How AI is shaping Generation Z’s music listening habits

We have been teaching a course on music and spirit for 4 years. At the start of every semester, we asked students to finish a brief, informal survey about their musical training and their favorite songs and artists.

Our students' musical training backgrounds all the time range from none to greater than a decade of lessons and ensemble lessons. But now we have observed that the list of favorite songs and artists gets longer and more varied yearly. When we ask the whole group about certain songs, it's often the case that nobody has heard them except the one that recorded them.

The results of those informal classroom surveys are consistent with current research showing diverse and varied music preferences amongst adolescents. In a study about the listening habits of middle school students in Los Angeleswe found that they value artists who represent a variety of genres, from K-pop supergroup BTS to heavy metal band System of a down to Beethoven.

But what happens when, as now we have observed, young people don't know what their peers are listening to? And does it matter that teenagers don't necessarily select the music they use to grasp themselves and the world, let alone that no human chooses songs they’re exposed to?

A shared soundscape becomes private

For centuries, the one method to experience music was to see it live – at small, private performances, at community gatherings or in large concert halls.

Radios and record players modified the way in which people interacted with music. However, because these devices were originally stationary, listening still had a social component. You could meet in a friend's basement to take heed to hits on the radio, have a listening party when a brand new album is released, make a mixtape on your friend, or sing a favourite song on the automobile radio together with your best friend.

Introduced in 1979, the Sony Walkman marked one other major turning point in the way in which people take heed to music. It became much easier to make music a deeply private and private experience – much more so with the introduction of the iPod and later smartphones.

Listening to music this fashion isn't all the time about what's pulsing through your headphones. It can even Cultivation Agency: No matter where you might be, you might be your personal DJ and control what’s played and when. And if you need to keep it private, nobody can hear it but you.

This is an enormous deal, especially for young people. A protective bubble is created This can counteract an absence of non-public space in school or at home.

Young people take heed to quite a lot of music in the middle of the day, be it doing homework, exercising, eating and even sleeping. There is a Element of mood regulation in the sport: Songs can distract unpleasant emotions or evoke positive ones and encourage reflection even during difficult experiences.

I even have 'algo rhythm'

Creating a playlist used to mean playing cassette tapes and recording individual songs onto one other tape, or waiting for the radio to play a song after which pressing record on the cassette player to record it song by song. until you had a mixtape of your favorite songs.

Now I'm listening often happens via streamingwhere artificial intelligence and social media platforms work together to suggest playlists for you.

As you discover and share music on social media, AI tracks activity and compares it with data from other listeners; In doing so, it refines its predictions about what you may wish to hear in the longer term.

AI is getting used to not only know what a user wants to listen to, but additionally to predict the following big hit that everybody will hear. Until recently, AI's ability to predict hits relied largely on song characteristics comparable to: Bounce, positivity and danceabilityand hovered at about 50% accuracy.

Other studies have analyzed physiological responses to music, comparable to heart rate, which could be determined from the biodata on teenagers' smartwatches. Predict top hits.

These studies reinforce existing concerns in regards to the exploitation of non-public information and data, and there have long been fears that that is the case AI can’t be trusted and can find yourself manipulating people. When it involves the way in which AI influences your listening habits, chances are you’ll be wondering whether you want a song because you actually prefer it, or whether you simply enjoy it since the AI ​​feeds you so many similar songs that familiarity led to appreciation.

Some listeners feel that algorithmic curation leaves them stuck in a listening rut. Their playlists are stuffed with songs and artists they've never heard of before, and yet all of them sound eerily similar.

The advantage of AI

In the past, an adolescent may not have noticed that he was consistently listening.

Subjected to a continuing eating regimen of the identical songs that play frequently on the radio – and later is MTV and VH1 – young people’s music consumption was dominated by “Top 40” artists. Their palettes were shaped by a widespread, if perhaps limited, repertoire of musical knowledge.

AI-generated playlists have disrupted this, and neither of us necessarily see that as a nasty thing. Young people have a panoramic selection of music at their disposal, and radio DJs, rankings and record labels now not act as gatekeepers.

Currently Spotify lists hundreds of genres and creates more yearly, in order that, as the corporate explainsThey are “more recognizable, representative and holistic for our listeners and communities”.

Just as you receive a treasured gift you never knew you wanted, young people could be exposed to great music—and the cultural traditions that accompany it—that they probably wouldn't have discovered on their very own Indian pop music, Japanese skirt or Afro Jujua form of Nigerian pop music.

Even if teenagers think their AI-driven playlists are boring, they still have the chance to go looking for brand new music. Just because algorithms and AI can suggest songs doesn't stop listeners from researching and discovering music themselves or sharing playlists with family and friends.

They can find every part that exists. The shop is all the time open.

Identity, community and music

Going back to our college class, we found little overlap between students. But moderately than simply consuming from a choice of industry megastars, our students demonstrated a willingness to take heed to quite a lot of genres and subgenres that AI has to supply.

When asked what song or piece they’d last heard in a given week, 6% heard R&B singer SZA, 2% heard singer Renée Rapp, 2% heard pop sensation Taylor Swift and a pair of% heard pop rockers The 1975 .

The remaining 80+ titles included a wide selection of genres: Computer musicRock, pop, rap, country, reggaeton, film music, heavy metal, indie and Latin ballads.

As young people transition from childhood to maturity, Two seemingly opposite processes come to the fore: forming a novel identity while becoming a part of a community. Listening to music and preferences play a very important role This process.

AI-generated playlists have the potential to challenge this transition.

So does AI make it easier to distinguish yourself but harder to attach with others? Or does it as an alternative offer a broader scope for self-exploration and community connection?

The truth is, nobody really knows.

Fears about latest technologies are commonplace. For example, as planned network television fell from graceAs a result, many common bases for discussion and connection disappeared. Will 50 million Americans ever tune in again to observe the series finale of a sitcom like they did with “Friends” in 2004?

If AI is actually helping to remodel teens' shared listening experience, then AI playlists are greater than only a convenient method to discover the following workout tune. They are a revolution price being attentive to.