The Vergecast - Making human music in an AI world

Episode Date: November 17, 2024

For the third episode in our series about the future of music, we talk with Ge Wang. Ge is a professor at Stanford, a co-founder of Smule, the conductor of Stanford’s laptop orchestra, and has been at the center of technology and artistry for most of his life. We talk about how humans can use AI without giving in to it, what it means to truly play with technology, and the value of art and creativity and friction when it feels like all those things are being taken away. Further reading: Ge Wang’s website The future of computer music | Stanford University School of Engineering Ge’s viral TED talk: The DIY orchestra of the future From Wired: Behind the Scenes With the Stanford Laptop Orchestra Ge Wang: Human Well-Being Should Be AI Creators’ Goal Email us at [e-mail] or call us at 866-VERGE11, we love hearing from you. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Welcome with the Vergecast, the flagship podcast of music apps you play on your phone with your mouth. I'm your friend David Pierce and I am at Union Station in Washington, D.C. It's like 454 in the morning. And I'm on my way to New York to go do some planning meetings with a bunch of other Verge folks. I've been at the Verge for like two and a half years now and there are a bunch of coworkers that I've just never met in person. It's weird post-pandemic universe we live in. But I'm going to go meet some of them in person. This is the third and last episode in our mini-series about the future of music.

We've talked about Trackstar and TikTok. We've talked about Autotune. And today I'm talking with a Stanford professor named Go Wang. Gah is fascinating. He's been in the music world for a long time, but he's also an academic. He's also a former entrepreneur who built a company called Smule that you might have heard of. He's just been in the music world thinking about this stuff for a really long time. So I wanted to talk to him about AI and about virtual reality and about what it means to make music now in a world where increasingly technology mediates all parts of this process.

We had a really fun conversation. It's not at all what I expected, but I really enjoyed it and I suspect you will too. All that is coming up in just a sec, but literally this train is best to leave without me. This is the first cast. We'll be right back. Support for the show comes from Retool. Too many companies run critical operations on duct-taped spreadsheets, Slack workflows, and whatever else they could cobble together. Not because they want to, but because building internal tools

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Welcome back. Let's get into my conversation with Go Wong. I wanted to talk to Go because he sits at a really unusual place in the music slash technology universe. A bunch of years ago, he co-founded a company called Smule, which is still around. You might have heard of it. They make a bunch of really popular music-based apps. One is a karaoke app called, I think, Smule that's still really popular. There's also one called Magic Piano, which is kind of like Guitar Hero or Beat Sabre, but it's for playing piano.

Gah also wrote a whole programming language called Chuck, which lets you write code that outputs as music. It's very cool and kind of wild to watch someone work with. He's now been at Stanford for a long time, also teaching in the Center for Computer Research in Music and Acoustics, which is a very cool thing that I just learned exists. He's also written a book about design. he's been teaching about music and technology for years, and in his free time, he's also the conductor of Stanford's laptop orchestra, which is exactly what it sounds like.

It's a bunch of students on stage using their laptops and other gadgets to make music, frankly, that you've never heard before. Here is just a glimpse of what that sounds like. That sound, if you can imagine it, is being made by Gah himself, who is standing on stage, holding a glove,

connected to his laptop, and it's changing the sound as he moves his hand in space. It's wild. You should watch it. Their concerts are very cool. I wanted to talk to Go about the future of music because I figured he would just see it all from an unusual perspective. He makes music.

He teaches about music. He's a programmer and an engineer, both for fun and by training. He's started companies before. He's seen kind of all sides of this. And I figured he'd have cool ideas about how we make music, how we can interact with computers to make music, and probably would have some, like, neat new AI apps that he was into that we might talk about.

Our conversation went really differently from that. And it went really differently in a way that I really love, actually. What we ended up talking about more than anything was what it means to be creative in a time when everything is being optimized and simplified and made more convenient and more efficient and more engaging, absolutely everywhere you look. This is much more philosophical than a lot of the stuff we talk about in this show, but I really like the way he talks about what it means to be human and be yourself among all of this technology.

And I hope you enjoy it too. So let's just dive in. To start with, I aska to try and frame the way he sees the world a little bit. One thing I've heard him say a few times in interviews and stuff is that he makes computer music. But it's 2024, right? pretty much all music is made with and on computers. So what does Gah's version of computer music look like now? And how did he get so obsessed with it in the first place?

