I sat down with Kevin Slavin to explore a Spotify-like transaction layer for nature's genomic data: open enough for science, but capable of rewarding the countries and communities whose biodiversity produced the value. This is part 4 of 4.

Transcript

Kevin: It looks some of the nearest term deployments are in a place that I never would have thought to look, which are in public databases of genomic data, which exist. They're all over the place. And so there might be a museum somewhere that has a whole bunch of specimens, botanical specimens or fossils or whatever. And they might be generating a lot of digital sequence information from that.

And they're good scientists. they publish it. And unlike Indonesia, they're we're not trying to make a profit. We're scientists. We're just trying to get this out in the world. And they do. And it's awesome. That's an awesome thing to do, to just have open data.

Pablos: But what you were describing before is it's not their prerogative. Somebody else is knocking on the door and saying you can't get that away. Turns.

Kevin: Out it's not their data. And they're giving it away, which is this problem that is visible to maybe 1 000 people.

Pablos: On the earth. If I sequence my own shit and post it on the internet, it's not my data to give away.

Kevin: Your own shit is yours. Okay. far in this jurisdiction. And if you want to put something from that tree out the window and you get the permission of the United States to do that, you can do that. But you can't go somewhere else, get mud on your shoes, scrape that off, and upload that. But that's what they've done in these public databases, not because they are trying to screw anybody over, but because they're just trying to be good scientists.

And I'm okay, You basically invented Napster for digital sequence information, which is awesome if you're a user and terrible if you're the person who produced it. And so what we're working on right now is we're talking with some of the alpha public database folks to basically build a transaction layer on top of the public database. To say that if you want this data, either we have cleared the use of that data with Brazil or Indonesia or Malaysia or Madagascar.

We've either cleared that and you can have that data under the following terms and conditions, which include sharing benefits if you turn it into something commercial. Or we don't have that agreement and you're on your own and you should know that this belongs actually to Malaysia and that if you develop something huge, there could be a knock at any time, same as there used to be with Napster.

Pablos: Instead of being the evil Napster that's exploiting the rights of these intellectual property holders that inherited through their sovereign territory or invested in sequencing this stuff and owning that data, instead of pillaging them, you are the salvation. You're Spotify. You're coming to be there for the rights of the artist and make sure they can.

Kevin: Monetize. Yeah. Basically, Spotify.

Pablos: For non human DSI is.

Kevin: Sometimes how we.

Pablos: Talk about it. Non human What does DSI mean? Digital sequence information, genomic data. That actually seems simple. It's the right idea. Good idea.

Kevin: Yeah, I think Spotify had it a lot easier because they had labels to work with, and labels had already done a lot of the, basically, almost all of the really hard work of acquiring rights, figuring out what distribution schemes looked et cetera. Whereas if we go to talk to Nation Y or Nation Z, they may.

Pablos: Not have a.

Kevin: Stress. Every conversation has to start from a very different place. It's we have to help define the field and not just the solution, and that's the rolling headache part. Got it. But making our way, we're heading to–.

Pablos: It's less Spotify. It's more iTunes. Maybe. I guess they had to deal with labels, but they were doing it for the first time, trying to navigate that.

Kevin: I was looking at how did Airbnb do And that's actually what led in part to the public database strategy. I learned, I don't know if this is true, but what I read is that when they started, they just lifted all the data. They just lifted all the couch sharing things off of Craigslist and just produced those as inventory in Airbnb.

And I was what is.

Pablos: That in this?

Kevin: It's oh, they're actually the public database. It's here's a thing that's being given away, but actually has value. And how do we–.

Pablos: I think Craigslist lifted classifieds. Also, yes. And they started. Yeah, exactly.

Kevin: Exactly, right.

Pablos: What can we lift off of Airbnb? Just kidding.

Kevin: Yeah. I don't know. It's an interesting question. But so we're heading to Yerevan, Armenia in October, which is where something called COP17 is happening. And they're basically convening in Yerevan to discuss exactly this question about how access and benefit sharing should work. And so we're going in part to be part of that conversation to say, maybe capitalism could.

Pablos: Help. You might not want to pitch it that way. No, that's not necessarily.

Kevin: The language that we're using. And it's not exactly really how I think about it. But it's a shortcut for really, in a way, to say everything that everyone there is going to say is correct and right and well intentioned And most of it will not take incentives into account. And what would it mean to take incentives into.

Pablos: Account? It might.

Kevin: Look something else.

Pablos: Right. And you guys have already started building something that can do that. You have actual customers yet? Not quite yet. No, we're six.

