For two decades, the economics of the open web rested on a simple bargain: platforms indexed content, publishers got traffic, and monetization happened downstream. AI breaks that loop by delivering answers without the click.

This week, I’m joined by Doug Leeds, former head of IAC Publishing and now CEO of RSL, to unpack what comes next. We talk about why the old traffic-for-content deal is collapsing, why pay-per-crawl is a dead end, and how collective licensing could create a new economic layer for publishers and creators. A conversation about leverage, incentives, and whether the web can adapt to AI without losing the ability to fund original work

This week's episode of the Rebooting Show is

brought to you by Beehiiv.

I wanna tell you about something I think a lot of you will find useful

when you are running a media business.

Email is often the backbone, and getting it right is unfortunately,

usually harder than it should be.

Trust me, I know this and that's why I've been so impressed with Beehiiv.

This is a platform that was built by the people who scaled morning

brew to millions of readers.

and they created the platform that they wish they had, when they were

just starting out as publishers.

so it's no surprise that companies like Time and the Texas Tribune are already

running their newsletters on Beehiiv.

It is designed for serious media operators, not marketers, bolting

on a newsletter as an afterthought.

And here's the thing.

If you're running a publication with more than a hundred thousand

subscribers, Beehiiv is built for you.

Their team has scaled newsletters at places like the information

puck and Morning Brew, and they understand the challenges.

Big publishers face from seamless migration to enterprise grade

deliverability and monetization.

Beehiiv makes it easy to grow, retain, and engage audiences, at serious scale.

If you wanna see what your next stage of growth could look like,

go to Beehiiv.com backslash TRB.

That is B-E-E-H-I-I-V.com/TRB.

And you can meet with Beehiiv's team of growth and newsletter experts today.

Again, that is Beehiiv.com/trb.

Thank you to Beehiiv.

Welcome to the Rebooting Show.

I am Brian Morrisey.

I'm joined this week by Doug Leeds.

Doug, used to run IAC publishing for many years.

He's a, he's a, a veteran of digital media.

That's what, that's what we say, Doug.

If someone's got gray hair, we say, I, I, I'm like, I'm a veteran,

seasoned veteran, that kind of

I'll take gray hair.

Yeah, exactly.

but Doug is now the CEO of RSL.

Okay.

Really simple licensing, which is an effort to address what might be

the definitive shift of our time in digital media, which is the rise of

these AI systems that ingest, all kinds of content, including publisher

content, obviously at massive scale, and return answers, to people.

which one of Doug's.

Former companies ask, formerly known as Ask Gs, promise to do, but

AI wasn't quite where it is now.

Right.

Like still the idea was completely right on.

so basically RSL is a, and Doug's gonna correct me if I get this wrong.

It is a, a standard, the Let's publisher set.

The licensing terms and prices for how AI systems can crawl and use their content.

it is basically an extension.

Of the logic of robots txt.

where, you know, robots txt was the little code that you could

put on webpages and told, search engines don't crawl this stuff.

I, once a developer once put it on every single page of ours at a company,

at a publishing company I worked with.

We couldn't understand why our search traffic had collapsed.

That was the reason.

So it's a very important, part of the open web and the history

of the open web, which we will.

Get into, but this is all part of a. Challenge, obviously that's out there.

And then there's different attempts to try to come up with a new economic

model basically for the open web and, and publishing because the old,

bargain was you can crawl our content.

You can take snippets of it and publish it, but you're gonna

send traffic back to, to us.

And Google was, was the biggest source of that traffic.

you know, they were gonna monetize it through ads and Google controlled the

ad system, so it was an uneasy bargain.

People complained every now and again, everyone likes to complain about

the landlord, but you know, overall.

I think it worked.

and what we have now doesn't work.

So, you know, the question is what is gonna replace it?

Very happy to have you here to, to walk me through it.

Did I get anything wrong in the intro, Doug?

No, you, you just missed a piece.

Um, so I, I can supplement it,

This is why I usually do the interests, afterwards, but go on.

No, well, you, you, you got it right.

We, we, RSL is a standard, an open standard so that, you can say

what your terms are for using your content and that can go into robots,

text it, it can do more than that.

But that's originally what we, we built it for.

But we also are building on top of that a collective rights organization,

which is distinct from the, standard, which it's one articulation of the

standard and allows all the publishers and creators across the entire web to

get together and say, okay, we'll use one agreement to license our content

to AI companies, and it solves a bunch of problems, efficiency, and a whole

bunch of things, which we can get into.

I'm happy to tell you about it.

Um,

sequence though, let's get into, 'cause this stuff can get, can get wonky.

But let's start like big picture, right?

I mean, you've been in this industry for a long time.

first of all, explain the bargain that underpinned the open web.

yeah, for sure.

So, as you said, I ran a search engine, so I was familiar with that.

Ran media companies so that there was a bargain between search

and media companies, right.

Or anybody to say you can use.

You can access my content in the search case, you can crawl my content and index

it, in exchange for giving me traffic when someone might be interested in that.

and Google gives, you had all, was, all they gave you was a list of,

of links, that were relevant to your search and you would go there.

I'm describing search.

Everyone knows what search is.

and find the content on the page.

So that's what the, the, the bargain was.

You can take my content and use it for the purposes of giving me back traffic.

When you determine that a user is interested in what I have, that.

Has gone away or is going away rapidly, with a better product, which is ai.

I don't have to search on a page for what I'm looking for.

I don't have to search on the Google website for what's the

right content to click on.

I don't have to search when I get to the website about what content do

I did I want, was I interested in?

It just gives me the answer.

And you're absolutely right.

That was the idea of chiefs was just give me the answer.

and this is

snippets.

What was it?

Smart snippets.

smart answers.

Smart answers.

