Not only does each generation get its own popular music, it also experiences music differently from previous generations. Never has that been truer than now, when computerisation and the internet have transformed the way songs are made and listened to. Here are three principal trends as pop enters the 2020s.
Part I: young producers
Teenagers have been the driving force behind the growth of pop music, ever since the “Sinatramania” that Frank Sinatra inspired in the early 1940s. But the making of pop has traditionally been undertaken by adults. Even when the performers have been teenagers or younger themselves, their producers have invariably been older. The Jackson 5’s first album, for instance, was co-produced by a soul singer in his mid-30s, Bobby Taylor.
Now, the adult grip on youth culture is being pried away. Technological disruptions to traditional ways of recording and distributing music have allowed young people to bypass the involvement of older generations. The producer, the person at the controls in the studio — or the laptop in the bedroom — is getting more youthful.
“At the younger end of the scale, we’ve got 14- to 16-year-olds coming in a lot,” says Anthony Larbi, co-founder On Da Beat recording studio. “They’re writing the music and co-producing with each other. They record and engineer the sessions as well.”
Based for the last two years in a west London industrial estate, On Da Beat is a port of call for up-and-coming rappers and producers wanting to make professional quality recordings. Often their songs are made at home using laptops, sound cards and music production software such as FL Studio and Ableton, which are easy to buy (or illegally download). If it does well, the song will be re-recorded using better equipment at the studio to take it to the next level.
Where once studio skills would require years of training, now they can be picked up quickly. “Some of them have experience but the majority have to be walked through,” Larbi says of the teenage producers who use his studio. “How to power things up, what different pieces of hardware are used, what plug-in to use. The majority of them don’t know, they have to be shown. But I’ve noticed they pick it up really quickly.”
As a technology-led art form that developed outside the music industry, hip-hop has always had young producers. Rap pioneer DJ Kool Herc was a teenager when he unveiled his breakbeat style at the record decks during a “back to school jam” in his Bronx apartment block in 1973: a foundational moment in hip-hop. Dance music is another genre with a tradition of teenage DJs and producers.
These days, Herc has numerous descendants around the world, all plugged into a new music industry infrastructure that rap has helped form. Among the producers at On Da Beat is Mikabeats from Newham, east London who began making beats at 15. Now 20, he produced “Haters” by west London rapper Lil Dotz, which has been viewed 3.3m times on YouTube, and “Hoods Hottest” by the Manchester rapper Meekz, which has 5.5m views. One of the biggest songs of 2019 was produced by a teenager: YoungKio was 16 when he provided the beat to Lil Nas X’s country-rap crossover single “Old Town Road”. Lil’ Nas X bought the beat for $30 from the website BeatStars, and the song went on to spend a record-breaking 19 weeks at the top of the US charts earlier this year (when it went viral, YoungKio and Lil Nas X negotiated a new contract).
The trend is spreading outside rap. Billie Eilish’s rise to stardom began in her brother Finneas’s bedroom in LA, where he produced her songs using commonly available music-processing tools when they were both teenagers. That was where her debut album When We All Fall Asleep, Where Do We Go? was made. Her whispery vocal at the forefront of the mix, at once introverted and forthright, is not just the perfect teenage register. It also heralds a new era of unadulterated production.
The days of adult supervision are not entirely over, however. “We have to communicate with their parents quite often,” Larbi says of the young producers at On Da Beat studio, “just to let them know what their children are up to.”
Part II: the new fandom
A few weeks ago, Ashnikko, a London-based, US-born rapper, discovered that her track “Stupid” had amassed 1,000 films on TikTok, the app that enables people to make short music videos, lip-syncing to favourite songs. “I was like, ‘Sick! That’s cool,’” she recalls. “Then a week later it was on 200,000. It just snowballed from there. Now it’s on like 2.5m. It’s crazy.”
TikTok is itself a viral hit. Launched in China in 2016, it now has 500m users worldwide, mostly aged under 24. Its parent company ByteDance was estimated last year to be worth $75bn. The app’s roots can be traced back to karaoke, another interactive technology that originated in Asia. But in this case the interactivity runs deeper.
Online platforms like TikTok have transformed the relationship between performers and audience. The act of creating memes and personal videos from favourite songs highlights the performative aspects of being a fan. Just as streaming has disrupted traditional ideas about owning music, so TikTok raises the question of who songs belong to: the original performer or the meme makers?
