WEBVTT

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 Thank you. Teksting av Nicolai Winther Thank you. Wow, what an intro.

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 I like it.

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 Hello, everybody.

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 Welcome to the next session. This is going to be about

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 embodiment. My name is Katya Zybrek. I'm going to be the session chair for this session.

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 I was cut off. Yay! So, yeah, this is the embodiment session. Welcome. We're going to have a couple of really exciting talks today. I'm really excited about it.

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 I'm a researcher in psychology and technology, so we work a lot in VR and with embodiment. So this is something that I am very interested in.

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 But it's true that I think the way we're going to see embodiment in this session is going to be a little bit more different,

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 expanded, should I say. And so, without making too much of a story about it, I'm going to welcome our first presenter.

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 This is Dan Xiyiao, who will present their work, so Wolf and Tar, Designing Mixed Reality Dance Performances

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 for Expanded Theater.

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 And she's also here with Anita Lam and Andy Stokes.

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 Thank you.

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 Hello, everyone.

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 Hello.

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 Hello.

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 Hello.

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 Hello.

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 Okay.

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 Hello everyone. My name is Dan Chiao I'm a creative technologist from the collective a digital art studio based in Hong Kong and I'm with Anita Lam and Andy Stokes

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 Who are the co-founders and the curator and directors of the collective and Alan?

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 We are here to present our art paper Wolf Wolf and Tar, Designing Mixed Reality Dance Performances for Expanded Theatre.

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 So before I start to talk about this project, I want to share a bit about what we do and what kind of mixed reality projects we have done before,

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 and then how those projects bring us to this one.

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 So we are ELLEN, an NGO from Hong Kong. ELLEN stands for Artists Who Love Animals and Nature.

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 We curate exhibitions and create artworks

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 about animals and nature.

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 We did exhibitions about marine life, Sumatra forest,

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 snow mountains, and urban city with wildlife.

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 We mainly do interactive installations

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 and mixed reality experiences.

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 So we started to explore mixed reality since 2023. So on the left hand side is our first

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 project, which is an MR underwater experience. So the audience wear the VR headsets, they can still

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 see the crocheted coral artworks in the reality. And at the same time, they see the virtual animals

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 and the stories about the fishes around them. So that's how they feel that they dive into the ocean.

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 And this is what's called mixed reality experience.

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 They see the reality and the virtual elements at the same time.

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 And on the right hand side, it's our second project.

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 It's an MR rainforest experience.

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 So we extend the recycled paper rainforest artwork into a virtual one

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 where the audience can interact with the world. We also did MR performances. We turned outdoor space into a virtual garden with dancers

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 in which the audience can interact with the virtual elements by using their hands.

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 We also brought MR performances into a theatre.

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 All these experiences brought us to this project,

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 Wolf and Tar, a narrative MR dance performance.

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 This is the video of it.

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 This is the video of the dance performance.

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 This is the video of the dance performance. and Ta, a narrative MR dance performance.

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 This is the video of it.

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 It is a practice-based research and public performance we did with the Hong Kong Academy

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 for Performing Arts in April this year in Hong Kong.

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 In this show, the audiences are allowed to room freely

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 and choose their own view.

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 And in the show, there are two dancers.

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 One plays the role as the wolf and the other

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 as the tar. The story is about

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 predator and prey. So they fight

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 with each other in the blizzard

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 on the snow mountain. And then

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 they got trapped into a cave because

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 of an avalanche. And then they have

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 to work together to get out of that cave.

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 So that's basically the story.

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 And the story reflects the relationship between the species

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 and also the relationship between human and nature.

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 In this project, we experiment body tracking as well.

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 So as you see in the video,

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 one of the dancers is wearing the headsets

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 and the motion track is on her.

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 So that's how we get the location data of and the motion track is on her. So that's how

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 we get the location data of all the body joints of this dancer and then the

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 audience can see the virtual elements following the dance movement in the real

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 time. And the whole show is a 10 minutes long performance. So within the first 8

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 minutes the audience watch the show with the MR headset on and then the

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 performers will help the audience to take off the headsets and then they watch the live dance without the headsets

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 with the projection on and with the lighting.

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 So that's basically the overview of this project and in our art paper

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 we raise up four main challenges when designing

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 narrative in my performance. I'm going to go through one by one and with our approach to this

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 challenge and with examples. So the first challenge is the immersion versus presence. So most of time,

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 the virtual content is rendered over the camera view. So how can the virtual layer support the

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 narrative and immersion without obscuring the dancers?

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 So our approach is to balance the virtual environments with live performance through

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 selective rendering, masking, and control the visual behavior.

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 So here is the example.

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 So as you see in this photo, this is the physical stage design.

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 It's very minimal with the plain steps where the dancers dance on and the

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 playing walls. And what we do is in the first chapter, we rendered a virtual snow mountain

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 from the floor level with the gradient at the bottom. That's how we make sure that the floor

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 is visible, the dancers is visible, and the virtual snow mountain hide the dancers who perform on the

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 steps at the back. And as the performance begins, the mask moves upwards. So imagine the virtual snow mountain hide the dancers who perform on the steps at the back. And as the performance begins, the mask moves upwards.

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 So imagine the virtual snow mountain like a curtain on the theater stage.

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 So it moves up.

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 Once its edge passes the dancer's height, the wolf is revealed at the peak.

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 So that's how the audience understands the steps as the mountain

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 and the dancer on the top as the wolf on the peak. The virtual layer gives the meaning to the physical space.

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 The two layers stay aligned without obscuring the dancers.

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 We also do building the atmosphere without occluding the dancers.

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 On the right-hand side is a cave we rendered in chapter 2.

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 It's a cave that's bigger than the whole space.

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 A full 360 enclosure of the cave with the chapter two. It's a cave that's bigger than the whole space. So a full 360

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 enclosure of the cave would hide the performers in the reality. So only the upper parts of the

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 cave is rendered, but Blizzard and the sky remain visible through the opening hole on the top. So

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 there's no drift scene, so the audience still reads that we are now inside the cave, even though

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 the bottom part of the cave is not rendered, the dancers remain visible.

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 So that's how we balance the virtual environments with the live performance, through selective rendering, masking and controlled visual behaviour.

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 And the second challenge is the attention in 360.

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 So as we know that one of the advantages of MR experience is the audience are

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 allowed to room freely and look anywhere. That means that they may look at the back, they may

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 look at somewhere else. Then how can the attention of the audience be directed to the key story

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 moments without restricting their movement? So our approach is to guide attention with location-based

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 cues. So for example, at the very beginning of the performance the audience are given a short period of time.

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 They can walk around, they can look around to get familiar with the snowy environment.

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 And then as the opening of the performance a glowing ball appears in front of each audience member and

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 drifts towards the wolf at the mountain top.

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 So it travels while the mask reveals the dancer.

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 When it reaches her, the wolf's performance begins so that every viewer's gaze arrives

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 at the same moment.

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 And on the right-hand side is another example.

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 At the end of chapter one, there is an avalanche happens.

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 So it's pulled down from the peak to the foot, then traveled towards each viewer's own position.

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 So wherever they stand, the avalanche feels their view of view and then transits into

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 the next scene.

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 So that's how we make sure that audience don't miss key story moments, by using location-based

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 cues, no matter where they are standing or looking at.

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 And then the third challenge is the two layers, one choreography.

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 So as we know in the MR experience

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 there are two layers of information. One is the live dancers in reality and the other is the virtual elements. And sometimes these two

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 compete for the same attention, which means that when you focus on the virtual elements

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 you may ignore the live dancers in the reality. And when you focus on the live dancers in the reality,

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 you may think the virtual elements as a distraction.

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 So how can we choreograph them as one performance, not two?

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 Our approach is to bind virtual elements to the dancer's movement

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 so that the virtual and the real moves as one

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 instead of competing for attention.

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 So for example, in the first chapter,

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 we have a large wolf head model follows the head dancers head movement and also this wolf head names the

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 character and gives the audience a strong visual anchor and at the end of

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 the story and we have some paddles following the hands movement of the

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 dancer. What we do is we ask one of the dancers to wear the headsets and the

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 motion trackers and then that's how we get all the headsets and the motion trackers.

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 Then that's how we get all the position data and rotation data of each body joint.

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 And then we send necessary information from the dancer to the server and then broadcast

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 them all to every audience headset.

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 That's how they see the virtual elements following the dance movement in the real time.

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 And yeah, that's how the virtual and the real move as one instead of competing for attention.

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 And the last challenge we have here is MR as a partial mode.

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 So we know that the headset is heavy to wear, so it's not comfortable for the audience to

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 wear for a very long time for the whole performance.

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 So we explore MR as a partial mode, which means they watch the performance with the

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 MR headset and then watch the rest of it without it.

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 Then here comes the challenge.

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 How can the audience move from headset to live performance without a break in the experience?

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 So what we do is in a performance, the headset removal is done by the performers turning a

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 potential break into part of the show. So as you see in the picture the

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 dancers remove each other's headsets first so it's a performative gesture so

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 that's like the wolf and the tar set aside their animal identities and

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 returning to a human state.

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 And then the dancers help the audience to remove theirs.

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 So the audience already gets a hint that it's the timing for removing the headsets.

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 And then the shift in viewing mode is carried by the performers.

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 So it stays continuous with the dance.

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 And then finally they watch a live dance without the headsets, with the project is done and the

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 project continues with the dance.

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 And then finally they watch a live dance without

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 the headset with the projection and the light

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 dimmed.

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 That's how we deal with MR as a partial mode.

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 This is the headset piece design of our show.

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 Due to the limitation of time I'm going to skip this part. the.

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 We're going to have a new project coming in next year

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 which is also a more performance about the relationship

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 between owners and the pets.

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 We're going to further develop about the interaction of the

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 audience and also how MR can work as a partial mode of

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 viewing in the performance. This is basically all of the sharing, and if you are interested in what we are doing,

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 you can scan the QR code.

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 And we also bring a headset with us.

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 So if you are interested in experiencing on your own,

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 you can come to us any time.

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 And I promise you, it will feel very different from just

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 viewing a video on the screen.

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 Thank you.

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 Thank you.

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 Do we have any questions?

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 There's one here.

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 Thank you for... Hello, hello.

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 Thanks for the wonderful presentation.

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 I have a question about the experience of the audience or the viewer when you are removing it. 안녕하세요. 시청자의 경험에 대해서 질문을 드리고 싶습니다.

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 여성의 관점에서, 메이크업이나 다른 것들에 대해서,

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 다른 사람들의 경험에 대해서,

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 헤드셋을 제거하는 것에 대해서,

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 편안한 경험이 있다면 어떻게 생각하세요? the headset and whether that is a pleasant experience? We have a short preparation time before it starts.