See I go way back, Doug.

Wow.

I'm season two.

That's not a lot of people remember smart answers, but that's great.

which actually started with a, with with actually a, a room full

of people writing smart answers.

and

there wasn't a lot of AI behind the smart

but there was no AI at that time.

Exactly.

so that bargain of like, okay, we'll use some of your content.

We'll be an intermediary and we'll tell people which is the most relevant, but

then you get the traffic and you can monetize it, as you said, with ads,

but with subscriptions, with commerce, lots of ways to monetize traffic.

When humans come to your site, that is going away 'cause you get what

you need at the AI interface and you don't end up going to the source of

the traffic and because you're not going there, they can't monetize you.

you're

That's the problem.

Right now that, so the situation right now is, that's

fundamentally broken because obviously publishers are seeing less traffic.

Some of that is AI related.

Some of that is just Google.

Google has been changing more rapidly in the last several years than it had been.

It, it became less reliable.

I used to.

I used to joke with, I used to tell Neil Vogel, I'm like, ah, you don't

wanna be dependent on any algorithm.

He is like, yeah, but this is the most, if you're gonna be dependent on

one, this is back in the Facebook era.

He goes, you want to be dependent on this one.

and now it's less reliable.

Some publishers are seeing, you know, really significant, have seen really

significant declines in traffic.

And the question.

Question is what replaces it.

Now, I've talked with, CloudFlare on this podcast.

I don't think I've had toll bit on, but there's different ideas floating

around and, and these are not, give, give me your overview of the sort of

landscape of concepts and companies that are looking to address this issue.

And I don't think, they're not like all opposed there, there, there's,

there's, they kind of all can are, are part of the same ecosystem.

that's right.

In fact, a CloudFlare is a supporter of ours, and we're working closely with them.

there is CDN for

those who to do not catch that.

And that's a, that is a critical piece of technology that basically compresses

and a lot of, basically a lot handles all the traffic for, for the internet.

I mean, CloudFlare doesn't handle all the traffic.

It's one of a few CDNs, but it is a leading CDN

It's leading CDN and they're working with us as is, their competitors.

Akamai and Fastly.

Yeah, exactly.

to, and we'll get into this I think, a little bit.

your question was, what are the models out there?

and there are a bunch of models out there.

you mentioned Tobe, and CloudFlare also has a sort of like, we'll block you and

then we'll charge you to enter the site.

and it's like

a common paper crawl.

And, and it's blunt, the way I understand is it's blunt.

Like, I mean, search worked because, you know, the, the

click prices were all different.

but this is just, you know, it's, it's setting like one price.

Well, it could be setting one price.

It doesn't necessarily have to be setting one price, but you start getting into a

lot of difficulty if in setting prices, look, setting prices is one of the

biggest difficulties with with Paper crawl because imagine yourself as an AI

company and you're like, I don't know.

Whether the content on your site is gonna give me value or not until I crawl

it and determine if it's useful to me.

So what price am I willing to pay before I know what content I'm gonna get?

Very low.

Right?

At that point, I don't know what's there, so I don't know how valuable it is.

So I'm only gonna pay you a little bit until I figure it out.

the publisher side, once you crawl, you have my access to my content.

You can use it a million billion times.

So if you're talking about from a publisher side, I want

that price to be very high.

You're gonna crawl me and I don't know what you're gonna use it for.

How often?

I think it's very valuable if I'm proven right, if I price it

where you want me to price it, I'm gonna get almost nothing for it.

So there's this, this in.

Balance in the marketplace in pricing for paper crawl and you called it out.

Exactly.

That is the problem with paper crawl.

especially for, types of media where you're not crawling it all the time, like

constantly like update, update, update.

Like New York Times, it's a little bit better.

There's other parts of New York Times, but just for like the, the top news

in New York Times, I'm gonna crawl it every day, every day, every day.

I know the value of that.

Okay.

Paper crawl might work, but for something like the Atlantic.

you crawl it when they have a story like Signal Gate, which is like a

feature film coming out, lots of effort put into that huge amounts of cost.

You crawl it once and you have all the content and that's

the only time you have to pay.

It doesn't make a lot of sense and doesn't pay for the investigative

journalism that went into that story.

So what we're doing is a totally different model under the RSL

collective, what we're doing.

Very much.

And Stephanie at, at your CloudFare conversation.

Had this conversation with you, which was really interesting

about how the world works.

and, and sort of the Spotify model.

When Spotify uses content, they pay for it using a collective rights organization

called ascap or BMI or others.

they pay one blanket fee and then the collective management organization

distributes that money based on how the content was used and when it was used.

So basically, 'cause it's music, it's easy to describe when your song gets played.

You as a musician or a rights holder, get paid, and that's what we're talking about.

When your content gets used in a result, in a response, then the

content owner rights holder would get paid, and at that point, it's much

easier to determine what the value is of it because it's being used.

It's delivering value.

You don't get paid by Spotify when you upload your song.

You get paid by Spotify when your song gets played.

Yeah.

One thing I would just push on on that is, that example, I mean, it's a song, right?

That, that is being played.

It's that it's the exact song.

And I just know, I mean, we're both seasoned, right?

Which means we have gray hairs.

a lot of parts of this industry ha, have, have run on plausible deniability.

all of ad tech, as far as I can tell, runs un plausible deniability,

and there, and AI has baked into it a plausible deniability.

That they're mixing all kinds of different stuff in there and

they're saying, oh, well, I mean we're using, who knows what it is?

It, it's not really playing a song, it's more like it's listening to a song and

then it's like humming a song based on a song, all the songs it listened to, and,

and then they say, well, it's impossible.

Then you sort of throw their hands up in the air and walk away with

Well, there's a couple things that I'd love to dig into that you just

mentioned that I think, Are interesting to talk about in this context.

