Hello and welcome to The Human Signal with me, Laura Sheeran. Today we are looking at part six of my eleven-part series, AIWTF?, which looks at AI in the music industry right now—what’s happening in the digital music ecosystem, the good things, the bad things, the complicated things, and the bits that make no sense at all. We’re looking at all of it.

In this episode, I’m trying to make sense of what happens when the copyright system we’ve relied on for decades no longer fits the reality we’re in. I talk through the foundations of copyright—authorship, ownership, original expression—and how all of that starts to break down when music is generated by AI.

I also reflect on what this might mean structurally for the music industry. It feels like we’re moving toward a split between two systems that don’t align—one human, one AI—and I’m trying to understand what that could look like, and where it leaves artists.

Full Episode Description

Today’s episode is focusing largely on copyright law, the copyright law as it currently exists today—the law that we as creators have depended on to defend our rights, to protect our work, and to make sure that we can get paid and earn from the work that we do.

Since AI music has been flooding the industry to the degree that it has, the limitations of copyright law have been becoming more and more evident, and it is clear that the current model that exists to protect artists and musicians is no longer sufficient or fit for purpose, and radical change needs to happen.

The previous episode, I talked a lot about fair use, which I would recommend if you didn’t listen to that episode, or if you don’t know much about fair use, to go back and listen to episode #50, because it gives the full picture and the context for how AI music is able to thrive to the degree that it has. There are complications with the fair use law as well, which we go into in the last episode.

If you want to go and listen from the beginning of this series, AIWTF?, the podcast episode number to go to is #46.

This series is for people who, like me, are trying to find their way through a muddy, murky haze which is very uncertain and very unclear as to how one might want to release music in the immediate future, considering the rapid change happening all around us and how unstable the infrastructure we’ve known and depended on feels right now.

There are a lot of ethical considerations with AI. There are a lot of people who are very torn creatively in relation to AI. I know that there are artists using AI in creative ways. But there are still very complicated webs of uncertainty and potential vulnerability that you can fall into by not understanding the underlying rules, regulations, and systems that are supporting the AI music industry.

There’s a lot of potential liability, and potential loss of autonomy and rights. It’s a minefield.

Quick disclaimer: I’m just a normal person. I am an independent artist. I am not a legal expert, not an industry expert, not an AI expert. I’m just an artist trying to do the right thing by my work, by my music, and to protect myself from potential exploitation.

I’ve always released my music as ethically as I can, so that’s the position I’m coming from.

So, this is part six: human copyright law. The law as we know it was not set up to deal with any of these AI complications. The original copyright was built on human authorship, original expression, and clear ownership. But now, generative AI has exploded that whole concept wide open.

AI music - who is the author? Is it the AI model? Is it the prompter? Or is it the (potentially) hundreds or thousands of writers who’s stolen work makes up the training data which spits out some kind of Frankenstein-esque amalgam on the other side of a generate button.. With AI music specifically, who counts as an artist? What does being an artist mean?

These are questions that must be asked and they are things we haven’t worked out or decided on collectively yet. At the moment, everyone is just going with what makes sense to them and what suits their own interests. There’s no culturally agreed upon set of rules.

If copyright depends on original expression, then how can that apply if something like a song has been generated from potentially millions of other works? Where does ownership begin and end?

If I own my music and it gets trained into an AI, and then I hear something in an AI-generated track that clearly resembles something I created, can I claim that? Or does my ownership end at the boundary of my original song?

How does this tie in with sampling? Sampling has been around for decades, with its own rules. I don’t know how this compares. That’s something I want to look into further (I really wish I was educated in law. It’s kind of a fantasy of mine to go and get a law degree!)

Back to the point. I think what needs to be worked out first is whether AI music counts as fair use. That will dictate everything. Because since AI outputs are being commercially distributed, charting, generating revenue, and organisations such as AIMPRO positioning themselves to start collecting royalties for AI music, then fair use becomes very hard to argue. If outputs are directly competing in the market, the fair use argument starts to fall apart.