Kevin: Months old. We're on the verge of a couple things in a couple directions, both on the provider side. And the user side. We're signing with some folks for federated infrastructure. Because there's also an interesting technological aspect to all this, which is, how do we make the data in Madagascar discoverable without revealing.

Pablos: It? Two things. explain the Glia Monster example, because I think that's a really good one that makes the commercial rationale. For this, pretty.

Kevin: Obvious. the Glia Monster is a lizard that we have in the United States. It's no coincidence that American pharma used digital sequence information from an American animal. And it's not a perfectly straight line between Glia Monster DNA and GLP 1s But it is also true that we wouldn't have GLP 1s in their current state without Glia Monster DNA.

It's somewhere in the middle. It was an essential component in the full commercialization of GLP 1s And GLP 1s are what? Something $60 billion a year industry, which will only climb. And it's fine from a geopolitical international law perspective because it's American companies working with American digital sequence information from the Gila Monster. But what if that Gila Monster had been in India?

Pablos: I see. Okay, I thought it was from South America. it's American. Good to know. We have all the best lizards here.

Kevin: American lizards are pretty good. I feel we could have done better, but still, we're all right.

Pablos: All right, great.

Kevin: But yeah, and you just think it's a very small percentage that would need to go back to the Indonesians of the world out of $60 billion to be extremely meaningful for the lab that found that. Or the university researcher.

Pablos: Who discovered that. the presumption in your business is that we can set up these agreements with different jurisdictions in Indonesia or Narnia or whoever. They make their data available to whoever agrees this licensing terms. I can click buy now. I get their data. I find the next GLP 1 I commercialize it. Some piece of that actually goes back to the original data holder originator.

Kevin: Yep. Some of it goes back to the provider of the data. And then also some of it goes to all providers everywhere, which is an alternative view on how to provide incentives, which is formalized to something called the Cali Fund, which is basically saying we just need to fund biodiversity. The Cali Fund comes out of biodiversity. And basically when there are commercial returns that have functioned, that were dependent on data that came out of biodiverse regions, again, it's policy.

Those folks should give back some percentage to everybody. The total amount that has been raised by the Cali Fund is 1 000 So that's also the right idea. Not worry. But we have something analogous to it. And we will also recognize the Cali Fund, which is to say that some percent goes back to the provider who provided the DSI for the Gila Monster or whatever it is.

Okay. And then a smaller percentage just goes out to everyone. Because the condition that we're trying to produce is just an overall incentive to just produce as much data as possible from everywhere all the time.

Pablos: Yeah. Right. you want to incentivize people to go out in the field, find some weird snail or bug or leaf or whatever, sequence it, add it to the sum of human knowledge, and understand work in the long run, if it correlates to some commercially useful thing, which of course some of these will, the money trail will go back to providing a return for, if not you, at least your country or your jurisdiction or whatever's going on in the place where you're at, and hopefully some beneficial thing will be done with that money.

But just fundamentally, what's this company called that you're building?

Kevin: Bio.

Pablos: Okay, and what Fairfield is doing is trying to basically just build that Spotify layer. Exactly. Build an on ramp that places have at least an option. Right now they basically are dealing with no option. That's right. And they have no plan, really. They just have bad attitudes and whatnot. here we give them an on ramp to a system that's at least functional.

And then on the other side of it, I guess, you want to find the customers who want this data. that would be pharma companies or drug developers or whatever. Pharma,.

Kevin: Ag tech,.

Pablos: Animal health.

Kevin: Is super interested and interesting for us. Biotech in general. And then also industrials. we've talked to a detergent company and a diaper company. Yeah. Those folks are, they are very interested in getting access to certain types of data that are fundamental to industrial.

Pablos: Products. Okay. any of those kinds of companies could become customers for you as well.

Kevin: Yeah. We animal health and ag tech in particular because the regulatory cycles between a discovery and its deployment are much narrower than they are in pharma. Yeah. it.

Pablos: Takes forever. Yeah. Basically forever. Yeah. And is there a, if I'm one of those customers, say even an ag tech customer, I come to you and what I think I'm getting is access to a metric load of data and where I have a clear relation, commercial relationship with that data. And so it's one stop shopping for me.

That's right. And then your job is just to go get more and more data in there for me to get.

Kevin: Access. And we know from talking with some of these companies and we know from talking with some of their lawyers, they have closed down certain lines of research because they don't have a clean way to get that data. Yeah. And for me, if we're when we're successful, they won't have to fear that.

Pablos: Anymore. Right.

Kevin: It's that. part of what, in the same way that what Spotify does is allow everyone to diversify their musical taste because it doesn't you now have access to everything. That's right. We it's want to do that first for.

