Artificial Intelligence (AI) has emerged as a transformative force in many areas of business including the music industry and there is currently much discussion and interest in music related AI software.
It seems that there are two fundamental areas to look at for music.
- Composition and the actual creative process
- Production β the recording and mastering of the song or composition.
Can a machine write a song?
The question of whether an AI-written song can be considered truly original is a topic of debate and interpretation. While AI algorithms can generate compositions based on existing musical data, the concept of originality often needs emotion and creativity, unique to human composers.
AI algorithms analyse vast amounts of existing music to identify patterns, structures, and styles, which they then use to generate new compositions.
The resulting songs may mimic certain genres or artists’ styles, leading some to argue that they lack the originality and authenticity associated with human creativity. So is it really just a clever βmash-upβ, or automated DJ?
However, AI-generated music can produce surprising and innovative compositions that transcend existing styles. The algorithms can combine various musical elements in unexpected ways or experiment with novel melodies, harmonies, and rhythms.
In such cases, the AI-generated songs can exhibit a level of originality in their composition, even if they draw inspiration from existing musical patterns. After all β isnβt that what human composers do? It is a brave person that says their compositions are 100% original and not influenced by other music.
Is AI a Threat to Originality?
Critics of AI suggest that algorithms analysing vast amounts of existing music can lead to the replication of established styles and structures, potentially stifling innovation and reducing the perceived originality of compositions.
A counterpoint being that this is often what popular production houses do once they get a βhit formulaβ. For example, look at Stock, Aitken, and Waterman in the 1980s. Their clear production style was applied fairly formulaically across their stable of artists.
On the other hand, proponents of AI argue that it can be a powerful tool for fostering creativity and expanding the possibilities of music. AI algorithms can analyse and combine musical elements in novel ways, generating compositions that may not have been conceived by human composers. By offering fresh perspectives and breaking conventional patterns, AI can inspire artists, stimulate their creativity, and act as a collaborative partner in the music-making process.
Production
Similar arguments apply to the AI tools available for the production and mastering of recorded music. AI based βautomaticβ mastering tools are very quick, effective and a godsend for getting quality output. This is especially true for those on a low budget or home recording.
I feel that AI in this part of the process is slightly less contentious, unless mastering techniques are considered particularly relevant to the creative process. After all, we have for years enhanced sound with technology. Right from the 1950s and 60s, guitars were used with effects pedals which significantly enhance tone.
Consumption
AI is transforming the way music is consumed and personalised. For example, Spotify is excellent at analysing listeners’ preferences, behaviours, and contextual data to provide personalised music recommendations.
Conclusion
AI is ultimately a tool that is guided by human input and intentions.
Musicians and producers have the agency to use AI as a creative tool, harnessing its capabilities to enhance their artistic vision rather than replacing their creativity. Like all things, it can be a force for good, or a threat.