All right.

One is, they're mixing it all together.

Let's just talk about that for a second.

They're mixing it all together.

Absolutely.

They're doing that and they're doing that, a lot of times because they don't

have the rights to not do that, they don't have the rights to the content.

They haven't licensed the content, they've crawled it.

So they believe that if they mix it all together, they have a fair use

argument to not have to pay for it.

I'll put aside the legal argument for a second.

We'll come back to it, I'm sure.

Right now the idea is they mix it all together because they,

'cause they're not paying for it.

So what happens when they mix it all together, one is they spend an

enormous amount of money to do that.

It's, if you wanna just like look up what, what Sam Altman said that OpenAI pays.

Just to respond to the words please, and thank you.

It's astounding when you talk about what it takes to actually

mix up all this content.

it's in the billions of dollars.

So they're spending a lot of money to mix up all the content.

Why are they doing that instead of, oh, by the way, John Roberts, who

works for Neil Vocal at People Inc. Who's brilliant on this stuff, had

a great analogy I heard recently.

He's like, when if you get a recipe that's all mixed up, what you get

out of that is food poisoning.

and, and that really is the

Well, he is got, he is, he is got a lot of recipe

He does have a lot of

protect.

So, but yes, I understand.

John's

Dr. John.

Dr. John's point.

Yes.

Dr. John Roberts.

Yes, he's, he's amazing.

but the, the, I think the point is well taken, which is, that's

where you get hallucinations.

That's where you get misinformation.

That's where you get the problems with AI, is because they're mixing it all up.

Now, if you ask them.

Courts have done, why aren't you licensing this content so

you don't have that problem?

They say literally in the pleadings, in the court documents, we are not doing it

because it's not possible to license from hundreds of thousands of different places.

That is essentially the problem that we are solving because they can

now license from, we are now in a position four months after launch.

Brian, we are now positioned to represent over half of the content

that AI uses on the internet to train.

Over half of the content, they can do a deal with us and get

a, a licensed access to that.

That's game changing for them.

And, and I think that's an important point because, you know,

the music analogy, music is structured very differently from the open web.

I mean, music is, and tell me if I'm wrong here.

It's an oligopoly, basically.

I mean, Spotify can go to like, through like ASCAP or BMI, there's

just, there's a few record labels that, that control much of the

They can, but they go through the collective rights because

they get everything that way.

this is where it's a little bit difficult is that music copyrights

are, have performance rights.

They have mechanical reproduction rights.

They have a whole bunch of different rights involved in musical and they

need a bunch of these rights so they can get some of them from the labels,

but they get a bunch of them from a bunch of that, the necessary rights

from ASCAP in a collective way.

Mm-hmm.

they do that because.

We had Napster and when Napster came out right, it was the, it's

what we're experiencing now.

It's, oh my gosh, this is a better product.

I don't have to buy

It was pretty cool.

I

Right.

I mean, I was listening to a cd.

I spent $15 to get one or two songs that I liked with five

or six songs I didn't like.

And then if I wanted to play another band song, I'd have to pull the CD out,

put the CD back in, play the next song.

That was terrible.

I could make a mix tape, but that took time.

This was like, oh my gosh, this is a much better system.

A playlist.

Amazing.

All the songs digitally streaming.

Fantastic.

The problem was.

Napster wasn't paying for any of that.

They took it all and they gave it away for free, and the music industry was like,

oh my God, this is going to crush us.

Because there it removes the incentives to create music, just

like the incentives to do anything

Do you know what's interesting on that?

Just, just to say on that for a second is like, at least I remember that, is

that everyone kind of knew it was theft.

Right.

Whereas I don't, and maybe it's just because of the way that the

internet developed since then, and just maybe society or whatever.

I don't think that that is common now.

like it's, it, it, I don't think people see going to an ai, a Chacha,

BT or Gemini or anything as being like, oh, maybe in this industry.

But you know why, Brian?

It's because music and the entertainment business was founded

on licensing way before technology.

And Hillary Rosen was out there saying, you're

stealing this, like nonstop.

That helped.

And Metallica and others, they were saying it, but, but music and

entertainment, film, others was a, is a licensing business and it's

been around a hundred years and it exists as a licensing business.

You don't go into a place to listen like you do with Spotify.

Now you go to Spotify to listen to music.

That wasn't really a thing back then.

You went and bought music, you went to a store and paid for it.

It was all licensing and no technology.

And technology came and disrupted it and said, oh wait.

We have a way to distribute this now without having to purchase it all at once.

You can buy a subscription to Apple Music, you can buy a

subscription to iTunes at the time.

You can buy a subscription to Spotify.

You can get all of it at the same time.

That was new and because that was new, it was breaking this

idea of, oh, I pay for music.

The web has been open, as we talked about, and you can have anybody walk in.

There was no licensing infrastructure for the web.

It was an open model.

We call it the open web because you can go anywhere and and consume it.

The difference was that was based on humans going there and consuming it.

Humans being there, consuming it themselves led us to give them ads

or subscriptions or commerce ways.

We would monetize it without the humans getting to the content themselves.

There's no monetization and it is in fact stealing.

It is saying, oh, the way you get paid for this, just like you got

paid for buying a cd, the way you get paid for this is by having humans

come and we're taking that away.

We are basically setting up a our own store outside of your store, selling

your stuff and not paying you for that.

And that is stealing.

We, we can see it.

Courts are starting to look at it there.

There's two issues on the legal side.

I won't go too far into this.

It's can they take the content and train on it and then can they use the content

and the training on it has been this fight about whether that's fair use,

but the use of it, especially where that use undermines the value of the

original content that's infringement.

It would explain the, explain the difference between

training and use a little bit more.

So I know, I understand.