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 So we have helpers on site to help wearing the headset for the audience.

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 And then I think that's where they already get familiar with people helping

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 them with the headset.

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 And at the end of the show, we have two performers.

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 One is a boy, one is a girl,

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 so they will help remove the headset from the audience. And that's what we do for this performance.

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 Do you consider it kind of a significant gesture that someone removes the headset for them instead

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 of them removing it themselves? Yes, and our design is that the performer removed the headset for them

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 with some body movements, so it's still part of the performance.

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 And then that's how the audience know that that's not a signal of the show ending,

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 but it's still part of the show.

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 So they won't leave after the removal of the headset,

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 but still watching the rest of the show. So they won't leave after the removal of the headset but still watching the rest of the show there.

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 So yeah, that's a part of the performance. And if they

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 remove the headset their own, I think they will consider

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 that's the end of the show. So that's why we choreographed

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 them in the performance as well. Thank you.

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 Thank you. Thank you.

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 Hello. Thank you.

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 Thank you so much for this very interesting presentation.

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 And I'm also a media artist.

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 I also work with theater.

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 So I find really like you have really precious solutions

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 to a lot of problems nowadays that happen in XR theater.

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 So I have a question regarding the dramaturgy and the choreography of this.

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 So according to what we have seen in your presentation, it's kind of like an animal fairy tale thing,

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 and introducing people to the natural environment and get them through that.

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 But what if it's a very complicated story, like something that's already have its own storyline, so how do you consider

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 integrating these technologies and all your solutions, like taking off the

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 headset or using something to get them into some dramaturgy that's more

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 complex? So I'm just wondering if you have thought about this and I'm really

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 glad to hear that. Thank you..

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 I will pass the mic to our curator of this show, Anita

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 Lam.

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 Thank you for your question. That is exactly the same

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 challenge we are facing as we are preparing our next show,

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 which is a full performance around one hour. So that will

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 include putting it on and taking it down.

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 the story is going to be a little bit more complex.

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 We want to have a story that is

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 not just about one hour, so that will include putting it on and taking it down.

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 So we don't want to have a topic around

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 technology because it makes it so easy that, okay, put it on

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 and take it down because it's about ML, then it makes sense.

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 But we want to have a more complex storyline.

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 So we also need to include how to embed this action into the story, right? You can't just having a headset just put it on.

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 So we're considering first, like, can we make a headset like a hat piece that is included

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 in the story?

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 And also, why is there a reason for mixed reality to exist in theatre?

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 You know, like, because it's about imagination,

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 it's about expanding the theatre, expanding the stage.

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 And we need to have a reason for that.

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 So these are all the challenges we need to put in.

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 And for creating a show, because not every performer

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 or the show director understand how mixed reality works and also the visual

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 director how things would work.

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 So to prepare that to happen, we need to all sit down together to discuss how to utilise

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 the ML without making an ML as just a technology demonstration...

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.

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 demonstration. I think that is super

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 can expand ML experience more than just technology showcase.

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 reason and to have that reason, everyone in the design team,

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 in the creative team, have to understand the possibilities and the potential of it

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 rather than just a checkbox of using ML.

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 So yeah, it's a challenge, but let's see how it goes in the next show.

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 But this 10-minute show, we did a survey with the audience to try ticking it off.

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 Does it break the energy? And it did not. So it seems

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 that we able to embed the storyline into removing so that they don't feel that taking it out

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 is a break of the story. Thank you.

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 Okay, in order, sorry, in order to keep in time, we, you can leave the questions for after this session.

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 I'm sure the authors will be around so you can ask them more questions.

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 For now, let's thank the speakers.

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 Thank you.

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 And we welcome our next presentation, which is by Kenji Maverick Lee and Philippe Posquier.

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 They will present Revival, Meta-Creation, Co-Creation, and Digital Afterlife with Musical Agents.

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 Hello, everyone.

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 We don't have a jingle?

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 I'm a little bit disappointed.

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 I'm just going to bookend Kian's presentation here.

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 Fantastic. I'm going to just bookend this presentation.

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 Looking at the pre-Ars Electronica catalog, they compiled statistics.

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 And this year they announced that over 50% of the artists use AI in the making of their artwork,

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 which I think is a really shocking number that we need to think about and question.

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 And they further reveal that the artists are using, for the most part,

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 so there's a list of tools that are most used, and that's ChatGPT, Gemini, Cloud, Midjourney, no surprise, like big corporation type of tools.

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 And so at the Meta Creation Lab,

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 we're in the business of using creative AI

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 to automate partially or completely creative tasks,

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 but we don't use anyone else's tool.

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 What we mean by meta creation is really in the tradition of generative art,

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 making a machine that make art partially

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 or completely and I think that's an important distinction.

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 And in order to do so, we have a research creation methodology in which we actually

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 do develop algorithm, we work with the industry and we release open source software that we

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 develop for everyone to use and artist to use and therefore we work with artists and both second person methodology

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 with artists with artistic residency and first person ourselves as artists with our tool

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 and we really find that it's important to have what we call participatory design.

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 This idea that if artists are involved in the making even of the algorithm, the interfaces

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 and the development of those tools then we end up somewhere else.

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 And so that's the distinction I wanted to start with,

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 and with that I give you Kian.

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 Thank you.

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 So yeah, let me start with the concept for this talk.

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 We'll begin by defining four terms that guide the talk,

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 and by musical metacreation I mean the design of computational systems that can participate in creative music making and by musical agents,

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 I mean computational performers that can listen, respond, transform material and act within a musical embodiment.

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 Co-creation refers to a process where human and machine

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 actions shape the artwork together rather than one simply controlling the other.

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 And then lastly, the digital afterlife refers to the reactivation of historical musical

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 traces through computation, not as resurrection of the exact replica, but as transformed presence

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 within a new performance context.

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 And so in revival artwork, the more interesting question is how agency is organized in performance.

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 So here, the central argument is that revival artwork is a live metacreative system rather

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 than a fixed AI assisted composition and musical form emerges through real time improvisation

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 and feedback among human performers, curated sonic traces and musical agents, generative

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 visuals and audio

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 visual systems.

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 Each action changes what can happen next, so the work is continuously shaping performance.

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 So here the key idea is liveness within an ecology of relationships and the system is

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 neither fully performer controlled nor autonomous. So responses are shaped by the corpus,

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 model design, live electronics,

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 mappings and improvisational decisions.

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 So authorship is therefore redistributed rather than removed

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 across curation, system design,

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 rehearsal and live interaction.

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 So in revival artwork, like composition

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 becomes the design of conditions from which form can emerge in real time.

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 So here, our paper is grounded in three conceptual anchors.

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 First, revival follows a research-creation approach where artistic practice, technological development, crafting, trading generative system as artistic instrument

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 shapes through data set selection,

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 parameter and interface design.

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 And also I mean including rehearsal of course

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 as an iterative design process.

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 And third, it adopts a small data ethics,

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 transforming and re-conceptualizing specific historical

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 and collective materials rather than simply reproducing them and trained on large-scale

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 data set. So for us, model crafting also means the learning,

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 tuning and rehearsing the technical system like a musical instrument and these technical choices are therefore also artistic decisions.

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 And small data ethics similarly shifts the focus away from large-scale extraction

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 toward the responsible transformation of specific materials within a live artwork.

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 And here, Makat and Makatart are the two main audio-based agents in the revival artwork,

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 and both begin with the curated recording selected by the artist and the system segment and analyzes these sounds,

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 turning the corpus into a landscape of related timbres and remembered sequences.

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 And Makata-eigen explores these landscapes through temporal modeling,

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 allowing it to propose where the music might move next,

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 and Makatarte-eigen listens more directly to the live performance and

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 finds related sound fragments and recombines them as an evolving music mosaic.

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 And it can operate both reactively and proactively.

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 And artistically, the agents do not simply replay the corpus, they reshape remembered

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 material in the moment and creating an ongoing dialogue in which the performers

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 also listen, respond, and redirect the system.

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 And here, the visual system extends the co-creative approach into image and lighting.

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 Revival combines Autorium, a small data GAN-based visual synthesizer with Touch Designer and

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 performer-facing Touch OSC interface.

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 And the VJ can shape scenes and effects in real time while also audio features such as

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 density, amplitude and rhythm influence visual motion and lighting.

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 Rather than serving as a background decoration, the visuals become a performable layer of

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 the work and allowing image and light to participate in the same

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 feedback loop as the musical agents and the human performers.

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 So here in performance, improvisation connects all parts of the revival artwork and the percussion

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 gestures can be captured, transformed or extended by the agent and while live electronics, visuals

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 and lighting continuously reshape the texture and perception of the performance.

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 So rather than following a simple cause and effect chain,

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 the work operates through recursive feedback between human actions and system responses.

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 So the MUTEC Montreal performance was particularly important

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 because it tested these relationships under real performance conditions.

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 And the rehearsal helped us explore the balance

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 between control and uncertainty while on stage

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 those relationships became more dynamic.

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 And the performer changes the system

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 and the system influences the performer's next decision

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 and the visual and lighting layers reshape

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 how those interactions are experienced.

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 One result of this ecology is distributed agency.

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 During performance, it can be difficult to tell

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 whether an event comes from a human performer,

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 an agent, or several layers of transformation,

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 and our paper treats this ambiguity as an aesthetic condition.

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 And this also connects to digital afterlife,

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 and revival artwork does not attempt to resurrect

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 or imitate DC's composer composer as exact replica, instead historical

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 musical fragments become transformed traces reactivated through machine

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 listening, recombination and improvisation including live performance.

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 And in this sense digital afterlife refers to how musical materials and

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 gestures continue to circulate through

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 new technological and performative contexts where memory becomes unstable, transformed,

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 and shared between human computational and historical elements.

380
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 So to conclude, Revival presents a co-creative audiovisual system where musical agents, generative

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 visuals, and human performers shape the work together, and it also explores a small data approach in which historical materials are

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00:29:30.079 --> 00:29:34.980
 transformed rather than simply reproduced, and while research, artistic practice, and

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 system development evolve together.

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 So more broadly, Revival Artwork treats AI not as a replacement of artistic agency, but

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 as part of shared and negotiated performance ecology.

386
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 And so the value lies not only in the final

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 audio-visual result, but also in the process

388
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 of building, rehearsing, and reflecting

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 on these relationships.

390
00:29:56.380 --> 00:29:58.660
 So thank you very much for listening.

391
00:29:58.660 --> 00:30:00.920
 So we'll now briefly watch a short excerpt

392
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 from the revival performance.

393
00:30:10.980 --> 00:30:14.440
 short after from the revival revival performance sorry the sound is not coming true

394
00:30:22.000 --> 00:30:23.059
 Increase the volume or something or

395
00:31:06.099 --> 00:31:06.259
 hear the sounds All right.

