The 3 AI Rights No One Told Creators About

All right, welcome back to Tuesday. Today I have trip Adler co founder of scripts 16 years as CEO and now building created by humans, a company trying to make AI companies actually pay for the books they train on. Did I say right?

Great to be here today. What's that?

Did I say it right?

Bye then.

my intro hopefully ⁓ intro

⁓ it's fine. I you want to record at this point, I guess. ⁓ Yeah, I mean, I mean, yeah, the first company is called Scribd. ⁓ New company is called Created by Humans. ⁓ Scribd, yeah, that's what we say. Yeah. If you want, can lead with Created by Humans. That's what I want to try to lead with, you know, that's our focus things on.

My bad script script. Okay. Let me just read that. Okay. Okay. Okay. I'll just say it one more time. Co-founder of script. And I'll replace that. Yeah. Trip, welcome.

Great to be here today.

Yeah, I don't think I can do you justice by giving this LinkedIn headline version of you. Do you have a version that's not on LinkedIn?

A version of my background.

Yeah, who you are.

⁓ I'm, ⁓ there's probably a bunch of them online. ⁓ I'm happy to also create one and share it with you if that would be easiest. Yeah.

Whatever you can tell us about you, that's not online.

Oh, you want me to share some new facts? Just fun facts, like any direction.

New facts, facts, whatever you want to, you can share. Any direction.

Well, I'd say I have a really fun new hobby, ⁓ is called jetboarding. It's basically an electric surfboard with a motor, and I've been riding that a lot. ⁓ yeah, there's a company I'm an investor and advisor to called Lind, Lind Jetboards, and I'm a big power user of product. So that's been my hobby lately.

That's interesting. Yeah. Okay. Let's start with your product right now. The Created by Humans. By the way, I really like this name, Created by Humans. Such a great name. Can you?

Yeah, thank you. Yeah, we're, ⁓ we are, ⁓ you know, the company that is sticking up for, for human creativity. So we call it created by humans. And ⁓ what the company is aiming to do is we're aiming to solve copyright in the AI era. ⁓ You know, so far when, when AI came along, it felt like copyright AI were oil and water, but we, want to try to, you know, figure out the nuances of how to make the two work together. And then ultimately create a business model where rights holders can get paid for their data and AI companies can get the data they need with legal confidence. And we've been really focused on books today. We have our hands full of books. We have aspirations to do other kinds of content too, but right now we're just really focused on books and trying to make this work for books.

What's your big bad here?

⁓ well, think the big bet is that we can make, ⁓ copyright and AI coexist. you know, rather than having, ⁓ the, the, the, the, the conversation has gotten very polarized. People are either like, well, we need to like end copyright law or we need to like fully follow copyright law to the letter. And I think like we can, we can make both of those true if we just build out the right, the right model. And I think our end goal is to, is to have great AI products being created, ⁓ you know, that are powered by human data. And then also.

We just fill that in,

have a business model that keeps humans creating things.

Let's talk about news. Earlier this month, ⁓ you must know this, Encyclopedia and its Merriam-Webster subsidiary suit OpenAI for training on their copyrighted articles. And last year, Anthropics settled for 1.5 billion with authors, the largest copyright settlement in the AI era. But the court, in history, but the court is ruling that

in history. Yeah.

training on lawfully purchased book is fair use. It's only the pirated copy that were infringements. But recently Patreon CEO also called the fair use argument a bogus excuse, right? And you're sitting in the middle of all of these. When you see these headlines, I'm curious, like what is the first emotion that comes to your mind?

Well, first emotion, think is, is it just, I guess, a little bit of confusion about what's going on? I also guess I feel a little, little sad that there's so much confusion, so much conflict, because I feel like rather than there being lawsuits and confusion, we should just build out solutions that work for everyone and make everybody work together here. Yeah, there have been some, really interesting lawsuits. And mean, they're really still going on. It's still very early days. And I think there's no clear answers to all this. It is this whole, this whole idea of like, is trading fair use or not? mean,

Thank

I think it's not a black and white answer. think it's going to be very nuanced, be very case by case. And I think as each of these lawsuits play out, as each of these deals get done, they'll slowly start to kind of form kind of market standards around these things. But I think it's still, even though it's been going on for a few years, I think it's still very much up in air how this all plays out.

I mean, as a creator myself, the first thing that comes to my mind was, it's not fair. And there has to be a solution at some point, right? The fact that the court says purchase book is okay. I don't really disagree with it. I don't really agree with it. Think about like if I purchase some books and I tear off the binder and I scan them and then just do training on top of that data. If I'm a creator, I don't think it's fair. But I'm struggling here because I'm also an AI engineer. I train models, so I understand the need for good input data as well.

Yeah. Well, I think it's the input data and it's also the outputs, right? Because right now you can ask these AI models questions about books and it gives you pretty good answers that serve in many cases as a substitute for the book. So I think there's like a lot to be figured out. ⁓ The way we've approached this is we've created the concept that we call AI rights. We realized the world needed some new set of rights here to ⁓ kind of make this possible. And we've created three categories of AI rights. So the first is training rights. That's the right to use books or other human-created works in model training. The second we call reference rights, and that's the ability to use books in RAG. And then the third is one that we call transformative rights, which we think is really exciting. That's the ability to take a human-generated work and transform that using AI. ⁓ And I think in order to solve this problem, we have to build solutions and a marketplace around each three of those categories of AI rights. ⁓ And that's what we're doing.

The training rights is really training the model. So you give the data and you have the RAG reference right, which is retrieval. So search and retrieval. And in the citations in like chat interface within ChatTPT, for instance, that's a reference right. And the transformative is the generative version of it, the result.

Yep, zoop. Yep. So the, the, the, the, the reference ones are like, if you ask a question and the answer is on page 100 of a book, we would be able to reference where that answer came from. ⁓ and then also get the author paid for that happening. cause you know, maybe someone didn't actually read the book or buy the book, but if they got, you know, some information from page 100 of the book, we think they should get some, some money for that. And we think that's a big new model for the, for the book industry. And then transformative, that's really kind of early days and we think there's a lot of potential there to just take a book and then transform it using AI.