Like the, the stuff that went out the door and I mean, they're

basically these ai, it's reading, you know, that's what Lay said.

It is like a machine, a robot is reading a lot of content out there.

Every piece of content that stuff is, is gone.

It's already read everything and it's continuing to read.

But what do you mean use?

it's diff, it's different, it's slightly different points.

One's a legal thing and one's sort of like a practical thing.

I apologize to your listeners because I used to be a lawyer and so

sometimes I drift into Yes, exactly.

So, so

pull you back if you

pull me back, please, please pull me back.

But the idea behind what the arguments are about why this is fair use is that they

can take the content and just like if you went to a museum and you saw a bunch of

Picasso paintings and then you went home and painted something inspired by that.

That would be fair use.

Right?

Oh, I, I learned about Picasso.

I painted something on my own.

That's a fair use of what you saw.

That was visual.

I learned.

I trained myself on it.

I painted.

That's fine.

If you took pictures of Picasso and you distributed them.

Got sold and paid and sold, those that would undermine the value of the

original work that would be infringement.

So one thing you can do is train and learn and create new things.

What you can't do is use that to undermine the value of the original work.

And so while the arguments have happened in court that hey, training

is just like looking at a Picasso and painting my own picture.

When you do that and you create a picture that is like Picasso and you're

saying, this is as good as Picasso.

You don't need Picasso anymore 'cause I got this and you, and

then you don't buy Picasso anymore.

That's infringement.

Does that help?

no, that's, that, that, that helps quite a bit.

So how does, so explain then RSL and how it, it will address this?

'cause RSL, as I said, it's, it's an outgrowth of RSS, which was a

foundational technology something.

There's a lot of RSS truthers out there who are like, you know what?

The web went to shit when we sort of went away from, from RSS, Google

Reader died for our sins, et cetera.

But explain the

role of Of

look, RSS is a great foundation.

Be for the web, but also for us because my co-founder, Eckert

Walter, was a co-create of RSS.

He, he created RSS back in the nineties when he was at

Netscape and brought it to Yahoo.

When he came to Yahoo.

And a lot of that it for, for good or bad, but really for good.

and for podcasts still for good.

'cause

Go ahead.

I still put, you know, you, you have a podcast, you send

the feed to lots of places.

that's right.

Exactly.

And by the way.

That's the model.

You're still using the model, right?

The model is you send your feed out and they listen to it, and then

you get paid from that listening.

'cause humans are listening to it.

And so you can have a sponsor and they can pay for an ad and they reach the listeners

and 'cause humans are consuming it.

But imagine.

Which is happening, that you've distributed your podcast.

It summarized everything and it said, here's what the podcast is.

In fact, we'll reproduce enough of it.

So you don't need to listen to the podcast and you can pay us for that.

That's just stealing.

So how do we, how do we change?

How do we change that?

Right?

The way we change that, by the way.

The reason why Google and Yahoo, I mean, and, and, and Meta and OpenAI

and all these companies are saying they're doing it this way is because,

and they've literally said this, there's no other way to use this content.

There's no way to license Hunt.

The open web was created and.

Millions, billions of webpage are out there.

How do we license everything?

It's impossible.

That's the problem we're solving.

We are saying it is now possible to license everything with one deal

because we will do one deal, one blanket license deal, and it can

be for all the content on the web.

And then if you, or if a mom blogger, or if a person who writes their

own recipe wants to participate in this, they sign up with us and

then when their content is used.

They get paid.

They get paid because let's say OpenAI pays us the licensing fee,

we look at when their content was used, and we pay them based on that.

Right.

that, does that make sense?

Yeah, a hundred

And did I answer your question?

I, I may not have

No, no, no, no.

You answered my question.

I think my next one, and we had discussed this earlier, this is

where we're going is okay, great.

Like you're kind of calling bullshit, honestly, on them because like they're

saying, oh, we'd love to pay people, but like, we don't, we can't actually do it.

Oh, that's too bad.

Like we can send like, you know, rockets to Mars and all this,

but we couldn't possibly pay for this content that we're using.

that would be too hard.

Technically.

How would we do that?

Maybe I'm a little bit, cynical about

No, I think that's a fair

I think it's a well or earned skepticism.

So let's just assume this is not a technical problem.

Right.

Then you run into.

Where's the leverage?

You know, like Dr. John's, Bo boss, I had a conversation with

him, I think it was in, in Cannes.

We did a podcast and he's like, you have to establish leverage to get them to move.

And right now we don't have leverage and we have to establish that leverage because

it isn't necessarily a technical problem.

They seem like they have plenty of money.

We can discuss how much money would go to, to, to publishers.

I'm sure there'll be a difference of opinion on that, but it's more than zero.

it comes down to where is the leverage?

What, why, why are they not beating down your doors to, to

license, the open webs content.

Well, I, I, I'm not in a position to tell you what those doors look like

and how open they are at this moment, but let me answer the rest of the questions.

So yes, you can call BS on their arguments.

and we've talked about a couple.

One is we can't license it efficiently and that's a problem.

We've talked about another one, which is that, That they ung all

this stuff up for the purposes of fair use, but it gives them bad

quality and it costs a lot of money.

So you, you would think that they have incentives,

but your

by the way, they're, they're using these publishers brands as citations in

their results to, to give, to give trust, and to give legitimacy to their product.

I mean, it's, it is a little, when that's started, I was

like, this is a little galling.

Yeah.

It's really going.

Okay.

So let's talk about the, that's the, the incentive system for them to do this.

from their business model is there.

But then let's talk about the enforcement mechanisms and why

you can force them to do this.

One is technical and we talked about that at the beginning, CloudFlare, Akamai

Fastly, the CDMs right now, the, the model that CloudFlare has used has been, we're

gonna block you by default, and you're not gonna, we're not gonna let you in.