Since I was a small child, I've had a fascination with computers, probably through video games. Actually, I still remember the first time I saw a video game. I think I was seven or eight in Beijing. You know, I had not seen a computer up to that point. I was thinking it's a big deal when we got a nine-inch colored televation. You know, this is in the early 80s in China. And the first time I went, my mom, I think, took me to an arcade, a video game arcade. I don't know if listeners still know what those are.

They've seen them in movies at the very least, you know. Yes. Those are places where you go and you put, like, coins into and you can play games. And there's these giant machines, arcade machines. And that's the first time I saw, like, a video game. And something about the pixels, I think, really kind of drew me in. Not unlike a moth to a flame, I guess. It's not entirely like a bad analogy, but I'm like, ooh.

And I think ever since then, I've been fascinated with just computers. But I think over time, I think I've really come to love computers in computer science as a discipline, but perhaps in a strange way. And I'll try to explain that. So all my degrees are in computer science. My Bachelor of Science is in CS. my PhD is in computer science and in some ways

I'm kind of a strange computer scientist but I think I say strange because I tend to build things that with computers that nobody quite asked for that solves no problems that seem to exist for example Ocarina

right this is something that was designed back in 2008 for the iPhone and you know let me so I can play a little here here, so I can hear this. So I'm holding my phone as I'm at a sandwich, and I'm blowing into the microphone located at the bottom of the phone,

and I'm using multi-touch to control the pitch, and vibrato is controlled by the tilt of the phone. Oh, cool. So I'm barely even seeing the screen, but, you know, it's kind of a physical thing. So I'm going to try to play a little ditty with this, for example. So that's me blowing literally into my... Well, thank you very much.

As me literally blown into my iPhone and into Okerina. And this is an app that I would say is took a lot of, you know, it took software engineering, software design, interaction design, signal processing. All the sound is generated live on the phone using, you know, the sound part is written in the programming language Chuck, which was my dissertation at Princeton in which I'm still developing. Right. Like 20, actually 20 some of you.

years later, I'm still working on it, and myself and a large team of people and a community of people working on Chuck. Right. Just explain what Chuck is just real quick for people who don't know. So Chuck is one of these tools that I've been talking about. So Chuck is a programming language for music synthesis. And you're writing code to generate sound, but also to write code to kind of either to algorithmically figure out or generate like kind of the music that's coming next, or it's

actually could be mapped from human interest. In this case, in Ocarina, it's human interaction, human computer interaction, and I am using my physical interactions to actually control the sound that's happening. And a lot of times it's a mixture of the two where there's some amount of automation, but also, like, it's really trying to also figure out what is an interesting way to kind of put human interaction into the loop of the thing that we're building. Again, nobody asked for. I solved no problems that exist. And I think in a way that's kind of been the running through line, if you will, for my students and I in my research group, is that we, you know, we think about engineering, we think about technology. We think about, what kind of problems can we solve with this? Right.

And while, yes, problem solving is something that we, as humans need to do, and I'm interested in doing myself, I also feel like as an engineer, we can build things that isn't always motivated by kind of a practical use of utility. Tell me how you go through that as kind of a creative process. I think I spend a lot of my time talking to engineers and developers and stuff who say, you know, some of the stuff you just said, and then they like small leap to and now I make B2B database management software. And or like, and so I made yet another AI chat. Right. And I think there is this easy way to work backwards from like, okay, what is the problem I can solve that will help people? And I think using technology in service of going the other way and saying like, what can I just make is just such an interesting and different kind of creative process. I'm curious how you have sort of, especially you have to teach this stuff to students. Have you refined the process of how to do this stuff for people? Yeah. I mean, I choose this.

I wrote a whole book about it, Artful Design Technology and Search of the Sublime, and it's really this idea of looking at tool building as engineers, but also as critical engineers. You know, critical tool builders. And the critical part is, really has to do the question, why are you even doing this thing, right?

Why did I design Ocarina? And it wasn't because, like, I went out and figured out, what do people need? You know, it's like, hey, David, what do you need? And you're like, well, I need to blow into my phone. I need a flute app.