What's the biggest one of the three? Right now.

Um, so, mean, the, the two we've gotten the most traction on our reference and transform. If we've gotten less traction on training and that's just because it's so legally up, up in the air. Um, it's, like, I think when there's all these lawsuits, I think a lot of people want to just wait for these lawsuits to play out before they decide to actually, um, license training data, um, at least license training that they can get for free, um, in other ways. Um, so. For reference rights though and transformative rights, those are more clear from a copyright perspective that licensing needs to happen. So we're having more traction around those too.

How do they get caught? Right? If I'm a company building something, I don't know. I wouldn't say that this would be the first thing that I think about.

Like how did they get caught? What do mean? Like...

Right, like how do you detect that there's reference needed or there's also transformative rights is even harder to detect, right?

Yeah, well, we're trying to build the rules around this and then like the framework around it. ⁓ Yeah, we actually, built all these tools to try to detect whether how data was used in training or in outputs. ⁓ We actually built some pretty cool tools internally. didn't actually, they kind of hadn't materialized the business just because we've been working on other things. But there are some technical tools we could build around this. But that's where the idea is to build kind of the framework that can get humans and AI working together in a ⁓ in a nice way and that's what we're trying to solve.

How do you think, I'm curious, how do you think the court's ruling might evolve over time, if at all? Do you think it will change? Right now it's like, know, if I buy the book, then it's okay.

Well, that was one ruling said that if they buy the book, it's okay. I think there's going to be many more rulings and each one's going to be a different outcome. ⁓ So I think it's really still up in the air. ⁓ yeah, the anthropic ruling, said if you buy the book, then they can do it. But I just think it could be different other cases. ⁓ But even if they buy the book, it's okay that way. It's still not a great solution because... I mean, it's just not efficient for every AI company to go out there and buy every book in the world and scan them in order to use them for training. It's just not an efficient model. ⁓ So, you I think there's a lot of work we can do just to make that more efficient and easier for AI companies.

How do you do that? Is that what what created by human is for?

Yeah, well, one, we clear the AI rights so that these companies can get the books with legal confidence. And then two, yeah, we're building out the infrastructure to make this really easy so that if an AI company just needs a million books or 100,000 books on particular topic, we can just get them the files. They're ready to use in an AI-ready format. So we're also building out an infrastructure layer here just to make this. make this really seamless for both, you know, rights holders and for ad companies.

So AI companies, instead of them trying to figure out how to acquire those books one by one, they can just come to you basically.

Yep, that's the idea. They can just do one simple deal. They can get all the data they need, have legal confidence, and it's just easy and simple. yeah, I think the one thing we've learned about companies, they want to move really fast. I mean, this is one of the reasons why they used books without permission, is they just want to move really fast. And we want to encourage them to move fast. We want to encourage AI innovation, but we want to allow them to move fast, but in an illegally clean way with the buying of critters.

Is it just fast you're looking for or it's also cost?

I think it's both, think it's fast and it's speed and cost. But I guess our goal is that if we could solve the speed problem, that they're willing to spend more money to get to solve their problems. Because at the end of the day, we all know these ad companies have a lot of money. They're raising these major rounds. And if we can just allocate a portion of that to go back to authors and creators, we think that's going to be a good thing for the world.

Yeah, that I agree. Do you think the settlement actually, all these recent settlements and maybe future lawsuits are actually changing AI company behavior that they're actually thinking about just paying it upfront instead of paying the lawsuit?

Yeah, I think it's definitely changing behavior. ⁓ there's an era where it seems like these companies were acquiring data by whatever means possible, and they've definitely cut back on that. They've also really reduced the outputs. Like if you try to ask Chatchity, for example, to try to replicate a piece of copyrighted text, it'll say it can't do that. ⁓ I mean, same thing with Claude and all these models. ⁓ They've put a lot of copyright restrictions into their products, which does limit the user experience. ⁓ building a model, we can actually then bring back those types of prompts and those types of outputs, but do it with the bind of rights holders.

I see. Yeah, that makes sense. Do you are you what are you since you're building this product and you're going to market right now, right? How can I ask how does the market react so far?

So ⁓ opinions are all over the place. think it's amazing just how diverse opinions there are. I mean, on the author-publisher side, I think it's all over the place. Some authors and publishers are just extremely excited about this. They see it as the next big thing. Some of them just are in the opposite perspective. They're unsure about AI and they're hesitant, and then there's all sorts of opinions in between. ⁓ and the AI company side of things, it's, similar. We've, we've had, you we've done some deals where there's been a lot of enthusiasm and there's a lot of, know, just kind of mutual agreement upfront on, on, on what they want to do and how they want to work with, with authors. ⁓ and then there's also been situations where I think AI companies, ⁓ just, they, don't want a license or, or another common situation is just that these, they, they want these lawsuits play out before they actually do deals. ⁓ so it's really been all over the place. but I think there's enough, ⁓ enough interest that we, you we're getting a good business going. And I think ⁓ over time, I think it'll just get more more momentum as these lawsuits play out and as this new model kind of just solidifies into place.

I'm really surprised that there will be authors who said no to this and there will be AI companies that easily said yes to this. Right? Really?

⁓ Yeah, there's been some, I mean, there's some AI companies that really believe in this model. mean, not everybody is just wants to get data without permission. ⁓ there's, companies are enthusiastic and yeah, there's authors who don't even want to have a conversation. just, they don't like AI, right? And I think our goal is to turn them around over time. I mean, by showing them that we're you ⁓ know, the solutions that work for them. mean, there is a lot of strong emotions around this. I a lot of authors feel like their work has been stolen from them and they feel like their best path here is just to resist working with AI companies. But we think that by building the right solutions and making this all work over time, we'll kind of smooth it out and get everyone working together.

Yeah, I see. So if it's more than just revenue, like this is not just a revenue channel, but it's also like whether you fundamentally agree with that your books should be ⁓ part of the input for an AI model.