What’s happening right now is that outputs are trying to be legitimised before the inputs have been legally resolved. I can’t see a logical pathway forward because there’s no agreed ethical code, and the law hasn’t adapted.

One thing feels certain: the music industry as we’ve known it is gone. Not that it will disappear entirely, but it will have to bend with this tide, or it will break. Maybe this is a breaking point, where the split starts to happened.

What we’re seeing is a traditional rights system, built over a century, now colliding with a new AI-native system emerging alongside it. I can’t see how these two systems can merge—they are fundamentally misaligned. It feels more likely they will split and move in different directions. We could be witnessing the great music industry split of 2026!

Ideally, they would coexist in a balanced way. But more realistically, they may compete for dominance. Based on what platforms are prioritising and how AI content is being pushed, it’s not hard to see which direction things are heading in the short term.

Looking at platforms like Deezer, if AI uploads continue growing at the current rate, they will exceed 50% of new uploads very soon. That would make AI the dominant presence in new music being uploaded.

From my own conversations with artists, many are choosing to step away from these platforms and return to Bandcamp, vinyl, or other physical formats. Of course that’s all anecdotal, but from where I’m standing, it’s clear that platforms are becoming less hospitable to human artists, while AI presence continues to rise. We see this reflected in the bilboard charts where AI’s are frequently landing number one spots and taking these places away from genuine human artists who have committed their lives to their craft.

If there really is a split beginning to develop between the human system and the AI system, it seems clear which one is positioned to dominate in the short term.

If you enjoyed this podcast please share it with a friend or consider leaving a comment or review, it really helps me out. You can also support me and my work by becoming a €5 member on Substack and Patreon. And lastly, you can still find me on YouTube / Instagram as @the_persona_project__ & @laurasheeran_ieThat’s all for now. Thanks for being here, and remember: Put humans first. Don’t feed the machines.

This is part five of an eleven part series called AIWTF? where I am discussing all things to do with AI and music and the digital music ecosystem as it stands today.

In this episode, I’m working through the concept of fair use and how it’s being used to justify the current direction of AI in music. It’s something that underpins most of how content is shared online, but when applied to AI training and generated outputs, it starts to break down in uncomfortable ways.

I walk through the key principles of fair use—what it allows, where its boundaries sit, and why creative work like music is much harder to defend within it. From there, I look at the ongoing lawsuits between artists, labels, and AI companies, and the contradictions that are starting to emerge.

What becomes clear is that the system is trying to hold multiple positions at once: claiming transformation under fair use, while also moving toward monetisation and licensing of AI-generated outputs. Those positions don’t sit easily together, and it raises deeper questions about ownership, value, and what happens when extracted work begins to compete with its source.

The episode addresses the tension of trying to make sense of a legal and cultural framework that no longer seems equipped for what’s happening.

If you enjoyed this podcast please share it with a friend or consider leaving a comment or review, it really helps me out. You can also support me and my work by becoming a paid member, it’s €5 per month on Substack and Patreon. And lastly, you can still find me on YouTube / Instagram as @the_persona_project__ & @laurasheeran_ieThat’s all for now. Thanks for being here, and remember: Put humans first. Don’t feed the machines.

Hello and welcome to The Human Signal podcast, this is part four of an eleven part series I’ve made called AIWTF?, about the most recent developments in our increasingly AI saturated music industry.

In this episode, I’m talking about a newly launched organisation in the US called AIMPRO, which positions itself as a performance rights organisation for AI-generated music. It’s a very recent development, and one that’s been sitting uncomfortably with me.

I walk through what AIMPRO claims to offer—royalty collection, licensing, and infrastructure for AI music creators—and question how any of this can function when the underlying legal framework around copyright and ownership is still unresolved. Platforms like Suno have already indicated that they cannot guarantee copyright protection for AI-generated works, particularly where there is limited human authorship, which raises a fundamental question about what is actually being licensed or monetised.

This episode sits right in the middle of a rapidly shifting landscape, where new systems are being built before existing ones have been clarified. It brings up deeper tensions around fairness, authorship, and who is being recognised—or ignored—in this new version of the music industry.

Full episode description

Today I’m asking the question: is this the birth of AI rights?

