top of page
  • Writer's pictureAntonia Curry

The Data Age Has Transformed Music with Aram Sinnreich & Jesse Gilbert

Updated: May 13

The age of Mass Data is here. From music discovery based on algorithms, to small artists using fan location data to plan tours, to AI-generated music, data is changing just about every aspect of the music industry. In this episode, Tristra talks to Aram Sinnreich and Jesse Gilbert, authors of The Secret Life of Data. Jesse and Aram show us that today’s music and culture is increasingly set by data. We discuss the scary implications of this, how AI-models learning from musicians brings a host of worries around copyright and exploitation. But we also discuss the exciting possibilities of this new age, including an explosion in collaboration in music making. 

Some things mentioned in the show today:

Aram and Jesse's book, The Secret Life of Data

Listen wherever you pod your casts:

Looking for Rock Paper Scanner, the newsletter of music tech news curated by the Rock Paper Scissors PR team? Subscribe here to get it in your inbox every Friday!

Join the Music Tectonics team and top music innovators by the beach for the best music tech event of the year:

6th Annual Music Tectonics Conference October 22-24, 2024 Santa Monica, California

Episode Transcript

Machine transcribed

You're listening to Music Tectonics. 

00:10 - Tristra Newyear Yeager (Host)

Hi everyone and welcome back to Music Tectonics, the podcast that goes beneath the surface of music and tech. I'm your host for this episode, Trista Newyear-Yeager, chief Strategy Officer at Rock Paper Scissors, the music innovation PR firm. Well, you know, in the music business, everybody loves to talk about data metadata, but what are we actually talking about? Well, today's guests can help us explore this. We have Aram Sinnreich and Jesse Gilbert with us today. They are both scholars, creatives and authors who have worked together on a new book with the intriguing title of the Secret Life of Data. Jesse is a transdisciplinary artist working across sound, image and code, who has shown his work at museums, festivals and happenings around the world and developed his own software to generate images based on audio data. Sinnreich, who's been on the podcast before, is the chair of the communications department at American University and an author of several books about the music industry, media and digital culture, and he's also a working musician in his spare time. I'm really excited to have you on the podcast today. Thanks for joining me, guys. 

01:16 - Jesse Gilbert (Guest)

Oh thank you. 

01:19 - Tristra Newyear Yeager (Host)

So let's talk first about what the heck is, or are, data. So data gets talked about a lot. Why are you so concerned or focused on data and what do you think? Why do you think it should be meaningful to people in the music field? Why do people in the music field need to be thinking about data? 

01:47 - Aram Sinnreich (Guest)

transition right now where, for reasons capital R reasons, pretty much everything that we do and say is being converted in real time into data and stored on massive cloud-based servers where they can be retrieved by various parties in the government, in the corporate sector and elsewhere who want to derive intelligence from it. And we haven't really yet begun to reckon with that collectively as a society, to figure out how that changes our cultures, our interpersonal relationships, our sense of identity, our democracy and, as you asked us in the beginning, our musics. And we've really begun to internalize the logic of these data systems in a way that changes the way that we make music, changes the way that we listen to music and changes the way that the music industry operates. So there are a lot of different rabbit holes we could go down, but they all center around this fundamental transformation in how society is now organized. 

02:43 - Tristra Newyear Yeager (Host)

So what are the important types of data when it comes to music? Jesse, do you want to fill us in on what are the different data categories, so to speak? 

02:51 - Jesse Gilbert (Guest)

Well, I mean, it's interesting because digital music is itself, right, a data type that has its own expression and formats. That is important when you think about the production process, post-production process and also the distribution process of music. I think that there are aspects of this that, as you mentioned, the metadata aspects, the attribution aspects, the ways that metadata are used to aggregate and combine intelligence about how music is consumed. Of course, we're operating in a streaming environment now, right? So the answer to this question has changed as the industry has changed. 


We have aggregation across global platforms and we have also less and less access to data about our audiences, right? So where is the music consumed? How is it being used? We don't really know much, and I don't think the streaming services provide all that much detail to musicians about the answers to those questions. Looking at the higher level data that's extracted from music in terms of understanding its form, structure sort of like the categorization of the music, segmentation in the ai parlance right to, to look at the different parts, to be able to disassemble music after the fact, to not, you know, look at it as a finished product, the demixing algorithms. 


Correct All of the configurable culture predecessors that Aaron was talking about 15 years ago and we're really seeing that playing out now with the kind of memification of culture, the use of music in all different new formats and licensing options that musicians have or maybe don't realize they're signing away when they post their music on various services. 