396
00:31:07.720 --> 00:31:07.819
 And so to conclude here,

397
00:31:09.160 --> 00:31:10.940
 this is a good example of a project that brings together a number of tools

398
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 that are not just used in this project,

399
00:31:13.039 --> 00:31:14.039
 but are also released.

400
00:31:14.619 --> 00:31:15.920
 And it's important to say that

401
00:31:15.920 --> 00:31:16.740
 because we live in a world

402
00:31:16.740 --> 00:31:18.359
 where there's increasingly in our field

403
00:31:18.359 --> 00:31:19.579
 and in creative fields

404
00:31:19.579 --> 00:31:20.880
 a polarization around AI

405
00:31:20.880 --> 00:31:22.059
 with a lot of haters

406
00:31:22.059 --> 00:31:23.740
 and a lack of nuance in the discourse.

407
00:31:24.099 --> 00:31:27.859
 And that's totally understandable because if you're being told, and you are, that your

408
00:31:27.859 --> 00:31:31.019
 work is being stolen and we're going to try to replace you, you're going to be pissed.

409
00:31:31.019 --> 00:31:32.579
 So people are pissed.

410
00:31:32.579 --> 00:31:37.200
 But it turns out there is a light at the end of this possible tunnel because there's diversity

411
00:31:37.200 --> 00:31:39.420
 in AI like in everything else.

412
00:31:39.420 --> 00:31:43.519
 It's hard to compete with the corporate discourse relayed by the media.

413
00:31:43.519 --> 00:31:50.319
 It's hard to surface above that noise, but there is a truly option there.

414
00:31:50.319 --> 00:31:56.539
 And so some of the tools that are used in Revival are available for everyone to use,

415
00:31:56.539 --> 00:32:01.759
 and in fact there's training material online about those tools, whether it's MIDI GPT,

416
00:32:01.759 --> 00:32:07.339
 a computer-assisted composition system that is used here to extend Wagner's opening of the Rheingold

417
00:32:07.339 --> 00:32:11.339
 as part of this project of reviving dead composers on stage,

418
00:32:11.640 --> 00:32:17.660
 Autolium, the small data and model crafting visual synthesizer,

419
00:32:18.160 --> 00:32:22.119
 and Fragmenta, which allows to do audio generation

420
00:32:22.119 --> 00:32:26.799
 and crafting small personalized model,

421
00:32:26.799 --> 00:32:30.000
 as well as a collection of model bending object in a Comfy UI.

422
00:32:30.000 --> 00:32:33.200
 All of that is available and doesn't require a line of code

423
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 because artists don't want necessarily to become coders.

424
00:32:35.599 --> 00:32:40.400
 And with that, I'll conclude by thanking the funding bodies that are supporting this work in Canada,

425
00:32:40.400 --> 00:32:48.619
 the CHIRC for social science, the National Science and Engineering Research Council for the technical work of developing those tools, and the Canada Council for the

426
00:32:48.619 --> 00:32:51.180
 Arts for supporting the making of artworks.

427
00:32:51.180 --> 00:32:55.220
 And I thank you all for your attention.

428
00:32:55.220 --> 00:32:59.940
 Thank you.

429
00:32:59.940 --> 00:33:01.859
 Any questions?

430
00:33:01.859 --> 00:33:09.420
 We have time for maybe two short questions. Okay, maybe I'll start with one.

431
00:33:09.700 --> 00:33:15.839
 I'm actually, it's really interesting to think about co-creation with AI, but what is the

432
00:33:15.839 --> 00:33:21.980
 subjective experience of the artist when they're co-creating with AI? Is there a time when you go

433
00:33:21.980 --> 00:33:27.079
 like, oh, I didn't like what they're doing, and oh, I want to control it more, but I can't.

434
00:33:27.079 --> 00:33:30.059
 Is there some sort of this kind of interaction

435
00:33:30.059 --> 00:33:33.799
 that can be quite negative or very positive?

436
00:33:36.579 --> 00:33:40.200
 Yeah, well, we rehearse with the musical agents,

437
00:33:40.200 --> 00:33:41.940
 and in fact, in some of the latest models

438
00:33:41.940 --> 00:33:44.859
 of the musical agents, we can give them feedback

439
00:33:44.859 --> 00:33:45.960
 of what happened on the rehearsal

440
00:33:45.960 --> 00:33:48.700
 because like any co-creation between humans

441
00:33:48.700 --> 00:33:51.440
 we talk to each other about what's happening typically

442
00:33:51.440 --> 00:33:56.660
 and then we try to do that with the agents as well

443
00:33:56.660 --> 00:33:58.420
 by saying hey I like that, do more of that

444
00:33:58.420 --> 00:33:59.819
 I don't like that, do less of that

445
00:33:59.819 --> 00:34:02.220
 so that eventually those rehearsals are not just about

446
00:34:02.220 --> 00:34:06.359
 fine tuning the data sets and retraining things so that we are up with it,

447
00:34:06.640 --> 00:34:11.199
 but that we can eventually really iterate and craft those models

448
00:34:11.199 --> 00:34:13.800
 so that they act as we want.

449
00:34:13.920 --> 00:34:18.079
 But there is an inherent risk in putting a machine playing live with you on stage

450
00:34:18.079 --> 00:34:21.159
 and when things don't go well, which with technology we all know

451
00:34:21.159 --> 00:34:24.380
 is more fun than we would like to,

452
00:34:24.900 --> 00:34:27.199
 then that risk can manifest itself.

453
00:34:28.980 --> 00:34:30.599
 And I think Ryan over there had a question,

454
00:34:30.719 --> 00:34:31.679
 and I see one at the front.

455
00:34:32.900 --> 00:34:33.340
 Hi.

456
00:34:34.579 --> 00:34:37.679
 So generally, when I worked on music visualization,

457
00:34:37.679 --> 00:34:43.059
 there's a communication layer between the music and the graphics,

458
00:34:43.380 --> 00:34:47.659
 and usually it's done with FFT or MIDI or OSC.

459
00:34:47.659 --> 00:34:53.860
 What I find interesting here is because both are generated by the same agent, you don't

460
00:34:53.860 --> 00:34:57.239
 need that communication. Is that correct? Do I understand that correctly?

461
00:34:57.239 --> 00:35:06.639
 Yeah, there is part of that, but there is also Vijay Amagi, who is live, intervening on some of the visual parameters.

462
00:35:06.639 --> 00:35:09.840
 And so there's, here again, a bit of co-creation

463
00:35:09.840 --> 00:35:13.000
 between Vijay Amagi, so human Vijay,

464
00:35:13.000 --> 00:35:15.960
 and what the agents are doing.

465
00:35:15.960 --> 00:35:16.800
 Cool, thank you.

466
00:35:19.880 --> 00:35:22.880
 Yeah, there's another, oh, there's another, yeah, sorry.

467
00:35:23.800 --> 00:35:25.059
 Take this one, Kian.

468
00:35:25.059 --> 00:35:30.059
 Hi, I'm also a music producer,

469
00:35:30.960 --> 00:35:35.960
 co-create with AI, but I'm very interested in this software,

470
00:35:36.460 --> 00:35:40.679
 but what the main key differences between this

471
00:35:40.679 --> 00:35:45.000
 and like mainstream platforms like Suno, etc?

472
00:35:45.000 --> 00:35:53.000
 Yeah. Okay. Yeah, so our system is nothing related to Suno and Udio. It's more

473
00:35:53.000 --> 00:35:58.199
 of a curated by us and we also trade our material as a small data approach as opposed to big

474
00:35:58.199 --> 00:36:03.199
 data approach. So it's like a, that's the main difference. And we tend to have more

475
00:36:03.199 --> 00:36:05.960
 control and the system that we are using is,

476
00:36:06.500 --> 00:36:08.519
 most of the people we are using

477
00:36:08.519 --> 00:36:10.639
 is like a techno-fluent musicians.

478
00:36:10.840 --> 00:36:13.920
 They know how to code and like a Maxim SP and all that,

479
00:36:14.039 --> 00:36:17.280
 and they craft their tools based on specific needs.

480
00:36:17.480 --> 00:36:19.599
 So it's like a fairly different from the,

481
00:36:19.920 --> 00:36:21.800
 like a big data model, like a Suno and Udio.

482
00:36:22.079 --> 00:36:24.179
 Personally, I'm opposed to Suno and Udio.

483
00:36:25.480 --> 00:36:29.900
 Yeah, I would, you know, those are very radical different sort of approaches.

484
00:36:29.900 --> 00:36:32.659
 And here we're talking about very small asset,

485
00:36:32.659 --> 00:36:34.519
 a few hours of recordings.

486
00:36:34.519 --> 00:36:37.460
 And so it's my data, it's my model, it's my artwork.

487
00:36:37.460 --> 00:36:39.559
 When you prompt Suno, you don't have copyright

488
00:36:39.559 --> 00:36:40.400
 over what comes out.

489
00:36:40.400 --> 00:36:41.840
 So that's, I think.

490
00:36:41.840 --> 00:36:49.079
 And the question, the authorship when you use Suno seems to be a bit diluted and so I think the differences for us are

491
00:36:49.079 --> 00:36:52.019
 important.

492
00:36:52.019 --> 00:36:56.960
 I think we need to move on. Thank you so much, thanks again to

493
00:36:56.960 --> 00:36:59.360
 speakers.

494
00:37:08.900 --> 00:37:09.159
 And our next speaker is Albert Borek-Duran,

495
00:37:12.320 --> 00:37:12.480
 who worked with Ada Loura-Docrespo on Synapticon,

496
00:37:15.460 --> 00:37:34.559
 creative alignment, and the brain AI model interface. Good morning everyone, thank you so much for being here.

497
00:37:34.559 --> 00:37:41.440
 Imagine a building in which every room can be seen from a central tower.

498
00:37:41.440 --> 00:37:47.679
 The people inside the rooms cannot know when they are being watched. They can only know

499
00:37:47.679 --> 00:37:57.519
 that they might be watched. This is the essential mechanism of Panopticon. Its power does not depend

500
00:37:57.519 --> 00:38:05.000
 on a guard looking continuously. The architecture itself performs the act of observation.

501
00:38:06.500 --> 00:38:09.599
 The possibility of being seen becomes something

502
00:38:09.599 --> 00:38:12.699
 each person carries within them.

503
00:38:12.699 --> 00:38:15.880
 And Jeremy Bentham imagined this structure

504
00:38:15.880 --> 00:38:19.119
 as a practical machine and then later Foucault

505
00:38:19.119 --> 00:38:21.599
 made it a philosophical one.

506
00:38:21.599 --> 00:38:24.380
 A model of understanding how visibility

507
00:38:24.380 --> 00:38:28.000
 can organize bodies, attention and behavior.

