Jose Oros

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.

Yeah, yeah.

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.

Precisely.