Chapter 1: What is the main topic discussed in this episode?
We're here because your heightened awareness deserves heightened entertainment. The Last Show with David Cooper.
AI can now write music with you. You type in a few words and boom, an AI-assisted breakup ballad plays. But can it feel that breakup? You know what I mean. Can AI-assisted music be deeply creative right now? More creative than a person writing that song alone? Researchers say algorithms are getting better at music, yet humans writing music alone still beat them out creatively.
So if that's the case, what exactly makes a song still sound human? I am here with someone who has researched just this.
Chapter 2: How can AI assist in writing music?
He's an information systems researcher at Carnegie Mellon University. His name is Jose Oros. Jose, welcome to the show. Hi, David. Excited to be here. Let's talk about your study, AI.
writing music with people it sounds less creative to the average ear what exactly did you find what exactly did you research so um in our study as you as you mentioned uh we're very interested in understanding how this new tools that can create very sophisticated human art like um
Chapter 3: Can AI-generated music convey human emotions?
do they actually are able to be leveraged by musicians in a way that expand their ideas, expand their horizon of creation? So what we do in this study is we pretty much give access to a group of participants that have musical training and have piano experience. We ask them to come in and create music with the aid of AI. And we're very curious to see then, OK, what's going to happen?
Is the music going to look different from what a human alone would do? Is the music going to be more creative? Is it going to have different elements? So that's what we're studying.
So what did you end up finding?
Chapter 4: What does research say about AI's creativity in music?
Was the AI-assisted music more enjoyable, less enjoyable, more creative, less creative?
So before I answer that question, I want to just think about, OK, if we think about how these type of systems help or not, in a way, when we think about these generative AI systems, It's basically, you know, when you have this, it's an idea machine, right? You can just query it. You can create things, you know, very quickly with a lot of speed.
So in a way, you can think that you're going to have access to these tools and you're going to find that they, you know, give you a lot of ideas that you can leverage and that should increase your creativity, right?
Yeah, you would think an algorithm with access to the entire history of music would help you make something deeply creative, right?
Precisely. But there's also this other concept of fixation, right? And it's studied on the literature and the psychology literature for a long time. But what this tells you is that, basically, these algorithms, such as the ChatGPT, or specifically the one we're looking at is a text-to-music algorithm. these algorithms tend to produce something that's very probable or high probable patterns.
So if you think about how these algorithms produce these patterns, the thing that they're going to produce is going to be highly probable. In the literature, you see that when people listen to these kind of exemplars, then you're going to see that there's a fixation effect. What does this mean?
Well, if you're looking at an example, then your search on alternatives, specifically in this case for music, is going to be around that exemplar. So it's hard to get away from that.
And if the exampler itself is something that comes from a high probability, something that's very common, something very average, then it is likely that what you end up producing is going to be very around that average.
MARK MANDELMANN, And for me, a lot of the hype around AI is increased productivity. But music isn't like a spreadsheet that you're trying to fill out efficiently. Music is something you're trying to do that's deeply creative. Is that the reason like AI is really good at kind of doing these productive, efficient, common flows and it doesn't sort of think outside the box, so to speak?
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Chapter 5: How do musicians perceive AI-assisted music creation?
It's a very likely reason that we are seeing these kind of patterns. And as you say, you know, there's a lot of research around AI right now. There's a lot of research trying to find like you know, how can we grow productivity? But the creation of music and art itself is something that is uniquely human, right? And, you know, at least that's how we think about it right now, right?
So it raises a lot of questions around, like, even if these technologies are able to replicate human art to some extent, you know, will creators adopt it? You know, how much, you know, will consumers accept it? So... So yeah, I think there's a lot of questions that are raised when we're trying to use these systems in a specific context, such as human.
And that's where we are very interested in understanding if it actually affects creativity.
So did you end up giving what was generated by these musicians to people to listen to what they created to kind of compare the two results?
Precisely. So our experiment had two steps, basically, or two main parts. So the first part was getting actual results musically trained people into our lab and getting them to create a melody. So the first part was, OK, we're going to ask you to come in. You're going to play this piano. We give them 30 minutes to work on a melody.
And then we ask randomly to a set of these participants to access a tool that's called Urio, which is a text to music So think about it as like a chat GPT, but instead of giving you text, you input a prompt like I want a song in the style of a rock anthem of the 80s and it's going to produce it in like 30 seconds.
And then what we're asking them to do is to use these outputs of this tool as ideas that they can then incorporate and create their melodies. So that was like the first part of our experiment where we have around 140 people come into our lab, create the melodies. Some of them were assisted by the AI.
And then once we have the melodies, then we can move forward to that next step that is asking people, what do you think about it? And specifically, how creative you think this is.
And what did people end up saying listening to the two examples, AI-assisted versus purely human?
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Chapter 6: What were the findings on the creativity of AI-assisted music?
Thank you so much for being on the show. Thank you so much, David. Jose Oros is an information systems researcher at Carnegie Mellon University.