Will AI compose your next song? The future of music has a legacy

Introduction and historical context

In the last decade, artificial intelligence (AI) has made inroads into numerous industries, including music. This phenomenon has not only transformed the way music is created and performed, but has also raised profound questions about the authenticity and value of musical art in a world where algorithms can mimic human creativity. AI has evolved from its early days, where it was primarily seen as a technological curiosity, to become a powerful tool used by Musicians and Producers. But can AI really create music that resonates with human emotion and experience? This article will explore how AI is being used in music production, its advantages and disadvantages, and what the future might hold.

The evolution of AI in music

From the first experiments with simple algorithms in the 1950s to the development of computer systems far from machine learning today, AI has come a long way. Milestones like David Cope’s Experiments in Musical Intelligence (EMI) program, which generated original compositions, opened the doors to new possibilities. Today, platforms like AIVA, Amper Music, and Open AI™s Muse Net are at the forefront of AI-based music creation. These tools use neural networks and deep learning algorithms to generate music in various styles, which leads to the question: can AI really compose songs that are artistically valuable?

Literature review

Recent research has begun to address the use of AI in music from multiple perspectives. According to a study by Mc Millan (2020), AI’s ability to generate coherent musical patterns is notable, but it lacks the emotional depth that humans bring to the creative process. This raises the question of whether AI-generated music can be considered art in the traditional sense.

In their analysis, Williams and Harper (2022) argue that AI should serve as a tool that extends the creative capabilities of musicians, rather than a replacement. This suggests that, as technology advances, musicians can integrate AI into their creative processes to explore new forms of expression without losing their artistic identity.

Our use of AI in musical composition and production (listen to the song we made!)

https://open.spotify.com/track/2tb0Xo F2efh0Nj5Sw WV60D?go=1&sp_cid=b69bffbdf0ae26389a32669bd174d75d&utm_source=embed_player_p&utm_medium=desktop

For the creative development of the project with Marky Stardust, we used artificial intelligence (AI) as a key tool in the initial phase to generate a large amount of sonic ideas and possibilities. The AI ​​helped us experiment with different combinations of styles, structures, and musical elements. In this case, we created a unique production in the genre that we call Pop Post Punk (PPP), a fresh sound inspired by the authentic, but with a modern and different look to how productions were in the past.

AI allowed Marky Stardust to have a wide range of sonic options, refining every detail to find the perfect character that defined the final production. This provided a more agile creative flow, allowing different configurations to be tested before choosing a specific direction. However, we always put the final touch, ensuring that the human factor remained at the heart of creation.

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📸 Fotograma Específico de Referencia (Fotograma 1)

Fuente y Atribución: Captura de pantalla técnica extraída en el minuto exacto del tutorial educativo por Laidback Luke / Pioneer DJ.

• Detalle Técnico: Demostración de cálculo armónico entre claves 8A y 9A sin choques tonales.
• Ver Vídeo Completo: Ver instante exacto en YouTube

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To get this fr es cure, we use audio feature analysis, like the following:

¢**Danceability (0.859):**Reflects the track’s high ability to make people move, which fits perfectly with the PPP’s Ethical energy focus.

¢**Acousticness(0.0843):**Indicates that the track has a low probability of being acoustic, highlighting its electronically oriented production.

¢**Energy (0.85):**Maintains an intense, active feel, which is a key element of modern pop and post-punk.

¢**Tempo (140BPM):**An accelerated rhythm that provides dynamism and movement, vital to maintain the intensity in the PPP.

These metrics helped us ensure that the sound was not only innovative, but also technically suitable to appeal to a modern audience looking for something fresh and relevant in today’s music. The analysis of The AI ​​was a creative process, but in the end, it was the artistic vision and manual adjustments that defined the unique character of the song.

Comparisons and debates

Kumar’s (2020) studies highlight the technical limitations of AI in music, which tends to reproduce existing patterns rather than generate genuine innovations. On the other hand, Jackson (2020) points out that, although some roles within the music industry are at risk of automation, AI is also creating new opportunities for music professionals, which reflects a transformation rather than an elimination of jobs.

Analysis of recent discoveries

The adoption of AI in music has been driven by musicians’ desire to innovate and optimize their processes. For example, a recent study by Smith (2019) found that, although AI can help speed up technical tasks, the artistic decision is still in the hands of humans. This highlights the importance of human intervention in music production, even in a world increasingly dominated by technology.

Recent trend charts show an increase in the use of AI software among emerging musicians, indicating that many see AI not as a threat, but as a tool that can enrich their creative process.

Practical impact and applications

The applications of AI in music production are diverse. From creating melodies and harmonies to generating lyrics, AI tools are changing the musical landscape. Artists like Taryn Southern have used AI to produce entire albums, proving that musicians can adopt these technologies to innovate and reach new audiences.

Advantages and disadvantages of AI in music

Greater Creativity and Productivity

One of the most notable advantages of AI in music is its ability to increase the Creativity and productivity of artists. Tools like AI-based melody generators allow musicians to quickly experiment with ideas and explore new genres without traditional limitations.

Loss of originality and the human touch

However, there are also disadvantages. The concern about the loss of originality and human touch in AI-generated music is valid. As Pérez (2021) and Cohen (2021) point out, authenticity and cultural context are essential aspects of musical creation that The AI ​​cannot yet fully replicate.

The future of music: humans or machines?

The question that arises is: can AI replace musicians? The answer appears to be no, at least in the short term. Music is an art form deeply linked to the human experience, and although AI can generate music, it still lacks the ability to understand and express the complexity of human emotions. As Levine (2020) concludes, authenticity remains a crucial element that AI cannot replicate.

Our musical composition + production course with artificial intelligence (unique in its kind)

Artificial intelligence is transforming music production in fascinating ways. While it offers exciting opportunities for creativity and productivity, it also poses significant challenges in terms of authenticity and emotional connection. The key will be in how musicians choose to integrate these tools into their art, using AI not as a replacement, but as an ally in their creative journey.

What do you think about the role of AI in music? Leave us your opinion in the comments!

Literature

¢Mc Millan, D.(2020).AIinthe Arts:Creativity, Emotions, and the Future. Harvard University Press.

¢Williams, P.,&Harper, G.(2022).AIasa Toolfor Creative Expansionin Music. Technology and the Arts Journal.

¢Kumar, V.(2020).Technical Limitationsin AI-Generated Music. Journal of Artificial Intelligence.

¢Smith, K.(2019).Human-Machine Col labor a ti on in Music Production. Researchin Music Technology.

¢Jackson, T.(2020).New Job Opportunitiesinthe Music Industry Thanksto AI. Employment Trends in Creative Industries.

¢Cohen, J.(2021).Skepticism Toward AI-Generated Musicin Traditional Audiences. Cultural Studiesin Music.

¢Pérez, M.(2021).Culturaland Contextual Challenges without AI-Generated Music. Cultural Studies Review.

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Captura de Referencia: Explicación técnica de procesado extraída del canal de autoridad Waves Audio / Pensado’s Place. Calibración del medidor de sonoridad para sesiones de club y streaming.

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