I need a flute app. Also in the same app, I need to be able to listen to other people around the world blown to their phones. That's been missing. That's a deficit. No, that did not happen. And so it wasn't really kind of this traditional idea,

at least traditional now when we think of engineering, we think of this as like, okay, that's a, what is the need? What's the problem? State the problem, and so we can find a solution. This is not need-based design, at least not in that sense.

So why was this designed? This is what some people actually might call, you know, for perhaps lack of a better word, value space design. And value space design is saying, well, you don't design out of a necessarily a clear and present practical need, but out of something you just really deeply, as a person, believe in. And so for something like Ocurean, perhaps for a lot of the other tools that my students and I build, perhaps one of the values that core values that we are trying to speak to in these design is just simply that music making is good. That's the belief.

Music making does a person good. And it's not about getting to a product necessarily, but about actually the process of playing and sometimes and often learning an instrument. Not unlike learning to play like a well-made, perhaps challenging video game. Because there's a great satisfaction in that if the game is well-made,

it does not matter if it's difficult. In fact, you might appreciate the difficult. Because then once you feel like you're learning the system, you really can then express yourself using the system. And then the challenge and then unable to overcome the challenges eventually of the game becomes hugely gratifying. Okay. Has that started to feel like a, I don't know, dying phenomenon to you, the idea that in this world of incredible convenience and efficiency where everything is available to you, you know, with all, with a push of a button or like a plug-in in an app, that doing something just for sort of the joy and pleasure and slog of doing it is worthwhile?

Like, that almost feels like a sort of beautiful, deeply anachronistic way of looking at the world right now. Well, unfortunately, it is. It feels anachronistic. It feels like it's out of time. It's not something that, you know, in this convenience-driven, optimization driven competition driven fabric of a society we live in. It feels deeply anachronistic to build things that are playful, that are interesting for their own sake. But at the same time, I feel like it's what makes us us. And I don't mean, I don't mean just building things.

I mean anything I think that you feel like makes you you, whatever that may be, I like to least offer the possibility that it actually is something that is that you you want to do and you and you care to do. In fact, you would probably forego a lot of practical needs in order to do. It's like a passionate hobby. And the passion hobby is usually not about getting to the result. It's not about optimization. Right. And so I think this gets to this idea that, yeah, while this idea of building things for its own sake or doing things for its own sake is feels like it's out of fashion, but it's also not.

in a sense, I think we actually still do these things. They're just usually not in engineering contexts. You know, for example, when people cook for themselves because they enjoy cooking, there's a deep joy to go in the pantry, work up, find the raw ingredients, and make a mess of things as you concoct a dish. And that dish doesn't that taste different because you know, because you made it? Right. It does. It has to, especially if you're someone that enjoys cooking. And I think tools are no different. And I think the danger of being in, I think, in a world or a society where the things, the tools we make are only about optimization, only about convenience, only about reducing the cost of labor, is that we actually, in those tools, those tools can actually alienate us from who we actually are. Because, you know, well, let's go back to music. and let's talk about music and AI, right? Yeah, today we have AI that can produce really impressive images, video, music, well, that's a tricky word to use. Even songs are tricky words to use.

Like, you know, what is this song? But let's, for all intents persons say, AI can generate quote-unquote songs. And with just a prompt, it's like this almost age-old thing that people thought they always wanted, which is if I have a musical idea in my mind, I just want this thing realized. Wouldn't that be great? And I don't, maybe perhaps I don't have any music education.

I'm never taking time, but I just want this idea realized my head. It wouldn't, wouldn't that be great. And in a way, AI kind of does that somewhat today. But then I think the question lies, what is it mean? And, you know,

and I'll draw another analogy here, and this is something that I call, I guess, it's kind of the bubble gum effect. And what do I mean by that, right? So, have ever chewed gum, David? Sure, yeah.

Okay, so when you chew a piece of gum, when you first pop the gum in, chewing gum or bubble gum, right, how do you feel? It's great. It's delicious. Yeah, it pops. It's like, the taste is great. How long do you usually chew that piece of gum? I mean, it depends on the gum,

but somewhere between like 10 seconds and three minutes, and then it's over. And when it's over, what do you do with that piece of gum? throw it away. And do you, after that, how much do you think about that particular piece of gum? Never for one second ever again. Okay.

