Can We Teach a Machine to Sing?

This article was originally posted March 7, 2017 on my DataExhaust blog.

The Artificial Musician

Recently in the past few weeks, a new artificial intelligence startup, Amper Music, has begun opening up a private beta of its AI-based music composition platform. This system claims to be capable of generating the musician-quality original music, but packaged up and delivered as a service. If their claims are true, this service could fundamentally change the way music is created and delivered for a whole variety of background tasks from restaurant ambient noise to the quintessential elevator music. In a world where the rising cost of music licensing is eating into the gross margins of music streaming services, the premise of an always-available, never hung-over, and infinitely scalable band seems like a godsend to those in the music industry who are trying to help navigate it through its digital transformation safely. However, as stewards of the human condition, we have to ask ourselves: is this a positive or negative net benefit for mankind?

There are, of course, several substantial benefits that an Artificial Musician could bring to the world that just are not possible with just their human counterparts. For example when trying to generate background music for say a powerpoint presentation, an algorithm can identify and understand nuances of the digital context of the presentation – such as the known preferences of the registered presentation attendees pulled from their Spotify profiles – that could be used to tailor the final musical result to not just the tone of the content but also how it might best be perceived. While a human musician could possibly work to understand the tone of the presentation and work with the author to create a compelling work of art, it is simply not possible to take into consideration (simultaneously) the wants and needs of an entire audience full of  stakeholders while also creating a composition on time and on budget.

Muse vs Machine

Interestingly, Amper is not the only company leveraging artificial intelligence to disrupt the music industry. LANDR is a new music technology platform that provides an AI-assisted studio authoring environment at a fraction of the price of professional-grade services. The core premise with their model is that much of the expertise that studio techs bring to music production process is routine and automatable through machine learning. Their platform claims to provide a cheaper, scalable studio process by removing the expensive, manual labor from going from raw creativity to a studio-mastered track. In theory, leveraging LANDR’s platform would not only widen the margin creative artists could make from the sale of their music, but it also could open up a much wider array of independent or part-time musicians to the world of professional music – in a way, increasing the overall creative mix of content in the world by removing the middle-men between creativity and profit.

When contrasting LANDR and Amper’s different approaches to augmenting music production, one must ask where does the human play a critical role in this unique aspect of our culture? A production-assistance platform such as LANDR takes an implicit stance that the spark of creative value resides in the mind of the musician and we simply need to reduce the friction in getting it to market. However, Amper’s product would suggest a view that musical genius – at least for certain use cases – follows a formulaic, automatable process and a machine can be trained to share the same qualities as any other muse out there. For the record, Amper’s leadership does not wish to replace composers, but rather they feel there are two distinct use cases for musical composition – either creative or functional value – and AI can absolutely be used to replace one of them.

How Will Consumers Respond?

Fortunately for mankind, these enterprises do not control one critical factor: consumer opinion and preferences. A big question looming over AI designers in the music field is just how good are the tunes that these systems can create? Will an AI be capable of weaving together a beautiful melodic story as full of depth and intrigue as any piece Mozart or Bach could whip up?

Probably not.

However, as Amper pointed out, there are plenty of use cases where music does not have to be the absolute best creatively – think studying music for example. In these cases, the limiting factor to growth and adoption is cost and scale – two elements that automated music has an undoubted competitive advantage in.

This, of course, should be taken in light of just how much of the music industry’s business model has been shifting over the past 20 years. Ever since early peer-to-peer file sharing services like Napster or LimeWire entered the scene in the late 90s, the music industry as a whole has been forced to shift focus from creating profit in the creation and distribution of digital media to how the artists are experienced. With album sales declining and music streaming services enabling consumers to “purchase” music with their ears, record labels and artists are being forced invest heavily in creating unique, engaging performances that cannot be digitally consumed. This combined with the fact that millenial shoping habits are shifting towards the consumption of experiences over hard goods en masse is providing a much needed increase in demand for these types of physical performances – enabling a shift in profit from music sales to music experiences.

The real question, of course, is what value do music customers (ordinary humans like you and myself) place on the act of creativity that goes into making a hit song? Will a machine ever be capable of drawing the same types of crowds as Taylor Swift or The Weeknd? The companies innovating in this space will ultimately be beholden to their customers, who will decide with their wallets over time. If there truly is enough space for two kinds of musical consumption, then perhaps true human creativity will prevail.

Creativity and the Human Condition

While music is an art form that touches us perhaps more emotionally and more frequently than many others within the liberal arts, there are many more fundamentally pivotal human activities that make up today’s knowledge economy. Writers, sports commentators, comedians, and actors – to name a few – all derive their value from harnessing their creativity. These kinds of professions do not have formal degrees in in universities because they have always been thought to be derived from elements of human nature that cannot be taught but rather embraced. As AI continues to permeate every part of our lives, society will need to make a stand on how we value the creative arts. Is it more important to lower the barrier for humans to drive acts of creativity or do we believe that it is inherently a process that can be modeled and encapsulated in software?

Time will tell.