AIMPRO, not to be confused with the UK-based trade body with the same acronym, is the AI Music Performance Rights Organization. It’s a brand new US-based company launched in April 2026 as the first performance rights organisation dedicated specifically to generative AI music creators. It aims to collect and distribute royalties for AI-generated works and establish a formal rights framework for this emerging sector.

From their website, AIMPRO is designed to serve creators of generative AI works, allowing them to collect royalties globally. They offer services to monetise AI music, including registration, royalty collection, licensing, and metadata tagging. They claim to collect royalties from streaming, public performance, sync licensing, and more, and to connect AI music creators with licensing opportunities across platforms worldwide.

I don’t even know where to start with this. I don’t know how this can exist or move forward at all, but I’m sure it probably will. Given the sheer volume of AI-generated music being created every day—tens of thousands of tracks—it could grow very quickly. It’s very unnerving.

What’s confusing is that there has been no resolution around the lawsuits concerning royalty payouts to human artists whose work is used to train these systems. Yet at the same time, new organisations are forming and acting as if a framework already exists. It feels like people are just setting things up and hoping for the best. What is copyright anymore?

If we look at platforms like Suno, their own terms of service state that AI-generated music cannot be copyrighted. You may own the file if you’ve paid for a subscription, but you cannot claim copyright over it. That means you can upload it anywhere, but you can’t stop someone else from doing the same thing with it. There’s no enforceable ownership.

So how can a new organisation claim to license or monetise something that isn’t legally protected? What exactly are they providing? For AIMPRO to deliver on its promises, the person uploading the music would need a clear and enforceable right to license it, which currently doesn’t exist.

This adds another layer of tension to an already unstable situation between major labels, independent artists, and AI platforms. Up to now, the arguments have centred on training data—whether AI companies owe compensation for using existing music. That’s still unresolved, largely due to claims of fair use.

Now AIMPRO is attempting to legitimise AI-generated music by advocating for prompters to be treated as creatives entitled to compensation. But these prompters are generating music using systems built on the work of human musicians. They are using words to produce outputs that rely entirely on pre-existing creative labour.

So how can they be entitled to compensation when the original creators are still fighting for theirs? It doesn’t make sense. It feels completely out of alignment. The idea that AI is seeking rights while humans are still struggling to secure theirs is hard to process.

This leads into the topic of fair use, which I’ll be covering in more detail in the next episode. I’ll be looking at what counts as fair use and where the line is drawn into copyright infringement.

If you’ve been following the series so far, thank you for sticking with it. There’s still quite a bit to go, and things are changing so quickly that by the time I reach the end, there will likely be even more developments. It’s moving at a pace that’s very difficult to keep up with.

If you enjoyed this podcast please share it with a friend or consider leaving a comment or review, it really helps me out. You can also support me and my work by becoming a paid member, it’s €5 per month on Substack and Patreon. And lastly, you can still find me on YouTube / Instagram as @the_persona_project__ & @laurasheeran_ie . That's all for now. Thanks for being here, and remember: Put humans first. Don't feed the machines.

This In this episode of The Human Signal (part three of my eleven part series, AIWFT?) I’m looking at AI detection technology and the role it’s beginning to play in the music industry. I talk through the rapid rise of AI-generated music on streaming platforms, and how detection tools are being developed in response—but not without serious limitations.

I reflect on the reliability of these systems, the risks of misidentification, and what happens when decisions about access, visibility, and income are being shaped by technology that isn’t fully accurate.

I also connect this to wider examples of AI detection failures, from education to facial recognition, and what that might mean as these systems become more embedded in everyday life.

Throughout the episode, I’m thinking about what this means for artists trying to release work in a way that is both ethical and sustainable, and how fragile that process can become when control is mediated by platforms and systems being driven more and more by AI.

Full Episode Description

This eleven part series is looking at AI in music, where the digital music ecosystem is at right now, and what some of the most pressing issues with this topic are right now. I’m digging into it from the perspective of somebody who has spent the past two or three years working on a collection of 6 albums which I am hesitant to release under the current streaming model.