So I think that's the analogy I'm trying to draw here, is that, yes, maybe it's so easy that I can go to a generative AI system and say, render me an image of Barney, the dinosaur, withdrawing cash from a ATM, but only broccoli is coming out. I think actually AI would,

generative I of today would do a rather impressive job. Yeah, yeah, that's it's it. And I may go and share this with my friend and be like, hey, check out, look what I made. And I think there's actually that social function of that.

But then, more likely than not, I'd probably be like, great, onto the next thing. Yeah, that took all of three minutes, five minutes. The time it probably takes to chew a piece of gum. Whatever, think,

about that thing again, maybe a little bit more than the piece of gum I discarded. And I think that's what I mean by bubble gumification. In fact, it is kind of almost in the limit of this kind of push of automation,

unquestionably pushed automation to basically try to reduce the cost of labor down to zero in like every case we possibly can. Right. Well, there's an argument inside of that, I think, that you hear a lot with kind of anything creative,

which is that the process matters, right? That the provenance of something and where it came from and the story of the thing and the person who made it, that stuff is sort of indelibly connected to the thing in a way that you don't always understand even, but matters in some way that is very hard to quantify and thus is very hard to talk about in some ways. That stuff matters.

And I really buy that premise. But I also, what I wonder then about, AI is if what AI is going to create is like some entirely other thing, that like maybe what we want from AI is not to make songs that sound like Taylor Swift, but something that sounds completely different. And this is part of why I think your work is so interesting and why I'm curious about how you're thinking about in using AI. Like you've made a career out of making computers make noises that they're not supposed to make. And I think what those ultimately make is something different, right? Like, you're not writing code to make Taylor Swift songs. You're

making something else. And I feel like if you approach AI as that kind of tool, both to sort of bend it to your will, but also to try to figure out, like, what sound it makes. I guess my general life philosophy can be summed up, or at least in aspirations, that there should be room for that, too. Okay. And I mean this both. In a way, like what I mean by that is I think about this in terms of music. I think about in terms of actually like people and a society. There should be room for that too. As long as the thing is not like harmful and dangerous.

Sure. But also it also means that I guess there's, you know, it's really what I'm trying to say is that it should be a pluralism. We should have room to have capacity to have a pluralism of, well, of what? I would say of values, aesthetic, social. In fact, that would be my notion of what part of what a civil society might have, but also maybe a necessary condition for humans to be able to flourish, you know, is this idea to have a capacity for pluralism. And so, yeah, in that sense, I think there's room to think about how,

Can we explore, use AI to explore the realm of untapped sounds? But how we do that, first of all, I think is really important because it does go back to what you're saying about the meaning that we ascribe to things that we might call art. All right, we've got to take a break, and then we have lots more to talk about. We'll be right back. Support for the show comes from Framer. Framer is an enterprise-grade, no-code website builder,

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one of the things Gah has talked a lot about over the years is the idea of finding new ways to interact with technology and computers. Like that glove I mentioned at the beginning, that's a new way of using a computer if you'd boil it all the way down. And the way he thinks about it is more explicitly playful and more exploratory. Instead of just trying to figure out how to use an app most effectively to get work done, it's just a totally different approach to all of this stuff.

But that can be a hard shift to pull off, I think, to go from trying to learn how to use a technology to figuring out what's possible with it. But that shift, that transition is, I think, what Gudd does all day with his students. So I asked him about it. I saw something that you either wrote or said about your music and AI class where one of your goals was to teach them how to play,

with AI. We don't talk about AI that way. What does that look like? What does it look like to play with these kinds of systems? Well, play what does it look like? I ask my students, for example, to build interactive tools with AI that they can deploy into their everyday lives, but also often would involve human interaction. My students have built instruments that basically track the opening, closing of your hand to generate singing sound. And turning your hand changes the pitch of the sound. Opening and closing your hand kind of articulates the sound. You can't do that with a prompt-based system right now.

Right. Right. That's not what that's about. But this means you need to go to the process of learning how to use that instrument. And another one, it's playful. I mean, that's playful and it's interactive. Another playful one of my students made this thing called auto-RIS. Okay.

It's a computer vision system that basically has been trained to classify between, like, to recognize a seductive look. And it plays like cheesy seductive music when it detects it. And that's all it does. It's like by the mission of the creator of Auto Riz, like this is such as, this is so dumb. And yet it's really, it's playful. Yeah. It's, it's, in the definition of play, is actually something that is not about the outcome.