Asknikko regularly sets aside time to chat online with her followers. “I engage in most of the group chats and try to make them feel appreciated,” she says. “It’s a good culture.” The likes of Instagram and Twitter make it possible for her to go engage instantly with them — a far cry from the days of sending out signed photographs in the post.
“That was so impersonal,” says Ashnikko, real name Ashton Casey. “Now you can have direct contact with your fans, which I think is so important because without fans you wouldn’t have a music career.”
There is a truism that music matters less to young people than it used to. But it is actually reaching further into their everyday lives than ever before. The internet enables communities of fans to communicate constantly, cementing their group identity wherever they are.
Camps of Arianators and Swifties stake out the digital commons like transnational powers. Rivalries are common: aptly, the followers of K-pop supremos BTS are nicknamed the “Army”. Often female in composition and mocked in the past for their fannish super-enthusiasm, such groupings are now a formidable force in pop’s landscape, a guarantor of cultural heft and revenue at a time when record sales have dried up.
Ominous possibilities for data capture are opening up. Last year it was revealed that Taylor Swift was using facial recognition software at concerts, ostensibly to identify stalkers. But fans are not just cash cows, meekly forking out for an overpriced Ed Sheeran hoodie.
There is a tension between exploitation and self-expression in fandom. Fans are the target of ruthless merch sales, yet they are also responsible for creative activities like fan fiction or cosplay (costume role play). This tension has been brought into sharper relief by the internet. Where once there were “fan clubs”, now there is “fandom” — the total condition of being a fan.
But there is a negative flipside to participatory fandom: haters can have their say, too. In Ashnikko’s case, the assailants are mainly male. “The thing that I don’t like is these lame ‘fuccbois’ doing their remixes to ‘Stupid’,” she says. “There are loads of them on TikTok right now. Like ugh, vomit. They can’t let a girl have anything.”
Part III: Artificial intelligence
“Popular song factories” where songs “are manufactured, advertised, and distributed in much the same manner as ordinary commodities” was how the New York Times described Tin Pan Alley in 1910. History’s judgment has proved kinder. These days the sheet music industry of Tin Pan Alley is viewed as a golden age of American songwriting.
Contemporary anxieties about manufactured music have shifted to artificial intelligence and machine learning. Powerful computer systems survey and analyse our listening habits. Others write music. To pessimists, it places us in a double bind. We are becoming machines, docilely accepting whatever music is presented to us by algorithmic recommendations and playlists. Meanwhile, the machines are turning into us, composing music as though ticking off another entry on their bucket list of conquerable human activities. But this nightmarish vision of displaced humanity is not quite correct.
“Artificial general intelligence” is the term for technology that can think autonomously, a digital version of ourselves. “Depending on who you talk to, it is either just around the corner or won’t happen in our lifetime,” says music technologist Arthur Carabott of Los Angeles-based music software firm Output. “That’s the vision that science fiction presents to us and the one that sells well in the media, of an artificial intelligence like us. Whereas what we have instead is a huge amount of targeted artificial intelligences, geared towards specific tasks.
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This year, an app called Endel that gathers data about its users and creates bespoke mood music became the first algorithm to sign a deal with major record label, Warner Music. But tomorrow’s Tin Pan Alley is unlikely to consist of a data silo with numerous Endels grimly churning out pop songs. Programmed to recognise and generate musical structures by analysing millions of pieces of music, AI compositional software is imitative, the Björn Again to our Abba.
Rather than replace human songwriters, AI is more likely to become established as an aid: a tool for helping find a chord progression, say. A bigger change will come with the convergence between machines that survey what we listen to and machines that write music. As AI understanding of music grows more sophisticated, it will go beyond melody and harmony to grasp fuzzier concepts of character and timbre. “There are some untapped, more human aspects to music that haven’t yet been mined but will be,” Carabott says.
The Japanese virtual pop star Hatsune Miku is a portent. Taking the form of a cartoon 16-year-old girl, “she” is a singing voice synthesiser with more than 100,000 songs in “her” catalogue (anyone can write one), who tours the world performing 3D concerts. It may not be long before such technology is able to mimic the voice of a famous singer — Aretha Franklin, for instance — and set it to new songs with the feel of Franklin’s work.
In such a future, the controversial ruling by a US federal court in 2015 that the hit “Blurred Lines” infringed the copyright of a Marvin Gaye song may be reassessed. The ruling has been widely condemned as a dangerous expansion of plagiarism to incorporate notions of musical character, the feel of the song rather than specific chords or lyrics. But it will take on new significance in an age of AI-moulded songs that sound familiar and new at the same time, simulacra but not exact copies.