Artificial Intelligence in the Music Industry

←Back • ↑Topics • ↑Categories

Artificial Intelligence in the Music Industry is a relatively new phenomenon that has already hugely impacted the way we produce, consume, and experience music. Artificial intelligence (AI) itself is essentially a system created to learn and respond in a way that is similar to human beings. To some degree, AI technologies can simulate human intelligence and many different companies have developed applications that can create, perform, and/or curate music through the power of AI . This industry is relatively new, but growing rapidly. Although it's creating great advancements, it might cause future problems for artists having to compete against machines for recognition and potential legal discrepancies regarding copyright infringement.

The Illinois Automatic Computer (ILLIAC)

History

A Look Into AI

Before diving into the musical aspect, we look at the history of AI production to better understand the ethics behind AI in music. The concept of AI was first accumulated in scientists, mathematicians, and philosophers' minds in the 1950's. In 1950, a young man named Alan Turing wrote a paper on how to build 'intelligent machines' and test their intelligence. There were a lot of times of flourishing for AI as well as setbacks when many people became less interested in AI and in doing research for it. Of course, new films and books that were popularized and contained futuristic AI made the majority of people interested in it again. Despite the setbacks, there were many breakthroughs in IA and programmers continued to test out different ideas. A great timestamp was when in 1997, IBM's Deep Blue Computer beat the then-current world chess champion, Garry Kasparov. AI has continued to develop itself and we see it often in our day-to-day lives, like when we talk to machines on our phones. A current project being evolved is facial emotion recognition and detection, which has been adapted by the MyHeritage App using Deep Nostalgia.

AI In Music

The first recorded instance of computer-generated music was in 1951 by a British mathematician, Alan Turing. Turing built the BBC outside-broadcast unit at the Computing Machine Library in Manchester, England, and used it to generate a variety of different melodies. To do so, he programmed individual musical notes into the computer. Artificial intelligence was first used to create music in 1957 by Lejaren Hiller and Leonard Isaacson from the University of Illinois at Urbana–Champaign . They programmed the ILLIAC (Illinois Automatic Computer) to generate music completely written by artificial intelligence. Around this same time, Russian researcher R.Kh.Zaripov published the first paper on algorithmic music composing that was available worldwide. He used the historical Russian computer, URAL-1, to do so .

From then on, research and software around AI generate music began to flourish. In 1974, the first International Computer Music Conference (ICMC) was hosted at Michigan State University in East Lansing, Michigan. This became an annual event hosted by the International Computer Music Association (ICMA) for AI composers and researchers alike .

Applications

Music Production

One of the biggest breakthroughs in computer-generated music was the Experiments in Musical Intelligence (EMI) system. Developed by David Cope, an American composer and scientist at the University of California, Santa Cruz, EMI was able to analyze different types of music and create unique compositions by genre. It has now created more than a thousand different musical works based on over 30 different composers .

In 2016 Google, one of the leaders in AI technology released Magenta. Magenta is “an open-source research project exploring the role of machine learning as a tool in the creative process” . Instead of learning from hard-coded rules, Magenta learns by example from other humans. It can be thought of as an assistant to humans in the creative process, rather than a replacement.

Recommendation Models

Another way AI is used in the music industry is by creating recommendation models. One of the most prominent users of this tool today is Spotify. Spotify uses a variety of machine learning techniques to predict and customize playlists for its users. One example of this is the Discovery Weekly playlist which is a list of 30 songs curated specifically for the user each week based on search history, listening patterns, and predictive models. One way they do this is through collaborative filtering. To do this, Spotify compares different users with similar behaviors to predict what a user might enjoy or want to listen to next. Another tool is natural language processing (NPL). NPL analyses human speech patterns through text. AI accumulates words that are associated with different artists by scanning the internet for articles and posts written about them. They can then associate artists who have similar cultural vectors, or top terms which each other and recommend similar artists to their users. One final tool Spotify uses to curate user-specific playlists is audio models. Audio models are most useful when an artist is new and doesn’t have much online about them yet or many listeners. Audio models analyze raw audio tracks and categorize them with similar songs. This way, they are able to recommend lesser-known artists alongside popular tracks .

Ethical Implications

Commodification of Music

Some ethical concerns about the future of music and AI have arisen over recent years. One of which is the commodification of music. With the popularization of AI-generated music on the horizon, there is the concern of music being made and sold solely for the purpose of profit. Music has always been a very human type of art that pulls from emotion and experience that you would assume no machine could recreate. However, that might not be required to make a chart-topping song these days. AI technology could easily come up with something modern and catchy with the power to analyze and remix music that is already popular. This also poses the threat of music becoming homogenous, lacking variety. Hopefully, people will continue to prefer something human-made, but as algorithms continue to advance and more data on our musical preferences are collected, it’s impossible to say what the future holds .

Computers generating new music through AI

Musicians

Although AI in music is an exciting development, with any AI product there is a risk for an increase in jobless people. Many musicians are passionate about their music and have devoted their lives to making it their full-time career. But what happens when AI starts to make music? There is a risk of AI's becoming more popular than human-made music because an AI will be programmed to learn what music the majority prefers. This may cause many musicians to lose their job or be forced to have music more as a hobby than a career. Although this can scare people to hear, AI could take away but also produce many more job opportunities. However, the process of losing and gaining jobs might not be as smooth of a process as we would hope.

Copyright

One of the biggest ethical dilemmas that AI-generated music is facing is copyright infringement. Allowing the AI to essentially listen to copyrighted music and then generate similar songs without compensating or even acknowledging the original artist themselves could result in legal complications. As laws currently stand now, copyright infringement can only occur if AI creates a song that sounds similar to an existing song and claims it as its own. This is a hard line to draw because it may depend on how similar the songs are to make this call. This law was written without AI systems in mind so it’s likely that they never considered a machine listening to and pulling from an artist's entire discography to create one song. From an artist's point of view, it may seem unfair to not be credited or compensated for something like this .

Conclusion

Even though artificial intelligence in music has been around for over 60 years now, it's still considered to be in its very early stages of development. No one knows for sure what the future holds for the music industry as we currently know it. Maybe in 20 years, the chart-topping songs will have been computer-generated or our favorite music streaming services will know exactly what we want to listen to based on our mood. We will just have to wait and see.

See Also

• Spotify
• Artificial Intelligence and Technology