On one side, there is what I would call AI Music: algorithmically generated sonic artefacts. These are the outputs of systems that produce audio, sometimes convincingly, sometimes not, with little or no human creative involvement in the compositional process. This is what most people picture when you say “AI and music” in the same sentence. It is what the headlines are about. It is what the lawsuits are about. It is, for many musicians, the source of a somewhat reasonable anxiety about the future of their livelihoods.

On the other side, there is Music AI: artificial intelligence technologies in the service of music creativity and music enterprise. These are tools that help musicians, labels, distributors, managers, promoters, choreographers, venues, writers (and, importantly, listeners – because let’s not forget that music is also communication and meaning-creation), and everyone else in the independent music ecosystem to do what they already do, but with new capabilities, new efficiencies, new modalities and new possibilities. Music AI is not about replacing musicians, though that is a genuine effect, and we do need to deal with that.

This is not a trivial distinction. It’s the distinction that determines whether you experience the next few years as something that happens to you or as something you have at least a degree of agency and deliberate control in.

I should make it clear that this is not a criticism of generative music. Algorithmic composition has been with us for a very long time, from Mozart’s dice games to Brian Eno’s generative systems to the procedural soundtracks of modern video games. There is a rich and legitimate creative tradition there, and it would be both inaccurate and unfair to dismiss it. The point is not that AI Music is bad. The point is that it is not the whole story, and treating it as if it were means missing the part most likely to be practically useful.

If you have ever read anything of mine before, you will know that I think of music as a fundamentally technological form. A goat skin stretched over a hollowed-out log to make a drum is a piece of technology. A musical scale is a technology. Notation, the concert hall, the vinyl record, the streaming platform: all technologies, all shaping what music is and what it can do. And importantly, we can not only use technologies, but we can also design them. We can hack into them. We can use them in ways that do not correspond with the manufacturer’s instructions. We can shape their meaning and purpose.

In 2014, at Music Tech Fest in Boston, we co-wrote a Manifesto for Music Technologists (the ‘Musictechifesto’) that put it this way:

“Music has always been technological. Bone flutes and drums are among the oldest known technologies.”

That manifesto asked what I think is still the most important question you can ask of any new music technology:

“For whom will this make things better? How?”

It argued that music technologies make worlds, and that we should endeavour to make better ones. That thinking still drives much of what I do.

It also means that none of this is particularly new to me, and I want to be clear about that, because the last thing the world needs is another commentator who discovered AI with ChatGPT in 2023.

In 2016, at Music Tech Fest in Berlin, we ran what we called Vocal AI Labs, experimenting with the intersections of artificial intelligence and the human voice in live performance. In 2019, we ran MTF Labs at the AI Impact Lab in Örebro, Sweden, focusing specifically on Music AI and Dance AI. Over the past decade, AI has been increasingly central to the work I have done and to how I think about the changing relationship between human creativity and technology. The reason I’m writing about it now is not that I have just arrived at the subject. It’s that the subject has arrived at a point where sitting down and carefully unpacking it has become genuinely urgent to an audience much wider than the leading-edge innovators and frontier artists I have the privilege of working with at MTF.

What I am interested in, and what I plan to write about here over the coming weeks and months, is the landscape of Music AI from the perspective of independent music, because that is what I am interested in. Not ‘how to’ use these tools. The world is full of YouTube tutorials and step-by-step guides, and I am not particularly interested in adding to that particular genre. I am not a ‘content creator’. But I do like to think about this stuff, and I sometimes like to talk about this stuff, and this seems a good space to do that. After all, it’s probably been sitting idle long enough.

What I’d like to try and map out is how to think about these tools: what their affordances are, what opportunities they present, what parameters are worth understanding, and what risks are worth taking seriously. As I’ve said for 20 years or more, in answer to the question “Should I be worried about this technology?”, the answer is always no. Worrying is not good for you, and it never actually helps. Understanding and acting, armed with knowledge, is a much better approach.

As with every significant shift in the technological environment around music, there are things that can help you and things that can harm you, and the difference is not always obvious. What matters is that you are equipped to make informed decisions rather than simply reacting to whatever the latest platform, product, or socially mediated moral panic has put in front of you. I am not here to tell you what to decide. I am here to lay out what there is to decide about. To help put the ‘think’ in whatever your ‘here’s what I think’ ends up being.

If you’ve been around New Music Strategies before, you will know that this is mostly what I do. When the internet was going to destroy the music industry, I wrote about what independent musicians could actually use it for. When social media was going to disintermediate and democratise, I wrote about what that actually meant in practice. Some of those observations turned out to be useful. I hope these will too.

For what it’s worth, I have what I consider to be the luxury of no longer being on social media, so people are unlikely to come across this in the usual sorts of ways people come across online articles. If you have found it, you read this far (thank you!), and you know someone who might find it helpful, please share it. Word of mouth is, as always, the most reliable and appreciated distribution mechanism in independent music.

And to answer your immediate question about whether I wrote this myself or used AI, the answer is yes. Yes, I wrote it myself, and yes, I used AI. As we go along, hopefully you’ll start to see how those two things can both be true, and how the more the latter, the more the former.

The post Music AI is not AI Music appeared first on New Music Strategies.

Take, for example, this quote:

“A world without crappy jobs means that rent has to be free, and healthcare has to be free, and every person has to have inalienable economic rights. And then suddenly we aren’t talking about AI at all – we’re talking about socialism.”