Exactly. there's also concerns around, ⁓ you know, the creative control, like, is the AI going to distort what their creative beliefs are? know, quality control, is the AI going to misrepresent them? ⁓ There's all those kinds of questions that we're working through. And so, yeah, so it's not just about money and the legal cases. There's also kind of like more fundamental questions about like how AI would modify humans work and whether the human behind that is comfortable with that or not.

Can you say more about what you say to them when they ask you these two questions?

with these are authors. I think we're at the phase, we listen to the feedback and we try to integrate it as, as best we can. And I don't think we're going to win over every author in the world right now. ⁓ But we're going to get enough that we can kind of prove out the model. And then I think over time we'll get, we'll get ⁓ more folks on board as we, as we prove it out. ⁓ But yeah, I think, I mean, I think we're all learning together. I mean, we're learning as a company, AI companies are learning, authors are learning. Everyone is just adjusting to this new AI reality.

Yeah, yeah.

So it's a learning process for all of us. And our role as a company is just to try to bring everyone together on this particular topic.

What do you think is the end state? What's your prediction on the author side or the AI company side or the core side, where you're playing with all these different stakeholders, right?

Yeah. ⁓ I mean, the court side, I think, ⁓ I think it's going to be some sort of middle ground. I don't think they're going to decide that all trainings fair use. I don't think they're going to decide that all training is not very useful. There's going to be some sort of middle ground solution that kind of works itself out. I think the, the, the, the, the long-term state that we believe in that we're trying to create is one where, ⁓ you know, humans keep creating things and they feel incentivized to create things and they, get paid for creating things. and there's, you know, appreciation for human creation. And then also AI innovation is moving forward at the fastest speed possible and innovation is not slowed down by copyright. And that these two are working together nicely and in a nice relationship. You know, got off to a rocky start with all these lawsuits, but we think long-term we'll get humans and AI working together and that's our goal.

I feel like there's a fundamental, you know, ⁓ I don't know, conflict of interest is the right word. How do you think, how do you think such a state would exist in the future that can balance among all these three, you know, different stakeholders? I got to imagine if I'm the, you know, bullheaded author, sorry. No offense. If I truly believe that, you know, the, my, my, my creation is my creation and I don't want any AI to use it for any, you know, derivative content creation, then maybe I just believe in that.

Yeah, I think there will be some people like that, you know, till the end of time. I mean, I'm sure there are some, you know, there's some like authors who only do print books and they don't want ebooks or audiobooks, or there might be some, you know, musicians who only do live shows. I mean, I'm sure that those kinds of things exist. But I think like overall, think over time as these things get built out, that, the majority of people get on board for the new model. But just we're still in a state of figuring it out and the model just needs to be built out.

Can I ask like what kind of AI companies are willing to pay willing to license?

So ⁓ it's been a mix. Some of the big guys, we've done deals with the big AI companies, the names you would know. And there's also a lot of startups. There's a lot of startups that are interested in this, which are just some earlier stage version of bigger AI companies. So there's startups, there's big companies. ⁓ And then there's other ones you wouldn't expect. I mean, we just did a deal with a government agency. you know, we've had interest from like universities. ⁓ and there's a lot of, a lot of different, ⁓ you know, people who are developing AI these days are looking for, for data and books. And those are kinds of deals that we, broker.

For the three categories that you mentioned about their training and the reference and transformative rights, ⁓ are these three different products in your mind?

Yeah, they kind of are actually. like three, they're each their own different thing and they're almost like three different businesses. I they do overlap. mean, often if we're doing a deal or building a product that it might leverage all three rights, it might leverage training, reference, transformative. But I mean, if we really want to, we could be building three separate companies here around each of these categories of rights because they all have their own different nuances. ⁓ So yeah, it is, I mean, it is kind of a wide ⁓ area of... of opportunity in that sense. ⁓ But it all kind of is just around this theme of bridging human creators and AI.

Who's buying each one? And can you share like what does the deal look like?

So I mean, each deal is different. So far, every deal has been very, very different. There hasn't been kind of one consistent template. I think over time, as we do more, it will become more standardized. But at this point, we're just kind of figuring out one deal at a time. yeah, mean, a trading deal looks different from a reference deal, which is different from a trans-hortive deal. they're all just had their own nuances to figure out.

Yeah, it's so interesting. If I think about the RAG use case, you said that you build some tools to detect if a book is being referenced. ⁓ How does that work? Are you providing that to the author side or the company side? Is it analytics that authors can look at?

Yep. Well, yeah, well, I'll give an example of a deal that we've done that we haven't announced yet. It's with a well-known AI company. What their licensing books to be ⁓ used via RAG. So the idea is if you use their service to ask question and the answer to the question is on ⁓ page 250 of a book, we would then surface that answer and then we link back to the book where that answer came from. ⁓ And, ⁓ you know, we think it's a really, it's a good progress for ⁓ how this is playing out because one, the AI company is getting permission to use the books. They're not using prior to copies. ⁓ Two, they're linking to where the book can be purchased so that you can drive sales of the book. ⁓ And then three, they're also sharing incremental AI revenue ⁓ with the author and publisher of the book. So there's an additional revenue source here. So that's like one of the deals we've done and we think it's a really good step in the right direction. We're hoping to do a lot more like that and see the industry play out more like that going forward. That would be one example.

How do you charge for it? A lot of the AI companies have a chat interface and then they answer some user questions and then they return the citation at the bottom. then based on my understanding, you have the book link and so people can actually, the users can buy that book over there and you do have the citation. How do you charge the AI company?

⁓ Yeah, so I mean, first of all, the one way to make money is that selling the books. So it's a new model for selling books. But then two, yeah, there is this additional incremental AI revenue that gets ⁓ shared. ⁓ We are negotiating that with each deal. I wouldn't say there's a standard yet. There's far from a standard, I think. But different AI companies are forming different ways of distributing AI revenue back to rights holders. ⁓ And yeah, I can't share this specific how we do it for this one deal. ⁓ But we figured out a model that works well and we think we'll be doing more deals like that going forward.

