The Human Signal — with Laura Sheeran

I'm talking about trying something a little different with the podcast in this episode.After a particularly busy year working across music, theatre, film and other creative projects, I've been thinking about how to get back into a more regular rhythm with the podcast without getting bogged down in research, editing and overthinking.In this episode, I reflect on what's been working, what hasn't, and my plans for shorter, more frequent episodes. I'm also experimenting with filming the podcast and sharing video episodes with my supporters on Patreon and Substack.A bit of a reset, really.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 on Substack and Patreon for €5 per month.You can also find me on Instagram and YouTube @The_Human_SignalThat'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.A year ago, I removed all of my music from Spotify for ethical reasons. I was convinced it was the right decision. A year later, my objections to the platform haven't changed, but my understanding of what leaving actually means for an independent artist has.In this episode, I reflect on what happened when I released music without Spotify, from navigating press interviews to confronting the streaming numbers, and what those experiences taught me about artistic independence, visibility and the limits of individual action.I also explore the relationship between art and activism, including a recent experience I had navigating censorship, and how that experience eventually led to my new song, D'Arcy's March, dedicated to the late Irish artist and activist Margaretta D'Arcy.It's brought me to an uncomfortable question: can putting a political song onto a platform I politically oppose, allow that song to do more politically than keeping it off said platform for political reasons?If you enjoyed this podcast please share it with a friend. You can also support me and my work by becoming a 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 machine.Disclaimer: The Human Signal is an independent opinion podcast reflecting my personal views at the time of recording. It is intended for discussion and entertainment, not as formal journalism or professional advice. Please verify information independently and form your own conclusions.

In this episode, I'm thinking through what it means to share work online at a time when artists' images, music, ideas, and creative processes are being absorbed into AI systems, most often without permission.I talk about finding my own music listed in AI training datasets, seeing another artist's costume work replicated through AI-generated images, and the pressure artists are under to keep posting, keep sharing, and keep themselves visible, regardless of these damaging consequences. I also reflect on my own uncertainty around releasing new music, especially when the platforms that help people discover creative work are often the same systems that make that work feel unsafe to share.If you enjoyed this podcast, please share it with a friend or consider leaving a comment or review—it really helps. You can also support me and my work by becoming a paid member for €5 per month on Substack or Patreon.You can also find me on YouTube and Instagram at @the_persona_project__ and @laurasheeran_ie.Thanks for being here, and remember: Put humans first. Don't feed the machine.---Disclaimer: The Human Signal is an independent opinion podcast. The views expressed are my own and reflect my understanding at the time of recording. They are shared to encourage discussion and are intended for entertainment purposes. This podcast does not constitute journalism, nor does it provide legal, financial, medical, or other professional advice. I encourage you to verify information independently, think critically, and come to your own conclusions.

Hello and welcome to The Human Signal with me, Laura Sheeran.After an unexpected two-month gap in the podcast, I’m back! The first half of this episode is me explaining what happened, why I ended up going dark for so long. I also talk a bit about the AI watchdog and how I found ten of my songs in the published datasets used to train Suno and Udio… the AI music saga continues…Then in the second half I pick up where I left off with the 11 part series I was in the middle of posting before I paused, returning with Part 7 of #AIWTF which is an episode I recorded back in April.Part 7 here looks at the extent to which AI music has been entering the charts, what that says about the collapse of chart integrity, and what happens when music becomes less about human choice and preference, and more about automated algorithmic success.We then move from there onto a wider reflection on social fragmentation, the erosion of shared culture, and the need for a lot more real spaces where people can gather, play, experiment, and feel connected again through their art.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 for €5 per month on Substack and Patreon. And lastly, you can still find me on YouTube and 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 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 DescriptionToday’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 a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit laurasheeran.substack.com/subscribe

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 descriptionToday 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 is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit laurasheeran.substack.com/subscribe

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 lastThere 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_ieThat’s all for now. Thanks for being here, and remember: Put humans first. Don’t feed the machines. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit laurasheeran.substack.com/subscribe

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 DescriptionContinuing 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. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit laurasheeran.substack.com/subscribe