It's about the process. Right. Right. Because if you're like, I'm playing, but if you're worried about the outcome that's going to be produced, well, that's more like, that's work, actually. If you need to walk away from an activity with a productive outcome, we'd usually call that work.

But play is almost exactly the opposite of that. Right. There's a difference I hadn't really thought about there between thinking about these technologies, AI or otherwise as tools versus thinking about them as instruments. And I think we talk about AI in particular as a tool, right? It is a hammer and your job is to go find nails. And that's what it's for. And we don't necessarily know what all the nails are and that's the exploratory phase, but you're looking for nails. But what you're describing is something very different, which is like, here is a thing with a set of capabilities.

Right? It can it can it can it can do a bunch of things and where all of the interesting stuff lies is figuring out What to do with those things and how they mix together and new unexpected combinations of those capabilities that turns into something Which is so different from I have a hammer that hits nails and I have to find more nails I go find more nails Yeah, let's let's let's say we make a Venn diagram which means let's draw a circle And that circle represents this that the sets of things that the AI is potentially good at doing or would be good of doing.

Let's draw another circle. Let's call that a set of things that humans do, want to do, and are perhaps, can be good of doing, like ping pong. We're making music or whatnot. In the event diagrams,

let's draw these two circles, but that's also they're intersecting. So there's a region where it's in, basically in space where it's in both circles. It's a stuff that humans are good to doing and AI will be good of doing. I feel like we're kind of automatically and almost unquestionably stuck in that intersection with AI is that we're constantly looking for things that humans already do, and now we just want to

have AI do that same thing. And in fact, the more the quote unquote better in AI can do it, the more progress surely does this must be. You know, some have called this the touring trap, actually, is this idea that that, we had been set down this path where progress in AI is judged by how indistinguishable a system is to humans. And the danger of that is that that becomes kind of the dominant and perhaps almost the only way we can imagine of thinking about progress in AI.

But if you go back to the Venn diagram, there's a whole region what AI could potentially do that is good at doing that does not intersect with a sphere, the realm of things that humans are going to do. How do we explore that perhaps far more vast region of what AI can do? I think that takes exploration, takes play, it takes imagination. And I think, and often in my courses, what we learn is that actually when you remove this external obligation to be useful or competitive, and you can simply be yourself in play, you actually produce things that are so different potentially. Arguably, it will certainly be different, but probably also like that's going to be more you, more expressive. So in my courses, I'm trying to help people use AI, but to try to explore the

unexplored space, but also explore the space where AI and humans intersect, but AI is doing that humans aren't doing, humans are doing things that AI aren't doing, and it's not about a collision or the actual overlap, but about a kind of like a critically thought through, but like a, but like a beneficial amalgamation, a union of two different parts. And what I like about that, even though it's not the way we think of AI as you're noting, what I like about that is it, you know, it still keeps human curation and I would say human intention and also what we might call human wisdom in the loop. You know, and the idea is that if AI could just generate me, even if it's a new piece of music,

but I don't have, you know, the provenance, as you said, of like, where did this come from? What was the story behind this? I did not come up with this, but I can, I do know who said this, but it's been said by someone. It's the role of art. It's the idea that art perhaps is this thing that humans endeavor to try to understand their emotions, but mostly they fail at that. But that's art. You know, it's a thing we try and mostly fail to try to understand ourselves. And so if we feel like that's, you know, if that's what art could be, then, yes, the provenance

matters and matters fundamentally to know what is trying to be communicated, what is trying to be expressed, or even more so, you know, if we think of art as a, as a, like, a lens to see things, you know, if I make a piece of art isn't just saying, hey, this is what I see, you know, yes, it's part of what the artists perhaps sees. But it's also an invitation for the experiencer to say, well, if you like, you can look through this lens too. And you see the world around, you see yourself, and what do you make of it? Now, that's, you know, a good piece of writing is absolutely that. You know, art in any medium, I think, is also a lens.

Whether there's film, writing, music. And so that requires this, I think, the human in the loop. If we buy that definition, the artist, this thing we do to try to mostly try and fail to understand our own emotions. Yeah. I will say my worry with that way of thinking about it would be that AI in particular runs the risk of kind of undermining that. because if you think about AI as sort of the lowest common denominator of all of its training data, what you're getting is basically this mush of all of its inputs that is kind of going to give you mush back, and it's going to give everyone the same kind of mush.