04:46 - Aram Sinnreich (Guest)

And there's also the crazy feedback loop between these data-oriented services whether we're talking about TikTok or Spotify or what have you and musicians themselves. So the vast majority of streams on Spotify are not on-demand streams, they're playlist-based streams and more and more and more musicians are being trained and record labels and publishers are reorganizing their businesses to adapt to the algorithm to maximize their chances of inclusion on all of these playlists and that has a feedback effect that changes what music sounds like and feels like. That's every bit as powerful as like the advent of the digital recording studio or multi-track tape were in their day. 

05:27 - Tristra Newyear Yeager (Host)

Yeah, that's a really interesting point. I'm curious, though you just mentioned it's really hard, Jesse, to find out exactly what usage is, even though we have this incredible amount of data that's constantly flowing into all these different systems. But so how could we potentially understand what people do with music? Where are you guys seeing most of the data coming from, and how could we potentially understand this? So I'm thinking about things like sales usage, data on streaming, social media, all those things. How do we start putting the puzzle together if we want to really understand what people are listening to? 

06:03 - Jesse Gilbert (Guest)

I mean it's a good question if we want to really understand what people are listening to. I mean it's a good question. I think that this goes to the fundamental business model that the level of development and evolution of these industries that we're at right now. 


And we talk about this quite a bit in the book where you're really dealing with, effectively a Trojan horse type situation where you have a service that's provided let's say, a distribution service or a social media service and you're getting quote unquote free access to that, but that there's an implicit signing away of your right to know these things when you engage with that. And increasingly, this is existential right For artists. You have to engage with these platforms in order to be seen, to be heard and and I think that what we really have to focus on, I believe, is more of a sort of collective input into the, the policies around what, what is equitable with regard to the, the data sharing and the use of the data that these companies derive right. We know, for example, that a service like Facebook, the product is us. The effect of social media sharing and interconnection, which they market as the primary use case, why you should be doing this is to become closer to your family and friends is not their primary business model, and we're living in the consequences of that right. We're living in the consequences of how that has been operationalized and aggregated for advertising. 


Now, I'm not probably answering your question, because by now many of us know this, but I do think that, effectively, you know, part of the reason we wrote the book was to try to engage everyday people in this conversation, to apply collective pressure so that we can actually have a realistic conversation. There's a cellist who who posted this long time ago. I can't remember her last name. 

08:00 - Aram Sinnreich (Guest)

Zoe Keating. 

08:01 - Jesse Gilbert (Guest)

Yeah, who advocated. You know, don't, don't pay me for my streams, tell me where my fans are. Right, the industry has not responded to that. They have essentially said we're comfortable with how things are and you know that's one artist, one voice. It was provocative, but it didn't spur a kind of more collective response, and I do think that that's what's needed now. 

08:23 - Aram Sinnreich (Guest)

And another red flag that we raise in the book is that you know there's no limit to the types of data that can be produced from music or from other kinds of engagement, and so you know, just today, for instance, I'm sure people won't be listening to this for another month or two when the book comes out, but just today it was announced that WordPresscom and Tumblr are changing their terms of service so that everything that users have posted on those sites for the last couple of decades will now be sold to train AI machine learning sets, and that was not an option for Spotify five years ago, but it very much is today, and so we're looking at the prospect where it's not just the kind of data that you and Jesse were talking about, about where are my fans, how many streams am I getting, how's the revenue split up, which is all super important but now there's this new variety of data, which is what are the aesthetic features of your music and how can they be recombined by algorithms to create artificial music that are now productizable and are as fast as you can say Spotify. 


All the digital music service providers are going to pivot and view that as one of their growth areas in the years to come is mining and extracting all of the creative labor that we've done and there's no, there's neither a legal nor a market-based pressure point that we can use at this point to get them to cut us into it or let us opt out of it. 

09:52 - Tristra Newyear Yeager (Host)

Yeah, I've seen I've seen some interesting opinions lately that IP lawyers are basically going to be the ones who decide exactly how at least certain aspects of generative AI shake out, because they're they're the ones that sort of at the front lines. But we don't know exactly how this battle can even be fought, or if it's even completely a battle per se. 

10:14 - Aram Sinnreich (Guest)

Well, there's no good guys, and also, for what it's worth, ip lawyers have been destroying the music industry for the last 40 years. 

10:22 - Tristra Newyear Yeager (Host)

Well, yeah, so maybe they're the heroes we deserve. I don't know and apologies to all our listeners out there who may consider themselves IP lawyers you are the good one. 

