AI and Music Production: Cheating or Revolutionizing Creativity?

TL;DR

AI is revolutionizing music production by making it more accessible and efficient. Platforms like Suno.com allow users to create music quickly and easily, sparking debate over whether this enhances or undermines traditional creative processes. While some critics see AI as "cheating," I view it as a collaborative partner that enhances creativity. This post explores the benefits, challenges, ethical considerations, and personal experiences with AI in music, highlighting how AI can democratize and enrich the creative landscape. Join the conversation and share your thoughts on AI's role in the future of music.

Today, I’m exploring a topic that generates strong opinions in both the music industry and among casual listeners: the role of AI in music production. Specifically, I want to delve into how innovative AI tools like Suno.com are revolutionizing music creation, making it accessible to those without extensive resources or musical training. Are these tools enhancing creativity or undermining the traditional values of music production?

Let’s explore this complex and fascinating landscape.

A New Era of Music Production

The traditional process of creating a song is a complex mix of art and logistics. It involves writing lyrics, composing the music, assembling a band, finding a singer, hiring a studio, and spending countless hours in recording and editing. This not only demands a great deal of time but also significant financial investment and logistical coordination. And that's before we get into the process of releasing and marketing your work...

Enter AI music production tools. Platforms like Suno.com have democratized the ability to produce music by simplifying these steps into a process that can take just a few minutes to hours. But does this ease of use compromise the integrity of the creative process? Let's consider further.

Suno.com: A Case Study in AI Music Innovation

Suno.com stands out in the growing field of AI music tools by offering user-friendly interfaces combined with powerful machine learning algorithms that can analyze user input and generate compositions in multiple genres. For example, I used Suno to create a song by writing a short prompt to define the production I'm looking to achieve. Usually, this includes identifying a genre, setting the tempo, choosing instruments and outlining a vocal style. The AI then generates a pair of outputs using the lyrics I have entered.

The exact results are still subject to a great deal of trial and error, especially if you have a very clear idea of what you're trying to achieve, but what might take months in traditional production process, instead take hours.

Redefining Creativity

Some critics argue that using AI to produce music is "cheating," suggesting that the value of music lies in the laborious effort involved in its creation. This perspective holds that the traditional, painstaking process of music production is intrinsic to the art's value.

I see it differently. AI should be viewed as a collaborative partner, not a shortcut. It’s about how AI and humans can interact creatively. The real value lies in the ability to experiment rapidly, test different musical arrangements, and fine-tune lyrics in real-time, which significantly accelerates the creative process. This symbiosis allows artists to explore new sonic landscapes and push the boundaries of their creativity.

Using AI tools, I can input my initial concepts and see them evolve into a structured piece of music. This rapid iteration process is akin to brainstorming with a partner who never tires—constantly offering new variations and inspirations. This interaction enhances the creative process by opening up possibilities that I might not have considered on my own.

Do I see the final results as comparable to high end song production? No. But they do provide at least an excellent starting point for a demo to start a conversation.

The Role of AI: A Collaborative Partner

One of the most exciting aspects of using AI in music production is its role as a collaborative partner. Traditional brainstorming sessions with family and friends, while valuable, often have their limitations and biases. They may lack the time, specific interest, or expertise to dive deep into every creative nuance with the same enthusiasm and endurance as an AI.

Engaged and Unflagging Creativity

AI, particularly tools like GPT-4, offers a level of engagement and consistency that is hard to match. When I brainstorm with GPT, I can start with a theme I want to explore, a selection of songs that inspire me, or a specific emotion I want to convey through music. GPT then works tirelessly, generating ideas, refining concepts, and suggesting new directions without ever growing weary or impatient.

For instance, if I want to write a melancholic ballad, I can input a few lines of lyrics or describe the mood I aim to capture. GPT responds with a plethora of suggestions, offering different ways to express that emotion. This iterative process allows me to experiment freely and rapidly, adjusting and refining my ideas as I go. If I decide to pivot and explore a different theme or style, GPT adapts immediately, providing new insights and suggestions aligned with my new direction.

This collaboration then extends into the song AI where I will often tweak and adjust lyrics based on how they are produced, and then iterating on the process.

Unbiased and Patient Collaboration

Unlike human collaborators, AI doesn't take offence if I discard its suggestions or change my mind repeatedly. It remains a neutral, patient partner that supports my creative journey without any ego or frustration. This dynamic creates a unique creative environment where I can explore ideas without hesitation, knowing that GPT is always ready to provide fresh perspectives and unwavering support.