What are the typical models, like categories or models that works? Like, is it by usage? Is it by flap?

Yeah, it's by usage is the one I'm referring to now. But I can also imagine in the future, there could be like a rev share model. mean, I'm a big believer in that where it's like, know, an AI company can just say, we're going to allocate X percent of our revenue to creators and pay that way. Another model could be they could pay for like an upfront payments for it. But the one today, it's mostly been by usage.

I see. So if I am a small, let's say indie founder who just started out, should I think about this or at what point do I need to think about licensing? For instance, let's say I'm building a therapy bot referencing articles and books, right? At some point I could use something like this.

Yep. Yep. Yeah, I know it's a good question. mean, if you're a startup founder listening to this and you're looking for licensed data, I mean, we'd love to talk. And this is a great way, I think, to get visibility for what you're doing, to take this approach of licensing data. Because I think it's the right way to do things. And it's a great way to just get visibility and do things the right way. I mean, I do think a lot of founders just want to move fast. And they don't think about this question very much. And that's why there is just a lot of piracy going on in the world of AI and it's all kind of legally gray area. But we think over time we'll kind of build new standards here, build new solutions and clear the rights. And eventually over time, this will become ⁓ just a more like legally clean situation.

When should I think about talking with you then?

I mean, think everyone should talk to us at every stage. mean, if you're just thinking about your idea, we'd love to hear from you and talk to you.

Okay, that's cool. do you think there's a, what's your suggestion to those founders, right? You know, the, because there's a legal ⁓ line at some point to my journey. Like if I'm building a therapy bot, I'm going to go to market. I'm trying to build a product, make it work, go to market, grow my user, right? These are the first journey. So yeah, what's your suggestion?

Yep. Yep. Well, I given my role at this company, can't encourage a founder to do copyright infringement. mean, that's just not what I can do. ⁓ So I would suggest founders reach out to us and work with us to do it right. ⁓ I'd say that what a lot of founders do do is they kind of like push the boundary on this a little bit just to get their business going. I mean, I could tell you like in my last company, Scribd, I mean, I'll give a little background how I got into the world of copyright. So ⁓ when I was just out of college, I launched the site Scribd to let people upload documents to the web. And I didn't at the time know anything about copyright. And of course what happened was people started uploading pirated books to the website. And then immediately within days, we had all these ceases and desists and threats from the publishing industry saying, hey, you have to take our books down. ⁓ And then that was when I started to understand this whole issue. And we implemented a whole DMCA takedown process. We built a whole copyright filter system. This is why I really learned about copyright. But I think I learned about it by first kind of making a mistake and misunderstanding it. So think that's a common founder journey. But I think ultimately though, think like, know, it's the earlier you embrace copyright, the better and you know, we're here to help and we do work with startups. So if you're a startup and you want to navigate this, we'd love to talk to you.

Yeah, yeah. Thank you so much. I think that's really helpful. mean, at least now, know, people, you know, without going through the journey, they are aware that there is something, there could be a block around the road at some point, even if you focus on go to market first. Right.

Yeah. I mean, it's all, it's all just so ⁓ kind of gray area. Cause like another thing people are doing is like they, they, ⁓ they'll take like a book and they'll, they'll upload the EPUB file to Claude or something. And then they'll like, they'll, they'll interact with the book and transform it. And it's, just, it's also legally gray area right now. ⁓ And I mean, our solution is like, let's, let's just build the right solution. So you don't have to like guess about what's, what's legal. Cause if look back at like, you know, the Napster era, right? Napster was also kind of legally gray area, right? And the answer to that was iTunes and Spotify, which is like doing the right, building out the right legitimate model. So that's what we're trying to be. We're building out the iTunes and the Spotify of this space so that people don't, they don't even want to use the Napster anymore. They want to just do the legit version. And that's what we're building.

And this is true. This is applicable to any AI company building, not just a research lab building the models, but also the application layer, right?

Yep, yeah, mean, it could be for training models or it be the application layer. ⁓ Yeah, those are the reference rights and transformative rights that's usually typically used the application layer. So that's what we've gotten a lot of the interest in transformative rights for.

Do you think an indie founder or one or two person team can afford the platform?

⁓ Well, like I said, we structure all kinds of deals. it could be a deal with a large upfront payment or it could be a deal that's entirely usage-based. ⁓ So yeah, we want to work with companies of all sizes and if you're a small team and you want to try to do this, we're very happy to work on it with you and find a model that works.

Other than the legal risk protection perspective, is there any incentive for the AI founders to use something like this?

Um, for AI founders, uh, well, well, yeah, I mean, I think it's, um, I mean, think ultimately you can build better products if you're getting legitimate data. mean, using pirated data is not going to lead to the best, the best products. Um, and I also just think it's, it's good for goodwill. mean, a lot of creators are very, you know, emotional upset about what these AI companies have done. So I think, I think building goodwill out there with, with your customers and with just the world in general is always a good thing. Um,

We are in the chat.

So I think, yeah, I think there's legal reasons, there's goodwill reasons, there's product quality reasons. ⁓ So, and yeah, we think this is where the world's gonna go over time.

Yeah, that's great. What about transformative rights? Who are buying those? Is it also not the big research labs?

Yeah, guess the transformative rights are the most complicated ones. There's just a lot of complexity and there's a lot of questions around ⁓ what authors and creators are comfortable with. I think actually the bigger issue there is not really the legal issues. It's like the questions of like, you know, taking the original work and modifying with AI and doing that in a way that creators are comfortable with. ⁓ So, I mean, that's the one I think that we are, in my opinion, has the most potential but also has the most still to figure out.

Yeah, the first thing I can think of as a challenger would be, how would you know, right? I don't know how people find out.

Yeah, mean, you mean like, how do you, how do you know?

If I'm an author, and it's harder to detect, I'm probably not policing myself actively either, right? So it's hard for the author to

Yep, yeah. It's hard to know what's happening. Once your file is out there, it's all sorts of things can happen. Yeah, I mean, I think we could bring back our efforts to kind of build these detection tools. But I think ultimately it's just building the best solution. I think if we build a really great solution here, people will choose that over these piracy options.

