With the rise of artificial intelligence and its increasing and pervasive presence in the music industry, curiosity abounds about how these developments might impact dancehall music and the artists who create it.
While it’s difficult to predict exactly how AI will shape the future of dancehall, it’s clear that this technology has the potential to both enhance and disrupt the industry in significant ways. From AI-powered music production software to machine learning algorithms that can help artists create new sounds and melodies, the possibilities for how AI could impact the industry are vast, exciting and somewhat terrifying, especially from the perspective of dancehall purists.
A Brief history of Dancehall Music’s Origin and Evolution
When the intersection of music and technology takes center stage in an argument of origins, Dancehall may be one of only a handful of genres that owe their existence to this initially unlikely coupling. Originating as a subgenre to Reggae, Dancehall – in almost every way – was everything Reggae music wasn’t. Where its predecessor sought the spiritual, Dancehall reveled in the carnal, and where Reggae flowed in live, rhythmic, and soulful performances, Dancehall proved more mechanic – relying heavily on fast-paced, pre-recorded digital music that eventually set the stage for its global ascension decades later.
Interestingly, the universal surge in Dancehall’s appeal was significantly aided by a concurrent explosion in technologies that not only expanded the genre’s reach but drastically improved its quality and creative latitude. This development, however, did not come without its pitfalls. With one of those being a kind of identity crisis for Dancehall itself, the discussion as to how it may not only cast aside doubts about what it is, but how it may also chart a sustainable path forward, must consider three important things: 1.) that Dancehall largely grew to its current state because of its use of technology. 2.) that Dancehall is, ironically, being severely impacted because it doesn’t quite understand the evolved versions of the technology that brought it here and, 3.) that in the final analysis, Dancehall may look and sound entirely different in the future because of the growing trends associated with AI use in every facet of music on a global and unprecedented scale.
What is Artificial Intelligence?
Through the prism of technological advancement, music, from creation to production, has essentially undergone its own version of a Renaissance, largely enabled by Artificial Intelligence (AI) and Machine Learning. Artificial intelligence, put succinctly by techtarget.com, is “the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI include expert systems, natural language processing, speech recognition and machine vision.” A more extensive definition, listed by Google, is that AI is, “the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.” The essence of AI, should we consider it within the parameters of the aforementioned definitions, seems to be a promise of enhancing, complementing and in some respect, replacing the need for human intelligence in certain processes. Powerful AI such as Google’s LaMDA is one such example of an AI fulfilling that mandate to near perfection. Earlier this year, Google engineer, Blake Lemoine, was fired after he had communicated extensively with the AI, and ultimately deduced that it was sentient – that it was alive. Google has refuted such claims, suggesting instead that the AI has only been trained to simulate human conversation based on data it has been trained on.
Though LaMDA has since been taken offline to undergo some tweaks, as a demonstration, the following was written by another AI when it was asked to, “Write a simple verse of an original Dancehall song for me”:
“Wine pon di edge, gyal you hot like a fire
Body so tight, yuh make me want to retire
You’re the queen of the dancehall, no one can deny
I’ll be your king, let’s rule the dance floor tonight
Dancehall queen, you shine so bright
Gyal you a superstar, shining through the night
Wine to the rhythm, let the music take control
We’re gonna dance until the break of dawn”
Though only the first verse and the chorus were posted, the AI provided an entire song – or a viable skeleton of one rather – with a bridge, in less than two seconds. With another prompt, it could have written 10 more unique verses in dramatically less time than it would take most skilled and professional writers. Considering this incredible efficiency, how do you imagine more advanced technologies dedicated solely to music production and creation might impact Dancehall music? Well, you don’t have to imagine it. It’s already here.
Powerful, open source music production AI, such as OpenAI’s MuseNet, is already being used in professional music spaces to create compositions that are virtually indistinguishable from, and in some cases superior to, those created by human producers. According to OpenAI, “MuseNet is a deep neural network that can generate 4-minute musical compositions with 10 different instruments, and can combine styles from country to Mozart to the Beatles. MuseNet was not explicitly programmed with our understanding of music, but instead discovered patterns of harmony, rhythm, and style by learning to predict the next token in hundreds of thousands of Musical Instrument Digital Interface (MIDI) files.”
It’s far from the only one. There’s Jukebox and Magenta, and hundreds of other tools dedicated to relieving the artist of the rigors associated with the creative process. Given how intensively automated most of them are, it may be more accurate to refer to them not as tools, but as vehicles – requiring the artist to not necessarily create, but to steer or operate a machine that needs only minimal input to produce. Mechanical, yes, but this incredibly high efficiency is nothing to scoff at, especially against the backdrop of a music industry that has become predominantly algorithm-driven itself, relying on the analytics from big data sets for their profitability, favouring a quantitative over a qualitative approach with regards to music. We know this as streaming, and it represents yet another frontier – dominated by AI – that the technologically lagging Dancehall industry, as well its artists, are having to contend with. For all the progress the genre has made on that front, one thing remains crystal clear – the chasm between the its aspirations and its reality is as glaring as it is abyssal, and, ironically, playing the game of the streaming giants may just be the way out. The cost, however, might be a deterrent.