And that actually has been working in some ways.

but it's very hard if you depend on things like search.

So like open AI is blocked way more than Google right now.

And the reason for that is because open AI doesn't give

you search, doesn't have search.

Right.

You understand?

So,

No, no, no.

But other people don't.

Other people don't.

so, so,

I'm sorry.

I'm just like, I forget that we're on video sometimes.

Gone.

So, so, and by the way, the EU is investigating Google for

this very thing right now, right?

So Google has said, if you don't wanna be in our AI abstracts, that thing at the top

of our search results, where we basically summarize the rest and tell you that you

don't need to go to the search results.

if you don't wanna be in that, you can't be in the search results.

So instead of separating the two different, the, instead

of having two different crawlers, they have one crawler and it's

like, you want the search traffic.

Well, guess what?

We're gonna take your content and we're gonna use it for the AI overviews.

exactly.

And the EU is investing in them, and I'm under very good, authority

knowledge to know that they're not the only ones investigating them for this.

and because they're,

seems, this seems like an issue that EU would, would, would feel

Yes, they have monopoly power or market power anyway in search, and

they're using that to get into ai.

but to your point, okay, that means it's very hard to, to block them,

without giving them a way to come in.

So that's the first thing.

There's a technical blocking.

That's great.

one more legal thing for you, just so you hear this very quickly.

Ziff Davis, one of our partners sued OpenAI.

in December, the court ruled on their, their lawsuit and upheld a bunch of their,

this is at a preliminary stage, so just can the, can the suit go forward or not?

And the court said, for the most part, yes, but one of the ways they said no

was under something called the DMCA, the Digital Millennium Copyright Act.

And that in order to pursue the claim under the DMCA, they had to show that

there was technically enforced, that they were creating basically a lock,

and that lock was broken and the court said, there is no lock that's broken.

Just putting yourself saying that you can't crawl me is not enough.

You actually have to take technical enforcement measures to do that.

So the reason why that's.

It's great for Z Davis to have all the claims go forward

and they don't need that one.

But the nice thing about the MCA is if you take advantage of that,

you don't have to prove fair use.

It doesn't matter if there's fair use.

That's not a defense.

If you broke someone's lock, it doesn't matter what you do with the information.

Once you took it, you broke it, you broke in, you're liable.

So all the little guys in the world could use DMCA against the search engines

or the AI companies very effectively.

If there was a technical needs.

To, to stop them.

CDNs provide that lock, but they don't provide a key to open it.

So it's very hard to say, okay, I'm gonna stop you from coming here it

without saying unless you do something.

And that's what RSL provides.

They say, okay, here are the terms for which you can unlock this gate.

And when you have that, then you can put the lock on your gate.

And if someone breaks it or circumvents it, you have access to a legal enforcement

regime that's much cheaper than currently.

Only the big players have access to only the New York Times and Ziff

Davis and others that are going

Right.

Yeah.

And that's the other thing is like how do you solve this

at at scale of the open web?

Because the New York Times has leverage.

They have, you know, for sure.

Ziff might have some leverage.

You know, the Atlantic has leverage, but like regular

publishers or just individuals even, do not have any leverage.

And that's why by the way, these giant tech companies love creator economy stuff.

They would relay love the idea of like, oh, how are we gonna negotiate with

10 million tens of millions of people versus like, you know, a small number of

Well, and, and, and this is actually exactly why collective

management organizations were created in the first place.

This is why this was back 110 years ago, radio mu recorded music was invented.

and radio said.

Radio was invented too, and said, we can play that recorded music, but

we don't have the rights to do it.

How do we negotiate with all these people?

And so collective management organizations said, we will give you an

efficient way of doing that, efficient way of getting all this together.

And if you don't do it, then you have to go license for all these other people.

So we're right now in the legal stage of proving that you have to go license

this with all these other people.

But once it's proven, which it will be, then how do you do it is a big problem.

And.

You can't do it with everybody without something like a collective management

organization, which is exactly what RSL and only RSL is doing right now.

and we're a nonprofit, which is a very important thing for the media industry

because you get companies like a Tolbert or others knocking on their doors

saying, Hey, we're happy to help you do this, and we're only gonna take 30,

40, 50% of your revenue to do that.

and, you know, media companies are, look, if I was running a media company like I

did once, I'd be saying yes to everything and see what happens, but Right,

there's no, there's no harm in that.

But the idea of saying, wait, all this value that I'm creating, you're

gonna give 30 or 40 or 50% away to someone who is just blocking

somebody from getting to there.

That seems hard to believe.

I mean, publishers are already sort of, you know, I mean, they, they

felt like intermediaries have been reaching into their pockets in, in

various parts of their businesses, like ad tech, et cetera, for a long time too.

and because me and my partner, founding partner have come from that

space, we specifically sort started this and are running this as a

nonprofit so that we don't have that issue for the big publishing companies

and also for the entire open web.

Honestly, whoever you are creating content out there, you should get

paid and you shouldn't toss you 30% or 40% or 50% of what your value is.

It should cover our costs and the rest go to you.

And that's how ASCAP works, by the

Yeah, so just to circle back to, to the incentives.

So why are they going to come to the bargaining table?

I mean, obviously this is, these are global companies and you know,

places like Europe are, are very different than the United States.

I don't see just politically in the United States that, you know, they're,

I mean obviously the, the Trump administration is all in on AI China,

China, China will be brought out.

It's like if we, if, if we can't compete with China, and it'll get all mixed up

into, into that, what is, and I don't, I don't know if the courts will, will

force this, but do you think that the collection of these kind of pressures

will lead to some kind of grand bargain?

Yes, I absolutely do.