Yeah. Yeah. Let me try something. Let's say if I'm the indie hacker to take a stab at building an AI rights licensing platform for books, just like how you did it. And here's my high level thinking I have. maybe, can you tell me what I missed?

Okay, sure.

Sounds good. So I'm thinking here, my high level thinking, that maybe I'll start with building a database of books with the ISBNs. There are public data set for that. So I get all these data about what books are out there. And then I'm going to co-call all the authors and let authors sign up and claim their books. then I like how you did it, create three license types, like training rights, RAG, transformative. And I'll set a price per book per license type, let's say. And then I'm going to reach out to AI companies to negotiate deals for them to buy. ⁓ This is my high level thinking, but I admit there's a challenge here, which is I think it's going to be hard for AI companies to respond. It's my first reaction. What do you think?

Are you thinking about starting this company? Are we going to be competitors? that what's about to happen? Yeah.

⁓ Only in this episode.

Okay, only this episode. I think what you said sounds right. ⁓ yeah, I don't think every AI company is jumping to license these books and these rights, but we have enough traction, I think, to get this going. You just need one deal, which leads to the next deal, which leads to the next deal, and then the snowball starts to go downhill. So yeah, mean, that's one of the challenges is getting AI companies to want to do this, but I think we're making good progress, and I think also once these lawsuits mature. I think that'll also be another catalyst for this to pick up even more.

Can you actually was able to get the AI companies that you mentioned to the table? And ⁓ can you walk me through how you design that deal? Like not the actual deal, but just the thinking process? Like how do you think about how to go out and get this company to talk with you?

Like how to just get the conversation started.

Yeah, yeah, get the conversation started and design a deal that it's more acceptable to them, right? That they are willing to talk with you. Because my first reaction, this must be the hardest part.

Yeah. Yep. Yep. Yeah. Well, I mean, first of all, mean, we, I mean, we kind of have gotten ourselves out there. We have a lot of big authors in our platform. We have a really good brand. So I think we've gotten a lot of attention just from the visibility of the company. Also, I mean, I've just been working in Silicon Valley for, I think, almost 20 years here. So I have a lot of relationships. I've been able to get to a of the right folks, these companies, just through relationships. So I think having just a good brand and having good relationships is kind of the first kind of the first kind of step. then, and then once you get the conversation going, it's just a, it's a matter of understanding what their, needs are and how, how we can help. And it just becomes ⁓ a discussion and a, and a collaboration.

So ⁓ the first step is going out and then have a conversation about this topic. what do you think? Is there a signal that can move them? I'm just curious that you realize, OK, they are actually the right customer, and they're really thinking along the lines that aligns with your goal.

Remember, most AI companies, ⁓ bigger ones have data acquisition teams who go out and license data. So this is not, it's not like it's, it's that, ⁓ that, that complex of a thing. ⁓ I mean, I think where it gets trickiest for us is a lot of these, these companies have already trained on the books using pirated versions. And we, have this challenge of like, well, well, you already have the books, but let's try to do this in a more legitimate way. And I think that's, that's the challenge, but most of these companies already have teams dedicated to this. So it's not like it's, it's that form of a concept to bring to them.

I see. Okay. So, so the data acquisition team is the right way to go. Okay. I think I can become a competitor of yours. Just kidding.

Okay. Uh-oh. I'll have to hold back our best ideas here.

Yeah. How do you figure out what's fair? There must be a revenue split somewhere along the lines when you talk with the author, the publisher, and ⁓ AI companies. How do you figure out what's balanced and what's a fair payment to all parties?

I mean, there's no one right answer. mean, there are some people arguing that all data should be free. There's some people arguing that data is the most expensive resource in the world. And I think the answer is somewhere in between. And the way we solve this is just each deal one at a time kind of gets a little more precedent set to start to figure out what's fair. Each lawsuit that gets resolved, like the anthropic one, that sets a little bit more precedent. And I think just like each baby step that evolves kind of starts to gradually form the market price over time. And we're not in the business of deciding what's fair. We're in the business of trying to bring the different players together, establish the market price, and discover over time what that fair market price is.

How do you discover the fair market price by talking to people?

Well, think ultimately if you get deals done, ⁓ one deal is one indication of the price and the second deal is another indication of the price and the third deal is another indication of the price and then after enough deals, you just get to the point where like, okay, well we've done 20 deals and this is kind of the average price, right? But I think we're still kind of in that process of figuring that out.

I'm like. How do you come up with the first deal, then first deal price.

So far it's been the ad companies give us an offer and we say, sounds like a good starting point. And then we bring that to authors and publishers. I mean, it doesn't always get done. mean, we're in the process of one deal and we've been bringing it to publishers and some publishers have said enthusiastically yes. And some of them have said that the numbers are good enough for them. ⁓ So, it's like, you know, and then we might go back to the ad company and say, well, we could get you these publishers, but we would increase these numbers. ⁓ So, it's those kinds of discussions. It's just kind of a, it's a lot of discussions that just sort of play out over time.

I see. What do you think of a web3 smart contract type of solution? Would that be applicable here?

⁓ yeah, I've, I've, I've thought about that a bunch. I've talked to a bunch of the blockchain folks about it, and there's a lot of enthusiasm for this sort of idea. ⁓ I just, I just too busy to do that right now. But I do think there's a big opportunity to put, ⁓ to put IP on the blockchain. and, ⁓ there's companies that are working on that. ⁓ and, I, I, I'm interested in expanding that over time, but like, I'm just, I got my hands full doing what we're doing right now.

Yeah, yeah, yeah. ⁓ So you're building this marketplace for book licensing, but it looks like you're not only one building a content licensing marketplace anymore. Microsoft just launched their publisher content marketplace, I think last month, two months ago, maybe February. ⁓ And it seems natural for Amazon to build this also, right? What's your reaction to that?

