What is generative AI?
There is a lot to be said about how the correct use of AI can improve what you are doing. You can get your code fixed, have whole articles written, and create stunning artwork. But that AI creativity is now heading into the music industry in a big way.
Writing, images, and music are all forms of creative expression, and AI can help you make it the best it’s ever been - but what are the pros and cons of using AI in music?
So, what is GenAI?
Generative AI, also known as creative AI, can conjure up brand-new content that we would classify as original in words, images, and music. On a basic level, the AI learns what it should be doing through training and data. A program will take instructions, sometimes a few, sometimes highly detailed, and deliver something that fits that criteria.
If you've never tested out AI but love music, a cool experiment is to use ChatGPT to create a playlist - see if it is better than one you'd curate!
Why is Generative AI becoming more common in the music industry?
For many, it might be a surprise to learn that AI has long been used across multiple industries, including music. It has been used to look at data, predict trends, and automate some processes.
Now, that is shifting to a more creative use of AI.
A few leading companies in the generative AI sector for music are Loudly, Amper, Boomy, Soundful, and Soundraw. These programs allow anyone to create music.
Using GenAI, you can create music on some platforms in less than one minute. For people who want quick music tracks for social media or even adverts - it is fast, effective, and, in some cases, a lot cheaper than hiring a professional.
What are the pros and cons of Generative AI in music?
It’s not just the music industry working through the pros and cons of generative AI - the question asked most often is, in the end, is that the work of the artists or the computer? So, what are the great things of AI that make sense in the music industry? And what are the downsides to having AI-generated music or using AI in someway?
Pros
Personalized music
We have already seen the use of generative AI in music for a long time, but as it improves, the personalized experiences we get through our streaming services are even better. So, a massive pro for music lovers is that you can enjoy an enhanced listening experience.
Efficiency
The modern world places a lot of value on speed, and generative AI automates things like effects, editing the audio, mixing tracks down, and other production tasks. For indie artists, this could be the answer to time constraint problems.
And for bigger artists, it could allow them to have more time working on their creative process and less time at the desk with producers.
Assistance and Inspiration
One area that can be particularly interesting for musicians is that instead of incorporating what has been produced by the AI music program into their work directly, they can look to it for some inspiration.
Since an AI music creator can often create rhymes, sounds, melodies, and harmonies quickly, it can make finding the right sound much faster.
Restoration and Preservation
Music spans centuries, and when some of those musical recordings are found - they are in a bad state; with generative AI, the chance to restore those pieces and clean them up, keeping them preserved for future generations is possible.
Cons
Bias
Generative models learn from the input they get, and one thing that has been prevalent over the last few years is that destructive and harmful information can be fed into the data pool. That then produces content with a set of biases, which can be reflected in the works it produces.
Unoriginality
Generative AI could be like Ouroboros - the snake that eats its own tail. We have seen examples of what AI-generated music sounds like through things like the ‘fake artists’ on Spotify and other platforms. Many journalists and music lovers noticed that the AI-generated tracks sounded almost identical. Over time, heavy use of AI in music could lead to a massive decline in music diversity.
Overreliance
When AI can do a job fast, with fewer mistakes - why would you do it any other way? While many artists wouldn’t go this route, younger artists looking for quick popularity might be tempted. In the end, this would see a decline in the overall skills in the music industry.
Careers
Imagine that you have trained for 20 years, worked with the best in the business - and are great at what you do. But an AI music generator or lyric creation tool can do it faster and, to some degree, maybe even better. Job displacement is something impacting almost all creative sectors with the rise of generative AI.
Which musicians are using generative AI or AI in any form right now?
AI has been part of the workflow for musicians and artists for a long time - but to a much lesser degree than it is right now. Here are some of the musicians and creatives using AI:
Kodak Black has been using generative AI to help create some personalized beats for his fans, which is also interesting. Using data about fans’ preferences, beats are designed to match up to what they like to listen to.
Electronic artist Arca has been using generative AI to create ‘textures and sounds’ that push the boundaries of her music. Specifically, it is used in the production phase.
In fact, they used AI to create 100 different versions of the same song, Riquiquí:Bronze Instances (1-100).
Creating an entire album with Amper Music and Taryn Southern has shown that something unique can be created when used effectively. In an interview with The Verge, Taryn talks about her experience using Amper Sounds.
She creates the lyrics and melody, while the AI handles some of the composition and production.
If you’re interested in hearing what an album with AI melodies and vocals sounds like, check out this album: Proto by Holly Herndon.
How does AI benefit the listeners on music streaming sites?
AI has been a key part of how streaming sites like Spotify, YouTube Music, and Amazon Music help you find more of what you love. But what does that look like?
Playlists
Entire playlists can be built on a single type of track - you might’ve seen the feature that Spotify has; when you select a playlist, you can shuffle or use the Smart Shuffle option. Songs that fit the tempo, style, and mood of the music you are listening to will be added.
Not only that, but streaming services can recommend other songs that fit your curated playlists.
And, for those with a specific listening pattern at different times, for example, metal in the morning but LoFi in the evening, when you open the app, you are more likely to see those recommended playlists at the right time. You can put Spotify AI DJ to the test, and see how much your Spotify really knows you.
Search and Discovery
When a search function has AI, it can help get you to what you want to listen to faster. It understands language to an extent and can work with queries and contextual cues, so the search and discovery feature is refined enough to match the user's intent.
Mood Detection and Matching
Let's say you wake up, and you’re feeling a little blue - and you are searching for sad songs or songs that might be classified as sad - even without using the search function.
The streaming service can detect that mood and match it in order to make suggestions that fit what you want to listen to at that moment.
Voice Search
With AI, you can tell your home hub or voice assistant to ‘play songs to dance to’ or ‘play songs for relaxation,’ and it will take that instruction and find something to match. Voice search is a language-based model.
What are the limitations of generative AI in music?
One of the biggest challenges faced by AI in the music industry is that a lot is missing that needs to be added. The nuances that come with the human emotion often displayed in music are part of the reason we fall in love with certain songs, which isn't something AI is great at.
If AI is overused, it can kill creativity - because if you aren’t truly in the creative process and let the AI take the reigns, there is a limited amount of personal creativity going into the work.
Not only that, but AI also has the potential to be misused to an extreme, and until there are some ethical guidelines, there are no real limits on the type of music that could be created.
And perhaps one of the biggest issues is who owns the music. AI-generated music isn’t the work of a human, and its legal status isn’t clear yet.
What does the future of generative AI in music look like?
With new technology, there is always a lot of incredible potential, and with generative AI in full swing and really just at the start of its possibilities, it could be an exciting time for the music industry.
But what could we see?
We could see a higher use of AI in songwriting and composition, and anyone who has used ChatGPT for written work will know how quickly it can work.
A combination of human and AI-generated works could result in more songs from your favorite artists. It might take a while for the AI algorithms to become sophisticated enough to understand emotions, patterns, and the context of what the musician is trying to create. But when they do, to a high enough standard, artists could produce more works at a faster rate.
Training and education in the music industry could see an influence from AI; building courses, adaptive learning experiences, and AI-powered learning tools for budding musicians is possible.
More interactive advertising and marketing that use some interesting taste and mood matching to create something more personalized to the users could be an interesting movie for streaming sites and record companies.
With the correct usage of generative AI, a general enhancement of the industry is possible - but it will depend on finding a balance between machines and people.
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