508
00:38:28.000 --> 00:38:35.000
 But what happens if we turn this architecture inward?

509
00:38:35.000 --> 00:38:40.000
 What if the rooms become synapses?

510
00:38:40.000 --> 00:38:43.000
 What if the central tower becomes a computational model?

511
00:38:43.000 --> 00:38:49.159
 What if the object of observation is no longer the body, but a trace of our cognition?

512
00:38:49.820 --> 00:38:52.500
 And at that point, who is watching whom?

513
00:38:53.619 --> 00:38:57.840
 This speculative reversal gives the project its name, Synapticon.

514
00:39:00.119 --> 00:39:09.019
 Synapticon is an artistic research project situated at the interface of the brain and foundational AI models.

515
00:39:09.280 --> 00:39:19.880
 It brings together brain-computer interfaces, VCIs, LLMs, large language models, real-time audiovisual systems, and live performance.

516
00:39:20.699 --> 00:39:23.860
 And at its center, there's a simple sequence.

517
00:39:23.880 --> 00:39:24.960
 And at its center, there's a simple sequence.

518
00:39:27.840 --> 00:39:28.159
 Brainwaves become natural language.

519
00:39:30.719 --> 00:39:31.380
 Natural language becomes aesthetics.

520
00:39:35.460 --> 00:39:36.099
 But the simplicity of this sentence is a bit deceptive, I would say.

521
00:39:38.960 --> 00:39:40.019
 Nothing passes through the system untouched.

522
00:39:47.920 --> 00:39:53.880
 A neural signal is captured, filtered, divided into time windows, encoded, interpreted through the prior structure of a language model, and then routed into an audiovisual environment

523
00:39:53.880 --> 00:39:57.579
 that has been carefully authored in advance.

524
00:39:57.579 --> 00:40:14.079
 So Synapticon is therefore not a transparent window into a mind. It's an apparatus for staging everything that happens between an

525
00:40:14.079 --> 00:40:31.679
 oral event and its public meaning. The system begins with a 16-channel OpenBCI headset and across 30 EEG sessions we collected

526
00:40:31.679 --> 00:40:36.179
 a few thousand paintings between neural recordings and text.

527
00:40:36.179 --> 00:40:49.239
 The training material was intentionally bounded, 108 curated sentences comprising 623 words which this makes a total of 3,210

528
00:40:49.239 --> 00:40:55.559
 trials. During data collection sentences were presented and internally

529
00:40:55.559 --> 00:41:01.940
 vocalized. 10 second EEG windows were aligned with those sentence and in

530
00:41:01.940 --> 00:41:11.500
 performance the system works with a streaming windows of approx five seconds and produces partial textile outputs.

531
00:41:11.500 --> 00:41:16.500
 These numbers matter because they define what the work can do and partly because

532
00:41:16.500 --> 00:41:23.320
 they define what it can honestly claim. The project makes something very

533
00:41:23.320 --> 00:41:27.940
 fragile public which is a probabilistic relation between

534
00:41:27.940 --> 00:41:36.519
 neural dynamics, a learned linguistic space and an out-of-order performance system.

535
00:41:36.519 --> 00:41:44.880
 The text that appears is neither a direct transcription nor arbitrary noise.

536
00:41:44.880 --> 00:41:46.699
 It lies in between.

537
00:41:46.699 --> 00:41:50.179
 The language model imposes a linguistic prior

538
00:41:50.179 --> 00:41:53.500
 on complex and noisy neural features.

539
00:41:53.500 --> 00:41:56.579
 So in other words, it gives the signal a field

540
00:41:56.579 --> 00:42:00.460
 of grammatical, lexical, and associative possibilities.

541
00:42:01.820 --> 00:42:08.099
 This means that the machine does not simply find a sentence waiting inside the brain.

542
00:42:08.099 --> 00:42:15.239
 It participates in producing the conditions under which something sentence-like can appear.

543
00:42:15.239 --> 00:42:22.880
 For us, decoded text is best understood as creative index.

544
00:42:22.880 --> 00:42:24.719
 An index points.

545
00:42:24.719 --> 00:42:27.920
 It does not contain the thing itself.

546
00:42:27.920 --> 00:42:34.320
 Like smoke can index fire, a footprint can index a body that has already left.

547
00:42:34.320 --> 00:42:42.300
 In synapticon, a textual fragment points towards a relation among intention, signal, model,

548
00:42:42.300 --> 00:42:43.679
 and context.

549
00:42:43.679 --> 00:42:46.360
 It becomes a cue that can organize transition,

550
00:42:46.360 --> 00:42:51.880
 images, sounds and attention. And this distinction I think it's very crucial.

551
00:42:51.880 --> 00:42:58.719
 If we call this mind reading, the output acquires an authority it has not really

552
00:42:58.719 --> 00:43:06.619
 earned. If we call this meaningless noise, We erase the situation relation that is producing it.

553
00:43:06.619 --> 00:43:12.199
 So the artwork occupies this unstable distance between these two claims.

554
00:43:12.199 --> 00:43:20.860
 It asks the audience to feel that instability rather than resolving it for them.

555
00:43:20.860 --> 00:43:27.480
 After the coding, the text enters a pre-created library of audiovisual scenes built in TouchDesigner.

556
00:43:28.079 --> 00:43:34.239
 The prototype does not depend on unconstrained real-time image generation, although this is our goal.

557
00:43:34.940 --> 00:43:39.019
 This is an important artistic decision right now.

558
00:43:39.019 --> 00:43:45.199
 Images, transformations, filters, compositing rules, scene changes, and temporal behaviors are

559
00:43:45.199 --> 00:43:47.960
 prepared as vocabulary.

560
00:43:47.960 --> 00:43:54.500
 The decoded text enters that vocabulary as a semantic and performative layer.

561
00:43:54.500 --> 00:43:58.579
 The Navleton Live operates as the sound engine.

562
00:43:58.579 --> 00:44:04.159
 It also sends control message to Touch Designer, coordinating part of the movement between

563
00:44:04.159 --> 00:44:07.179
 the visual chapters.

564
00:44:07.179 --> 00:44:10.639
 And the sonic architecture is also site-specific.

565
00:44:10.639 --> 00:44:15.480
 Pure tone tones are calculated in relation to the physical dimensions of the venue, of

566
00:44:15.480 --> 00:44:20.179
 the room, exciting low frequency.

567
00:44:20.179 --> 00:44:26.960
 And at certain acoustic notes, the audience can feel vibrations moving through their bodies from the floor upward.

568
00:44:28.239 --> 00:44:38.000
 So the brain produces data, the model produces language, and the room answers with pressure, with light, with rhythm, and with scale.

569
00:44:38.000 --> 00:44:49.659
 So what began as an internal neural variation returns as an external collective sensation.

570
00:44:49.659 --> 00:44:56.099
 To describe this relation, we use the term creative alignment.

571
00:44:56.099 --> 00:45:01.960
 In conventional AI discourse, alignment often means bringing a system's behavior closer

572
00:45:01.960 --> 00:45:04.619
 to our human goals or values.

573
00:45:04.619 --> 00:45:05.880
 Here the question is a bit more

574
00:45:05.880 --> 00:45:13.639
 specific. How can a live system sustain an intelligible relation among

575
00:45:13.639 --> 00:45:20.159
 performer intention, neural capture, model priors, audiovisual design and audience

576
00:45:20.159 --> 00:45:26.599
 perception? So creative alignment does not eliminate ambiguity, it makes

577
00:45:26.599 --> 00:45:33.440
 ambiguity usable in some sense. And we describe it through four

578
00:45:33.440 --> 00:45:41.260
 connected layers. Signal alignment asks how noisy low signal neural activity

579
00:45:41.260 --> 00:45:45.159
 becomes technically processable through windowing, filtering,

580
00:45:45.159 --> 00:45:48.320
 and temporal encoding.

581
00:45:48.320 --> 00:45:55.039
 Semantic alignment asks how those features enter the learned structure of a language

582
00:45:55.039 --> 00:46:01.219
 model and emerge as fragments of natural language.

583
00:46:01.219 --> 00:46:12.000
 Narrative alignment asks what happens when those fragments are mapped onto images, sound, pacing, transitions and sensory intensity.

584
00:46:13.000 --> 00:46:31.519
 And finally, social alignment asks how an audience interprets what it encounters. Does it attribute an output to the performer, to the model, to the artist slash creative technologist, or to the situation created among all of them?

585
00:46:32.480 --> 00:46:37.260
 Each layer aligns something, but each layer also introduces a new displacement.

586
00:46:38.420 --> 00:46:42.400
 There is no single moment at which meaning arrives complete.

587
00:46:43.460 --> 00:46:47.059
 Meaning is negotiated across the whole chain.

588
00:46:48.659 --> 00:46:52.380
 This changes, obviously, how we speak about authorship.

589
00:46:53.380 --> 00:46:56.500
 Synapticon is not authored by the performer alone.

590
00:46:56.739 --> 00:46:58.639
 It's not authored by the model alone.

591
00:46:58.639 --> 00:47:03.400
 And it's not authored only by the people who build the apparatus.

592
00:47:04.300 --> 00:47:07.500
 The performer generates neural events,

593
00:47:07.500 --> 00:47:12.000
 the model turns variation into textual possibilities,

594
00:47:12.000 --> 00:47:19.500
 the artists and developers decide how that text can act inside the audiovisual system,

595
00:47:19.500 --> 00:47:23.000
 and the live environment shapes timing and scale.

596
00:47:23.000 --> 00:47:28.619
 And the audience finally resolves all that ambiguity into experience meaning.

597
00:47:31.679 --> 00:47:35.239
 Authorship is distributed, but it's not equal.

598
00:47:37.579 --> 00:47:41.800
 Agency is distributed, but it's not equal.

599
00:47:41.800 --> 00:47:47.139
 The point is to make these differences or these different agencies and their different

600
00:47:47.139 --> 00:47:50.219
 responsibilities perceptible.

601
00:47:50.219 --> 00:47:55.619
 On stage, the boundary between intention and inference remains visible.

602
00:47:55.619 --> 00:47:57.880
 That boundary is not a technical defect.

603
00:47:57.880 --> 00:48:02.300
 It's actually the material of the work.

604
00:48:02.300 --> 00:48:08.000
 And when brain-derived outputs become public, ethics is not an appendix.

605
00:48:08.000 --> 00:48:10.000
 It's part of its form.

606
00:48:10.000 --> 00:48:16.000
 Neuro-rights scholarship gives us the necessary vocabulary.

607
00:48:16.000 --> 00:48:22.000
 Cognitive liberty, mental privacy, mental integrity, psychological continuity.

