Music: What is it Good For? [Hanna Kahlert, MIDiA & Stephen Love, Socially Driven Music]
[EXCLUSIVE] In this companion piece to “Music – It’s About Purpose, Stupid,” Stephen Love, former EVP of ATV Music, and Hanna Kahlert of MIDiA Research dig deeper into how revaluing meaning and purpose in music is the antidote to its increasing commodification.
With tens of thousands of tracks already uploaded daily and AI promising to multiply that number, the pair argue it is time for “a conscious reconsidering of what makes music valuable, what makes it good, and how to make sure the important bits get communicated…”
By Hanna Kahlert of MIDiA Research and Stephen Love, founder of Socially Driven Music
In our companion piece previous essay, we spoke at length about the ‘purpose’ of music, and how in the scramble for likes and streams and the ‘next big mainstream hit’, the impact of its meaning has been increasingly diluted and, perhaps, devalued. Something which needs conscious addressing, by recontextualising music with regards to wider social needs and movements.
Nothing makes this conversation more important to have today than the rise of generative AI.
A recent op-ed by Nick Cave contends thus; “ChatGPT’s intent is to eliminate the process of creation and its attendant challenges, viewing it as nothing more than a time-wasting inconvenience that stands in the way of the commodity itself. Why strive?, it contends. Why bother with the artistic process and its accompanying trials? Why shouldn’t we make it ‘faster and easier?’”
Others have greater optimism. Some artists are already using AI as a tool to support their new work and collaborate with others. Like autotuning, MIDI keyboards, or synthesizers, they see AI as just one new piece of tech that can allow them to explore new creative highs.
To quote MIDiA’s Tatiana Cirisano,
“The artists that will stand out in the future, or the ones that stand on their own outside of this AI-generated arena, will be the ones who are constantly reinventing themselves and are unpredictable, and are inimitable… so I think it will actually push creativity forward, which is a good thing in the end.”
Indeed, the ‘threat’ of generative AI is also its opportunity: it frees existing creators to do more with what they have, and opens the creative field to anyone who wants to explore it without the resources previously gatekeeping entry to the music-making space. Yes, this is putting pressure on discovery and remuneration, but these were already issues the industry faced as a result of streaming proliferation – nothing new, only increasingly strained. If anything, putting creativity back into the hands of everyone can only be a good thing, if one looks at art for arts’ sake. The caveat here is that we must devise a methodology for separating genuine talent from average hobbyists. This is essentially the same distinction employed by successful A&R executives over the decades, but which has seemingly fallen behind in the digital deluge.
The philosophical challenge is thus: will AI increase and expand creativity, or will it simply commodify it? The sci-fi future promised us in the 80s was one of robots doing menial labor, freeing us all for creative challenges of our choice. Instead we have robots doing our creative thinking for us, that it may be made faster, uploaded faster, consumed faster, and forgotten faster – and, in the meantime, make money for services through sheer quantity rather than any consideration of quality. This seems concerning. It should be a question in all of our minds as we explore this new technology and its uses, and should shape our decisions on all levels to protect the creators and their fans who have built this industry in the first place. Music is not a commodity: it is a form of art, language, and expression which has been with us since the dawn of our species. It is part of what makes us human, and thushanding it over to the robots can feel inherently wrong… but it is our thoughtless packaging of it that forces this devaluing, accelerationist frenzy that is the heart of the problem.
Labels and DSP’s created and now exacerbate the deluge of dubious quality music. They will have to embrace purpose in the AI realm as a key to isolating professional music from hobbyists, including identifying voice cloning versus impersonations to help determine copyright protection. This purposeful music is that which can be licensed to generate ancillary revenue, beyond streaming, especially when tied to causes and supportive brands. The Blockchain and watermarking will prove invaluable in determining and tracking the underlying music rights provenance and distinguishing background and mimicked music from that more deserving of larger royalties earning.
“Imagination is everything. It is the preview of life’s coming attractions.” – Albert Einstein
Optimists will say that there is no difference between AI and synthesizers or autotuning, which caused similar anti-progressive (luddite) fear mongering that they would devalue the art of music. However, there is a substantial dynamic shift. Whereas synths and MIDI keyboards and autotuning came about as technical discoveries and explorations by music creators themselves to support their own work, AI has been created by tech companies in a race to beat the competition to the next iteration of the internet. Unlike previous new technologies, AI has become available to everyone all at once, with no clear use case except anything one can think to try. It is a leveling free-for-all, and thus its ups and downs are likely to serve only those in the fortunate position to take advantage, wherever and whoever they may be. As we have seen in the past few years, given the existing challenges of streaming and broader digital proliferation and attention saturation, this usually means those who are already ‘successful’ – making it ever harder to become so for those who are not.