And we end up in this space where, okay, you have this collaborator that has incredible access to incredible amounts of information. But it, like, that's actually not useful in some of the ways that you're talking about. That maybe having access to every song ever made is actually a hindrance to making great new songs instead of just making the same kinds of songs that are the average of every other song ever made before. Well, it's, I mean, what you're saying is that it's still, it's exactly square in that region of the intersection. That's true. I'm still in the middle of the Venn diagram. You're still, right? That's really in the middle of that Venn diagram.

That's kind of where we are in a way that's like artists, all the artists I know generally don't want AI to, maybe they want help to do part of their work, but they don't want AI to do the work. In the moment that core writing part is actually done for me, the activity ceases to be like an activity. It's just like a checkbox.

Right. And what meaning I might derive from that activity, as time consuming as activity may be, is, I think as you articulate it, is the worries that that would be lost. You know, that meaning and the meaning of doing that activity may be lost. And I think it is, this way of thinking that I think that we're talking about is very much counter to the prevalent thinking in AI, which is, I, unfortunately, I'd say is an unquestioning, uncritical, like, race for optimization. race to like for AI to outperform humans without asking what do we really want from that and when is that actually good and when is that not good? Okay, we have to take one more break and then we're going to talk about where everything is headed from here.

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I think that stuff encounters one set of issues as we look to AI and the future of technology. But then all the way on the other side of the spectrum, you have like navigating. navigating government bureaucracy and filling out forms. One thing God mentioned to me was figuring out the health care system, terrific use of AI, right? I think that's the kind of stuff that almost everyone would be psyched to turn over to some kind of machine. There are tough questions about whether those machines are good enough to be trusted,

how we can rely on them, how they fit into businesses, all that stuff. But in general, that feels like a good use of technology. And then there is this whole messy middle, where it's stuff like, I don't know, writing emails. There is something meaningfully human about writing an email to your team at work. But all these AI tools are promising to write that email for you, but then on the other side, there are AI tools saying they'll summarize it for you.

And at some point, it's like, what are we even doing here? Are there any humans in this loop anymore at all? So maybe the three parts of the spectrum here are art, life, and nonsense. We're happy to give up nonsense to technology. We're reluctant to give up art, and I guess it's case-by-case on life. So how do we draw the lines between those things, though? And how do we decide where it's worth outsourcing and offloading and embracing AI and where we shouldn't? And then maybe most importantly, how do we protect the stuff that's worth protecting on that spectrum?

That is the next question I asked Go Wong. He answered by talking about email. So this is actually the other thing that maybe we don't think about. Like, first of all, I don't, for me, I remember the first time I used an email. It was when I first got to college in 1996. This was the Duke University, and I got an email account. And I was like, oh, dang, this is so convenient. And I wrote my dad.

I was like, dad, I'm writing an email. I don't have anything to say. I don't write to email. Okay, bye. It was like an email with no purpose except to say, it's so fun to email. I don't know anyone today who was like email is so fun. No. No, no.

That was 19996 for me. Now in 2024, we're like, and also emails is not something I do my job without. In fact, this interview was set up through email. Yeah. In fact, I imagine you probably, like me, are inundated by emails.

Unfortunately. Yes, unfortunately. So I think that was fun and useful and convenient to begin with. Because of that convenience, you know, you would think like, oh, it's a labor-saving thing. And it was for email. But because that labor was saved, and we're all using it, we've all saved that labor.

Suddenly, it's like, oh, we have more time to do, well, more work. Like, between now and, say, when you first used email, do you feel like your work has gotten any lighter or any easier? No. No, I don't either. No. All of the studies on this are so alarming that it's like you go back and everybody is like, oh, due to all the increased efficiencies, we're all going to work for like six hours a week. week. And it's like, yeah, I do the job y'all used to do in six hours a week. And now I have 40 other hours of stuff to do. Yeah. And maybe it's like almost like, I mean, there's so many