10:36 - Aram Sinnreich (Guest)

Right, exactly, you're the exception. 

10:39 - Tristra Newyear Yeager (Host)

You're the exception. All right, we're going to take a quick break and we're going to come back and talk about some of the more interesting developments when it comes to how data changes culture. 

10:50 - Shayli M. Ankenbruck (Host)

Don't miss the first ticket drop for the Music Tectonics Conference. A limited number of super early bird tickets are on sale now, but they won't last long. We're organizing three amazing days in Santa Monica, california, october 22nd to 24th. Your ticket gets you into a keynote with Mark Mulligan of Media Research, high energy panels with music innovators, thinkers and builders, the Swimming with Narwhal's startup pitch, competition, networking by the beach and more creative surprises to come. This is the best price for the best music tech event of the year. So get your ticket before super early bird sells out. 

11:40 - Tristra Newyear Yeager (Host)

Head over to musictectonicscom slash conference to get yours now. Hey, we're back with Aram and Jesse talking about the secret life of music data and the crazy world that we have just woken up in that involves stuff like AI and data mining for generative purposes. However, I wanted to go back to something you were talking about before the break, aram. We were talking a little bit about some of the most significant insights that you've gleaned from how data influences cultural decisions, and I'm wondering how, like if you could point to some specific examples you thought were particularly intriguing or harbingers of what's to come when it comes to people changing the way they make music. I mean, it could be everything. I know there's been a lot of talk in the industry about songs getting shorter, about certain reducing complexity in pop music, of certain melodic features. What other things have you seen happening as people adapt to this data ecosystem that artists live in? 

12:35 - Aram Sinnreich (Guest)

That's a great question, and let me preface this by saying there's nothing new about this. Right as long as there's been a music industry, music has been shaped by industry. Mozart wouldn't have written the way that he wrote if it hadn't been for what his sponsors and audiences wanted at the time and what was allowed by the technology at the time, and it's true in every time and place. We just happen to live in this hyper data saturated environment. A great example is Beyonce's pivot to country music. 

13:04 - Tristra Newyear Yeager (Host)

That's a good one. 

13:05 - Aram Sinnreich (Guest)

Well, if you look at the data, country has been growing really rapidly as a format and genre category in recent years. Data also shows country music is strongly aligned with racialized politics in America right now, and so I think there was a calculation made in Team Beyonce that pivoting to country at this point in time would serve the dual purpose of re-amplifying Black voices as crucial elements of the American cultural tapestry and cash in on a growing trend where a lot of other styles, including R&B and hip-hop, are stagnated. 

13:44 - Tristra Newyear Yeager (Host)

It's kind of amazing when you can both criticize society and benefit. 

13:49 - Aram Sinnreich (Guest)

That's the Beyonce special right there. 

13:51 - Tristra Newyear Yeager (Host)

That's true, that's true, she is. That is one of her superpowers. That's pretty, that's pretty cool. So, Jesse, how do you think the data impacts how people make music? Perhaps who approach it less from a commercial standpoint and more from an experimental or or artistic standpoint? Do you see data influencing creative practitioners in the more experimental reaches of the music world? 

14:12 - Jesse Gilbert (Guest)

Yeah, I mean I think certainly algorithm awareness. It flows to all elements or all aspects of the creative community, right? So thinking about how to present your work typically right now you know they're. This has kind of been amplified since the 80s when you know music videos start coming through that visual elements have to be part of that. 


We haven't talked at all about kind of the collaborative opportunities that technology is enabling right now, which I think might be more in the positive light, you know, thinking about international collaborations, looking at how musicians are finding each other, finding education about music, finding new instruments, new sounds that they haven't, you know, been able to locate otherwise, and I think that artists are definitely leading the way. I mean, obviously, my social media is overrepresented by artists, probably. I think that there's much more understanding of process in music making right now than there ever has been. I think that there's really an emphasis on the development of songs, the development of narrative arcs, the development of technique, the development of studio technology. It's really become much more of a window into a process and I think that's incredibly valuable. 


I don't think that's going to solve all the bigger issues that we're talking about in the music industry, but I do think, from a cultural standpoint, we're at a very good place with respect to the ability to actually collaborate in meaningful ways. When we were starting to try to do internet collaborative work in the early, when we were starting to try to do internet collaborative work in the early days, we were dealing with a very different level of tech than we are right now and we are sort of a global datafied society. I don't know that that means we've solved the distribution questions or the equity questions within the music industry. But I think, in terms of the process, I think we're at a very interesting time. 

