Today, we are going to talk about AI, but not in the way you expect.
Today, I’m going to give creatives a solid three-point plan to beat AI in the marketplace. I’m going to explain how musicians, podcasters, authors and other artists can survive and even thrive amidst the unstoppable flood of AI generated slop we will all be forced to wade though for the foreseeable future,  And to maybe do some good in the process.
It’s taken me over a year to write the script for this episode, and like so many of my solo episodes, I originally planned on it being very different from how it turned out. But sometimes the scripts takes on a life of its own, and I have to follow it to what always ends up being a far more interesting place.
Those episodes tend to be my most popular
I hope you enjoy it.

Introduction
This is a solid three-point plan for beating AI in the marketplace. I’m going to explain how musicians, podcasters, authors and other artists can survive and even thrive amidst the unstoppable flood of AI we will be forced to wade though for the foreseeable future.

Artists, don’t kid yourself, generative AI is here to stay. There is no going back.

But there is a way forward.

This is a personal topic for me. I used to be a professional musician. I put myself though college playing in bars and clubs. I was Japan’s first professional podcaster. I also love generative AI and am excited about the amazing creative potential it promises.

I want to see all of these things thrive. AI will be fine, of course. It’s supported with practically unlimited funds and by lawmakers and industry leaders around the world.

Artists, however, could use a little help.
What exactly does AI create?
People asking if AI can create real art are asking the wrong question. Artists who need to put food on the table need to be asking what artistic needs AI meets in our economy.

With those parameters, let’s look at what exactly AI is creating, using podcasts as an example.

Google NotebookLM can take any textual input (your website’s FAQs, a press release, last quarter’s sales reports, anything) and create a convincing podcast from that input.

A male and a female voice will smoothly and professionally banter about the topic and tease the listener that they won’t believe what’s coming up, and they express broadcast-caliber levels of surprise and admiration over the most trivial bits of information.

It’s really good. NotebookLM has very high production standards.

But there is nothing really inside. After a minute or two, it’s just not that interesting to listen to — even when the input information was interesting.

This is because NotebookLM is incredibly good at imitating the structure and affect of a quality podcast. This is how all LLMs generate art, music, and video. They imitate a particular structure and affect, but the quality of the content is irrelevant.

Structure and affect are the logical and emotional cues that let us classify a work as a particular type of art.

The structure is the logical parameters; a pop song should be about three minutes long, it should have an identifiable melody. An image should be rectangular. An email should start with a greeting and end with a signature. Those kinds of things.

The affect is the emotional parameters. It refers to the emotional reaction we have to a given work. It’s the vibe. Rock and country covers of the same song will have a different affect. They will feel different.

Generative AI is successful today in those areas where structure and affect are important but quality is irrelevant.

Saying “quality is irrelevant” is not an insult or a backhanded way of saying that quality is poor.

The key fact is that AI-generated art (whether it is of high or low quality) excels in situations where quality is irrelevant, and human-generated art (whether it is of high or low quality) excels in situations where quality is relevant.

If you are an artist arguing about the quality of AI-generated art, you are having the wrong conversation.
What is art to us?
Since your future income depends on leveraging this, let’s take a closer look at how we humans interact with art, whether generated by human or machine.

AI music startups like Suno and Udio have announced that they have created hundreds of thousands of “top-40 quality” songs that include vocals and full orchestration. It’s unquestionably impressive, but if you were to ask them “Pick the best two or three, and let’s listen to them together.” it would be an utterly bizarre request.

Quality is irrelevant. There is no “best”. When Suno says they create “top-40 quality” songs they mean they can reliably produce the structure and affect of a top-40 song. All of the songs can plausibly pass for a real song. The quality of any individual song is irrelevant. The quality is not necessarily bad, it’s just not relevant.

For a human counter-example, let’s say your young friend has just put together their first garage band. They play their three best songs for you and ask what you think. You are not going to respond in terms of structure and affect. Saying something like “Wow. That sounds like a real song. I couldn’t even tell it was written by you.” would be so odd it would not even be insulting.

No, you would talk about their music in terms of quality. You might say things like “The lyrics are really clever.”, “The second song had a great groove.”, “You know, maybe you don’t really need a two-minute drum solo.” It’s not that the quality is good, it’s their first band so they are probably terrible. However, we interact with human-generated art in terms of quality. Structure and affect are mostly assumed.

Why things got so hard for artists
The real problem artists face today is that almost all commercial uses of art focus solely on structure and affect, with quality being irrelevant.

As tempting as it is to blame technology, AI did not create this rift between structure and affect on one hand and quality on they other. AI is taking advantage of culture-wide shift in how we engage with art that has been growing for about 25 years.

Unless artists stand up for themselves, it’s going to get much worse.

It’s important to understand that we all used to experience music completely differently. As a kid growing up in the 80s, if you wanted to listen to a particular song, you had to go buy the record. In addition to the friction of going to a physical store, albums cost about $10 and CDs about $15.

In today’s dollars that’s $29 for a record and $44 for a CD. For a student, that’s about the price of a six month subscription to Spotify premium. For a single album!

I’m not saying that was a better system. It was terrible in many ways. However, it forced us to interact with music in terms of quality.

After making such a major investment, you didn't just put that album on your shelf. You read the liner notes, and you listened to every track multiple times. You then got together with your friends and listened to these albums together.

You would each play your favorite tracks from the album you brought over, say what you liked about it, and everyone would talk about the music — and about all kinds of other things too.

This dynamic forced you to engage in terms of quality. Nobody cared how many albums you had. They cared about what you brought that day and the specific things you liked or disliked about it. “Listen to what he’s doing with this guitar part.” “The vocals in the second chorus are amazing.” “I think he screwed up the bass part there.”

Every kid was a music critic. Quality mattered. The music was not necessarily better quality, but engagement with music focused on quality.

Some of my Gen Z friends have told me they would consider that situation horrifying. “Why would I want to sit around and be forced to listen to other people’s bad music and having to make some kind of presentation about why I like my music? Why not just let everyone listen to the music they enjoy?”

Yeah. I get that.

Being immersed in music in your headphones is pretty awesome too. Those music sharing sessions got annoying sometimes. You had to sit though some bad music occasionally, and there was always that one jerk who would jump up saying “We have to hear that guitar solo one more time!”

I was that jerk on many occasions.

So, my Millennial and Gen Z readers, I’m absolutely not saying this was a better way to listen to music. I might get nostalgic about it, but I don’t listen to music this way any more. (Although, perhaps I should.) However, these constraints, as annoying as they could be, forced previous generations to engage with music very differently.

They forced listeners to consider and commit and engage with music in terms of quality. This is why every Boomer, Gen X kid, and all but the youngest Millennials will longingly tell you about the first album they ever bought with their own money. (Kansas, Point of Know Return)

 
When things got so hard for artists
Things began to change in the early 2000’s. Many blame the streaming services and the super-abundance of music they brought, but the change is deeper and more pervasive.

About that time, structure and affect started to get locked down across most mainstream culture from music to books to movies. This lock-in has nothing to do with AI, but it has set the stage for AI dominance of artistic output.

If you listen to the Spotify top ten, perhaps a third of the songs would not have sounded out of place if they hsd been released in the 80s or 90s.

This is unprecedented. The hits from the 80s sound nothing like the hits of the 40s. The hits from the 70s sound nothing like music from the 30s. Since the beginning of recorded music, every decade of popular music had a unique feel. A unique vibe. A unique affect.

Until now.

As an aside, I feel kind of cheated here.