608
00:48:22.000 --> 00:48:26.639
 These ideas are often presented as protections for a rapidly approaching

609
00:48:26.639 --> 00:48:35.119
 future and in this work they are already practical questions. What is exposed? Who controls the

610
00:48:35.119 --> 00:48:48.000
 exposure? Who can interrupt it? What authority does the audience grant to the machine? And what remains private even after a fragment appears on screen?

611
00:48:48.000 --> 00:48:54.000
 This is not a contradiction of the project's openness.

612
00:48:54.000 --> 00:48:56.000
 It's a boundary within it.

613
00:48:56.000 --> 00:49:01.000
 Perhaps cognitive liberty also includes the right to opacity.

614
00:49:01.000 --> 00:49:07.860
 The right to remain opaque, even to the systems who have trained on ourselves.

615
00:49:07.860 --> 00:49:15.139
 This is why Synapticon is both an artwork and an apparatus. As an apparatus

616
00:49:15.139 --> 00:49:19.900
 it includes the headset, the data set, pre-processing choices, model priors,

617
00:49:19.900 --> 00:49:25.380
 decoding parameters, interfaces, timing systems, and a stage logic.

618
00:49:33.199 --> 00:49:34.460
 And as an artwork, it composes all these elements into a public encounter with partial cognition.

619
00:49:41.059 --> 00:49:41.639
 So the research does not exist only before the performance in the lab or after it in the analysis.

620
00:49:47.039 --> 00:49:52.360
 The performance is itself a way of producing knowledge. The performance does not demonstrate that the interface has disappeared, it actually

621
00:49:52.360 --> 00:49:55.480
 gives the interface a sensible form.

622
00:49:55.480 --> 00:50:02.119
 We can see it, we can hear it, and even at certain frequencies we can feel it vibrating

623
00:50:02.119 --> 00:50:04.619
 in our bodies.

624
00:50:04.619 --> 00:50:09.559
 So let us finally return back to the panopticon.

625
00:50:09.559 --> 00:50:14.119
 In the classical model, power belongs to an observer

626
00:50:14.119 --> 00:50:15.960
 who may remain invisible.

627
00:50:15.960 --> 00:50:19.019
 The watched subject is made visible

628
00:50:19.019 --> 00:50:23.820
 while the machinery of watching disappears.

629
00:50:23.820 --> 00:50:26.780
 Synopticon tries to reverse that condition.

630
00:50:27.599 --> 00:50:28.679
 The performer is visible,

631
00:50:29.460 --> 00:50:31.260
 but so are the mediators,

632
00:50:31.480 --> 00:50:33.119
 the electrodes, the filters, the windows,

633
00:50:33.320 --> 00:50:35.239
 the training sentences, the model priors,

634
00:50:35.360 --> 00:50:37.199
 the mappings, the scene libraries,

635
00:50:37.800 --> 00:50:40.739
 the sound cues, and acts of interpretation.

636
00:50:41.340 --> 00:50:43.460
 It can show that every output

637
00:50:43.460 --> 00:50:45.280
 has traveled through an

638
00:50:45.280 --> 00:50:50.500
 architecture and perhaps the most important output is not that sentence

639
00:50:50.500 --> 00:50:56.239
 that appears on the screen. If the panopticon asks how architecture

640
00:50:56.239 --> 00:51:05.000
 governs what can be seen, synopticon asks who authors the visible when the material is cognition.

641
00:51:07.059 --> 00:51:11.300
 The mind is not opened yet.

642
00:51:11.300 --> 00:51:16.300
 The relation is performed and cognition keeps expanding.

643
00:51:17.320 --> 00:51:18.159
 Thank you.

644
00:51:26.400 --> 00:51:30.619
 Thank you. We have maybe one quick question time.

645
00:51:30.619 --> 00:51:32.719
 Okay.

646
00:51:32.719 --> 00:51:36.940
 I'll just have one quick question.

647
00:51:36.940 --> 00:51:41.860
 So do you think that in time, if you do a lot of these kind of interactions, do you

648
00:51:41.860 --> 00:51:51.480
 think that it might actually converge where the language model will be able to respond to the user and to the audience in a way that's

649
00:51:51.480 --> 00:51:53.599
 actually meaningful to us?

650
00:51:53.599 --> 00:51:58.639
 I guess, yes.

651
00:51:58.639 --> 00:52:07.760
 I was thinking like in the way we trained the model, In this case, it could be even interpreted as a toy version,

652
00:52:07.760 --> 00:52:11.400
 because we're talking about a very unipersonal data set,

653
00:52:11.400 --> 00:52:15.960
 just with myself, and with very strict boundaries and conditions.

654
00:52:15.960 --> 00:52:21.000
 But again, if we start playing around introducing new variables,

655
00:52:21.000 --> 00:52:27.059
 new ways of this language model to express itself, let's put it that way, I'm sure we could find ways

656
00:52:27.059 --> 00:52:31.239
 of incorporating, of adding, in this case,

657
00:52:31.239 --> 00:52:33.219
 you were suggesting the audience,

658
00:52:33.219 --> 00:52:36.280
 even to enhance somehow this feedback loop

659
00:52:36.280 --> 00:52:38.760
 between performer and audience, for sure.

660
00:52:38.760 --> 00:52:43.760
 I mean, being performed this for some time now,

661
00:52:44.300 --> 00:52:53.280
 I have to say that the audience changes a lot how the performance goes.

662
00:52:53.280 --> 00:52:56.239
 I mean, because I'm in that specific environment,

663
00:52:56.239 --> 00:53:03.159
 I'm feeling the vibes or how the audience reacts to what they are seeing,

664
00:53:03.159 --> 00:53:04.960
 and that thing influences me,

665
00:53:04.960 --> 00:53:10.159
 which is in real-time influences the whole architecture that I was sharing.

666
00:53:10.159 --> 00:53:17.079
 Thank you. Let's thank the speaker.

667
00:53:22.079 --> 00:53:25.980
 I believe the next presentation is online.

668
00:53:25.980 --> 00:53:27.880
 This is by Shachma Abdullah.

669
00:53:27.880 --> 00:53:33.239
 She's going to present Ouroboros, the anti-game, diagnosing the achievement subject through

670
00:53:33.239 --> 00:53:34.239
 real-time EEG.

671
00:53:34.239 --> 00:53:35.239
 Hello, everyone.

672
00:53:35.239 --> 00:53:36.239
 My name is Shachma.

673
00:53:36.239 --> 00:53:54.579
 I'm a student atciplinary artist, designer and researcher joining you

674
00:53:54.579 --> 00:54:00.000
 virtually from Singapore. I'm really gutted I can't be there in lens with you today due

675
00:54:00.000 --> 00:54:05.920
 to some administrative issues, but I'm very excited to share my paper with you. The project I'm

676
00:54:05.920 --> 00:54:12.079
 presenting is called Ouroboros, we init the anti-game diagnosing the achievements subject

677
00:54:12.079 --> 00:54:19.920
 to real-time EEG. This project is a BCI interactive installation driven by real-time brainwave data

678
00:54:19.920 --> 00:54:25.940
 but at its core it's really an exploration of why we literally cannot stop trying so hard.

679
00:54:26.500 --> 00:54:30.820
 It is a diagnostic tool for what we might call the achievement subject.

680
00:54:31.699 --> 00:54:33.519
 This is the setup of the installation.

681
00:54:34.139 --> 00:54:36.960
 A participant walks up, sits down at a small console.

682
00:54:37.739 --> 00:54:42.000
 First, an iPad prompts them with a single, slightly loaded question.

683
00:54:42.500 --> 00:54:46.239
 What are you currently working towards in your life?

684
00:54:51.119 --> 00:54:57.199
 After entering a personal goal, they put on a Muse 2 EG headband and pick up a controller they have been handed. However, the controller is merely a decoy. What is actually driving the

685
00:54:57.199 --> 00:55:07.219
 visuals is not their hands, but their brainwaves. The screen in front of them begins rendering a live environment of pixelated forms that gather and fall apart.

686
00:55:07.920 --> 00:55:14.260
 For this experiment, I observed 14 participants across different ages and briefing conditions,

687
00:55:14.699 --> 00:55:17.840
 yet every single one responded the exact same way.

688
00:55:18.360 --> 00:55:24.000
 Upon discovering that their effort caused the visual to collapse, they applied even more effort.

689
00:55:24.000 --> 00:55:30.000
 caused the visual to collapse, they applied even more effort. Seven of them were told in advance in plain language that trying would destabilize the image.

690
00:55:30.000 --> 00:55:39.000
 They could recite the rule back to me, but it wouldn't matter because the reflex of theirs simply ran faster than the knowing.

691
00:55:39.000 --> 00:55:45.119
 That gap between what the cortex understands and what the rest of the nervous system does

692
00:55:45.119 --> 00:55:52.539
 anyway is the conceptual center of this entire project. The harder a person

693
00:55:52.539 --> 00:55:58.019
 tries to stabilize the visual on the screen, the more violently it fragments.

694
00:55:58.019 --> 00:56:03.340
 Touching briefly on the project's lineage, PCIe Art has a strong tradition of

695
00:56:03.340 --> 00:56:05.960
 using biological signals as raw material,

696
00:56:06.420 --> 00:56:14.480
 seen in the works of artists like Anadol, Aksin, Terrell, and Ikeda. However, almost all of these

697
00:56:14.480 --> 00:56:22.320
 works rewards calm and pernicious agitation. While that is a comforting orientation, it quietly

698
00:56:22.320 --> 00:56:26.099
 reproduces the exact same logic as the productivity

699
00:56:26.099 --> 00:56:32.719
 software it is sometimes pitched against. And I know there are a lot of works that are BCI

700
00:56:32.719 --> 00:56:48.679
 related today, and I'm excited to experience them, but I could not find a sustained version of a reward gradient in the existing literature and I treat that

701
00:56:48.679 --> 00:56:51.340
 absence as diagnostic in itself.

702
00:56:51.340 --> 00:56:58.099
 So my project aims to build an anti-game, an installation that sustains this inverted

703
00:56:58.099 --> 00:56:59.440
 gradient.

704
00:56:59.440 --> 00:57:12.199
 So to understand why we double down on effort even when it actively hurts us, we have to look at the biology of striving. And I very briefly touch on four key sources that built this

705
00:57:12.199 --> 00:57:19.440
 biological case. Perridge and Robinson tells us that wanting is dopaminergic, it is structurally

706
00:57:19.440 --> 00:57:26.980
 insatiable. Shules demonstrates that dopamine flies on prediction error rather than upon arrival at a goal.

707
00:57:27.400 --> 00:57:36.800
 Furthermore, Sapolsky and Lemke point out chronic stress actually erodes the prefrontal capacity that would otherwise allow to step back and reflect.

