- That's Mat:
and this is not his voice.
It's hers.
Wait, no, not her.
There you go.
That's Holly+.
It's a voice model AI that's trained
on Holly's voice, and is an experiment on consent in AI.
- What does it mean to be an artist
when anybody can create as you?
Do you say, "Nobody should be able to create as me,
and I'm gonna shut this down?”
Or do you lean into it and say, "Let's acknowledge
that this is now a thing, and see how far we can take it?”
- Hello.
- Hey.
- It's Holly.
- I never really saw myself as a kind of true vocalist.
Let's give it a little shimmer.
- Ooh.
- So when I learned of machine learning
and the ability to train on my own voice,
that's when I could really create a kind of digital version
of my voice that could kind of do all
of the vocal gymnastics that my physical voice
and my own training can't do.
She is a kind of digital version of myself.
Holly+ was dreamed up
in the latent space of machine learning algorithms,
and is a collective hallucination
of who I am through the filter of the internet.
- For now,
the Holly+ site allows anyone to upload sounds
and hear them sung back in Holly's voice.
But the publicly available version doesn't
allow Holly+ to sing actual words.
We weren't quite ready to unleash
the fully language-capable version
without figuring out what kind
of guardrails we wanna put up around that.
What kind of words do I not want people to sing
through my natural singing voice?
Do I wanna make everything available?
- It feels like we're
on the cusp of something big, like really big.
- I think it's fair to say we are going
through a bit of a renaissance in machine learning,
and it doesn't show any signs of slowing down.
- Now, more people than ever are equipped
with tools-
- to remix the world.
- In almost any way they can imagine-
even if that means making Drake
rap about beans.
Or rap another artist's song,
or have Eminem profess his love for cats.
Using AI to mimic an artist's voice
has led to massive controversy, with questions
around artist's rights and compensation.
But if we go back to the early days of sampling,
we just might find some answers.
- We all love the rich, sampled music history
that we can all enjoy, but there were also a lot
of people who were treated really unfairly at that time.
You have the Amen Break with Gregory Coleman,
who was never remunerated for that drum sample,
which was the most sampled sound in music history.
- The lack of a licensing structure
led to a bunch of lawsuits,
like when Vanilla Ice sampled the baseline
from "Under Pressure."
While sampling created new forms of music,
licensing helped strike a balance
between protecting artists and encouraging creativity.
- In actuality, sampling was a net good for the world.
It produced interesting new art forms.
You could likely say the same
with machine learning technologies.
There will be new kinds
of artistry that we haven't necessarily seen before—
and that's delicious.
For this one, I think we can just play out the MacBook.
- So then all we have to do is this, okay.
- Hello, hello, hello.
Oops. Oh, it didn't like that.
- So we've trained several algorithms now.
There's Spawn: it was trained on our ensemble.
There's also Holly+ that was trained exclusively
on my voice.
And then for "Proto," the album that we made,
dealing with largely co-created models.
We worked with people who knew what was gonna happen
with the data,
knew that they were training an AI,
and were really excited about the prospect.
It's kind of like farm-to-table data or something.
- We were quite explicit,
and probably I think the first, to really acknowledge
that consent regarding training data
of these networks was gonna be a major issue,
as has been proven.
- Remember this?
Well, it's already been taken down.
And Drake, he's had enough of these AI renditions,
which has led the Universal Music Group
to ask streaming services
like Spotify to restrict AI companies
from accessing copyrighted music.
- There has been a kind of culture war emerge
that I would argue presents a kind of false dilemma
between pro-AI people or artists, and anti-AI artists.
Holly and I ignore that premise.
We don't see any conflict between being very,
very excited about development and machine learning,
and also being very concerned about artist welfare.
So, we thought, "Oh, okay,
it would actually be quite constructive
and useful to provide people
with a tool to understand how these systems work,
and get a more intimate, personal understanding
of how they feel about it."
If you're in there, do you want to be in there?
- So Mat and Holly created a website
called 'Have I Been Trained?'
which lets artists search for their work
in major AI art systems, like Stable Diffusion and Imagen.
- Hey.
- To see how it works,
we had Mat walk us through it.
- If you just right-click on any one of those images,
you can add that image to your opt-out.
You've now registered that to opt-out of AI training,
and we can deliver that request to organizations.
This is kind of like the first step in beginning
consenting relationships with AI models
and AI training practices.
We both believe that consent is the way forward
for this stuff, and it just so happens
that we actually consent.
- I think we'll look back on today
and realize that we're really
at a kind of crossroads at this moment.
How will we deal with consent?
Will this end up in walled gardens and silos,
or will this be something that anyone can use?
- Now is the time to get excited about it
and start having some big ideas because
I think that over time, consenting data
will actually be better
for artists and individuals, and be better for AI,
and everyone will want to opt-in—
but on their own terms.