Could musicians eventually be replaced by machines? New technology makes it possible, although the idea hasn’t caught on yet. Humans still seem to enjoy the music created directly by humans and not so much by machine learning platforms. Artificial intelligence (AI), though, has many uses that industries connected with music benefit from.
Rise of Computer Compositions
Just as Bob Dylan shocked folk music fans when he shifted to electric guitar at Newport Folk Festival in 1965, purists who support acoustic musicianship without electronics may not be on board with computer-generated musical compositions. Yes, AI software can now compose songs through an analysis of music theory and history. Since the 80s technology has existed for computers to compose songs with the help of a randomness generator, developed by classical musician David Cope.
But using digital tools doesn’t have to mean machines are taking over, as they can speed up the recording process and provide a wider range of sonic choices. Deep machine learning software can be used to track the history of popular songs so that new songs can be tested against the database for possible copyright infringement issues.
Tools for Enhancing Musical Performance
Musicians may find AI technology most useful for recording projects. An AI application such as Spawn provides machine learning to analyze songs and make analytical suggestions for refining and performing them.
Virtual assistants based on machine learning can now handle the redundant and mind-numbing tasks that traditionally have slowed down production or contributed to a loss of focus. It’s easy to give up on a project when you get too bogged down with busywork that doesn’t directly affect the sound of the finished product. Even on the road, AI has been embraced by touring musicians as a promotional tool for scheduling distribution of messages to fans.
Furthermore, AI raises the quality of mastering, the final stage of the recording process.
Collecting Streaming Data
Music industry research leader Billboard shifted its chart methodology in 2017 to increase emphasis on the growing streaming trend. The shift to this new direction involved creating complex algorithms that weigh different types of digital music activity. The publication’s charts now assign certain values to music based on how it’s consumed, such as through a paid subscription or ad-supported model.
Big music aggregators beyond Spotify and Apple Music such as Amazon Music Unlimited, Google Play, YouTube and Pandora now contribute to the national music charts. Higher volumes of data are used to process the charts. With 20,000 new tracks uploaded daily to Spotify, AI is essential to sort through this big data.