When new tech meets music, panic often follows
New technologies have repeatedly reshaped the music industry—from cassette tapes and file sharing to streaming and social media. Each innovation has also sparked warnings that music itself could be in danger. In his ninth book, Music Technology Panic Narratives Beyond Piracy: From Taping to Napster to TikTok, University of Texas at Arlington sociology Professor David Arditi explores how the recording industry has historically responded to technological change.
The book examines how labels and industry groups have framed emerging technologies as threats to recorded music and how those narratives influence policy, public opinion and the evolution of the industry. It also looks ahead to one of today’s most closely watched developments: AI and its potential role in the future of music.
Your new book examines what you call “music technology panic narratives.” What are these narratives, and why did you want to study them?
Arditi: In my initial research, I looked at file-sharing. To create the political will for the state to regulate cultural production, the Recording Industry Association of America (RIAA) created what I call a “piracy panic narrative” in which the recording industry claims to be experiencing financial turmoil. With the narrative, they tried to implicate fans for hurting their favorite musicians. This narrative’s structure follows this pattern: file-sharing is piracy, piracy is stealing, and stealing hurts artists and their labels. Therefore, major record labels argue that music fans who file-share are not listening to free music, but rather, they are stealing income from their favorite artists. This has been predominantly about “piracy,” but different powerful entities have stated the narrative in different ways. As a result, I call this rhetoric “music technology panic narratives.” For instance, in my research I found John Phillip Sousa, the famous march composer, wrote several essays claiming recording technology would kill music. I think most of us would look at that in hindsight and understand how hyperbolic these claims were.
You trace these narratives across several decades of technology—from cassettes to Napster to TikTok now. What similarities did you see in the way the industry responded to each new innovation?
Arditi: At each moment, major record labels tried to discourage music listeners from participating in emerging cultural practices. However, my research shows this is really about limiting competition by limiting access to independent music. With cassette tapes, a common practice among hip-hop and punk fans was to trade tapes of their favorite artists. This activity not only operated outside of economic exchange, but also meant these music listeners were not buying music by major label artists. The key point is we have a limited amount of time to listen to music, and major labels don’t want to compete with free options. Similar processes take place with TikTok because people can stream music by anyone without ever paying for music.
In many cases, technologies that were initially criticized later became central to the industry’s business model. What does that pattern reveal about how the music industry adapts to change?
Arditi: The fact that the industry always comes back around to the technology is the tell, so to speak. Major labels aren’t opposed to the technology; they are opposed to the way people use them. What I found in my research is that when industry entities speak to each other in trade publications, they are far more candid about their goals. For instance, in the early 2000s, while labels were decrying file-sharing as the source of record sales declines, they were candidly discussing how their new competition was with video games for entertainment consumption. Again, they use the narrative not necessarily to stop the technology, but to gain more profit and stop competitors.
Artificial intelligence is the latest technology raising questions about the future of music. How does the emergence of AI compare with earlier technological shifts the industry has faced?
Arditi: As opposed to other technologies I discuss, AI isn’t about distribution, but rather addresses production. In this way, I think AI music follows the same patterns as recording technologies. The rhetoric sounds almost identical to John Phillip Sousa’s fears at the turn of the 20th century. We see the rhetoric again about sampling music and digital production. However, in both cases, powerful interests used piracy as the boogeyman. Labels argued sampling and digital production technologies violated copyright, but they ultimately changed to digital production as a way to undercut costly musician labor. To fight AI initially, the industry leaned on the idea that feeding AI music to train it is a violation of copyrights through the unlicensed reproduction of music. I think they’re wrong about copyright law, but I supported their actions to try to limit AI music. But as I predicted, as soon as they found a way to use copyright to leverage policy changes, labels began to make deals with AI companies. Warner Music agreed to drop a lawsuit against Suno and allow them to license their artists’ music. Now Warner will earn revenue from the licensing at the same time as they undercut the labor of musicians.
As labels, artists and technology companies begin to experiment with AI tools, what developments will be most important to watch in the years ahead?
Arditi: For me, the big question is: Will people want to listen to AI music? Part of the answer is yes. AI music is simply music created by algorithms. Pop music is generally created by algorithms already, just not machine-generated algorithms. Producers know what hits, so they make music similar to other hits. They shy away from anything too different. It’s formulaic. We’re going to see something similar with AI music. Some people will listen to it without thinking, others will reject it altogether. However, the interesting music will always happen without AI. People will be necessary to innovate music, which will ultimately be co-opted by producers using AI. It is a cycle like any other cycle.
About The University of Texas at Arlington (UTA)
The University of Texas at Arlington is a growing public research university in the heart of Dallas-Fort Worth. With a student body of over 42,700, UTA is the second-largest institution in the University of Texas System, offering more than 180 undergraduate and graduate degree programs. Recognized as a Carnegie R-1 university, UTA stands among the nation’s top 5% of institutions for research activity. UTA and its 280,000 alumni generate an annual economic impact of $28.8 billion for the state. The University has received the Innovation and Economic Prosperity designation from the Association of Public and Land Grant Universities and has earned recognition for its focus on student access and success, considered key drivers to economic growth and social progress for North Texas and beyond.