So, look, there's the, there's, we talked about technical enforcement, we

talked a little about legal enforcement.

You're hinting at regulatory enforcement.

even if it comes first in the eu, like why does Apple not have a lightning?

Plug anymore.

That's 'cause of the EU said we all have to have the same thing.

Right?

So they complied with that everywhere because it was efficient to apply

with that everywhere as opposed to having two different devices.

So it's okay that it's starting in the eu, because it will create

the leverage, the, the regulatory leverage to require some, some change.

But also in your Trump analogy, or your, your, not analogy, but your Trump

reference of China being the bad guys.

It's so easy to show who the bad guys are, if they're the ones who aren't

licensing content, and that's actually the difference right now and can be

the difference in the in the future.

Good AI companies, American based AI companies who value human created content

can pay for it efficiently and bad AI companies, Chinese Steelers won't.

And by the way, that's the best model for saying those guys are bad as a country.

We are blocking them.

These guys are good.

As a country or as a, as a, a federation of countries, these guys are allowed,

that crosses political aisles like.

Not, not.

And that's pro ai.

And by the way, I'm extremely pro ai.

I'm extremely pro ai.

I love to use it.

I love the future of of using it.

I have become so much more productive.

We're doing this as a nonprofit, which means we're pretty lean.

I don't think we could do a lot of what we're doing without the help of ai.

Right?

So it's a much like we talked about Napster.

It's a much better product, but it has to be a sustainable ecosystem.

If we want it to continue.

And that's my biggest point about why does AI gonna do this?

'cause they understand that.

They totally understand that if they don't pay for the content, ultimately

the content will go away and so will their value of their product.

So what is a fair, what does a fair system look like?

Right.

Like, I mean, I think about like sports leagues and, you know, they're basically,

you know, when they negotiate with, with the union, they're, they're saying,

okay, well are the, are the players gonna get 55% or the owner's gonna get 45%?

Is it gonna be 55% of the owners, 45% of the players, you know, ultimately.

There needs to be, you know, the economics in place and how do you sort that?

Because the obvious thing is, you know, publishers will set a price and,

you know, AI companies will be like, yeah, we're thinking maybe like a

third or a fifth of what you're saying.

It's, it's worth,

Yeah.

So with collective rights organizations, like you mentioned, like a, a labor

union is, is not that different 'cause you're representing everybody right?

In the labor union.

you have to come up, you have to bargain, and you have to come up

with a reasonable reason why what you're proposing makes sense.

there are three pillars of ai, right?

There's power, there's chips, and there's.

Information, and they're not paying for information right now.

So we know that what they're paying billions, tens of billions,

trillions for the rest of the stuff.

So we know it's more than what they're making now.

We know it's probably less than what publishers on their own would ask for.

So how do we figure out your question?

How do we figure out what it is?

And I'll tell you how we're doing it.

We've hired economists and we're looking at the market specifically with the

intention of being what's called Fran.

Fran is an acronym meaning fair, reasonable, and non-discriminatory.

And that is what we're looking to be.

And we are hiring economists to say, okay, how does the market work?

What is the value of it?

Look, take, take it apart again, my friend, my good friend John

Roberts, has done some of the analysis on a token value.

and it's actually very, the, the, the amount of money that pays for

all the content in the world is not.

Unlike Napster where they were giving itself away for free,

this is already being collected.

This money very close to the amount of money that it would

take to pay for all this.

It's already being collected.

So one reason I'm not saying let's just take the money that's

being collected is because I think they're underpricing AI right now.

I'll give you my

Explain that.

Why?

Why, why is that?

Because, because we're early, I, I, I mean, I we're talking about gray beards.

We've been around, we've seen plenty of this stuff.

You price low at the beginning so that you capture market share, and then you

raise your prices when you have it.

so that's the mode we're in right now.

I pay $20 a month for chat.

GPT, they raised it to a hundred dollars a month.

I pay it in a second.

There's no question.

I pay it.

Would they lose five four of their other customers if they raise it?

No, I don't think so.

But they're basically doing this because they wanna capture market share.

It's not based on the value that they're delivering.

It's based on a long-term thought of, what can I get later if I

get a bunch of customers now?

Which is fine, but that doesn't affect how much they pay for power or how

much they pay for processing, and it shouldn't affect how much they pay.

For information.

So how do we figure that out?

We hire economists and that's what we've done, and they're working on it

right now to tell us what is a fair amount so that we can say to the world

transparently and to AI companies.

This is a fair amount.

Yeah, I mean it's, Spotify pays, I believe about 70% out

I think it's higher than that.

SE seven I saw 75% or 76%.

Of course, I think I saw that through AI and it could have been

That's quite a bit, so I'm not like, you know

But that's not, but, but, but look, like I said, I'm pro ai.

So here's the pro ai, uh, AI company, LLM thing.

Spotify is like a mechanical jukebox.

That's not fair.

But like all you do is you go there and you consume.

They're not paying for, they're not adding a ton of value.

They're adding some value, but they're not adding the ton of value

that AI companies add and pay for.

So that 75% is not realistic given just the product, right?

I, I think understanding who adds what value is.

Look, I mean, I always, anytime I talk with, you know, people in, on

the programmatic side, the differences between the, what they believe the

value is that they are, they are when they enrich a, an impression

with some kind of unique data set.

Maybe it's unique, maybe it's not.

but they're claiming that.

Oh, that's transformative and you know, that is where the real value is.

And you know, the place where the ad ran is, you know, kind

of, you know, not that valuable.

There will be undoubtedly disagreements about this, but if we

go back to the music model as cap BMI, they don't represent everybody.

They represent almost everybody.

I believe Taylor Swift has her own deal.

and that makes sense and there can be your own deals in these situations,

but everybody isn't Taylor Swift.