16:06 - Aram Sinnreich (Guest)

That's all true, and I think again, there's kind of a virtuous circle where process becomes data, which becomes productizable. So you have like podcasts, like Song Exploder, or like a gazillion different videos on TikTok and YouTube and Instagram that kind of show how the sausage is made, and they themselves can be just as profitable and generate just as much brand affinity and attentional economy as the song, as the finished product itself. We also now live in this perpetual beta society, right? You know, anything that's downloaded is never the finished product and you're expected to update your iOS and your laptop OS and every app on both devices every goddamn day, otherwise you're opening up some security vulnerability or it'll stop working. And I think we've imported, stopped believing in a finished product which has all the benefits that you talked about but also turns culture into kind of a run on sentence like the one that I'm speaking right now. It just keeps happening. 

17:15 - Tristra Newyear Yeager (Host)

You know another thing about sort of this productizing of the process. It makes me think of things like speed runs to sort of recreate an iconic track using a certain DAW, so the sort of gamification of studio workflows and things like that. That's really, really interesting and I do think you're right. I think we are looking at a time when there's going to be finished, and you know, sort of bracketed, completed recordings, and then there's going to be a whole other swarm of stuff that is maybe a commercial artist that morphs into a casual creator, and it's all going to be, you know, worked on together in this big, big mass of who knows who knows what exactly. But some of it will be great. 

17:55 - Jesse Gilbert (Guest)

It's interesting. You know I've been looking, so I studied electronic music years and years ago and then about two years ago I started looking into it again and you know we're at a very interesting moment in that world, right, so I know more about that than a lot of other parts of the music industry. There's been a real transition from purely analog to sort of hybrid digital analog systems that are programmable, which means that a whole new group of people are actually being invited into that community who can contribute other skill sets and thinking about how to make music. What you do see is what Aram just said that the process becomes a product. Then you have brands that are finding those people becoming creating how-to videos, tutorials, that then you know, ultimately, that you can't escape the ultimate sort of like creative crisis questions that any artist has to approach right now, right, like as they move into how do I make something I want to listen to? There's so many options, there's so many variables. 


I am probably a little bit biased, because I think it's good for the culture for that to happen. I think that for that to be so visible and for for that to be witnessed and to actually see some of those artists kind of having these moments of crisis and talking about them publicly, which is happening all throughout that industry right now is actually beneficial collectively, need to see that and we need to be asking questions about why is this happening? Right, because there is. You know, that's a perfect example of like a total DIY ethos that is then getting productized and that there's a tension between them, and I don't think that's necessarily a bad thing but it does add what what our friend Nancy Boehm calls relational labor to the process of being a working artist. 

19:45 - Aram Sinnreich (Guest)

Right Is that you know, a musician's job is no longer just to gain mastery on their instrument or to write songs or to record and perform them. It's also to develop ongoing relationships with audience members, with brands, with other musicians, and to make those relationships have the appearance of transparency to the greatest degree possible. And a lot of that is is not directly compensated. You don't get to clock in for the time you put in on tick tock, like answering the people who have left comments, and so that benefits a certain kind of artist who's amenable to that kind of social labor. But a lot of people, especially older artists and artists who are on the margins of mainstream American society for various reasons, get left out in the cold because they don't have the fluency or the access to the means of production. 

20:37 - Tristra Newyear Yeager (Host)

Or it's a very unsafe place for certain kinds of artists or certain people from certain backgrounds, and putting yourself out on TikTok could be a very unpleasant and scary and even frightening thing for some people. So, but those were maybe the very people we need to hear from musically. Right, I'm in. It's a difficult situation and and. But I do love that there is this sort of growing fluidity between people and, in some ways, while we're getting segmented and and I'm not saying there's no bias in data or the way data is organized in some ways, like the algo, don't care on Spotify, it's like it'll serve up. If you've listened to enough of music from Indonesia, you'll get a track like you can listen. Your suggestions will be the weirdest thing, like you know Taylor Swift and then some Indonesian rock and then maybe some classic country. I feel like you're talking about yourself. Tristra, just for now. I'm asking for a friend. 

21:30 - Jesse Gilbert (Guest)

Just a hunch. 

21:33 - Tristra Newyear Yeager (Host)

But what I'm saying is that data can be used to build these barriers between us. If you read some stuff by, like, say, kyle Chayka right, who's really into talking about how algorithms have flattened and simplified culture, I have some big question marks about that and I'm wondering what's your take on that as people who are in the trenches kind of trying to sort all this stuff out? Do you feel like the algorithms have become too dictatorial, too much of a shoot, like sending us down a certain cultural passageway, or how do you see? 