708
00:57:37.539 --> 00:57:46.739
 So simply knowing that you are in a toxic loop does not interrupt it because your subcortical system acts much faster than your conscious

709
00:57:46.739 --> 00:57:53.559
 reasoning. However, biological vulnerability only evolves into a civilizational structure with a

710
00:57:53.559 --> 00:57:59.159
 little help. So I have layered the Calvinistic work ethic, the Benetian manufacture of desire,

711
00:57:59.159 --> 00:58:03.760
 and finally what Byung-Chul Han terms the achievement subject in his book,

712
00:58:05.159 --> 00:58:06.159
 what Byung-Chul Han terms the achievement subject in his book, The Burnout Society.

713
00:58:12.699 --> 00:58:13.400
 We now command ourselves so efficiently that we no longer need an external boss to crack the whip.

714
00:58:18.519 --> 00:58:26.920
 And as Han argues, burnout is not a malfunction of the society, it is actually treated as proof of your capacity. Now, how do we measure this in the gallery? The anti-game maps beta-bad activity,

715
00:58:27.199 --> 00:58:31.900
 which we generally associate with focused goal-oriented cognition to visual fragmentation.

716
00:58:32.460 --> 00:58:38.599
 When your beta waves go up, the world falls down. Ironically, the exact state that every school,

717
00:58:38.599 --> 00:58:46.480
 workplace, and productivity app has trained you to maintain is the state that accelerates collapse in this installation

718
00:58:46.480 --> 00:58:52.159
 i want to be precise though because the eeg literature on beta waves is contested so i'm

719
00:58:52.159 --> 00:58:57.920
 using it strictly as an operational marker within this specific paradigm not making a universal

720
00:58:57.920 --> 00:59:07.360
 claim about what beta means everywhere and technically speaking we pull a 256 hertz signal from the Muse 2 via OSC,

721
00:59:07.360 --> 00:59:12.400
 run a rolling average, calibrate the 30 second baseline and push it through a residual

722
00:59:12.400 --> 00:59:20.480
 low pass filter to drive a live GLSL shader and touch designer. Now I know that the Muse 2 is a

723
00:59:20.480 --> 00:59:26.059
 consumer grade device, it cannot cleanly separate deep cognitive effort from,

724
00:59:26.380 --> 00:59:31.179
 say, jaw tension. But this imprecision is not a bug, it's conceptually load-bearing.

725
00:59:31.780 --> 00:59:37.780
 Every wellness dashboard and engagement metric quietly presents this flawed, imprecise biological

726
00:59:37.780 --> 00:59:47.800
 surveillance as authoritative, and I'm just being honest about it in my work. So two more design decisions, the pedestal is graphic on purpose,

727
00:59:47.800 --> 00:59:51.699
 the loop it's reading runs from Calvinistic soteriology

728
00:59:51.699 --> 00:59:55.699
 to Venetian advertising to the platform engineering of the present,

729
00:59:55.699 --> 00:59:58.159
 and it shouldn't look contemporary.

730
00:59:58.159 --> 01:00:02.159
 And at the end of the session, the participant receives a printed diagnostic

731
01:00:02.159 --> 01:00:05.280
 that closes with a single recommendation which is to continue

732
01:00:05.280 --> 01:00:10.719
 the recommendation of every system that has ever needed the participant to keep going.

733
01:00:11.400 --> 01:00:17.420
 Now returning back to our participants, 14 out of 14 intensified their effort. They leaned forward,

734
01:00:17.659 --> 01:00:23.099
 narrowed their eyes and tried to verbally outsmart the rule. One participant put it beautifully,

735
01:00:23.619 --> 01:00:26.320
 the part of her brain that knew was watching the

736
01:00:26.320 --> 01:00:33.840
 part that was doing and the watching part couldn't reach the doing part that's very confusing while

737
01:00:33.840 --> 01:00:40.800
 i acknowledge that a sample size of 14 is not statistic statistical proof of a universal human

738
01:00:40.800 --> 01:00:45.760
 condition it is an empirical homogeneity that certainly warrants a structural

739
01:00:45.760 --> 01:00:53.380
 reading. And now, when stabilization did finally arrive, it came through one of these three routes,

740
01:00:53.800 --> 01:00:58.360
 which is depletion, frustration, or accidental destruction. None of these were deliberate

741
01:00:58.360 --> 01:01:07.920
 decisions. Nobody chose to let go and successfully held that choice. that absence is crucial for the reading that I want to advance

742
01:01:07.920 --> 01:01:14.880
 because intentional release is simply not a strategy that any of the participants had access to.

743
01:01:16.320 --> 01:01:21.519
 I want to be direct about the limits of this work. Three alternative readings deserve serious weight.

744
01:01:22.320 --> 01:01:25.940
 This could merely be a general problem solving. The game-like

745
01:01:25.940 --> 01:01:32.480
 framing itself could be priming people to solve, or it could be a universal physiological response

746
01:01:32.480 --> 01:01:38.059
 to any unpredictable stimulus devoid of cultural specificity. I cannot rule any of these out at

747
01:01:38.059 --> 01:01:45.400
 this sample size. What the theoretical framework provides is a prediction that matches the observed consistency,

748
01:01:45.400 --> 01:01:47.000
 not absolute proof.

749
01:01:47.000 --> 01:01:52.000
 I also want to take the deepest vision of this concern seriously.

750
01:01:52.000 --> 01:01:56.679
 The insulation may partly produce the very behaviour it attempts to diagnose.

751
01:01:56.679 --> 01:02:03.579
 That is exactly why the next-scale version of this insulation has removed the puzzle

752
01:02:03.579 --> 01:02:06.340
 mechanic altogether, replacing it with a

753
01:02:06.340 --> 01:02:13.420
 categorical reading system. And those findings would be for my next paper. The most ambitious

754
01:02:13.420 --> 01:02:19.219
 claim in this paper, I would say, is this proposal that is a category of design environments that I

755
01:02:19.219 --> 01:02:25.280
 called diagnostic rather than optimizing. every environment touching cognitive label right

756
01:02:25.280 --> 01:02:31.679
 now is to build the extract out of it or to extract more out of it and none of them measure

757
01:02:31.679 --> 01:02:37.840
 the cost a diagnostic environment conversely points the instrument inward so there are two

758
01:02:37.840 --> 01:02:45.699
 questions this preliminary study cannot resolve on its own which which is, does this hold at scale and is it strictly bound to

759
01:02:45.699 --> 01:02:51.920
 the gallery setting? So the next phase, which is already underway, is a multi-part spin configuration,

760
01:02:52.179 --> 01:03:00.000
 as I mentioned. And ultimately, this project began as about ambition and it has ended as a project

761
01:03:00.000 --> 01:03:05.559
 about conditioning that produces ambition as the next involuntary reflex.

762
01:03:07.480 --> 01:03:07.659
 The diagnostic print's final word is to continue.

763
01:03:09.300 --> 01:03:09.619
 It doesn't tell the participant to stop.

764
01:03:12.960 --> 01:03:13.260
 All it does, and it cannot tell the participant to stop,

765
01:03:16.579 --> 01:03:17.119
 all it does in three short minutes is using their own brainwaves,

766
01:03:19.679 --> 01:03:20.159
 is show them that on this occasion they didn't.

767
01:03:24.559 --> 01:03:25.719
 What they do with this knowledge is not mine to make or decide.

768
01:03:28.519 --> 01:03:28.719
 Thank you so much to everyone here for your time.

769
01:03:31.239 --> 01:03:36.579
 I would love to hear questions and thoughts. So please do reach out to me via Gmail, LinkedIn or Instagram at shalmaxart.

770
01:03:36.940 --> 01:03:38.780
 You can scan the QR code here.

771
01:03:39.360 --> 01:03:45.800
 Special thanks to the expanded team, Arts Electronica, for this opportunity and letting me present virtually.

772
01:03:46.360 --> 01:03:52.780
 Thank you as well to Associate Professor Ina Konradi for her supervision and to all 14 participants.

773
01:03:53.519 --> 01:03:54.059
 Thank you.

774
01:04:00.320 --> 01:04:06.179
 Yes, please, if you have any questions, please reach out to Shahma online or through social media.

775
01:04:07.340 --> 01:04:12.460
 But we're moving on to our next, to basically our final speaker.

776
01:04:13.440 --> 01:04:17.739
 So it's going to be Oliver Gingrich, Alain Renaud and Erika Mundria.

777
01:04:18.659 --> 01:04:23.940
 And they will present Kima, Resonance, Humming in Harmony and Resonance for Creative Health Outcomes.

778
01:04:24.239 --> 01:04:24.480
 Thank you.

779
01:04:24.639 --> 01:04:26.000
 Thank you so much.

780
01:04:26.000 --> 01:04:28.000
 Yeah, my name is Dr. Oliver Kingrich.

781
01:04:37.000 --> 01:04:39.000
 So, thank you so much for the introduction.

782
01:04:39.000 --> 01:04:42.000
 My name is Dr. Oliver Kingrich. I'm from the University of Greenwich.

783
01:04:42.000 --> 01:04:50.719
 I'm joined online by Dr. Alain Renaud and Erika Mondria from the Art University here in Linz. We're presenting ChemoResonance,

784
01:04:50.820 --> 01:04:56.719
 which is a project that rests on a decade of research by the Analema Group and supported

785
01:04:56.719 --> 01:05:05.440
 by Erika Mondria through her own research also as a neuro expert. The Analima group has been looking at visual properties of sound

786
01:05:05.440 --> 01:05:09.880
 in mostly massive and participatory contexts.

787
01:05:09.880 --> 01:05:14.320
 And we've initially looked at physical properties of sound,

788
01:05:14.320 --> 01:05:19.440
 studying some of the work by Ernst Chladni into semantic patterns,

789
01:05:19.440 --> 01:05:24.159
 really quite fundamental relationship between matter, physical matter,

790
01:05:24.159 --> 01:05:27.760
 granular substances and resonance and how these visual

791
01:05:28.239 --> 01:05:32.340
 properties look in the real world. We studied this and then also

792
01:05:33.139 --> 01:05:36.699
 developed our own mostly digital responses to this.

793
01:05:37.380 --> 01:05:43.780
 And here you can see a commission by the Roundhouse in London for the 50th anniversary, which was one of the first

794
01:05:44.659 --> 01:05:47.119
 immersive House in London for the 50th anniversary, which was one of the first immersive participatory

795
01:05:47.119 --> 01:05:53.980
 installations that we did. I hope this works as a video, and if it doesn't, oh, it takes me out.

796
01:05:56.400 --> 01:06:02.139
 I'll do this very briefly, and hopefully I can jump back afterwards. So here you can see a 360

797
01:06:02.139 --> 01:06:06.880
 presentation using early forms of machine learning and mapping

798
01:06:06.880 --> 01:06:10.460
 this into a 360 immersive environment.