Everybody can't get, Hey, I need my own deal type of negotiation.

They just won't do the deal.

So we have to have a fair and reasonable economic basis for

charging for all the content.

Even if it's not all the content.

It's all the content.

But the Taylor Swift version of the content.

Yeah.

So when you think back, could this like end up making the web less ad reliant?

Oh yeah.

We we're going that way.

Because you've been in ad businesses and there's pluses and

minuses to being in ad driven models, and there are a lot of minuses,

there's a lot of trade offs, and we all see it when we experience the web.

and, and the

hard to think of anybody who's gone into an ad business where a subscription

business would've given 'em the same.

Revenue portfolio.

Usually the ad business is taken up because there's a trade off.

I give you my content for free.

You look at ad, doesn't cost you any money to do that, so I make more money.

You make more money.

Right.

All that makes sense.

The question is, it's not that ads are gonna go away, and we've seen this already

with perplexity, which is talking about ads or prorata, which is talking about ads

or open ai, which is talking about ads.

It's just where do those ads live?

They live where the humor humans.

I dunno what humor is, where the humans interact with content and

when the humans stop interacting with content, or do so less on the publisher

side and do so more on the AI side, that's where the ads are gonna go.

Just like there's ads and versions of Spotify, there are ads and versions of

Spotify, that's fine, but where does, how do the musicians get paid for those ads?

They get it through a licensing deal as opposed to hosting their own advertising.

Right.

But I think it seems like, like publishers, and I've talked with John

about this, like what, like they'll end up having a larger licensing.

I mean, you see it, right?

Even in people links

of results now their, their licensing line is, is, is much

different than it was a year ago.

And and I wonder how that changes when, when publishers start to

operate, like, almost like wholesale businesses and retail businesses.

Businesses, it's not like they don't have licensing and

there's different forms of it.

Look, look, look at the entertainment business

we just talked about.

Like music is all licensing.

You still know who Taylor Swift is, even though she makes her money from licensing.

That's how

Well, she makes, she makes her money from, from her touring.

I think that's what a lot of publishers are gonna be doing.

You know,

you're

know this from the B2B

world, like

right.

You're absolutely right.

I always compared like being a publisher, it's like.

You know, being a musician, it's like your recorded music, you know, is

not, it used to be, oh, you could go into the, the studio and cut an album

and then like, make a ton of money.

And now you look at the, the Oasis tours, you know, they gotta be

out there touring and you know, the, it's not like the albums do

a job, it's just a different job.

And I think

Yeah, and there is a, there, there's some bad parts of the analogy,

and this is one of those because, because the rights have been so fractured in

music and because as you said, there's an oligopoly in the labels and take a

lot of the value, a lot of it doesn't go downstream to the musicians themselves.

We don't have that structure in publishing actually, so there's much more

likelihood that licensing value goes from.

The place where the value is created, like an open AI to the place where the value

is produced, like People Inc. That there, there's gonna be less intermediaries

in there in our model, in, in our, in our industry than there is in music.

What would be the what if you had to make it, obviously you're, you're,

you're, you're giving the bull case.

Put yourself in the other side, like what would the bear case be for a, a fair in

quotes, like workable solution coming.

Well, I think it depends on who you are and how, how valuable your content is.

And let's just look at past evolutions.

the, and I think we just saw that the pi, the Pittsburgh Post, Gazette, thank

you, Pittsburgh Post Gazette just folded.

Would that have happened 40 years ago?

Heck no.

Right?

Because you needed local news, and the way you got local news was by buying a

newspaper, you had to buy it locally.

And now with distribution being, oh, I can get most of that news

online, the very hyper local.

Has a different use case.

It used to be like, for newspapers, I've talked with a bunch of

newspapers about this, a bunch who are supporting us like, USA today.

it used to be that the ad, the ad model for newspapers was,

is there a big mall in town?

Because they're gonna supply all the ads.

What are classified, what happens with M?

Okay, classifieds a big ad source and all that changes.

And so those who become over reliant on a. monetary system that is going

to evolve are not going to make it.

And the bear case, I would say, is not for the industry, but for some actors

in the industry that don't evolve.

Right.

And I would think like, look, everyone follows incentives, right?

And the incentives of.

The ad driven model, particularly when platforms had a choke hold

on distribution, was to chase algorithms with some fairly

undifferentiated content, right?

If you're a, a Google quote unquote Google discoverer publisher, look, a lot

of your stuff is not that unique really.

It's like, it's, it's, it's trying to get.

Front of the line and Google sends a bunch of traffic to you.

It might bounce real quick, but like, you know, you'll put

a lot of ads in front of them.

I think when you get into a licensing context, I would think the, the

incentive shift, I mean, I think like in the best case scenario,

the incentive shift to create unique, valuable, essential content.

Whereas the last system, the way a lot of people operated within

it, not all, but a lot was.

Really focused on just trying to get the piece of content to get picked up by the

algorithm in some way.

The algorithm was a, what the algorithm was was a way to try and

determine what content was best.

That's what the algorithm was, right?

And then you, once you say, here are the rules for determining what content is best

and I only want the best content, then everyone who makes content says, okay,

I'm gonna understand what those rules are and I'm going to optimize for those rules.

So I bought about.com.

And that's when I hired Neil Vogel to be the CEO of the business

that's now People Inc. Right?

To run that business.

That business was based on a version of page rank that soon went away,

which is why Neil evolved the company.

but that was, Hey, if you have one giant storefront of all the

content you could possibly want.

Google thinks that's more valuable, page rank is higher.

So about.com was, was formed under the idea of will be about everything and

therefore all the content lives here.

And page rank gives us, says we're our, their algorithm says we're more valuable

because of that, so that's how we're gonna operate when they change their algorithm

and said, you know what, that's stupid.