Pablos: Science, for research,.

Kevin: For guided research. when we do that, it's a shift in how we're going to do that. How companies operate right now, they have to be extremely careful about the data that they get. They have to be very thoughtful about it. They have to spend a lot of money on compliance just consideration and just internal counsel and what's.

Pablos: Up. And yeah,.

Kevin: And we're basically trying to say or you can just agree to a standard.

Pablos: License. Yeah, there you go. I love the standard.

Kevin: License. That's that, no one has I think a lot of good people figured out the general dynamics of it. But no one has approached it from a standardized licensing and contracts point.

Pablos: Yeah. And.

Kevin: That's.

Pablos: What we're bringing. I think it can be huge. look, I'm here all day signing safe notes. I don't have to read anything. Yes, exactly. I love it. Yeah, exactly. I don't have to call lawyers. Pay lawyers. I'm just, it totally has changed makes what's possible. And I use that analogy all the time.

Kevin: We there's a there's an interesting there's a subtlety in this whole field, which is that there's a difference between the sovereign owner of the data Mexico and the provider of the data the University of Mexico City or whatever. what is the relationship between the provider, the university and the sovereign Mexico? by international treaty, that's for them to figure out.

Right. And it's we it took us a while to understand that that's how things are working. And it's and then, immediately, as soon as we have any conversation, well, I'm going to have to talk to, I even know who to talk to in Mexico. we realize, we need to do for that relationship between providers and sovereigns what safes did.

Pablos: Yeah, you need to create a guidance. Yeah. Guys, I know you haven't thought this over or worked it out. Here's what everybody else is doing. Right.

Kevin: And so we spent a bunch of money on lawyers to generate the equivalent of a safe document. the agreements between sovereign owners of data and the providers of data. Wow. And we will execute hopefully our first one next week. Wow. Because I think, this is it's there are these two things that are just such killers in this whole space.

And they're the opposite of each other. One of them is just incredible amounts of friction. Yeah. And then the other is just total amounts of ambiguity. Right. sometimes it's there's just so much paperwork that you can't even get through it. And the other times you're just I don't even know what paperwork it would be.

Pablos: Right. And so.

Kevin: We're just trying to get rid of both of those. Right. Just try to get rid of those. And if you can get rid of the friction, if you can get rid of the ambiguity, you're also eliminating the risk. Yeah. For users of the data. And you're making sure that the providers data aren't exploited.

Pablos: Cool. what do you guys need at this point? Partners, customers, investors, countries. Right. Yeah.

Kevin: Every we. Yeah. If anyone has lizards, we're short on. We're especially. No. we need more of we need more. we need more conversations great providers. OK. could be universities. They could we're talking to. I don't know if I can talk about.

Pablos: It. You don't have to. It's good. I'll just put it.

Kevin: I'll just put it. We're talking with somebody. Everybody in we're talking a guy in a European country who is who sequenced maybe a hundred plants and trees that have never been sequenced before. Yeah. That he has unique access to. and he contacted us and he was I don't want to give this away. Yeah. But I also know that it's there's a decent chance that this is useful to somebody.

Can we do it? And some people look that and then other folks look we're building a new municipal wastewater surveillance program. We're going to be generating tons of data. Can we work with you to commercialize some of that? And it's well, it could also be.

Pablos: That. I love.

Kevin: It. We're working with there's a nonprofit in a state in America that is looking to back up the DNA of every organism in that state. Great. And they contacted us and they were this. I think this is what you're for. And we're yes, this is exactly what we're for. There's and the providers could look anything.

Pablos: OK, cool. Right.

Kevin: And then and then we're really we've been talking a lot with animal health folks who are extremely interested. We're trying to get to ag tech folks. That's especially interesting for.

Pablos: Us. And yeah.

Kevin: And then also we're trying to make better inroads with the little biotech companies flagship pioneering in Boston has something 100 companies under its wing. we want to talk to whoever can help us get this idea into 100 decision makers at 100 companies. Maybe only half of them care,.

Pablos: But that's fine. Right.

Kevin: Yeah, so just exposure to the more folks on either side of the system, the.

Pablos: Better. OK. Yeah. Super cool. what so in the long run, when your company is wildly successful 100 years from now, the IPO for a quadrillion dollars. what's the net effect? we've sequenced vanishingly close to everything on Earth. Research is, one click,.

Kevin: In. Yeah. to answer it, you have to use your imagination of What have we what is undiscovered in those billion species? And I use this example, they found something maybe three or four years ago. Pretty recently. I want to say it was in a graveyard in Japan. It was either in a graveyard or a recycling center. But it's a specific microbe that eats plastic.