22:02 - Aram Sinnreich (Guest)

it. This is a key question that Jesse and I address in our book, and it's not a binary yes or no, and what it really comes down to is remembering that algorithms are just complex mechanisms used by powerful people and institutions to accomplish different tasks. So the real question is we now have three global megacorporations controlling three quarters of all record labels and publishing. We have basically one television programmer responsible for all music viewing in the US. We have basically like one company vastly controlling all the performance venues in the US. We have an oligopoly of radio providers in the US. We have an oligopoly of radio providers in the US. 


This tiny handful of corporations can use algorithms in a way that maintains their market dominance and their cultural dominance, in a way that does flatten us out. 


But those same tools, those algorithmic tools, can be used in all kinds of ways that resist that corporate hegemony and encourage a diversification and greater degree of nuance in our shared culture. And Jesse and I describe a lot of examples of how that works in practice in our book, and one of our favorite principles is what Jesse termed triangulation, which is the notion that when you build an AI, it doesn't have to have what Donna Haraway called the God trick. It doesn't have to pretend to know everything and put the user into one point of perspective where the whole world seems knowable from above. You can actually build AIs that don't only gather data from a variety of people, but gather perspectives from a variety of people. But gather perspectives from a variety of people and offer kind of conflicting versions of the truth and overlapping and intersecting versions of the truth as part of the user interface in a way that privileges multivocality over the kind of unitary corporate agenda, and that happens all the time. 

24:02 - Tristra Newyear Yeager (Host)

How would that work? I'm trying to think of an interesting music interface that would allow us to do that. Would it be like I can imagine a streaming music service being like? You will probably hate this song. I love that. 

24:12 - Aram Sinnreich (Guest)

Try it out. Yeah, I mean imagine sliders, for, like you know, would my mom like this song, yes or no? I feel like listening to music. My mom would hate, you know. 

24:21 - Tristra Newyear Yeager (Host)

Right, or that my dog would love Like. What song would make my dog happy right now? 

24:25 - Jesse Gilbert (Guest)

Sure sure, or even what Aram is also talking about, is that a lot of the ways that we deal with the algorithms are really guided by the interfaces that we have available to us. Very good point. There's a huge amount of work that can be done on interface level to show us this kind of valence of possibility within these and have a little more of a sophisticated interaction than a thumbs up or thumbs down to interact with an algorithm, especially when, as we've just pointed out, a lot of cultural music making, culture making right now it has already been done in relationship to the perception of an algorithm. So the more that that perception can be opened up and we can incorporate different perspectives into the interfaces, the more positive impact we're going to have in the culture making side of things. 

25:21 - Aram Sinnreich (Guest)

I want to do a big shout out to a teacher that we all studied with when we were undergraduates at Wesleyan University back in the 90s, the great composer Anthony Braxton. And one of Braxton's big schticks was the audio visual spectrum is a spectrum, like radio is literally a spectrum. And then he would say when I turn on the radio, why is the music that I hear not also a spectrum? There should be some morphological relationship between the technology and the subtlety and plasticity of the culture that is distributed and produced on the technology, and I think it took me decades to understand what the heck he was talking about. But the more that Jesse and I work on this stuff together and on our own, the more we get to understanding that Braxton really opened up our heads to allow us to ask those questions in the first place. 

26:20 - Tristra Newyear Yeager (Host)

So I'm going to switch gears slightly here, even though this is really really interesting, and maybe this is part of the same kind of user interface or how we can relate to data in a different way. I'm really fascinated by sonification, and you do have some great examples in the book of different ways people use data to create new sonic experiences or new ways of interacting with sound. I'm thinking of the visual microphone, which I don't know which of you wants to explain that fantastic example, jesse. 

26:46 - Jesse Gilbert (Guest)

We're kind of getting into a discussion almost of like a forensic approach to culture and in this case it goes to the use of video information that is taken where you cannot actually hear Maybe it's a silent film or it's shot through glass or something like that and you're actually able to observe subtle vibrations within the room, sympathetic vibrations that are picked up on camera and then re-synthesize the audio. 


This is, I think, now probably something which we would consider to be experimental in a lab, but it's pointing to the possibilities of what we were talking about in our previous academic work is this idea of a carrier wave principle, that any piece of media can become a vector for the extraction of other information. 


There's no limit to the amount of information that any piece of media can produce, given the right circumstances and distance and time. Circumstances and distance and time and this is a very good example of that kind of early experiments that show and prove that to be something which will become more and more prevalent in the culture. Again, a kind of forensic way of thinking. And as we wrote the book, I think we began to see that as a pattern over and over again in all of these different areas, from data mining to policy breakdowns, understanding power structures within a document, all of the ways that we as a culture have kind of built up our capacity to read these messages. And the visual microphone is kind of a great you know whiz bang version right Future tech type example of it. 