And I agree.

All the, the best content doesn't live in one place.

The best content lives in different places like.

Then, and Neil and I, it was there and I'm running it at the time, but

it was Neil and his team's ideas.

Let's break this apart.

We have really good content.

Instead of putting it all in one place, let's put it in very well.

I bought Investopedia.

Let's put it in, the balance.

Let's put it in spruce.

Let's put it in these brands, because the algorithm then says that's the

better place when we got to social media.

It started to be shares.

Shares were the way to see if your content was valuable.

The more shares you had, the more the algorithm said your

content is high quality.

So what happened?

Click bait.

Okay.

If I wanna share, or if I'm gonna get you in there, I'm gonna say

something provocative to get you in there to share it out, right?

So this is time and time over again.

All the way back from town criers reading headlines out.

When you say, what is the algorithm for what is valuable content, content

producers will produce to that algorithm.

That's not necessarily a bad thing.

The thing is, this is where technology disruption comes from, that someone says,

I have a better idea for an algorithm.

This isn't as good as it could be if we did something else.

And if it's right, then the world adapts.

And that is what we're seeing.

It could in some ways, like reward a different type of publisher

disproportionately to than the last, I mean, 'cause like you mentioned,

like, you know, the, the brands like breaking apart, about into the brands.

I mean, a lot of those, a lot of the brands, I mean, I had said this to

Neil, like, you know, at the time they were kind of like minimally plausible.

Like, I mean, they were plausible within a search context.

It was like, oh, very well, but very well didn't, I mean that's, I assume

why, why, you know, Meredith was, was purchased because those brands

had more resonance beyond a nice logo, but no history or anything.

Nobody had like independently known of them necessarily.

Not nobody,

Yeah, no, the business did so much better when we went from about

to very well, so much better and better when you have better brands.

So we all, that is right.

All that is describing the same thing, which is an evolution of

what is the algorithm valuing and then content producers going after.

Whatever the algorithm, I, I'm saying it like it's some bestowed upon from high,

like, but what it is, is, is is technology people or others saying, I have an idea

or I have a process that can make you get better content than the old idea.

And it's embodied it in algorithm and if people agree with it, because

it is actually better than content producers produce to it, and there will

be winners and losers along the way.

There's no question there'll be winners and losers along the way.

So RSL will include individuals too.

A hundred percent.

This is about the entire web and making sure that, again, like ask him,

like it doesn't matter who you are.

If your content is used, then it provides value and you should

reap the rewards of that value.

Right, because like, you know, if it's, if it becomes just a, a,

you know, a negotiation, one-on-one negotiation, I'm like, I can't negotiate.

I mean, maybe I can, but like, I don't think I can negotiate with open ai.

But like a New York Times can.

Wikipedia is one of our partners, which we haven't actually announced yet.

So hey, we're all, Wikipedia is one of our partners, which is cool.

They, today, I think I read about today in the last four eight

hours, did some ideals, right?

They were saying that even Wikipedia wasn't getting their

phone call answered for a long time.

Wikipedia, which is like the heart of where these things are

being trained on, weren't getting their phone calls, the sort

Yeah.

Sip.

No, no, I was just sort of saying there is the problem of when you start

getting, if Wikipedia isn't, it's not surprising that if Brian Morrissey

wanted to it, it wouldn't be as easy.

Or if you are, a recipe blogger or if you're a creator or an influencer,

that your content might not get a call saying, Hey, do a one off deal.

Someone has to represent that in a collective way so that there's a efficient

process for getting your content into ai.

Last thing is, and tell me if I'm wrong on this,

Google, this is the big one.

Like when if, when Google will move to.

some kind of economic model.

It could be this, that, that rewards, you know, publishers

because again, Google was the hedge.

It still is the hegemon of the open web.

They determined where the traffic goes and, and it was a really difficult job.

It was difficult to balance all the different constituencies.

They did fine for themselves as well.

They should.

They came up with a great search engine, no offense to ask chiefs.

No, no, none taken All

Okay.

And, but, you know, they have it and they, they ha like, and that is like a glaring,

that's a glaring piece of information, I feel like, what is it gonna cause Google

look.

It's happening already.

Um, Ricardo Terzi, I believe his last name is pronounced, but I could have

it wrong, is the head of business development for Google in Southern Europe.

He wrote just last month a post saying, RSL is the future.

head of Google Business Development in Europe said, RSLs the future.

Like they know that this is offering them.

Now, I don't, I can't say he was saying this for himself or

whether he was saying it for

Yeah, Google's a big company, so you know,

I'm not sure if Ricardo, it goes right to.

Right?

But, but what I'm saying is, is that it is making its way inside of Google to

say, okay, if we're talking about how do we become a sustainable value add

product, we have the value add product.

It.

We have to get to sustainability and if we simply just take the content,

it's not gonna be sustainable.

'cause the content won't survive.

It just won't work.

And if we try to license from everybody individually, because we don't wanna just

take the content 'cause it won't survive, it costs way more than the billions

of dollars to actually process it.

In having individual deals with every single producer and creator, the way to

solve this is the way it's been solved for hundreds, not hundreds, but over a

hundred years, which is with a collective.

Rights organizational structure.

That's the way to solve it efficiently gets people the content they need to be

able to have it a sustainable ecosystem.

It's really the only way.

Awesome.

this has been awesome, Doug.

Thank you for, for this.

you'll have to come back next year.

I was just doing a little, little Google, I admit I use Google, not

ask, but like next year is the 30th anniversary of the start of Ask Gee.

So like, we should have like a reunion bring back different characters.

Wouldn't that be fun?

I would.

I would love it.

All right.

Thanks so much.

Brian.

Thank you so much.

It's a lot of fun.

Appreciate it.