799
01:06:10.460 --> 01:06:16.880
 This was really co-designed with the audience who basically becomes an actor within the

800
01:06:16.880 --> 01:06:17.880
 installation.

801
01:06:17.880 --> 01:06:25.000
 I hope I can jump back to the presentation.

802
01:06:49.760 --> 01:06:52.920
 Okay, so the project is also part of a larger research project into participatory arts practices in digital and online context

803
01:06:52.920 --> 01:06:54.699
 and their effect on health and well-being.

804
01:06:55.260 --> 01:06:57.300
 And we've been working with a lot of different organizations

805
01:06:57.300 --> 01:06:59.539
 supported by the Arts and Humanities Research Council,

806
01:07:00.179 --> 01:07:03.639
 the NHS, Brunel University, RNIB and others.

807
01:07:04.179 --> 01:07:07.500
 And I just want to briefly talk about this wider context.

808
01:07:08.019 --> 01:07:10.420
 Specifically, we're looking at social connectedness,

809
01:07:10.780 --> 01:07:14.579
 which is a concept that has been defined really as a feeling of including

810
01:07:14.579 --> 01:07:17.980
 how emotionally distant or connected one feels to somebody else.

811
01:07:18.840 --> 01:07:21.579
 We know also from the HEART study and other studies

812
01:07:21.579 --> 01:07:30.159
 that there's a strong link between artistic engagement and social connectedness and that this has a possible effect on perceived loneliness.

813
01:07:30.159 --> 01:07:36.340
 We also know that social connectedness has been correlated with higher self-esteem, with

814
01:07:36.340 --> 01:07:40.420
 higher life expectancy and to health overall.

815
01:07:40.420 --> 01:07:43.980
 What we don't know is whether this applies to digital context too.

816
01:07:43.980 --> 01:07:47.719
 And so part of the PARTICIP participate research project was to look at digital interfaces

817
01:07:47.719 --> 01:07:54.039
 and to see whether we can translate these experiences, this effect into these digital context

818
01:07:54.039 --> 01:07:57.659
 and what the challenges are specifically in the context of accessibility

819
01:07:57.659 --> 01:08:01.019
 and also some of the data ethics around this.

820
01:08:01.139 --> 01:08:06.559
 We've been working with the Annalima group and also with other partners like Neurocreator here in the room

821
01:08:07.079 --> 01:08:10.519
 on understanding some of these implications better.

822
01:08:11.739 --> 01:08:20.560
 So one of these interfaces, Kima Voice, was the predecessor to Kima Resonance and here what we were doing was to map vocal harmonies

823
01:08:21.180 --> 01:08:31.220
 onto this Fibonacci spiral that you can see here. This was co-designed with a charity called Show Off Sound. They're working with people with disabilities, physical disabilities

824
01:08:31.220 --> 01:08:37.180
 but also cognitive disabilities, and together we tried to understand what are the limitations,

825
01:08:37.180 --> 01:08:41.479
 what are the challenges when facilitating these artworks but also when designing them.

826
01:08:41.479 --> 01:08:46.720
 And we combined this with a small study with 21 people, and we found that there was

827
01:08:46.720 --> 01:08:53.319
 indeed an effect between these artistic engagements and social connectedness and health and well-being.

828
01:08:55.079 --> 01:08:59.979
 And so yeah, this builds kind of the research context for chemo resonance, which we presented

829
01:08:59.979 --> 01:09:05.319
 here at Ars Electronica Center last year in 2025 in the citizen science lab downstairs.

830
01:09:06.279 --> 01:09:12.380
 And here we have an interface for two people. It's a physical situated site-specific installation

831
01:09:12.380 --> 01:09:17.060
 with a holographic screen. Two people are singing. Their vocal harmonies are being

832
01:09:17.060 --> 01:09:27.420
 visually represented in the center. And you see an outside halo. This is a third person who's sitting here behind the screen and who is

833
01:09:27.420 --> 01:09:34.359
 listening to these vocal harmonies, to this idea of humming. And what we tried to understand is,

834
01:09:34.479 --> 01:09:40.199
 can we actually create this meaningful visual representation of the effect of humming

835
01:09:40.199 --> 01:09:46.739
 on the self? And I'm going to hand over to Erika Mondria now to talk a bit more about the facilitation.

836
01:09:46.739 --> 01:09:59.939
 Thank you. Yes, so I will talk about to you about the facilitation and the process. I

837
01:09:59.939 --> 01:10:05.920
 will talk about humming, listening, and the interaction.

838
01:10:05.920 --> 01:10:11.680
 So we're talking here, the project is about embodied interaction.

839
01:10:11.680 --> 01:10:14.680
 Therefore I ask you a question.

840
01:10:14.680 --> 01:10:25.579
 Do you carry your body, or is your body carrying you. When you were a baby,

841
01:10:27.739 --> 01:10:32.300
 maybe some of you had the pleasure to experience

842
01:10:32.300 --> 01:10:35.380
 that your mom or your dad

843
01:10:35.380 --> 01:10:38.159
 were humming you while they

844
01:10:38.159 --> 01:10:41.060
 laid you down in bed.

845
01:10:43.420 --> 01:10:49.899
 And you might be thinking, oh I don't remember this. But

846
01:10:49.899 --> 01:10:59.079
 humming, as everything else, but humming has, does create a network from the brain

847
01:10:59.079 --> 01:11:10.760
 to the body. And even if you don't know, maybe you were humming when you were an older child, or even,

848
01:11:10.760 --> 01:11:14.560
 I don't know, anywhere.

849
01:11:14.560 --> 01:11:17.960
 Humming creates a vibration in your body.

850
01:11:17.960 --> 01:11:27.220
 And this vibration, if you put your sensory perception inwards, you can feel it maybe in your whole body

851
01:11:27.220 --> 01:11:29.539
 till down to the toes.

852
01:11:30.840 --> 01:11:32.800
 So this is one part, the humming,

853
01:11:33.819 --> 01:11:36.199
 and the network about it in the body.

854
01:11:37.579 --> 01:11:42.520
 And now I would like to talk with you about listening.

855
01:11:43.500 --> 01:11:47.520
 So everyone has maybe had the experience

856
01:11:47.520 --> 01:11:48.819
 to listen to someone

857
01:11:48.819 --> 01:11:53.859
 and actually there are a lot of thoughts in your mind

858
01:11:53.859 --> 01:11:55.720
 like your opinion

859
01:11:55.720 --> 01:11:58.819
 or your impression

860
01:11:58.819 --> 01:12:02.000
 or the shopping list.

861
01:12:02.000 --> 01:12:06.079
 Some thoughts and you actually should listen.

862
01:12:08.060 --> 01:12:11.600
 And listening also is something,

863
01:12:12.159 --> 01:12:14.180
 there is a pattern in your body.

864
01:12:14.960 --> 01:12:18.000
 When you were a baby and you were listening to something,

865
01:12:18.899 --> 01:12:21.399
 there was no opinion in your head.

866
01:12:21.939 --> 01:12:23.319
 There was no shopping list.

867
01:12:23.960 --> 01:12:25.720
 There's also a network for this

868
01:12:25.720 --> 01:12:28.460
 and this is what we call active listening.

869
01:12:29.199 --> 01:12:32.279
 That's what the third person's task was.

870
01:12:32.800 --> 01:12:34.819
 The one wearing the BCI.

871
01:12:35.979 --> 01:12:38.720
 So in the setting we had three participants.

872
01:12:40.199 --> 01:12:44.119
 The ones, they needed to be encouraged

873
01:12:44.119 --> 01:12:46.899
 of course to hum in front of the public,

874
01:12:47.079 --> 01:12:49.739
 because humming is not something we like to do in public.

875
01:12:51.439 --> 01:12:55.960
 And the other one, we mounted the EEG.

876
01:12:55.960 --> 01:13:00.619
 We mounted eight gel electrodes on a temporal lobe.

877
01:13:01.420 --> 01:13:03.939
 And all this person had to do was listen.

878
01:13:10.239 --> 01:13:31.239
 lobe and all this person had to do is listening. Stand behind the transparent screen and listen to what he or she feels, hears and senses in the body. So this was then visualized. The voices you can see in the picture, the square,

879
01:13:32.300 --> 01:13:47.439
 and the listener was visualized when this person was touched and moved very calmly, then the color would turn darker and darker.

880
01:13:48.340 --> 01:13:53.720
 And when it was exciting for the person, then it was lighter and lighter.

881
01:13:54.539 --> 01:14:13.579
 So the findings, maybe is connected to the own body, the embodiment,

882
01:14:13.579 --> 01:14:20.460
 the more the social connection works. Yeah and this really ties up a little

883
01:14:20.460 --> 01:14:31.159
 bit with the findings from the PARTICIPATE study. So the beauty was that it was truly a participatory interface in that the participants created

884
01:14:31.159 --> 01:14:35.500
 the visual representations and we had this part of active listening where you were just

885
01:14:35.500 --> 01:14:41.520
 literally observing, listening inwards, looking inwards almost, and then observing your own

886
01:14:41.520 --> 01:14:46.039
 brain waves coming to life as these outer rings that you can see on the

887
01:14:46.039 --> 01:14:47.880
 image down here.

888
01:14:47.880 --> 01:14:52.319
 So very briefly, we're going to keep the technical presentation quite quick because you can read

889
01:14:52.319 --> 01:15:00.119
 all of that up in the paper, but we used TouchDesigner for the visual representation, we used MaxMSP

890
01:15:00.119 --> 01:15:01.119
 for the sound analysis.

891
01:15:01.119 --> 01:15:06.739
 There was an immersive sound design that went along with the installation as well,

892
01:15:07.260 --> 01:15:10.500
 so that supported the interaction.

893
01:15:11.579 --> 01:15:14.359
 And as Erika was saying, we used a holographic screen,

894
01:15:14.359 --> 01:15:17.199
 a semi-transparent screen, to project the work

895
01:15:17.199 --> 01:15:20.359
 and to create this really interesting triage

896
01:15:21.000 --> 01:15:23.739
 between the two participants and the active listener.

897
01:15:25.439 --> 01:15:28.659
 Yeah, and the findings, just very quickly

898
01:15:28.659 --> 01:15:31.220
 if this works, I'm going to show the video.

899
01:15:31.220 --> 01:15:34.859
 I'm leaving the presentation again.

900
01:15:50.000 --> 01:16:12.000
 social events music

901
01:16:27.939 --> 01:16:28.979
 Is it possible to turn the sound back down?

902
01:16:30.939 --> 01:16:31.100
 Yes, briefly about our findings.