28:26 - Aram Sinnreich (Guest)

Or structured light or all of these cool, but there are very real ways in which our culture is currently being impacted by new forensic techniques. Right, like what Jesse was just describing doesn't like visual microphone, you know. Pointing a camera at, like a you know, a bag of chips in the other room and extracting audio data from it, like Jesse said, is still very experimental and requires high quality equipment in a laboratory space. But right now, in 2024, there are millions of people online collaborating in what's often called OSNs right or, like you know, open source intelligence collaborative forensic efforts to take photos that are posted to social media or documents that are posted to newspaper websites and to extract maximal intelligence from them in order to figure out what's going on behind the scenes or what was surrounding the frame. And new AI tools, like the kind of outer painting techniques, for instance, are at their best, can assist people to fill in the gaps and kind of reconstruct what's been hidden from us. 


So much of media culture is about framing right, and if you study communication theory or media theory, that's like one of the very first things that you learn about is that whoever gets to point the camera or point the microphone or choose the point of view for an article kind of over-determines what you get out of it, because they're putting you in a spot and putting something in front of your face and showing it to you. But more and more and more, both online collaboration and extractive forensic digital tools allow people to kind of like peek around the corners and behind the curtains and collaboratively develop a kind of alternate narrative to what's being shown in the mainstream press and mainstream organs. And that can be great in terms of like allowing people to you know, unmask the mechanisms of like lobbyist influence over policy. But it can also be terrible when it like creates like a QAnon series of conspiracy theories where people are like claiming to have extracted real data from these public artifacts. That's like total nonsense and ladders up to a BS cosmology. 

30:44 - Tristra Newyear Yeager (Host)

Or falsely accuses someone online of committing a crime or being involved in something pretty nefarious, when they had nothing to do with it. 

30:52 - Aram Sinnreich (Guest)

Yeah, I mean, I live in Washington DC and I'm a frequenter of Comet Ping Pong, which is a great pizza place and music venue, and very famously, these QAnon crazies claimed that the restaurant has a basement, which it doesn't, and that children were being tortured in that basement, which they're not, and that Hillary Clinton was somehow in on it, which obviously she's not, since it doesn't happen. But those kinds of things I'm not sure how we can get the one without the other, how we can empower people to reconstruct narratives from their own perspectives and to triangulate and collaborate through OSINT communities, but not also have increased credibility for crazy conspiracy theory. 

31:33 - Tristra Newyear Yeager (Host)

Thinking like you and I, Well, on that festive note, we're going to take a quick break here and we'll be right back. 

31:42 - Shayli M. Ankenbruck (Host)

Will you be at Music Biz this May? Some of my team is hitting the ground in Nashville and I'm leading a music tech meetup. Meet the movers and shakers of music tech and innovation will be taking place on Wednesday, May 15th at 1 pm in the JW Marriott Room, Griffin FGH. That's the community hub. Join me and other music industry innovators to meet, share ideas and learn from one another. Come ready to expand your network or make a friend. See you in Nashville. 

32:18 - Tristra Newyear Yeager (Host)

And we're back with Aram and Jesse and we're going to let's talk about something that's a little. It's sort of segues not too abruptly from what you were talking about, aram. But there's two issues that I think come to mind in the music industry that we often think about and then want to stop thinking about really fast because they're very discouraging. So one of them involves AI and things like training sets, right. So the whole question of ethical AI has really come to the forefront in the music business. So how do we treat creators right? How do we have a mechanism for consent or control in some ways, and monetization and I think the control part is just as important for a lot of artists as the money, to be completely honest. So how do you guys see that? What can we learn from the secret life of data that can help us answer some of these questions or maybe ask better questions? 

33:04 - Jesse Gilbert (Guest)

This is actually an interesting topic, because I'm not sure that Aram and I always have the same perspective on this, but I think that it's important that that's the case, because we're at a critical moment. The capabilities of AI are increasing so rapidly and, really, with the level of quality that can come out of them, we are forced to grapple with these questions. But, as Aaron pointed out, these aren't new questions. This is an iteration of a process that's been happening over many, many decades since the advent of recording technology. There are multiple perspectives here, so one of those perspectives is the cat is out of the bag. The technology is here and we, as artists, have to grapple with that and we have to learn how to adapt to it. 