I need to make serious decisions about how I want to release them, sooner rather than later, or they will be doomed to sit abandoned on a dusty hard drive forever. As a result, a lot of this investigation is about helping myself make more informed decisions - ones that feel ethically aligned, while still maintaining visibility and access to listeners. To be honest, at this moment in time, I’m not entirely sure that option exists!

In the past two episodes, part one and part two, I discussed personal experiences shared online by musicians who have had royalties cut off due to AI-related interventions. I also spoke about Deezer and how they’ve been collecting data on AI-generated uploads. Their most recent statistics now show that 44% of all music being uploaded to their platform is AI-generated. This suggests we’re approaching a point where the majority of music on streaming platforms could be AI very, very soon.

This is happening incredibly fast. The ease of producing AI music and the difficulty in distinguishing it from human-made work are accelerating its growth. This has serious implications for human artists for a number of reasons, but one of the most practical issues is that there is a limited royalty pool. Every AI-generated track that gets streamed is taking from that same pool and limiting the income of a human artist who’s work was most likely scraped without permission to train the AI in the first place.

Deezer’s detection technology has allowed them to identify and label AI-generated music. This has helped them gather data and maintain some level of visibility for human artists. They’ve now developed this into a commercial product, selling their detection software to partners.

There are thousands of AI detection tools out there, many focused on niche use cases. Deezer’s system is strong because it has been trained on a massive dataset. But this raises questions about incentives—allowing AI to flood the market also creates demand for tools to regulate it.

The key question is how reliable this technology actually is. In text detection, studies have shown that none of the major tools exceed 80% accuracy. All of them produce false positives and false negatives. That means human work can be flagged as AI, and AI work can pass as human.

There are also real-world consequences. I came across a case where a grandmother in Tennessee was jailed for nearly six months due to a facial recognition error linking her to a fraud case. This is where these technologies start to become deeply concerning.

If these systems are being used to make decisions that affect people’s livelihoods, or even their freedom, then the margin for error becomes critical. I don’t trust it. I don’t think it should be allowed to operate without serious safeguards.

In music, we’ve already seen examples where albums are removed from platforms due to suspected AI involvement. If an artist invests significant time and money into a release and then has it taken down, the consequences can be devastating. It can make it impossible to even consider investing in the next album if no costs can be recouped from the last

There are multiple layers of erosion happening. Access to royalties is being reduced due to AI saturation. Music can be removed entirely, cutting off income streams. In some cases, artists’ work is cloned and re-uploaded, with someone else collecting the royalties, leaving the original artist powerless and burdened with the responsibility of trying to fix it themselves through platform systems that refuse to engage, using tactics like automation shielding and service hollowing, which make it even harder for artists to meaningfully challenge these situations.

All of this ties into ongoing legal battles. Major labels have filed lawsuits against AI companies for using copyrighted material without consent to train their models. Independent artists are also being represented in class action cases. The outcomes of these cases are still uncertain, with AI companies claiming fair use.

While all of this remains unresolved, new systems continue to emerge. This brings us to the next part of the episode, where I introduce AIMPRO, the first organisation set up to collect publishing royatlies for AI music, and I begin to ask: Are we witnessing the birth of AI rights? 🫣

If you enjoyed this podcast please share it with a friend or consider leaving a comment or review, it really helps me out. You can also support me and my work by becoming a paid member, it’s €5 per month on Substack and Patreon. And lastly, you can still find me on YouTube / Instagram as @the_persona_project__ & @laurasheeran_ie

That’s all for now. Thanks for being here, and remember: Put humans first. Don’t feed the machines.

This In this episode of The Human Signal (part two in my eleven part series, AIWFT?) I continue looking at how AI is shaping the music industry, but this time through the lens of the streaming platforms themselves. I compare and talk through the different approaches being taken by Spotify, Deezer, and Bandcamp, and what those approaches reveal about how each platform is positioning itself in relation to human artists and AI-generated content.