903
01:16:33.319 --> 01:16:34.020
 So there was really a positive response by the participants,

904
01:16:36.279 --> 01:16:36.420
 which did show that they were genuinely engaged,

905
01:16:38.140 --> 01:16:39.119
 immersed and absorbed in the installation.

906
01:16:42.399 --> 01:16:43.300
 Several participants noted they found it relaxing and meditative.

907
01:16:45.079 --> 01:16:47.880
 And one participant mentioned that they really saw a link between the art and health

908
01:16:47.880 --> 01:16:49.479
 and listening to the sounds of humming

909
01:16:49.479 --> 01:16:52.020
 and the relaxing effect on the human mind.

910
01:16:53.300 --> 01:16:54.340
 Yeah, and we really enjoyed

911
01:16:54.340 --> 01:16:56.420
 that there were so many different generations,

912
01:16:56.619 --> 01:16:57.239
 different backgrounds

913
01:16:57.239 --> 01:16:59.279
 that all created these sounds together

914
01:16:59.279 --> 01:17:01.640
 and literally just tuning into the humming

915
01:17:01.640 --> 01:17:03.800
 of their own voices.

916
01:17:05.460 --> 01:17:09.359
 So just very briefly about the context, the political context.

917
01:17:09.779 --> 01:17:12.920
 We tried to write up some of these findings.

918
01:17:13.220 --> 01:17:15.960
 There's guidelines on digital participatory arts that we've published.

919
01:17:16.359 --> 01:17:18.479
 We were invited by the National Centre for Creative Health

920
01:17:18.479 --> 01:17:22.819
 to present some of the research findings at the House of Lords in the UK.

921
01:17:23.880 --> 01:17:26.119
 And there's a summary report on digital creative health

922
01:17:26.119 --> 01:17:30.159
 and participatory arts that was published with our research partners

923
01:17:30.159 --> 01:17:32.180
 and that you can see online.

924
01:17:32.579 --> 01:17:34.859
 Also, the guidelines are available online.

925
01:17:35.619 --> 01:17:38.279
 And I will share with you a QR code where you can access them.

926
01:17:39.039 --> 01:17:43.340
 And this is us together with a colleague, Shama Rahman,

927
01:17:44.140 --> 01:17:46.220
 at the House of Lords presenting the

928
01:17:46.220 --> 01:17:50.800
 research and then holding our own parliamentary roundtable as part of the

929
01:17:50.800 --> 01:17:54.819
 old party health group and what is so interesting is that there is really a

930
01:17:54.819 --> 01:17:59.380
 bit of a political deficit in acknowledging the role of digital and to

931
01:17:59.380 --> 01:18:04.640
 think about regulations about pathways about accessibility about co-design is

932
01:18:04.640 --> 01:18:06.199
 something that is built into

933
01:18:06.199 --> 01:18:08.199
 the funding landscape.

934
01:18:08.199 --> 01:18:12.140
 And this is part of what the summer report is trying to raise.

935
01:18:12.140 --> 01:18:14.739
 And I think with that, we're probably at the end of time.

936
01:18:14.739 --> 01:18:23.079
 And we're going to leave it for any questions.

937
01:18:23.079 --> 01:18:24.079
 Thank you so much.

938
01:18:24.079 --> 01:18:30.560
 Do we have any questions?

939
01:18:31.579 --> 01:18:38.840
 There's one question.

940
01:18:39.439 --> 01:18:40.060
 Hello.

941
01:18:40.539 --> 01:18:42.899
 Hi. Thank you for the wonderful presentation.

942
01:18:43.640 --> 01:18:44.539
 I was curious,

943
01:18:44.819 --> 01:18:46.140
 do you collaborate with

944
01:18:47.079 --> 01:18:48.699
 experts in

945
01:18:48.699 --> 01:18:50.699
 somatics or well-being?

946
01:18:50.800 --> 01:18:56.180
 How big is that role in your practice? Because I imagine it's included in the picture

947
01:18:56.180 --> 01:19:01.439
 but I don't really understand in which moment of the research or perhaps

948
01:19:02.140 --> 01:19:07.659
 after the results if there are some social impact actions where you have

949
01:19:07.659 --> 01:19:11.380
 people that are more close to this kind of events?

950
01:19:11.380 --> 01:19:14.039
 Yeah, thank you for that question.

951
01:19:14.039 --> 01:19:18.739
 So part of the participate project, one of the co-I's, the co-investigators was Central

952
01:19:18.739 --> 01:19:27.920
 Northwest London NHS Foundation Trust and the co-I there, Claire Grant, she's a music therapist so she has

953
01:19:27.920 --> 01:19:33.520
 this background from a creative health context and she was part of the initial

954
01:19:33.520 --> 01:19:38.119
 development of Kimo Voice and so really supported this whole process also

955
01:19:38.119 --> 01:19:42.680
 working on these co-design sessions with the charity Joy of Sound so yeah that

956
01:19:42.680 --> 01:19:50.239
 actually was the foundation for for this project that we then brought here to Ars Electronica. Thank you.

957
01:19:53.699 --> 01:20:06.800
 Hello. What was your decision about the visual, the cube and the rings and how do you find these kind of forms and colors?

958
01:20:07.600 --> 01:20:13.680
 Yeah, thank you. So this mapping is meant to be super intuitive, right? So it needs to work for

959
01:20:13.680 --> 01:20:20.079
 everybody and anyone. Yeah, no matter how old they are or which cultural background they have.

960
01:20:20.079 --> 01:20:25.640
 And so we were with these forms, we were visualizing vocal harmonies.

961
01:20:25.979 --> 01:20:28.779
 So the cube, for instance, alludes to a fourth.

962
01:20:29.319 --> 01:20:33.699
 We had a triangular shape, which was alluding to a perfect third.

963
01:20:33.699 --> 01:20:38.159
 So these are kind of musical harmonies that you can...

964
01:20:38.159 --> 01:20:39.699
 If you're a musician, you would know,

965
01:20:39.779 --> 01:20:42.039
 but if you're not a musician, you're a layman,

966
01:20:42.539 --> 01:20:44.319
 they still are intuitive enough.

967
01:20:44.420 --> 01:20:48.000
 And what happens is that they change quite instantly.

968
01:20:48.199 --> 01:20:49.880
 So we detect these vocal harmonies.

969
01:20:50.020 --> 01:20:52.220
 When me and you are making a sound,

970
01:20:52.359 --> 01:20:55.039
 we hum together and there is this meaningful interval

971
01:20:55.039 --> 01:20:59.880
 between our voices, then these shapes, they merge.

972
01:20:59.880 --> 01:21:02.720
 So the mapping is quite literally connected

973
01:21:02.720 --> 01:21:06.399
 to the type of vocal harmony that we detected sonically.

974
01:21:12.960 --> 01:21:14.699
 Any other questions?

975
01:21:16.680 --> 01:21:18.840
 I actually have one comment.

976
01:21:19.020 --> 01:21:26.960
 It was very interesting when Erika started speaking I felt a very huge shift in because I think you

977
01:21:26.960 --> 01:21:31.399
 were trying to be very present and speak from a very present place maybe this is

978
01:21:31.399 --> 01:21:34.439
 just my perception I was sitting right here and I was I could kind of feel it

979
01:21:34.439 --> 01:21:39.619
 and I actually it did what you mentioned later it kind of focused me out of my

980
01:21:39.619 --> 01:21:44.000
 head and more into what was happening around me so I'm really interested in

981
01:21:44.000 --> 01:21:47.560
 this connection between feeling embodied and social connection.

982
01:21:47.739 --> 01:21:49.779
 Do you know why there is a connection

983
01:21:49.779 --> 01:21:53.180
 or have you found this maybe in some theories before?

984
01:21:54.100 --> 01:21:55.600
 Just some comment if you want.

985
01:21:56.840 --> 01:22:00.539
 Yeah, it's right connected to my research

986
01:22:00.539 --> 01:22:10.500
 because I haven't found it in the series. I found it in practice when I do my

987
01:22:10.500 --> 01:22:19.380
 projects and I believe, well that's my belief, if you're not connected to yourself really

988
01:22:19.380 --> 01:22:27.439
 deeply into your body because you're, in my opinion, you are your body.

989
01:22:27.439 --> 01:22:32.079
 And if you're not connected, you cannot connect to anything else.

990
01:22:32.079 --> 01:22:37.039
 You cannot connect to Earth, you cannot connect to the climate change,

991
01:22:37.039 --> 01:22:43.039
 you cannot connect to another person.

992
01:22:43.039 --> 01:22:47.779
 And once you experience being really connected to yourself,

993
01:22:49.960 --> 01:22:54.720
 that's when you have the pleasure to experience,

994
01:22:54.939 --> 01:22:59.819
 to be connected to someone else or to a group.

995
01:23:01.020 --> 01:23:05.180
 And this is not something you can read in theory.

996
01:23:06.659 --> 01:23:10.579
 You can, of course, but it doesn't change how you feel.

997
01:23:12.100 --> 01:23:14.699
 That's something, it happens.

998
01:23:15.560 --> 01:23:18.779
 And with the project, humming, it does.

999
01:23:19.539 --> 01:23:28.199
 Because you're brave, you stand there, you just do humming. And I remember maybe 15 years ago,

1000
01:23:28.739 --> 01:23:34.840
 I was leading the brain lab and many, many visitors came and asked me a lot of questions

1001
01:23:34.840 --> 01:23:40.420
 because I'm in the brain lab. And she said, oh, my daughter, she's always so nervous when she has

1002
01:23:40.420 --> 01:23:45.260
 an exam. What can she do? And I just said to her,

1003
01:23:47.399 --> 01:23:48.100
 just maybe she can try.

1004
01:23:50.800 --> 01:23:51.279
 Go to the toilet before you have the exam.

1005
01:23:53.060 --> 01:23:53.340
 Go to the toilet and just hum.

1006
01:23:54.859 --> 01:23:56.060
 Hum for yourself.

1007
01:23:56.720 --> 01:23:57.239
 And feel.

1008
01:23:59.680 --> 01:24:00.140
 When you're humming, you cannot think.

1009
01:24:03.680 --> 01:24:04.439
 If you not think, then the body relaxes.

1010
01:24:11.000 --> 01:24:12.000
 And it's, you know, you don't need to know this theoretically, you need to do it.

1011
01:24:14.000 --> 01:24:19.000
 That's beautiful, thank you.

1012
01:24:21.000 --> 01:24:26.319
 Thank you very much.

1013
01:24:26.319 --> 01:24:30.659
 This we conclude the embodiment session.

1014
01:24:30.659 --> 01:24:35.460
 I'm not really sure what's next on the program, but maybe it's time to eat perhaps?

1015
01:24:35.460 --> 01:25:05.039
 Thank you.