Yeah, there's now a lot of competitors in this space. We were kind of, guess, earlier than most. There's now a lot of players. I mean, I think this is how it goes. There's a lot going on right now, a lot of different players. I think that we're going to find our niche. mean, we're doing particular kinds of deals that are working. We've been really focused on this whole multi-rights holder problem, which is something I think we've uniquely tackled. Um, you know, cause we're, still, we're still the only platform that's going direct to authors. Um, so, so, you know, a core idea what we've done is that, um, you know, when in, in, know, there's different types of data out there, different types of books, but when it comes to trade books, which are kind of like the books you see at the bookstore, um, um, like those types of books, the, rights get pretty complicated and there's, there's multiple rights holders. So for a particular book, um, there's, you know, if you want to license the, the, the AI rights, you typically need to get sign off from.

What is that? What is mobile?

author, maybe the co-author, the publisher, sometimes there's multiple publishers involved, there's often a literary agent involved. So there's a lot of rights that holders need to be cleared for a particular book. And we've been really the only company to take that particular approach to the market. So I think for that particular niche, we're sort of, you know, we're really kind of in a leading role for that.

Multi-rights meaning that all of those parties will get paid. Sort of process.

Yes, yes, that's a large part of the complexity of what we're doing. Because, know, one of the big reasons these large AI companies didn't license the books for trading in the first place is that they just looked at how complicated their rights were. They're like, this would be impossible to clear the rights for, because they all needed a lot of books, like a million books, it was just impossible to clear the rights for the books. And that's really, you know, one of the key problems we've solved is clearing those rights across multiple rights holders. and yeah, and compared to other AI rights marketplaces out there. We've, we've really, ⁓ kind of gone the furthest and solving this particular problem.

And this is every book has different set of rights stakeholders.

Exactly. Exactly. And it gets very complicated and there's a lot of nuance around it. And in the world of AI, they just want to get a million books and just trade on them and not think about all the complexity. that's kind of the big divide here. And that's the problem we're trying to solve is how do we combine this world of complex rights with the speed of AI? And that's really the problem that this company is working to solve.

See you later. How do you scale that solution? How do you scale it?

⁓ What's worth figuring out? I mean, we've built a pretty good platform for this. you know, like when we started this, we were talking to publishers and they all said, well, there's no way you can get authors on board because there's millions of authors. You can't get millions of authors to sign up. And we built a platform that allows an author to just sign up, verify their identity, select the rights they want to license, and then with one click, sign a licensing agreement. we've built a way to kind of scalably get these rights. And I mean, that's one component of how we solve it.

Do you have a unique insight that you know about this industry that maybe Amazon doesn't?

⁓ I mean, I've, we've gone further in this whole AI rights direction than I think anyone else has as far as I know. mean, ⁓ maybe Amazon's working on this in a way that, that we're not, but we've, we, ⁓ I don't, as far as I could tell, we've kind of gone down our own creative path. mean, sometimes I feel like we're, we're on our own path so much that we're the only ones thinking the way we're thinking, which I think is, it's hopefully a good sign. but we've, ⁓ I think, I think we're definitely, you know, we're, kind of thinking about this in a pretty original way. And I, I. I can tell you like, know, competition is not really the thing that, that worries me. mean, I think we just have big problems to solve. I mean, these markets are just so huge or so much opportunity that I think there's room for, for multiple players. And, I mean, I think this is just, it just, it's really, can we execute what we're trying to do or not is really, the question.

I mean, as a content creator, I mean, as an author, I think it's a good news because I can be on your platform. I can be on Amazon at the same time. And you'll just maybe working on different deals with different AI companies.

Yeah, exactly. mean, there's just, there's so many companies, there's so much going on in the world that there's plenty of room for lots of companies here.

Right. And you run a script for 16 years. That's quite a long time. Right. Yeah. What controlled how fast script could grow versus what do you think today is controlling how fast created by human can grow?

Had a long run, yeah. Well, I think the rate of growth depends on how quickly you find product market fit. I find the ability to find product market fit is just the ability to land the right strategy and execute really quickly. mean, at the end of day, it's just execution. It's like how quickly you can execute. Scribd was, yeah, I was there 17 years. It was actually a very steady grower over the years. mean, if you look at the 17 year revenue growth curve, we grew every single year by, you I think it's like average of 30 % growth per year and just kind of very steady upward growth for many years. I think, yeah, I mean, I'm intending to do the same thing here. You build a company, takes time. I mean, sometimes you have these companies where they launch and then they grow extremely quickly overnight. But I think in my experience, it's like you got to just keep thinking long-term, placing the right long-term bets and just kind of... ⁓ keep executing and then things compound over time.

What's your long-term bets on Created by Human?

in terms of what?

In terms of everything, what's your long-term thinking about this company you're building now?

Well, yeah, I we want to be the company that protects human creativity in the AI world and creates a business model for it. And then also helps drive AI innovation and gets those two working together. And I think, know, there's an opportunity to build a really big business. I mean, this is an enormous market and there's some competition, but overall, I think there's a lot of room for us to help solve this problem and build a big business.

Do you think there is something that you learned from script that's applicable here?

I think I learned a lot just about building companies. mean, I entrepreneurship is a learned skill and I think just spending years working on it, you learn all the skills of how to build companies. But I think more specifically, mean, at Scribd, we pioneered the subscription model for books and that was, had a lot of similarities we're doing now. I mean, we had to get authors and publishers on board, we had to get consumers on board, we had to bridge that gap. And similarly now, we're working to get you know, working to get authors and publishers on board, working to get AI companies on board and bridge that gap. ⁓ So I think there's a lot of parallels and ⁓ there's some differences too, but I think there are a lot of parallels to like what I learned there and how that applies to this current situation.

Why did you leave script? What made you walk away after like so many years?

Yeah, it was just, uh, it was time to do the next thing. Um, I just, uh, I, yeah, it wasn't, it wasn't the right place to do exactly what I wanted to do. And, um, yeah, this is, this company is related, but it's, it's different. And, um, I gotta say, it's been, it's, it's actually really, really nice to start from scratch. Like starting a company in, in 2025, 26 is like, it's really a joy. There's just so much funding out there. There are so many like tools for getting started. There's so much like enthusiasm for startups that it's been. It's been really nice starting over. yeah, I'm just having a good time and just taking everything I learned and channeling that into a new vision.