NOTE: This episode was recorded before Deezer announced new stats (just today) indicating that 44% of all music on it’s platform is now AI generated. If uploads to Deezer continue along the established trend pattern, we are now just weeks away from AI surpassing 50% of all music on Deezer, making it the majority. This trajectory has extremely negative implications for all human artists’ ability to earn from what was already an incredibly shallow pool of streaming royalties.

Full Episode Description

Continuing on from part one, where I discussed Karra having her album completely deleted by Spotify with no pathway forward, we can see that Spotify has taken a very reactive approach. They allow things to run freely and then step in afterwards with enforcement. There’s no prevention, no clear system, and no labelling of AI content, which they still refuse to implement.

From the artist’s perspective, this is a very harsh system. There’s no negotiation, no warning, and no opportunity to fix an issue. It’s just immediate removal. That puts the administrative burden back onto the artist and creates a constant sense of risk. The system becomes volatile and inconsistent.

All platforms are introducing changes in different ways, and over time you can see them developing distinct identities in how they handle AI. Spotify, in this context, feels the most anti-artist. Bandcamp is at the opposite end, having completely banned AI music.

One of the most interesting platforms is Deezer. They chose early on to label AI-generated music clearly and invested in detection technology. Instead of clamping down immediately, they allowed uploads but tracked everything. This gave them the ability to collect detailed data and analyse trends.

From their data, in January 2025 there were approximately 10,000 fully AI-generated tracks being uploaded per day, representing about 10% of daily uploads. By June, that rose to around 18%, and by November 2025 it had reached 34%, or about 50,000 new AI-generated tracks per day.

There is no human production system capable of producing 50,000 quality tracks per day. That scale is only possible with generative AI.

They also conducted a study showing that 97% of listeners could not reliably distinguish between AI-generated and human-made music. That’s a striking figure.

In January of this year, Deezer reported that its detection system identified over 13.4 million AI tracks during 2025. They also stated that up to 85% of streams on fully AI-generated tracks were fraudulent. As a result, they announced that these tracks would be removed from algorithmic recommendations and editorial playlists.

This is significant because it means real listeners and real streams can be directed back towards human-made music, and the royalty pool can remain focused on human creators.

This is not what’s happening on Spotify or YouTube Music. Both platforms played a role in the original scraping of music to train AI systems, and now they are fully integrating AI features without offering users meaningful choice. There are also growing reports that their algorithms are prioritising AI-generated content.

What Deezer has done is shine a light on what’s actually happening by collecting and sharing data. They have also announced plans to commercialise their detection technology for external partners.

If you enjoyed this podcast please share it or consider leaving a comment or review, it really helps me out. You can also support me and my work by becoming a paid member, it’s €5 per month on Substack and Patreon. And lastly, you can still find me on YouTube / Instagram as @the_persona_project__ & @laurasheeran_ie That’s all for now. Thanks for being here, and remember: Put humans first. Don’t feed the machines.

Today’s episode of The Human Signal is the first part of an ELEVEN part series I recorded yesterday about the most recent developments relating to AI and the sinking ship that is the digital music industry.

In the series I discuss Suno, Spotify, major labels and how the newest player in the game, AIMPRO, adds a whole new layer of chaos into an already turbulent battlefield. I discuss copyright law, the murky water of music and AI rights (!), how gaming economics could be the final nail in the music industry’s coffin. I also discuss the psychology of musical practice, the pros and cons of uploading music digitally in 2026, and look at realistic paths of resistance for those who wish to fight the algorithmic creative complex!

Today in episode one, I’m reflecting specifically on a situation where a musician, Murphy Campbell, had her voice and songs replicated through AI, the replicas re-uploaded via a digital distributor and her own authentic videos flagged for copyright as a result, removing her from accessing her own royalties/monetisation while the AI perpetrators siphoned off . through a chain of occurrences she had no part to play in and no control over.

I use this example to explore bigger structural issues—things like responsibility diffusion, administrative burden, and automation shielding. I also revisit earlier examples of artists being removed from platforms without clear explanation or recourse, and what that reveals about how these systems are designed and how AI supremacy is fast becoming the norm in the online music space.