Enhancing Human Creativity

This collaborative process with AI doesn't replace my creativity; instead, it enhances it. Left on its own, GPT will not compose anything, in the same way as keyboard won't write code.

As a partner, GPT can offer a vast array of possibilities that might not occur to me initially. It can draw from an extensive collection of training data, including musical patterns, lyrical themes, and emotional expressions, enriching my creative palette. This partnership allows me to break through creative blocks and discover new ways to express my ideas.

For example, if I’m stuck on finding the right words to convey a specific sentiment, GPT can suggest numerous alternatives, each with a slight variation in tone or phrasing. This not only saves time but also opens up new avenues for creativity that I might not have explored on my own.

Continuous Learning and Adaptation

Working with AI also means continuous learning and adaptation. As I interact more with GPT and other AI tools, I become better at articulating my creative needs and understanding how to leverage AI's strengths. This ongoing process helps me to refine my skills, both in using the technology and in my overall approach to music production.

In my experience, AI serves as a tireless, unbiased, and highly adaptable collaborator in my music production process. It allows me to explore and refine ideas rapidly, supports my creative shifts without hesitation, and enhances my ability to express complex emotions and themes in my music. This partnership not only streamlines the creative process but also expands the boundaries of what I can achieve as an artist.

Ownership and Authenticity

One of the thorniest issues in using AI in music (and other creative endeavours) is the question of ownership and authenticity. When an AI tool helps create a song, who really owns it? The legalities of this question are still being debated, but ethically, I would argue that the human creator retains primary ownership, as the original impetus, idea, lyric selection and song direction came from them. Current legal frameworks, like those used by Suno, often stipulate that songs created under their free tier remain the property of Suno, while those produced under a paid plan are fully owned by the user. This approach ensures clarity and respects the artist's contribution.

One aspect in the way Suno has chosen to implement their solution that I really like and support is their restriction regarding naming artists or using any existing lyrics. It will simply fail to produce anything, which I think is great and goes some way to ensuring you need to bring your own creativity to the process. The AI is merely a tool, much like a guitar or a synthesizer; albeit a highly advanced one.

Where visual art is feeling the bite of AI now, music has been using AI-like elements for decades in different forms, such as loops, equalizers and synthesizers. Yes, the addition of producing an entire song around your lyrics and direction in terms of genre, instruments, vocal style, etc, is still a massive leap forward... but it seems that more than most, the music industry seems to have been warmed up to this.

The Debate Over "Cheating"

Is using AI cheating? This debate centres around what we value most in music creation: the process or the outcome. Let's delve deeper into this question by examining the various perspectives and measures involved.

Process vs. Outcome

Value in the Process

For some, the true value of music lies in the intricate and often arduous process of creation, celebration of the 'craft' for lack of a better description. Traditionalists argue that the labour-intensive aspects of writing, composing, and the performing and producing of music are what imbue a piece with its authenticity and soul.

This perspective holds that the struggles, years of practice, depth of experience and emotions, and time invested by the artist are crucial elements that shape the final product. From this viewpoint, using AI could be perceived as undermining the integrity of the creative journey, thus making it a form of "cheating."

Value in the Outcome

Conversely, others argue that the ultimate value of music should be measured by its ability to connect with and move listeners. They assert that if a song can evoke strong emotions, tell a compelling story, or provide enjoyment, then the means of its creation are secondary. From this outcome-focused perspective, AI is seen as just another tool—like a guitar or a synthesizer—that artists can use to enhance their work. Here, the use of AI is not considered cheating but rather an innovative approach to achieving artistic goals.

Measures of "Cheating"

Effort and Skill

One common measure of cheating is the amount of effort and skill required in the creation process. Traditional music production demands a high level of skill in various areas, including instrumental proficiency, vocal ability, mastery of instruments and technical know-how in recording and mixing. AI tools like Suno.com can simplify these tasks, reducing the need for extensive training and effort. Critics may argue that this diminishes the artistry involved, as it allows individuals with minimal musical knowledge to produce complex compositions.

Originality and Creativity

Another measure is the degree of originality and creativity in the work. While AI can generate music based on user inputs, some argue that it might lack the unique touch that a human artist brings. They fear that AI-produced music could lead to homogenization, where songs start to sound similar due to algorithmic patterns.

