From Kraftwerk to AI — how how tech powers music creation
Publication date: September 20, 2024
Artificial intelligence is fast becoming a part of our lives, especially in popular culture — fuelling many debates about the effect of AI on creativity, plagiarism and authenticity.
The use of AI-generated visual art and deep-fake videos on social media is rising exponentially, and Chat GPT is now the scourge of teachers and lecturers worldwide, but one recent story has opened up a huge discussion about AI in music, and the legal implications.
North Carolina man Michael Smith was arrested for creating AI-generated music and fraudulent streaming schemes. By using bots and AI-generated songs, Smith allegedly scammed streaming platforms out of over $10 million in royalties — and it’s safe to assume many people worldwide are also gaming the system and haven’t been caught yet.
AI is also being used to resurrect the voices of musical legends. Recently, a demo recorded by John Lennon in the 1970s was restored using AI, allowing The Beatles to release a ‘new’ song, Now and Then, decades after their last track.
And let’s not forget the viral sensation created by Ghostwriter977, whose AI-generated song Heart on My Sleeve, featuring vocals mimicking Drake and The Weeknd, was pulled from streaming after Universal Music Group condemned its use of “infringing content”.
As we keep playing catch-up on the rise of AI, let’s explore how coding and AI are revolutionising music production — the benefits and the ethical minefield.
The rise of coding and AI in music creation
Music production has always been a blend of artistry and technology. From early synthesisers to digital audio workstations (DAWs), tech has played a key role in pushing music forward.
When German electronic pioneers Kraftwerk appeared on the BBC science programme Tomorrow’s World in 1975 to introduce their new form of rudimentary synthesiser music, even the prophetic Germans couldn’t have predicted the seismic shift of AI in music.
Kraftwerk’s Ralf Hutter said the band had a symbiotic approach to music, saying: “We are playing the machines, the machines play us, it is really the exchange and the friendship we have with the musical machines which make us build a new music.”
However, most AI-generated music is largely stripped of human input, instead capable of creating compositions autonomously.
Kraftwerk revolutionised music in the 1970s by using sequencers, synthesisers and early computer-based technology, but when Ralf sang in 1980, “I programme my home computer, beam myself into the future”, would he embrace the musical landscape in 2024?
Algorithms can analyse millions of songs, understand patterns in melodies, rhythms, and even emotional tone, and then generate new pieces that mimic those patterns. Platforms like Amper Music and AIVA allow users to input parameters, and the AI will compose a piece of music tailored to those instructions.
Meanwhile, coding tools such as DAWs (like Ableton Live, Logic Pro, or FL Studio) provide producers with the ability to manipulate sound in ways that were once impossible. These platforms allow for precision editing, real-time effects, and collaborative projects with artists across the globe. Coding is also behind many of the plugins and effects that producers use to alter sound, from reverb to pitch correction.
One of the most popular uses of coding in music is through DJ software, such as Serato or Virtual DJ. These programmes allow DJs to manipulate tracks in real-time, beat-match songs, and even create seamless transitions using coded algorithms. AI has recently entered the DJ space, with features like automatic beat detection and song recommendations based on crowd response.
And the ability of a DJ to select tracks from a choice of millions in the cloud feels light years away from the 90s, with techno DJs travelling with heavy bags of vinyl that got updated gradually as they visited record shops in different cities worldwide.
AI and music production — the benefits
- Accessibility and creativity: AI tools and coding software have democratised music production. Historically, creating music required expensive equipment and years of training. Now, with tools like AIVA, aspiring musicians can create complex compositions with little to no musical background. This opens the door for more diverse voices in the music industry, fostering creativity and innovation.
- Efficiency: For seasoned producers, AI and coding can speed up the creative process. AI tools can suggest chord progressions, generate harmonies, or even recommend mixing techniques. This allows artists to focus more on the creative aspects of music-making, reducing the time spent on tedious tasks like editing and mastering.
- Preserving musical legacies: AI has shown promise in preserving and restoring the works of past artists, as demonstrated by the restoration of John Lennon’s demo. These tools can clean up old recordings, remove noise, and even fill in missing parts to bring forgotten tracks to life.
- Collaboration and innovation: AI-driven music creation encourages cross-industry collaboration. Coders, data scientists, and musicians are working together to push the boundaries of what’s possible in music. This has led to entirely new genres and musical experiences that blend traditional composition with AI-generated elements.
The ethical implications
Despite its potential, the use of AI in music raises serious ethical concerns, highlighted by cases like Michael Smith’s alleged streaming scam or Ghostwriter977‘s viral track.
- Ownership and originality: One of the biggest issues with AI-generated music is the question of ownership. If an AI creates a song based on millions of pre-existing tracks, who owns the final product? Is it the creator of the algorithm, the user who inputs the parameters, or does the original artist whose style was mimicked have some claim?
- Fraud and exploitation: As seen in the case of Michael Smith, AI can be used to exploit streaming platforms. With bots streaming AI-generated music, it’s possible to manipulate the system and earn royalties without a single human listening to the music. This undermines the integrity of streaming platforms but also takes money away from legitimate artists.
- Deceptive content: The viral song Heart on My Sleeve raised concerns about how AI can be used to create fake content that mimics real artists. When listeners can’t tell the difference between AI-generated and authentic vocals, it raises questions about authenticity and the potential for deep-fake music to mislead fans or damage artists’ reputations.
- Impact on musicians: There is growing fear that AI-generated music could replace human musicians, particularly in industries like advertising or video game soundtracks, where AI can churn out music at a fraction of the cost. While AI can’t yet replicate the emotional depth and nuance of human composition, it seems only a matter of time before this ‘uncanny valley’ is crossed and we can’t tell the difference.
Navigating the future of AI in music
As AI and coding become more intertwined with music production, the industry must strike a balance between embracing innovation and protecting artists’ rights. One potential solution is clear guidelines and regulations on how AI-generated content is labelled, credited, and monetised.
Additionally, collaboration between tech companies and the music industry is essential. By working together, these sectors can develop tools that benefit both artists and consumers while addressing concerns about fraud, ownership, and originality.
AI’s role in music is still in its infancy, but its impact is already profound. The industry must balance innovation with artists’ rights through clear guidelines on AI-generated content and collaboration between tech and music sectors to address concerns like fraud and ownership. As these technologies continue to evolve, the challenge will be to ensure that innovation enhances, rather than diminishes, the artistry and integrity of music.