If you enjoy this podcast please share it with a friend or consider leaving a comment or review, it really helps me out. You can also support me and my work by becoming a paid member, it’s €5 per month on Substack and Patreon. And lastly, you can still find me on YouTube / Instagram as @the_persona_project__ & @laurasheeran_ieThat’s all for now. Thanks for being here, and remember: Put humans first. Don’t feed the machines.

In this episode of The Human Signal, I talk through the evolving shape of my Electric Picnic show coming up in August. I share how I followed an instinct to learn how to DJ by doing a great lesson with Eimear Keating aka DJ BURE, what that experience was like, and how it helped something click into place creatively with The Persona Project.

It made me realise that what I had been calling the “performer persona” was actually something more specific that I hadn’t fully understood yet.

This episode centres on the process of building a live performance through layered creative labour—coordination, experimentation, skill acquisition, and collaboration. It also touches on embodiment through the integration of physical performance elements like dance, pole, and DJing, and the experience of stepping into new creative identities.

Creative growth requires stepping beyond competence into uncertainty. But at what point does ambition stop expanding the work and start destabilising it?

If you enjoyed this podcast please share it with a friend or consider leaving a comment or review, it really helps me out. You can also support me and my work by becoming a paid member, it’s €5 per month on Substack and Patreon. And lastly, you can still find me on YouTube / Instagram as [@] the_persona_project__ & [@] laurasheeran_ie

So I had an idea earlier in the year when I was booked to play Electric Picnic in August. I’m really looking forward to this gig. It’s the only live show I’m doing this year, well so far at least, and I have so many things planned. I’m in the process of really trying to get the production stuff locked in at the moment and get a realistic picture of what’s doable.

I performed at this stage in Electric Picnic the year before last, in 2024. I did the whole show solo. I talked about this gig already on the podcast in episode number 30, so if you’re interested you can go back and check that out. At that time it was pretty close to when I had just been booked for the gig, and my imagination was on fire with all of the amazing things that I was hoping to squeeze into the set. And the overarching question of that episode was, am I insane for wanting to plan or trying to achieve what I was planning?

Many of you who listened to it will probably argue yes, Laura, you are, sorry to tell you. But I would say fair, because I also agree with you. But it doesn’t stop me from having the ambition and the excitement, and maybe you need a bit of delusion in order to try and bite off more than you can chew. You have to bite off more than you can chew to find out that that’s more than you can chew. But if you live your life constantly trying to play it safe, you’re not going to get very far, in my opinion.

So anyhow, I was full of all of my wild ideas, and I would love to say that since then I have stabilised my ideas a bit in scale and worked out a realistic middle ground, but that’s not the case. If anything, I’ve just added more.

At this point I’m really happy because I have a stage manager. I’ve been having discussions with a lighting designer and a projection mapping artist, I also have an incredible group chat with 30 women who have been working with me since last year and are eager to perform, so it looks like I am going to be able to have my dancing troupe after all. I also have a whole section of the live show involving pole dance. This time I want to have three poles on stage and I already have two other amazing dancers on board to join me 👍🏻

I’ve also been taking steps towards getting my live band set up, which feels good because I haven’t performed any of these songs with other players yet, so that’s a whole process in itself.

As I break down the different sections of the show, I can see how the one live show will allow all the different personas to come through. I have a background in theatre, so I tend to think in terms of scenes, shifts, tension and release, and I want to bring that way of thinking into my music shows.

It felt like the set needed to culminate in a rave, and I was wondering how I could achieve that.

Within the persona project there are clear personas that have come through like the dancer, the fighter, the true human being, the dreamer, and others emerging like the witch and the simply daughter. But there was also this vague “performer” persona that never fully made sense to me but was there in my imagination none the less.

Then I had this realisation that maybe this is actually a DJ persona, and maybe this was the solution to the rave climax. That’s all well and good, but I have no clue how to DJ…. so I would need to learn. I texted my friend Eimear and asked if she would teach me.

We booked a session in Pirate Studios, and today was the day. It was so much fun. I wasn’t expecting to even be able to do a mix, but I did. She was such a good teacher, pushing and challenging me. By the end I had so much new knowledge to take home with me and bring with me to my next practice session.