You said that it wasn't exactly what you wanted to do anymore. you, at the time when you decided to leave, do you have something in your mind that that's exactly what you envisioned that you want to do?

Um, no, I think I, I mean, I left in, um, kind of what late 23 and then, um, once I was out, I, I like, pretty quickly, um, sort of just sort of like coalesced around this idea. Um, I mean, I actually had, um, at the time there's all this conflict between, I mean, there still is between the book industry and the industry. And I had folks in the book industry, like reaching out to me to ask for my input. Um, and then I like knew all the people in Silicon Valley were kind of involved this. And I was like, oh, I just, I just felt compelled to solve this. So. It was like pretty quick that I was just sort of like the new vision clicked and I was like, okay, this is, this is the thing I want to do.

Do you think creators will actually get the control and get compensated in the end? Or do you think the industry will continue to steamroll them?

Oh no, think we're gonna solve this. think the way we get the industry not to steamroll them is to build out a better solution. And I mean, I'm an optimist that we're on the right track here, so I think we'll figure it out.

We'll figure it out. I hope so too. Yeah. Your platform is literally called Created by Humans. ⁓ But there are so many AI content right now, everywhere. And maybe some authors are leveraging AI when they write, right?

That's right. What we're called created by humans dot AI. We're very much an AI company. That's what we want to be. We want to be the AI company that supports creators. Because I think most creators think AI companies don't have their backs and we want to be the AI company that has the back of creators. And that's just really what we want to be known for.

Yeah So you have both.

Yeah, we're still very pro AI. We're trying to be the company that bridges the gap here.

Do you have to verify the books are actually written by a human?

⁓ so when you use our product, you, have a checkbox. You have to verify it. The books were written by human. ⁓ I think this is still a, this is a really tricky issue of how like, you know, human, texts, the AI texture are to, are going to, are going to come together. ⁓ I mean, we still think that, you know, there's a lot of value to human, Jerry texts. There's a lot of valued AI texts and we want to be, you know, create clarity around which is which. ⁓ but yeah, it's, that's, it's a really, it's a really tricky thing. Cause I think, you know, humans are using AI to write. mean, if you're just using. you know, spell check or something that's that is your technology is helping you. Right. So these two are coming together and it's still going to, you know, still have to kind of figure out how those two co-exist.

Is there a percentage point using AI will disqualify me as the human creating this piece of IP or content?

I think in our project we said it has to be at least 90 % human generated, but exactly what that means, I mean, who knows? That's kind of up to the author to decide if it was 90 % human or not. So I think there's no clear answer to that, but I think around 90 % is what we were using.

What about your personal opinion?

Yeah, I think that probably sounds around right. it's, I mean, I think if you, if, the whole thing is just copying pasting chat, CPT outputs, uh, I think that's probably not human generated, but if it's like, you know, if, a, if a human is, you know, really thinking about every aspect of it and applying their, their brain, their creativity to it, then I think that's, that's human generated. Um, so I think, yeah, 90 % is kind of where I place it, but I think that that'll, that'll probably evolve over time.

Probably, probably, okay. I mean, I think human will crave human made things. ⁓ But once we can't tell the difference, will it really matter?

I still think it will. I think there's going to be times where humans really want to see something created by humans. And I think if we as a company can help create clarity around that, think people will appreciate that clarity. ⁓ But I also think people are not going to be so religious about that they're only going to want to read human content. think that people are also going want to read AI content. think figuring out how we can present those to users at the same time and create clarity around that, I think, is just part of what you do.

Okay, I have some rapid fire questions for you. maybe you can answer very quickly. Number one, training rights, reference rights, or transformative rights, which one wins long term?

Sounds good. I mean, I'm not sure one of them is going to win. think they're all really important. But I'll say I think I'm most excited about transformative rights.

I'm looking forward to learn more about it. Maybe when you figure it out, you can come back and tell me more about how did you figure that one out.

Happy to. Yeah, I I have more to share on a lot of this soon. We got a lot of stuff in the works we're gonna come out with soon. So I'd love to come back on and share more. What's that? Not today, sooner than you'd think. So hopefully it'll be back soon.

Not today. Not today? Not yet today? OK, well, let's go. Let's save that to session two then. I'm really curious about that transformative rights. Most AI companies will eventually license content willingly, true or false?

Sounds great. Let's do it. Yeah, think so, yeah. mean, most already are, especially once you get big, most do. So I think they will.

Okay, 16 years or 17 years at script versus two years at created by human. Which one is harder?

I think ⁓ Scrib was definitely harder just because I was a first time founder. I mean, I started that company in college, I made a lot of mistakes and was learning as I go. And this time I feel like I'm just, yeah, more experienced at this point.

Can you share a mistake that you made that you can publish here?

I made, I made lots of mistakes. mean, you know, hiring mistakes, ⁓ building, you know, just building the wrong products or, ⁓ you know, just resource allocation mistakes or misallocating funds or, ⁓ you know, having the wrong investors. mean, there's all sorts of, ⁓ there's all sorts of things. ⁓ yeah, I could probably talk about that for a long time. So that's how you learn, learn from mistakes. And then, and then, ⁓ that's how you learn, grow.

Yeah. I guess I have to ask you about these at a coffee or lunch another time. ⁓ One person billion dollar startup, is that actually coming?

Sure, you happy to. ⁓ Yeah, I don't think it's gonna be as common that quickly as people say like I don't think there's gonna be Yeah, it's like there's gonna be a ton of those but I think they were they're definitely coming I mean cloud code is really amazing. I mean, it's amazing would get done ⁓ You know, sorry, it's already happened. I think some people say Bitcoin was probably created by one person. That's a that's a you know ⁓ Yeah, but multi trillion dollar one person startup. So I think it's already been done. I think it'll happen more and more But probably not gonna happen it quite as quickly as a lot of people are saying.