In short: it has never been easier to become a music creator (quality be damned), but has never been harder to be a successful one. And, yes, this will have an impact on the amount of music that gets made. Who makes it, and why. It affords opportunities for socially poignant songs to become successful, bringing lasting cultural value. Our premise illuminated in both our companion essays is that it behooves the music industry to embrace the value of #Music4APurpose across diverse business sectors for major reciprocal impact at a time when companies are coming to understand that consumers want social purpose in turn for product brand loyalty. Consultancies like Socially Driven Music (SDM) understand this and is the de facto leading, forward-thinking consortium that connects the dots between a mosaic of the complex music business and positive social advocacy groups for reciprocal benefit. It is a facilitator that cultivates original copyrights and links talented music creators, their fans and brands with positive social impact causes who don’t despair, but instead share a passion for actively making a difference.
There may even be a supplemental role for AI to play. Some established artists (like Grimes) are already being selectively encouraging, inviting “open-verse challenges” and the like, with fans using AI to iterate their own version of a song. This can be a potent artist strategy to pursue, made more meaningful if parameters are set to funnel the iterations to social impact themes which can lead to brand support and contests.
In this rush for automation, then, the human touch with its Emotional Quotient (EQ) must become the distinction – across the value chain. If AI is simply another tool, it is those artists who can wield it well that will stand out. Amid the algorithmic chaos of what is most likely to earn a ‘like’ from the masses on a social platform, personal curation – be that individual, or through tastemakers like radio hosts of Ye Olden Days of ten years ago, remains the differentiator. And from the growing cacophony of background noise at every turn, it is music with purpose that can resonate through and beyond.
Inextricable from this broader philosophical crux point are a myriad of other foundational quandaries. Copyright is one. AI has to learn from something in order to be useful – and that ‘something’ is the vast catalog of all recorded music, which it analyzes, judges, and spits back out in ways that are sometimes novel and sometimes close to mimicry. The current ‘black box’ problem of the models makes it impossible to attribute output to input, something which has caused lawsuits in visual art and literature, and is a hotbed topic in music as well. Who gets the rights to what AI helps generate, and when? If you create music, and it goes into the void, will you ever see a return – or will it simply feed an algorithm that never looks back to say ‘thanks’?
This is likely to grow more complicated, as a recent Europol report estimates that as much as 90% of all content on the internet could be AI generated or assisted by as soon as 2026. As this AI content goes back into the training datasets to make more AI content, the origins grow ever more complicated, and the output increasingly will homogenize. If anything, this will up the value of human-generated works: a potential win for creators. In all this, the blockchain – dismissed as a novelty up to now – may find its use as a way to track origin and ownership… but the increased fragmentation of rights, and further dilution of value through proliferation, will remain issues.
The saga of iterative artists may also raise questions about the legitimacy of some infringement claims, where derivative works do not contain prior works of the mimicked artists. “Right of publicity” pertaining to Name, Image and Likeness is unsettled law as to whether voices and characters of people can be infringed (ironically, fictional characters can be protected). So, we could see more ‘virtual artists’ like Gorillaz and avatars represented by agencies (as in the case of CAA and Angelbaby) – and these could, in turn, push boundaries of existing copyright laws which differ around the world.
The Human Artistry Campaign (HAC), was created by the RIAA and a coalition of over forty others to begin to set out copyright parameters for using AI in music and other works. However, the initial draft HAC outline is defensive and doesn’t meaningfully contemplate positive applications of AI that extends music reach; e.g., the artist Lauv’s venture with Microsoft and innovation agency Superfly, called “My Blue Thoughts,” which utilizes AI to allow fans to express their insecurities and share solutions by connecting with like-minded others. In addition to prose, this will inevitably spawn generative AI musical responses which may challenge and transcend inflexible restrictions as it builds a community.
Another project involves fans developing an Annual Soundtrack for Intentional Living, themes instead of New Year’s Resolutions, with music they choose for motivation across diverse activities for which one wouldn’t necessarily create playlists. The interactivity potential is endless. Major transformation will also potentially come with extensive use of AI in lyric translation and transposing music videos to local languages, especially should translations be licensable and copyrightable by the original songwriter or publisher. We also envision a proliferation of “pitch records” which use AI to demonstrate to artists what they would sound like were they to record a proposed song, including as a collaboration with other artists or the fan songwriter themselves. An extension of this is the potential of licensing emerging voices (not necessarily aspiring artists) to create virtual artists and avatars and pairing them with new songs which seem undeniable. And, as we discussed in our companion piece (LINK), there are tremendous opportunities to develop “Exponential Rights” as an established songwriter or artist collaborating with emerging or fan-based creators.
In summary, the threat: a potential existential threat to the value of music through commodification. The challenges: rights, remuneration, ownership. The opportunities: a freeing of creativity from old constraints, available freely to everyone. And the actions that need taking: a conscious reconsidering of what makes music valuable, what makes it good, and how to make sure the important bits get communicated across, from creators to audiences to the immortality of cultural impact.
Superfans can only derive from music that speaks to (or for) the listener and holds and pumps hearts with intensely relatable emotion that cannot be created by machines alone.
The answer is complicated yet simple at the same time: this is an unfolding turning point, a sea-change event in music and culture. Across the industry, we are all exploring its uses and testing its boundaries. And to ameliorate the threats, and capitalize on the opportunities; the more the conversation turns to robots, the more the answer is to remember what is important at the heart of what we do: humans, our communities, our world, and the meaning we create together.