Exactly. If you’re going to fundamentally change society, and you’re going to do it rapidly, you need to do it intentionally and design it in such a way that you don’t ruin it for everyone. In fact, since you’re at it, why not actually address some of the problems that were already there.

Redistribution of wealth isn’t going to solve everything, but in the long list of things you could legislate to fix that would make a positive difference in the world, it’s in the top one.

However, I’d take issue with one aspect of the piece, and it’s this:

In the case of copyrighted material that we now know trained the models (including this newspaper), various lawsuits have been filed that will argue this was clearly illegal. Why, for instance, should a for-profit company be permitted to feed the paintings, drawings and photographs of living artists into a program like Stable Diffusion or Dall-E 2 so it can then be used to generate doppelganger versions of those very artists’ work, with the benefits flowing to everyone but the artists themselves?

And, of course, the same arguments are being made about music. But here’s the thing: that’s not how training an AI works. It isn’t making replicas any more than a country singer-songwriter, who’s clearly listened to a lot of Johnny Cash, Dolly Parton and Merle Haggard, is in the business of generating duplicates.

The AI is, as best as we can ascertain, looking at images, listening to music, reading text and then creating something new.

Now, the words ‘looking’, ‘reading’, ‘listening’ and ‘creating’ are all doing a lot of heavy lifting here, but those are more accurate analogies than, say, forgery.

And while I have about as much disdain for the motivations behind the wholesale swallowing of all scrapeable material off the internet for the economic benefit of a handful of billionaire-in-waiting tech bros as Klein does, I would go so far as to suggest that until or unless the AI generates a ‘copy’, no infringement has taken place.

Yes, it’s learning from your hard work and everyone else’s. And yes, it seems unfair that the people who are going to make money off that aren’t you – but the same principle applies as it did in the recent Ed Sheeran court case.

Obviously, Ed Sheeran has heard the music of Marvin Gaye. He’s probably ingested every piece of scrapeable content that Marvin Gaye ever produced (and isn’t that a lovely turn of phrase, ‘scrapeable content’?) – and a lot more besides. But it wasn’t copyright infringement. It certainly wasn’t theft.

He came up with something new.

Forget ‘originality’ because, like authenticity, it’s a myth, and nobody has a decent working definition for it other than that it’s something apparently magical that humans do. Ed Sheeran didn’t copy Marvin Gaye or replicate his work. He made something that was not the work of Marvin Gaye, but had very clearly been influenced by it. As certified by law.

And that’s the problem. This is not and should not be the battleground. This is not where we’re going to achieve ‘fairness’.

To do that, we need to look back at that first quote. The issue is not that the robots are stealing our work and taking our jobs. The problem is simply how society has organised itself with respect to money, who gets it, and for what purpose.

More to the point, the problems with AI (and they are many and vast) primarily lie elsewhere. Which is, I think, another conversation for another day – or you could just read the rest of the Klein article.

But just so we know where we’re at – the image at the top of this post is (obviously) AI-generated. It’s based on the prompt “Renaissance painting of a group of robots playing a rock concert to a large audience”. I’m not sure which Renaissance artist the AI could be said to have plagiarised here. If the picture resembles anything, it resembles itself: an AI-generated image, clearly derivative of other AI images.

It’s very literally painting by numbers.

The post AI isn’t plagiarising your music appeared first on New Music Strategies.

On 22 May, I’ll be speaking (all day!) about Emerging Technologies in Independent Music, with a particular focus on AI, Blockchain, Web 3.0 and Metaverse technologies. I’ll discuss the ways that independent artists, labels, promoters, venues and other independent music participants can use those technologies effectively, and I’ll also be talking about their wider cultural, economic and socio-political implications.

In other words, we’re not going to simply focus on which buttons to press and what levers to pull in the hopes of making extra cash (though that will come into it, of course), but we’ll also come to an understanding of what it means to use these technologies, how to think about them both as tools and the environments within which independent music takes place – and how not to get overwhelmed by an incredibly steep and exhausting learning curve.

It’s about coming away with a critical toolkit that we can apply in our day-to-day practice that makes the most of the technologies available, while engaging with the deeper issues that these changes also force us to address.

I imagine I’ll also be visiting my favourite shop in town while I’m there

The event is taking place in Aveiro (which, if you’re interested, is a city I made a short documentary about last year). It’ll also be available online with live streaming of all activities, so you can watch from anywhere. I’ll be there in person, along with some of my favourite people from the worlds of music technology and innovation.

In addition to the Masterclass, I’ll be joining an evening panel with Miguel Carvalhais (Crónica) and Terry Tyldesley (Kitmonsters), moderated by Tiago Abelha (Viral Agenda) about Technological Innovation & Disruption in the Music Industry.

Terry’s Masterclass the following morning on Technology, Creativity and Entrepreneurship in Music will also be pretty unmissable.

Other highlights of BREAK include a workshop with Matt Black (Ninja Tune) and Lucas Palmeira (Imaginando) on Creative Sound Processing, a Music Rights masterclass with Nuno Rodrigues (Arda Academy), Designing a Music Marketing Plan with Amber Horsburgh (Deep Cuts) and Independent PR for Independent Music: an International Context by Melissa Taylor (Tailored Communication).

This is all incredibly useful stuff.

You can register for all of this. Grab one of the few remaining tickets to be there in person, catch all the phenomenal live shows and hang out with us in Aveiro… or you can sign up to join us for free online!

The post Break in Case of Emergency appeared first on New Music Strategies.