different reasons why that is not like, yeah, it's like, oh, now this thing is so, so, so if we apply that analogy to AI and just email today, is like, if AI does save us more time on email, does, do you think that'll just give us more time to actually, I don't know, live our lives, go make our, cook, be with our family, you know, go outside. No. I would be very not, like, given, like, where we are with email, I would be very skeptical of that possibility. I think, however, what might happen is, unfortunately, with LLMs and kind of this generative AI technologies, we might produce not just email, but, like, writing that is deemed good enough for a certain purpose, and now we just need to hire less people to do them. Yeah. For example, and this now started going back in that creative realm, like, for example, like script writing for a TV show. You know, and I have an uncle who has been in the industry. He lives near L.A. and he was talking about, you know, there was a time when the writing room for a TV show would actually be on set talking to, you know, the production team, the actors. And in that process actually really got both everyone involved to, you know, the production team. The actors. And in that process actually really got both everyone involved to, you. even be, like, really figure out what this is about, what each person, each character is actually could be about. It opens up all kinds of imagination for where things could go. And then you have

the case where, well, now we just hire, like, a kind of interchangeable room of human writers to write, like, kind of each episode, and in fact, we'll do the lowest bidder. And then with AI, you can imagine, well, now that labor has been saved, well, we don't need to hire even those interchangeable room of writers. Instead, let's have one person who prompts and oversees and curates the output of the AI system. And the result might not be good, but it might be good enough to make entertainment that people will pay for. And I think that's a huge, well, it's a huge loss of livelihood, but also a huge cultural loss in terms of the kind of art that is being made. Because now we have shows that would be like, well, that's entertaining, but is a really, like, entertaining doesn't mean it's

good. Entertaining doesn't mean it's, it's thoughtful or interesting or, you know, all of, or playful. It just means it's something, okay, it's better than being bored. Yeah. It's something to do. It's content. It's TikTok. Yeah.

It's, yeah, it's just uses this dreaded, like, content word. She just means stuff that you can do. And, you know, I think the fear is that we'd have. We live in a world where we'd have content that is serviceable often, but maybe sublime, never. You know, and that's a world of generic and age of generic. And yes, we, a lot of kind of our popular culture is things that are already kind of generic things, but right now the generic things are still made by humans. Right.

Right? But like, yeah, humans can do bad work too. It is, we're just as bad as anything, yeah. Yes. But at least, like, but if we make, we have machines do all of that, how does that change the truly, like, sublime, the truly expressive things that humans still do? Will that, how, I can, I don't know how we'll alter, but I can't imagine this not altering it, right?

I think, and then on this point of where this intersects with livelihood, you know, I think the fear among a lot of artists, you know, my, self-included, if I account myself as an artist, yes, part of that is that is livelihood, but it's not only livelihood. The fear isn't just that we'd be replaced by a machine. The fear is that we'd be replaced by something that is far more generic and far less interesting. But that's acceptable to the powers that be, because good enough is, it might be good enough to make someone a lot of money. Right.

Right. That's the larger fear of isn't just livelihood lost. That's a huge issue. But livelihood lost in favor of something that's actually more generic and less interesting. That seems like undesirable on like multiple levels. That maybe our standards go down far enough that we don't care anymore. Our standards go down. We don't care anymore. And also that people that motherwise have tried to, as difficult that it is, to pursue any kind of art. that they may not be room to do that anymore. Yeah. Even if someone wanted to. Well, and I think it strikes me that that comes all the way back around to the idea of how to approach these tools, right? Because I think the sort of glass-half full version of that future you just described

is that actually rather than using AI to pull everything down to this lowest common denominator, average of everything. We learn to play it like an instrument and we learn to use it to expand that Venn diagram and this whole universe of things that we can't do, but we learn how to do with this tool. Like that, if you want to paint like a beautiful future of AI, it's that sort of spirit of play that you're describing comes to everyone in all disciplines of AI. Right. Like that's, that's the hope. That's the only thing that might work. That would be nice. Except, I mean, there, but there's every reason, unfortunately, to think about the challenges to that scenario where everyone has the tools to play. One is just human nature itself, including my own, which is the kind of

playfulness we're talking about is actually an investment. Yes. Of time and effort and probably a lot of frustration and confusion. It's part of the process of doing anything, I think, worthwhile that you derive meaning from, whether there's a difficult video game or learning a new thing, or getting better at an instrument. All of these things come with its challenge or like basically climbing up to a mountain. It's like climbing the mountain. And the other challenge,

so that's one challenge is that we actually like, you know, we actually would need a supportive environment where we actually can do that, have the time and to do that, and have the will and the desire, the motivation to do that. But as we're saying,

like life is not getting easier for most people. In fact, it's kind of getting harder for most people. And I'd love for that timeline to come to pass, but it's difficult. It's increasingly a higher and higher privilege to be able to have time to do things just because. You know, that's the hard part of our reality. And it's only going to get harder. For example, like I mentioned the instrument where you use your hand and computer vision and AI to kind of track the opening and closing your hand to sing.