However, proponents counter that AI can also inspire new creative directions, offering endless variations and ideas that might not occur to a human composer alone. In this sense, AI could be seen as expanding the creative palette rather than limiting it.

Emotional Authenticity

A key aspect of the debate is whether AI-generated music can possess the same emotional depth as human-created music. Detractors argue that AI lacks the human experience and emotional insight necessary to create truly moving art. They suggest that music born from human struggles, joys, and life experiences has a depth that AI cannot replicate.

Supporters, however, highlight that AI can serve as a medium through which human experiences and emotions are expressed, enhancing rather than detracting from the emotional authenticity of the work. The human input—be it lyrics, melodies, or thematic direction—remains central to the creation, with AI facilitating the realization of that vision.

Innovation and Accessibility

AI’s role in democratizing music production is another factor to consider. By lowering the barriers to entry, AI makes it possible for more people to create and share their music. This can be seen as a positive development, fostering diversity and inclusivity in the music industry. Critics might view this accessibility as a dilution of talent, where the market becomes flooded with AI-generated content. However, supporters argue that true talent will always stand out, and AI merely provides more people the opportunity to discover and hone their artistic abilities.

The question of whether using AI in music production constitutes cheating largely depends on what aspects of music creation we value most. If we prioritize the traditional, effortful process, AI might seem like a shortcut. But if we focus on the emotional connection and enjoyment that music provides, AI emerges as a powerful tool that can enhance and democratize the creative process. Ultimately, the use of AI in music is a subjective matter, shaped by individual perspectives on art and creativity.

Real-World Success Stories

Consider the case of Holly Herndon, an innovative artist who utilized AI to create an entire album, using her digital twin named 'Spawn.' Herndon's work is a prime example of how AI can become a co-creator, contributing to music in ways that push the boundaries of traditional composition. Her album, PROTO, showcases the potential of AI as a creative partner, blending human and machine-generated sounds to produce a unique and captivating listening experience. 'Spawn' was trained on a diverse range of vocal performances, including those of a choir, allowing Herndon to manipulate and evolve the AI's output to fit her artistic vision. This collaboration between human and machine opened up new possibilities in sound design and composition, highlighting how AI can enhance, rather than replace, human creativity.

Similarly, my own journey with AI music production has been both exciting and fulfilling. Within six weeks of discovering Suno, I published my first album, The Skin We Wear, on Spotify. While it may not be a hit album, it represents a significant personal achievement. The process of creating this album using AI tools allowed me to experiment with different genres, arrangements, and lyrical themes in a way that would have been time-consuming and costly using traditional methods.

One of the most rewarding aspects of this project was the ability to infuse deeply personal themes into the music. For instance, one track on the album, "My music, My friend", explores the the relationship I have with music as a way to connect with my late mother, her enjoyment of music and the love of music that she passed on to me.

Another song, "Until Then", allows me to share the emotions surrounding the loss of my dogs, a subject with very little in the way of options online for people grieving with the loss of a family pet.

Suno allowed me to take my lyrics and apply them to a variety of different production styles, until I found one that accurately produced what I was looking for.

The rapid iteration and creative feedback provided by Suno allowed me to refine each track meticulously, ensuring that the final product was a true reflection of my artistic vision. This experience has not only broadened my understanding of music production but also reinforced the idea that AI can be a powerful ally in the creative process.

Moreover, sharing my AI-assisted music on platforms like Spotify will hopefully allow me to connect with a wider audience. While The Skin We Wear may not have topped the charts, it stands as an early example of the potential of AI in democratizing music creation and allowing artists to bring their unique visions to life.

These real-world examples, from Holly Herndon’s PROTO to my own The Skin We Wear, illustrate the transformative impact of AI on music production. They highlight how AI can serve as a co-creator, expanding the creative possibilities for artists and making high-quality music production more accessible than ever before.

Cost considerations

Suno offers a free tier which grants a user 50 credits, which they suggests will allow you to create 10 songs - however it may be a little more depending on how quickly you are able to create a combination that works for you. A paid monthly subscription with Suno currently starts at $10/month, which will secure you 2,500 credits.

Whilst Suno says this will allow you to produce 500 songs, I'd challenge that reality is closer to 100 songs - still an amazing number for songs that I'd argue are comparable to studio produced arrangements.