Now, what does that mean practically? Perhaps it means that we need to develop our own models, that we need to develop alternative aesthetics and alternative practices that can provide, again, an alternative presence within the industry that can attract attention. This is the sort of consummate issue with independent artists that they are always going to face, but it means that they have to become fluent in this new language, which means that they will have to engage outside of their immediate community right, or they'll have to acquire those skills. That isn't to me a bad thing, but I think it is. It does mean that the category of what does it mean to be an artist is changing. 

34:33 - Aram Sinnreich (Guest)

I mean, we could literally talk about this for like eight hours straight without taking a bathroom break, but let me give you a very quick and dirty hot take. I think that most people, especially artists who are paying attention to AI, perceive a moral harm, and the moral harm is measurable economically, because what's happening is that the revenue that's being made from creative labor is shifting over, so a larger and larger percentage of it is being recognized by technology companies and not by the record labels and publishers and other companies that are contractually bound to share their revenue with artists, and so artists perceive accurately that they are being structurally excluded from participating economically and reputationally in these new business practices, which is bad. It's definitively bad. It's anti-artist. It causes people to be disincentivized to create new work, to share their work with the public. It's bad for society. That being said, we don't have any good legal remedies for this, because a lot of people have proposed well, let's just create copyright for AI. 

35:47 - Shayli M. Ankenbruck (Host)

Well, first of all, what does that even mean? 

35:51 - Aram Sinnreich (Guest)

Would copyright confer on artists the ability to prevent their work from being included in machine learning data sets? Would it give artists some degree of control over what kinds of algorithms are applied to those data sets? Would it give artists ownership over the outcomes of what's churned out by the machine learning algorithms? Those are all, from a legal standpoint and an economic one, very separate questions, and any use of copyright law to create to solve one of those problems would create more knock-on effects and secondary problems than it would be worth, and I'm not gonna go through all the details right now. You're just gonna have to trust me on this as someone who's researched and written extensively on this subject. 

36:36 - Tristra Newyear Yeager (Host)

Wait for the thousand page sequel. Yeah, so then the question becomes like, and written extensively on the subject. 

36:39 - Aram Sinnreich (Guest)

Wait for the thousand page sequel. 

36:40 - Tristra Newyear Yeager (Host)


36:40 - Aram Sinnreich (Guest)

So then the question becomes like how do we solve the larger moral harm of artists not being adequately compensated and recognized for their contributions to culture without creating some kind of like hyper litigious, hyper surveillance, techno legal regime in which, like nobody can create art to begin with, because everyone's afraid of getting sued Right? And unfortunately, the only way that I see to square that circle is to recognize the harms that came along before AI did, which is what I was mentioning before, which is the radical hierarchical oligopolization of every aspect of the music industry and the reduction of collaborative cultural work to monetizable individual labor, which was a false kind of system to begin with and has always sat poorly. The music industry has never fit in its economics and legal and technological parameters with how actually human beings actually use music in their lives, whether they're making music or listening to it. And the more new tech we add to the mix, the more of a rupture there is between the way that the music industry works and the way that music works for and with and between people. 


And so I think we're going and this isn't just true of music, I think it's true of cultural economies in general is we are going to have to go back to the drawing board and rethink what cultural production actually is and under what circumstances it should be propertized, and when it is, who should get to participate in that property economically and reputationally and in terms of like, having a say in the uses and distributions of their work, and that that's going to be an undoing. Decades and decades and decades of quick patches that we've made over our copyright system throughout most of the post-World War II period, which is just going to be super painful and involve entire giant companies going out of business and other ones having to change their strategies and labor being re-skilled. Just a few little things here and there. There's not an easy fix. Yeah, it's going to be ugly, but I do think that there's light at the end of the tunnel. 

39:07 - Jesse Gilbert (Guest)

Yeah, I think what's interesting to me about that answer is also that it's, in a way, a continuation of what I was saying, that ultimately, this is going to catalyze what we would call a crisis right, Some type of actual reckoning that has to happen within these industries and the recognition of the impact of computation into this mix. Anyone can speak into this. Anyone can write these algorithms. I think the tech industry likes to present itself as this exclusive club. 


But you know, if you look at the development of open source technologies or just the profusion of computing culture around the world, I mean it's anything but that. It's an expansive culture and what I? What I find interesting about this I've been saying this for a long time it's like, on the one hand, this is presented as this inevitable conclusion of this is how these industries have to function, but the first company that comes along and actually proposes and operationalizes an ethical model is all of the people are going to migrate to that platform. 


This is actually a business opportunity. 