that needs a different way to think about AI. That needs a different human-computer interaction that is perhaps not saying get rid of prompt-based engineering. I'm saying, yes, there should be room for this other ways of working with AI that's interactively, at the very least, different and actually speaks to all these other dimensions of who we are, including our bodies, our physical bodies, but also all the things that humans are.

you know, or could be our capacities, they should be more comprehensively considered in how we do. Unfortunately, I think there's way more evidence to the contrary that AI is not headed into direction of inclusion, or rather extraction. It's as in how can we extract value from people with this thing. And it's not a tool for human well-being. It's not a tool for human flourishing.

it's a tool for maximizing profit. Which involves removing humans from loops in every possible way. And like you mentioned, all of the easy money in this space is at the middle of that Venn diagram. Like there might be other things in other places someday, but like if you want to make a lot of money right now, it's at the middle of that Venn diagram. And it's how do I take a job humans used to do and take it away from them. But you don't ask, okay, so now we have this. And if everyone actually used this thing, like email, what now? Right.

They don't think that's a cultural question that requires, but no, it's, it's, that's not being considered. And yes, I get, having been a startup co-founder, I can get that it's never, starting a business, a startup or running a business is not an easy thing. It's an exceedingly difficult thing. I've been there. And yet, I think with AI, there's an like an added dimension of, of, of, of just social accountability. Because the things you use are going to be used by people that, you are never going to meet, but whose lives that you will affect an influence? You will affect not only their lives,

and affect their communities, and affect their families, their kids. And while you may be like, well, how do I survive even to the next quarterly hurting call? Yeah, I get it. Been there,

but I think there's an added dimension of, I think, social responsibility to think, What if everyone, it's not just like, what if the things we made went awry? It's like, what are the things I make actually worked? And a lot of people used it. Then what? How does that change the very culture we're living in? I think the through line in all of these is kind of this question,

a kind of insistence to critically question what we do. And an aesthetic, social, cultural dimension, in addition to all the other dimensions that I would have mentioned. And also, another through line is play in expression. You know, can we help humans feel tools for people to feel more like themselves? That's, I think that's what play is. And I think if we can do that, I'll take those as victories. You know, if someone is playing music for the fun of it, like inside the room for no one, for no one in particular,

I think that's a win already. And I think there's things that if we just did, it actually makes. makes us, you know, in however small ways, makes us feel more ourselves. And I, that's my, I still hold out hope, if only because hope must be there, that we can use technology as a tool for perhaps above all for humans to be more themselves, to feel more of themselves. And to do that, you need to feel included, feel safe, feel free to be yourselves, and I think feel understood. You know, So that's, I think that's, that's my hope, but it's, like, gosh, there's so much work to be done and so many challenges. And that's not the way that the world is going.

But it's, it's a thing that's, I think it's worth, it's worth working towards. All right, that is it for the Vergecast today. Thank you again to Go Wong for being here. And thank you, as always, for listening. I'll put a whole bunch of links to all the stuff we talked about in the show notes, the Akarina app, all the Smule stuff, the laptop orchestra, some of the funny stuff his students have worked We'll put it all in the show notes. You should check it all out. It is weird, and I mean that in the best possible way.

Also, lots more on all of this stuff, future of music and everything else in this series at the verge.com. It's a good website. We like it. As always, if you have thoughts, questions, feelings, or other songs that you think I should learn in that Akarina app that's really cool, you can always email us at Vergecast at theverge.com, or call the hotline 866 Verge11.

If you have thoughts on anything that Guy and I talked about today, anything from this whole series, really anything at all. Call us, we love hearing from you. This show is produced by Liam James, Will Pore, and Eric Gomez. The Vergecast is a Verge production and part of the Vox Media Podcast Network. We'll be back with your regularly scheduled programming on Tuesday and Friday. The news just keeps happening, y'all. Just a lot of news, but I did manage to squeeze in a conversation about 13th century Florence for Tuesday's episode.

So that one's a fun one. We'll see you then. Rock and roll.