Streaming, Trends and Sales
Spotify is the most popular music streaming service in the world. Created in April 2006, the Stockholm, Sweden-based organization lists its mission as, “to unlock the potential of human creativity—by giving a million creative artists the opportunity to live off their art and billions of fans the opportunity to enjoy and be inspired by it.” Whether intentional or an unlikely coincidence, Spotify’s mission explicitly communicates its reliance and dependence on numbers. That principle largely informs how the platform’s algorithms work.
While the fine-prints on Spotify’s internal churnings are a lot more sophisticated and detailed, to keep things simple here, it all boils down to what is deemed Quality Engagement, and the metrics imposed to determine such. They are:
High follower-to-listener ratio
High save-to-stream ratio
The traffic you generate outside of Spotify (websites and other social media)
Shares of an artist’s music elsewhere online
It gets more complicated when other important engagement metrics are considered, such as Popularity Index – which is a 0-100 scale rating of how popular an artist is compared to every other artist on the platform. Those elements, and the other cogs in the machinery that is Spotify, all mean improved chances of success for the artist, but also require effort that, quite honestly, Dancehall music has not been accustomed to giving, at least on the front of data and analytics. Of course, given that Dancehall is a genre whose existence and success predate Spotify and other popular streaming services such as Apple Music and Amazon Music, an alternative, instead of kowtowing to the ‘algorithm gods’, could be to simply avoid the platform and its ilk and do things the old fashioned way. Right? That would be a huge mistake.
Forget Spotify. Streaming has been on an absolutely destructive tear, particularly against traditional forms of revenue generation for artists, and this was especially evident in 2019. The RIAA reported then that the size of the U.S. streaming market surpassed the size of the entire U.S. recorded music market just two years prior to that period. By extension, in that same year, streaming services accounted for nearly 80% of all music revenue generated. As for subscription services, they contributed $6.8 billion, and paid subscriptions increased 29% to 60.4 million. Conversely, radio services declined 4% to $1.16 billion in that same year. Digital download revenue also fell below $1 billion for the first time since 2006, dropping 18% to $856 million. Album downloads decreased 21% to $395 million, while individual track sales fell 15% to $415 million. Downloads only made up 8% of total revenues last year.
All that’s a roundabout way of saying – unequivocally – any artist who takes themselves and their careers seriously must also take streaming seriously. Put another way, unless an artist has already established a career that can stand without being buttressed by streaming, they stand to make an incredibly risky gamble by attempting to circumvent Spotify’s stronghold on the global music industry. The AI game demands to be played, and Spotify can either be a very valuable ally, or an extremely formidable foe.
So, where does Dancehall stand amidst the AI web?
Here’s the competition – powerful AI that can write multiple unique songs in seconds; AI-driven music composition tools used by mainstream producers to create album-grade tracks, and algorithms that demand a consistent, committed and methodical approach to musical content before it grants you access to millions of new listeners. All this is juxtaposed against the fact that streaming giant Spotify adds a new song to its platform every 1.4 seconds. That amounts to 60,000 new tracks per day. How does Dancehall – a genre still trying to decide whether it’s more like Hip Hop than an offshoot of Reggae – begin to compete?
Well, perhaps the more readily apparent solution to jolt Dancehall from its state of limbo is to suggest that we simply join them. As it stands, Dancehall – or any genre for that matter, would be hard-pressed to find a chink in the AI-streaming machine’s armor. It begs the question though – what more do we stand to lose should we maximize efficiency for quality? What makes Dancehall… Dancehall? Can we afford to sacrifice some amount of the content of the music, and by extension some amount of its already troubled identity, for a shot at widespread and consistent exposure? With new forms of Dancehall, such as Trap Dancehall emerging, it appears that compromise is already being made.
In the final analysis, it is unclear how much of Dancehall – from the genre’s creative processes down to its end products – can change before it stops being Dancehall. That concern, however, must be tempered by the reality that Dancehall isn’t going anywhere any time soon. It remains a popular genre of music, and artists like Drake, and producers like DJ Khaled, have capitalized on it to their, and to a lesser extent, the genre’s benefit.
Depending on how it’s used, Artificial Intelligence can be a powerful ally for Dancehall. Use it too much and the genre becomes a homogenized mass of algorithm-pleasing-blocks of superficial content by artists dying for fame at the expense of authenticity. Use it too little and we drown beneath the inevitable wave of AI-optimized music. Use it just right, and the genre may secure its future while proving its viability as a genre deserving of sustained global attention and – of course – capital.