What AI tools are you using day to day right now?

Um, I mean, I'm using a bunch. mean, Claude code is the one I've been using lately. Uh, I mean, Claude code is really amazing. I mean, I've just, I, it's, I still don't even know what to, what to make of it. It's, feels so revolutionary that I'm still trying to wrap my head around what it, what it means, but, um, I've been using it. It's really, really impressive.

What are you using it for?

Just like prototyping things. I'm not really writing ⁓ production level code, but I've been ⁓ just prototyping things. mean, it's a lot of fun. Have you tried it?

Yeah, yeah, yeah. I mean, pretty much only using Cloud system, like co-work, code, chat. Co-work is fun too. Yeah. Yeah. I use it to connect all my calendars and meetings, emails, so that in the local directory, so I have everything planned out, which is a very, cool automation tool. OK. Can you give me one tip that you can, sorry.

I actually haven't tried co-work, it's on my list, but.

What is one tip you can give me to become a better founder?

I think just persistence. I ⁓ think there was like a Steve Jobs quote or something where he said like 50 % of this is just persistence. Like think if it was persistent with your company, you'll eventually figure it out. So that would be it.

Okay, thank you. I'll keep plowing through.

Keep going, 10, 20, 30 years. Eventually most founders figure it out. It just takes a lot of persistence and eventually you learn and you figure it out.

They are. I'm curious, when do you feel, how many years in was scripted that you felt like you figured out?

I mean, ⁓ I'd say on some level, feel like I'm still figuring it out right now. ⁓ With Scribd, it was interesting because it felt like we were failing and not going anywhere ⁓ and no one wanted to talk to us. And then we launched the site. We got a lot of traffic off of the initial launch. suddenly, my phone was ringing every day with investors trying to invest. So Scribd had an interesting moment where there was this turning point where it went from like, No one wanted to pay attention to us, to suddenly everyone was paying attention to us. So for there, there was this moment of like, we figured it out. But in reality, think that that was in the grand scheme of things, that was just one small moment. I think you don't want to let any of these moments be too positive or too negative of a signal. think what matters is just the long-term persistence and shipping away over long period of time.

So if I can compare with learning how to bike, at the longest time when I'm practicing biking, I have no clue. I couldn't keep my balance. It's the same as swimming. I don't know what I'm doing. And then once you figure it out, you feel like, I figured it out. The hard part is when you're right before that figuring out moment, how did you keep yourself and your team motivated? Because you don't know, right?

Yeah, I think it's just blind faith. You just got to believe and go for it. I mean, there's all sorts of tricks you could use to stay positive and communicate that motivation to others. I think just blind faith. You just believe in yourself and you just go for it and eventually it works.

Is that what you did?

Yeah, that's, that's, ⁓ I think that's how a lot of entrepreneurs work. They're just, you know, they have a vision. There's always marching towards the vision. And sometimes you have days where you like accelerate towards the vision. Sometimes you have setbacks, but you don't want any of those moments throwing off too much. You just want to keep, keep marching forward to the vision.

Okay, I have a traditional closing question. If you could recommend a book to maybe yourself 20 years ago when you first graduated yourself today building a successful company and then starting a new one and maybe one 20 years from now, what would they be but no pressure for all three of one or two is great.

So there's a book for like the present, the past, future. Yeah, I I read like a lot of books, it's kind of hard to choose just one or two or three. I can share a few. So I think for the present, the book I've been kind of referring to a lot is Good to Great by Jim Collins. Have you read that? I think it's like one of the best business books I've read. It's just how to like basically build a really great world-class company. And I read that a long time ago, but I feel like right now, trying to again, build a world-class great company. So I've been finding myself revisiting that book a lot. So I really recommend that one gets great. ⁓ Let's see to my 20 year old self. ⁓ I guess what I was, I was just reading again recently, was Siddhartha by Herman Hesse. I think the idea of that book is that, you you don't want to spend too much of your life seeking teachers. And sometimes you just want to live through learned experience. And I think I could have learned that lesson earlier. And I think a lot of folks learned the lesson earlier. I think that's related to what we were just talking about with building a company. Like, you know, how do know if it's working or not? How do you keep going? I mean, there isn't really actually answers to that. It's more just like, you should just live the experience and enjoy the ride. and things usually work out if you just take that, take that approach.

I love it. Just get on a bike, right?

Yeah, as long as if you fall and you hurt yourself, as long as you're not gonna die or anything and you can get back up and keep trying, then sure. yeah, just safe proof yourself so that you can, in a worst case, you still get back up and keep going and you should be good to go.

I love it. Yeah, thank you. Trip, thank you so much. ⁓

And then I guess I'll answer the future one. Yeah, the future book, ⁓ would say ⁓ Barbarian Days by William Finnegan. So it's a book about surfing. It's just a great book about surfing. I mentioned I'm now a jet boarder. That's my new sport. But I just think it's a great surfing book. So I I keep, I read that one again in the future.

Yeah, awesome. Sounds great. Yeah. Thank you. Thank you so much for today. I mean, the whole, this whole thing about fair use, copyright data for AI. It's, it's a hard topic for everyone. I can tell that you're still trying to figure out the answers. And this is not just in AI, right? It's for everyone. Engineers writing code. Like we don't get paid at all. Right. Yeah. Yeah.

Yep. Well, no, I chose this problem because it was challenging. It's like that. And that's sort of the part of the fun. It's a very challenging problem. But I think we're making good progress and ⁓ on track to solve it.

Yeah, creators of all kinds. mean, I don't know if anyone has the answer yet. But as you said, you're actually on the bike. You are actually working on solving it, at least for the book authors, right? So thank you so much for being so open about where this is going and your deep thoughts about this space. I'm looking forward to learn more about what's going on and maybe getting paid as a content creator now.

Yeah, yeah, it's been great to have to be here. Great conversation and happy to come on again and give you the future updates.

I would love to know to learn more about your transformative rights, like how's it going? And you can tell me more later. Happy to have you again.

Yep, yeah, more in the works. We'll talk more soon.