After the lesson I was so excited and I started thinking about DJ names. DJ Persona was cringe and too clunky, DJ Sheero (one of my nicknames) felt too old or from a different era of my life. Then I thought Laura, how about LALA… I text the idea to my sister and she sent me a screenshot which was pretty funny, showing me that that’s exaclt how she already has me saved in her phone.

It feels like something has clicked into place. The vague and random ‘Performer’ persona I had been holding a place for has finally found where it belongs.

I know this show probably sounds chaotic from the outside, with all the different elements and all the different personas, but when it’s fully realised with the visuals, the music, and the performance, it will make sense!

That’s all for now. Thanks for being here, and remember: Put humans first. Don’t feed the machines.

Lx

In this episode of The Human Signal, I’m closing out my series on the Delta flight saga I documented in Episodes #36, #37 and #38, by stepping back and trying to understand what was actually going on beneath the surface of the situation. I examine how platforms and interconnected systems distribute control while avoiding accountability, showing how power operates structurally rather than individually.

I talk through responsibility diffusion, administrative burden, automation shielding, platform intermediation, service hollowing, and enshittification — not as abstract ideas, but as patterns I experienced directly. It’s an attempt to name the structures that make people feel powerless, and to understand why it’s become so normal for the human being to come last.

If you enjoyed this podcast please share it with a friend or consider leaving a comment or review, it really helps me out. You can also support me and my work by becoming a paid member, it’s €5 per month on Substack and Patreon. And lastly, you can still find me on YouTube / Instagram as @the_persona_project__ & @laurasheeran_ie

Hello and welcome to The Human Signal with me, Laura Sheeran.

This episode is fundamentally about returning to the body—through dance, flow, and improvisation—as a counterpoint to control, anxiety, and perfectionism.

I’m reflecting on a performance I did last week where I decided to experiment with improvisation in my pole dance practice. Alongside that, there is also a clear tension around time, urgency, and learning to slow down, particularly in the studio mixing process which is currently underway with Brian for my first Persona Project record.

I talk about the shift from following strict choreography in dance performances, with it’s promise of performance security and perfection potential (despite the stress and anxiety it can also generate), to following musical instinct and freeform improvisation above all, in pursuit of true embodiment. I reflect on the pressure I put on myself to perform perfectly, and what happened when I felt brave enough let that go.

I also share how that experience is shaping my thinking around the Dancer persona in The Persona Project, and how I might present that work live.

Next I reflect on the studio process, the tension between urgency and patience, and what it means to allow time for quality to emerge in the music while time is passing and the toxic, unavoidable, cultural narratives around women and aging, start affect your ability to truly enjoy what is a beautiful and precious gift given by the universe.

If you enjoy this episode, please share it with a friend or consider leaving a comment or review, it really helps me out. You can also support me and my work by becoming a paid member, it’s €5 per month on Substack and Patreon. And lastly, you can still find me on YouTube / Instagram as @the_persona_project__ & @laurasheeran_ieThat's all for now. Thanks for being here, and remember: Put humans first. Don't feed the machines.

Below are the relevant links and videos mentioned in this episode, along with a condensed transcript of this episode which has been AI generated from the raw transcript, for those who want to scan the gist of this episode without having to listen to the full audio. 👇🏻

It’s been a while, guys. I have been very busy in the studio for the past week. I posted about this yesterday in the Persona Lab post on my Substack. I have been mixing, and mixing and mixing with Brian at his studio, third Ear. I took a break on Friday to do a pole dance performance in Navan for a fundraiser. It was a beautiful thing to be part of. Here is a link to the GoFundMe relating to the fundraiser, it’s for my friend’s brother who suffered a very severe stroke at just 33.

It was really a brilliant thing to get to dance and perform, primarily for the cause but also because I had been spending so much time in the studio, which demands a lot of sitting down, and I find that I get so stiff so quickly. The older I get, the more intense that is. We have been spending long hours in the studio, so I was very grateful to have the chance to dance and perform.