40:17 - Tristra Newyear Yeager (Host)

I was thinking about this lately A lot of the people who are running these companies right now that are pretending to be sort of spearheading these major technological quote-unquote disruptions are in their 60s, right. So how disruptive are they? These are people who are wealthy people in their 60s. So what are we? I mean, no offense, wealthy people in your 60s. I'm sure some of you are delightful, but, like, this is not a disruption, this is a continuation and attenuation, and perhaps it's more and more chaotic. We haven't really had a true disruption of the music industry, have we? 

40:51 - Aram Sinnreich (Guest)

Well, I mean, is disruption the goal? Yeah, it's a good question, right, it's a word that gets used a lot in like VC and private equity and Silicon Valley circles. But, like, I think the goal is universal liberation and participation. Yeah, Right, like disruption is, can be a means to that end, but it's not like I don't. I don't stay up at night thinking about how can we disrupt things. I stay up at night thinking about, like, how can the human species deliver on its full potential and create a better world for everyone to live in? And music is a crucial part of that. 


I think that by changing our definitions of success, we can open up a lot of new avenues for exploration when it comes to how technology is used productively in musical culture, and we don't have to reinvent the wheel there either. 


If you look at, like you know, historical examples, right, like the example of sampling, right, so you know 1940s comes along, you have someone like John Cage in the kind of Western classical avant-garde, using tape loops and found audio to create these kinds of sound collages, and that had a lot of influence inside of this tiny little world, like Glenn Gould got turned on by it, right, but you know, flash forward to the 1970s. 


You've got like DJs in playgrounds in the Bronx, like inventing turntablism and giving rise to what became hip hop and this whole larger tapestry of sample based musical styles, out of a form of kind of play and resistance that was not dogmatic, that was not predetermined, that was not even doctrinal in any way. It was just people having access to the tools and having the social need to get a party started and you know, all of this kind of innovation and liberty comes out of that, and so I think we will never build tools that are so fundamentally authoritarian and totalizing that some community can't come in and find a way to create new musics and new musical practices with them. That turns the world on its head, and I've just been waiting for that to happen, and I'm sure it will with AI and with algorithms. 

43:07 - Tristra Newyear Yeager (Host)

And you know there's a thousand different ways to build a community and people were building communities below the surface of the quote unquoteunquote music business for centuries and they're really poorly documented. Right now we can, finally, we can kind of sort of see a lot of stuff, even if it's still pretty fragmented, and I think that's sort of distorting our understanding of previous music practices and maybe we're missing some of the clues from the past that we could use to create these more liberating and inspiring structures. So I think you got a good point there, aram. Thank you and thank you. This was a lot of fun. We got sort of deep into the philosophical aspects of it and I think that's wonderful. I think data is often seen as this dry, lifeless, dehumanized thing when it is, you know, an extension of our living, breathing selves. So thanks for bringing that aspect of it to life. 

43:55 - Aram Sinnreich (Guest)

Oh well, the animating philosophy of our book is that data is cultural and culture is becoming datafied, and so you can't really talk about the one without the other, and that means all the glorious complexity and contradictory quality of the culture that we lived in applies to everything data oriented as well, and anyone who says otherwise is selling you something. 

44:19 - Jesse Gilbert (Guest)

All right, thank you for having us. This was fun. 

44:21 - Tristra Newyear Yeager (Host)

No thanks, this is a blast, all right. 

44:30 - Dmitri Vietze (Host)

Thanks for listening to Music Tectonics. If you like what you hear, please subscribe on your favorite podcast app. We have new episodes for you every week. If you like what you hear, please subscribe on your favorite podcast app. We have new episodes for you every week. Did you know we do free monthly online events that you, our lovely podcast listeners, can join? Find out more at and, while you're there, look for the latest about our annual conference and sign up for our newsletter to get updates. And sign up for our newsletter to get updates. Everything we do explores the seismic shifts that shake up music and technology, the way the Earth's tectonic plates cause quakes and make mountains. Connect with Music Tectonics on Twitter, Instagram and LinkedIn. That's my favorite platform. Connect with me. Dmitri Vietze, if you can spell it, We'll be back again next week, if not sooner. 

Music Tectonics at NAMM 2024

Let us know what you think! Tweet @MusicTectonics, find us on LinkedIn, Facebook and Instagram, or connect with podcast host Dmitri Vietze on LinkedIn, Twitter, and Facebook.


The Music Tectonics podcast goes beneath the surface of the music industry to explore how technology is changing the way business gets done. Weekly episodes include interviews with music tech movers & shakers, deep dives into seismic shifts, and more.


bottom of page