Ethical Considerations and Future Implications

As we embrace AI in music, we must also consider the ethical implications.

AI-generated music raises questions about authenticity and the diminishing role of human effort in artistic creation. How we answer these questions will shape the future of music and potentially other creative fields.

Authenticity in AI-Generated Music

One of the primary concerns is the authenticity of AI-generated music. Critics argue that music produced by algorithms lacks the genuine emotional depth and personal touch that come from human experience. They suggest that the nuances of human creativity and the subtle imperfections in performance are what make music truly special. Ultimately they argue that there cannot be originality, as the output is a result of the training data. According to this view, AI-produced songs might sound perfect but could miss the "soul" that human artists bring to their work.

On the other hand, proponents of AI in music production believe that these tools can enhance human creativity rather than replace it. AI can be used to explore new musical ideas, push creative boundaries, and produce high-quality compositions that might not be possible otherwise - at least not to larger number of people. They argue that the authenticity of music should not solely be measured by the process of its creation but also by the emotional and intellectual responses it elicits in listeners.

Ownership and Intellectual Property

Another significant ethical issue is the question of ownership and intellectual property. When an AI tool helps create a song, who owns the rights to it? The creator of the AI, the user who inputs the initial ideas, or the AI itself? The legal landscape is still catching up with these technological advancements, and different jurisdictions may have varying rules regarding intellectual property rights.

Some believe that the human user should retain ownership, as they provide the initial creative input and direction, and ultimately the final selection of a massive set of potential outputs. Others argue that the companies developing these AI tools deserve a share of the ownership, especially if their algorithms play a significant role in the creation process. And then there is the question of the training data and originators of this content... This debate highlights the need for clear legal frameworks that can address these new challenges in a fair and equitable manner.

Impact on Employment in the Music Industry

The rise of AI in music production also raises concerns about the potential impact on employment in the music industry. With AI tools capable of composing, arranging, and even performing music, there is a fear that human musicians, composers, and producers may find their roles diminished or even obsolete. This could lead to a significant shift in the industry, with fewer opportunities for traditional musicians and more emphasis on technical skills related to AI and music production software.

However, others see AI as an opportunity rather than a threat. They argue that AI can handle repetitive and time-consuming tasks, allowing human musicians to focus on more creative aspects of their work. Additionally, AI can democratize music production, making it accessible to a broader range of people who may not have the resources or training to create music through traditional means.

An uncomfortable question is whether we should (or can) try put the genie back in the bottle if it really does reduce jobs for an equivalent or better outcome... such was the challenge for the much lamented Luddites.

One line of thinking even suggests that large platforms that deliver music to many end users, such as Spotify, YouTube and TikTok, might just dynamically create music based on their massive data sets and customer knowledge, to secure higher shares of revenue. I don't think this likely, but it is definitely a possibility.

The Future of Creative Collaboration

AI's role in music production also prompts questions about the future of creative collaboration. Will AI become a co-creator with human artists, offering suggestions and generating ideas that humans might not have considered? Or will it overshadow human creativity, leading to a homogenization of musical styles and a loss of diversity in artistic expression?

Some might envision a future where AI and human musicians work together seamlessly, with AI providing a wellspring of inspiration and technical support. This collaboration could lead to innovative new genres and styles, enriching the musical landscape. Others worry that reliance on AI could stifle originality, with artists becoming overly dependent on algorithmic suggestions and losing their unique voices.

Evolving considerations

The ethical considerations and future implications of AI in music production are complex and multifaceted. As we navigate this evolving landscape, it's essential to engage in ongoing discussions and debates about these issues. The answers we develop will not only shape the future of music but also influence other creative fields as AI technology continues to advance. While there are valid views on both sides of the debate, embracing the potential of AI while addressing its challenges can lead to a more innovative and inclusive creative environment.

Conclusion

As we navigate this new landscape, it’s crucial to keep an open mind about what AI tools mean for creative fields. AI is not here to replace human creativity but to augment it, pushing the boundaries of what’s possible and making music creation more accessible. Embracing these tools can lead to more innovative and expressive art forms that were previously unimaginable.

Thank you for reading. I look forward to exploring this brave new world of AI-enhanced creativity with you. Let’s start the conversation—share your thoughts in the comments below or on social media. What’s your take on AI in music production? How do you see it shaping the future of the music industry?