The Past is Prologue—How Prior Challenges with New Technology May Guide the Music Industry in Dealing with AI

In a peer-to-peer file-sharing case1 involving tens of millions of users sharing millions of sound recordings, Judge Sidney R. Thomas of the Ninth Circuit Court of Appeals wrote: The introduction of new technology is always disruptive to old markets, and particularly to those copyright owners whose works are sold through well-established distribution mechanisms. Yet, history has shown that time and market forces often provide equilibrium in balancing interests, whether the new technology be a player piano, a copier, a tape recorder, a video recorder, a personal computer, a karaoke machine, or an MP3 player. For the music industry, artificial intelligence (“AI”) is a technology full of virtue and promise that has already proven valuable in numerous ways. In the creation of music by human artists, AI has been useful in assisting in the production of songs and sounds, as well as in the automation of related tedious technical tasks, thereby freeing creators to focus more deeply on their artistry. With respect to consumers, AI has been useful in helping to organize, categorize, and index their music, as well as in supporting their discovery of music through song curation, playlist creation, and recommendation. At the same time, AI also poses a number of disruptive threats. By training on unauthorized uses of copyrighted works, AI can create music that has the potential to oversaturate the market, thereby undermining the artistic integrity of music created by human beings and threatening the economic welfare of creators. How might these various threats be minimized so that AI neither inflicts serious harm to the careers of artists and songwriters nor cripples an industry that is based on and supports human creativity? History may offer a guide. In this Article, I will: set out the issues surrounding four moments in music industry history in which a new technology (often, a new format) posed challenges to copyright law and/or business norms of the time; describe how those challenges were overcome and their disruptive effects muted; and highlight how the lessons of these past challenges may be useful as the industry confronts the challenges posed by AI.