Speaker 2 (09:01):
To day I is doing so in the Schubert project.
Just to give a little bit of context for people
from Schubert composed his symphony number eight in eighteen twenty two,
never completed it. There were two movements along with an
outline of a third, and you were commissioned by Huawei
to work with AI to finish that symphony. Yes, what
was your task? Then?
Speaker 4 (09:20):
Huawei was at the time the biggest self film manufacturer
in the world it is today one of the biggest,
and they wanted to use this capability to show off
their new phone.
Speaker 3 (09:31):
And this was for them.
Speaker 4 (09:32):
It was a marketing exercise, and marketing executives don't know
what goes into making a symphony generally, and so they thought, yeah, okay, great,
pressa button will get a symphony. But you know, what
even is a symphony is a symphony the written work,
the music notation is that the sounds in the air
is it? You know, any individual part, And these are
(09:54):
questions that you don't need to know every day with
the questions that you need to answer if you're going
to produce a symphony. And so they had envisioned was
this sort of push button get symphony, but that doesn't
really exist.
Speaker 3 (10:04):
There are too many steps.
Speaker 4 (10:05):
Between an idea and something going on a stage.
Speaker 3 (10:09):
So what I was able to and they had.
Speaker 4 (10:11):
Tried to do it without a human and they got
basically complete nonsense results. I mean not even like I'm
not saying that they've gotten results that were not musically interesting.
They were like cats walking on a piano. And so
they asked me if I could help, and I suggested
that the same way that a Huawei phone is useless
(10:32):
without a human operator, this capability is useless without a
human musician. And so what I suggested was that, like,
why don't I work with it and train it and
figure out how it's training data should be structured, and
then figure out how to prompt it and then get
results that we like, get melodies that make sense, and
then orchestrate those in a context that would make sense
(10:52):
for the time and make sense for Schubert. So we
prompted it. We trained it with every Schubert melody we
can get our hands on. We prompted it with the
two movements that Schubert to finish, and we got back
melodic ideas that would go in the second and third movement.
And then I used my knowledge of nineteenth century symphonies
and use some of the organic unity techniques that they use,
(11:13):
like reprising melodies from the first movement in the third
movement and.
Speaker 3 (11:16):
That kind of thing.
Speaker 4 (11:17):
And the result is a I think, a pretty listenable
and interesting symphony.
Speaker 2 (11:21):
So this was in twenty nineteen, and I know you've
worked on several projects with AI since then. If your
role was to in twenty nineteen to as you more
than just fill the gap, but in part fill the
gap and help interpret for the system what it was
going to come up with, What is the role going forward?
Is that gap something that is going to be Is
(11:42):
it going to be filled? What is the role of
the artist going forward?
Speaker 4 (11:46):
So I think the role of the artist is it
hasn't really changed. And that's the conclusion I came to
in the book. I don't know if it's a conclusion,
But this is my feeling, is that the role of
the artist is to understand what it is we do,
how it is meaningful to our audience, and how it
is meaningful to us to and what it means for
(12:07):
the world broadly, and then to understand how tools have
helped to create that in the past and how they
can help to create those feelings in the future.
Speaker 3 (12:16):
There no, there's no new.
Speaker 4 (12:19):
I mean, it makes for a good copy to talk
about artificial intelligence doing things, but technology helping to create
art is not news. It is something that has existed
for every listener's entire lifetime, and hundreds of years before that,
and thousands and tens of thousands of years before that.
You know, the history of technology and the history of
(12:39):
music specifically are intertwined, and there is no factor that
affects the way music sounds more than the technology that
it's used to make it.
Speaker 2 (12:48):
You also came to the conclusion, I don't know if
this was when you were younger, or it's just been
sort of underlined through your work in the last few years,
that the emotion that someone feels for music is more
about the listener perhaps the composition itself.
Speaker 4 (13:02):
Yeah, the I mean, the composer's intent is almost irrelevant
frankly too, how a piece of music is perceived, and
you can find examples of that without looking too far.
One of them that I write about in my book
is that Leonard Cohen's idea for Hallelujah was very, very
far away from how.
Speaker 3 (13:23):
The song is perceived today.
Speaker 4 (13:24):
And I picked that one because it's a famous example,
but you could find almost anything.
Speaker 3 (13:31):
I love to think about.
Speaker 4 (13:32):
Gun Non Style, which you know, the hit of fifteen
years ago, which I don't know what he was thinking
when he wrote that, and I don't know what we're
thinking when we listen to it, but they're definitely not
the same thing. You don't decide, like you know, all
art is the audience has to meet you halfway.
Speaker 3 (13:47):
You know, as an artist, you can create it and you.
Speaker 4 (13:49):
Can put it out there in the world, but you
really can't predict how it's going to affect your audience.
Speaker 3 (13:55):
That's marketing, and marketing you can predict.
Speaker 4 (13:57):
But in art, you're trying to say something that is
true for you and sort of see if it's true
for anybody else, and you learn that the answer is
sometimes yes and sometimes no, and both.
Speaker 3 (14:07):
Can be beautiful.
Speaker 2 (14:07):
It's the difference between looking at a painting and crying
and looking at a painting and walking to the next one.
Speaker 4 (14:13):
Yeah, or I guess the opposite of looking at a
painting and crying would be looking at a painting and laughing,
which I think is also the great.
Speaker 2 (14:19):
Response Lucas Canter Santiago's book is Unfinished, The Role of
the Artist in the Age of Artificial Intelligence. Thank you
for being on to Get Connected.
Speaker 3 (14:28):
It was my pleasure. Thank you so much for having me.
Speaker 1 (14:32):
This has been Get Connected with Nina del Rio on
one oh six point seven light Fm. The views and
opinions of our guests do not necessarily reflect the views
of the station. If you missed any part of our
show or want to share it, visit our website for
downloads and podcasts at one oh six to seven lightfm
dot com. Thanks for listening.
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