For this gig, I decided to experiment with improvisation. Every time I perform with pole, which isn’t that often, I use it as an opportunity to try something new. I dance a lot in the studio, but it’s not the same as performing in front of an audience. The more I perform, the more I’m finding confidence in my own style, which is very slow and flow-based.

At the beginning, I felt pressure to fill every beat of the music and include as many tricks as possible. Part of that was nervous energy, but part of it was the psychological pressure to entertain the audience. Recently, I’ve been finding more value in slowing down. The more confident I become in that, the more I feel I can turn something slow into something magical.

The pressure to fill a routine with tricks also means having choreography prepared, which makes me anxious. I have a perfectionistic mind, so if I get something wrong, I can leave a performance feeling like I failed instead of enjoying it. That tendency to criticise afterwards takes away from the experience.

For this performance, I chose a song I often use in training, “Problems” by 6lack.

I decided to prepare by freestyling rather than setting choreography, getting familiar with the song and letting the movement come from that. On the morning of the show, I found out there were cancellations, so I offered to do a second performance.

I chose a Baroque piece by Marin Marais, something I’ve danced to privately before. It’s not typical pole music, but it allows for a deep, slow, emotional flow. I looped a short section to create a longer piece.

I often dance to baroque music when I’m pole training, there’s something about the raw emotion contained in the music which really lets me feel the movement more deeply somehow. I especially like dancing to the slower music of Henry Purcell

I was nervous right before I performed on Friday, because both performances would be improvised, and one of them was very unconventional. I opened with the Baroque piece and kept the movement simple, focusing on what I knew well and could do gracefully.

The second piece was more intense, because I felt more confident after the first performance and allowed myself to fully let go. I extended the movement onto the floor, used the space, and followed instinct all the way through.

I loved these performances so much and definitely came away wanting to lean more into improvisation when it comes to pole dance performance. This connects directly to The Persona Project then too.

The album I’ve written and recorded as Dancer Persona is music which encapsulates this exact energy, this vibe. It is something I’ve been thinking about a lot over the last few months in terms of how I might approach the live performance of that record. The songs for that persona don’t sit easily alongside the other songs in a traditional style set, but they do make way more sense in a dance context.

I’m starting to think about creating a dance-based show for that album, possibly in smaller, more intimate venues. Performing the music through movement rather than singing might be a more accurate expression of where the work comes from.

At the same time, I’m still working in the studio with Brian on the mixes. He’s doing incredible work. I keep trying to rush the process, saying it’s good enough, but every time he takes more time, it comes back significantly better. The improvement is undeniable.

I’m recognising this tendency in myself to rush things, to want everything done immediately. I’m trying to let go of that and trust the process. I’m also challenging the narratives around time and aging that create pressure to produce quickly.

I’m choosing to be defiant against that and to allow the work to reach the level of quality it deserves. I’m proud of what we’re making.

I’ll leave it there for today, but just to say that I have a few things I want to follow up on in upcoming episodes, including a final reflection on the Delta situation and revisiting articles about leaving social media. I’ve noticed how easy it is to slip back into old habits, like defaulting to WhatsApp instead of Signal, even when I’ve made a conscious effort to change. So I’ll be revisiting those topics this week.

Until then! xx

In this episode I talk through the process of self-producing, self-directing, and self-filming a music video for Simulacrum in which I am the only subject. I’m working alone on this one, trying to translate a very clear image that I have in my head into something real on the screen, and running into all the friction that comes with being both the subject and the cameral operator at the same time. Add in the challenge of incorporating synchronised projections in the mix and you have a perfect recipe for a potential disaster or a potential success.

I reflect here on frustration, persistence, technical limits, and the importance of staying open when a process starts to shift away from what you originally imagined. An we are being pushed further and further into believing that speed and convenience is what we need and should all want, here I am settling back into a tricky, lengthy and at times very frustrating process, knowing that it is the process which leads to growth and ultimately it is the work itself. The idea of throwing my video idea over to AI and getting something far slicker done in a fraction of the time does not appeal to me at all, and that is because it’s in the difficulty and the friction that we find the humanity in the work, and in overcoming it we find fulfilment.

Some preview clips below for my treasured paid subscribers, thank you all x