OK, cool. It's OK, we didn't we had no idea that such a thing existed on Earth. how would we even if we could detect that it was there. Yeah. What then? now we can take it. We can figure out what makes that tick and we can engineer what we need to engineer. Exactly. Get rid of all the fucking plastic.

Exactly. we could do that.

Pablos: These things. We're doing it, actually. Did I tell you that? No, I did that. We have a company doing that. I don't know if they did it that way, but they've been engineering enzymes that can break down the plastics into monomers. what happens now is you just melt this shit down with useless crap and you can go make recycled stuff that sucks.

Yeah. But if you can break it down into the monomers, well, that's the feedstock to make plastics in the first place. they just can take a, yeah, they could take Coke bottles, whatever, break it down into the monomers. And then those monomers become the industrial feedstock to go make fresh plastic that's 99% pure. there's no compromise. And now your landfill becomes a mine for plastic.

We don't need natural gas. We don't have to make it out of fossil fuels anymore. We can literally just use all the fucking plastic we already have. And that company, what's cool about it, that one's called Rhea's Factory. What they're doing is designing a full set of enzymes that can break down any plastic into any monomer. they'll make what, basically a gut microbiome for plastic.

Yeah. They take off, because the problem is recycling. You've got to sort all this shit out. It's not worth it. These guys, you just take all that mixed plastic, throw it in one big vat. It's amazing. Where all the enzymes break down all the plastics into monomers, and then you sort them out and sell them. And so they're building their first pilot plant in California right now.

That's amazing. Yeah. It's so cool, because that's the.

Kevin: Future. And, yeah, and it's.

Pablos: An infinitely recycled plastic.

Kevin: I don't want to oversimplify.

Pablos: It and say,.

Kevin: All you have to do is just discover this thing and then it's done. There's a whole bunch of hard work and failure in the middle. Of course, yeah. But it is all contingent on continuing to learn.

Pablos: From nature. Yeah, there you go. Exactly. How did nature solve this?

Kevin: We have to do the best job possible at learning how to solve every single.

Pablos: One of these problems.

Kevin: From nature. And we can't do.

Pablos: That if we don't know what it is. Totally right. Yeah. Totally.

Kevin: Right. that's the.

Pablos: Goal. Super cool.

Kevin: Yeah, that's the goal. It's not, yeah, it's the goal is not to bring capitalism to the Nagoya.

Pablos: Accord. it's not for you. No, the.

Kevin: Goal is what is it going to take to.

Pablos: Unlock that? I think, what you said is totally right, which is that to solve a lot of these problems, you have to look at it from a perspective of the incentives. Any problem that involves humans, human nature, human decision making, humans in large groups or groups of any description, humans basically are awesome one on one all of them.

We've got an exception every one out of a thousand or one out of a hundred sucks one on one Most of them are all awesome if you just hang out and get to know them. Once you put them in groups, then they start to really suck at a much higher rate. Yeah, that's right. But the incentives are what guides their behavior, and especially in groups.

And so part of what I love about capitalism is it basically has that as its north star. It's okay, let people duke it out with incentives. It's I'm incentivizing you to do the thing I want you to do. You're incentivizing me to do the thing I want to do. And we're going to figure out who wins in that context.

And so I think it's a good scheme, not for everything, but for a lot of things. And I think that a lot of the things that we want to accomplish in the world, the good stuff, suffers because we have this ideological bent against capitalism being the solution. There are a lot of things where capitalism is not able to work.

And what I think is great about your project is you've figured out a way to align the incentives so that you can attract the money to solve the problem. Exactly. And there's a bunch of cases, in a lot of cases, what's going to solve climate change is fucking hyperscalers. Because they have the money. They're incentivized to buy as much energy as they possibly can.

They need it to be cheap. They need it to be abundant. They need it to be clean. They're going to save us. We bitched and moaned about it for decades and got jack shit done because we didn't have any way of attracting capital to carbon credit. or carbon sequestration or ameliorating carbon emissions and all this stuff. I worked on a bunch of those things.

I wasted a bunch of my life trying to solve these problems. But I don't have any way of incentivizing the capital. A bunch of great ideas that aren't going anywhere because we don't have an incentive to bring the money that's going to be required to make a difference. And so I think we've got to be honest about these things.

And we have to be reflective and say, OK, well, we tried. Our pipe dreams didn't work. Now we've got to figure out what is going to work. And what works is business. What works is attracting money from the people who want something done to the people who can do the thing. And so I don't see any shame in what you're doing.

I think it's exactly the right idea.

Kevin: I think maybe a different way to state what you were saying is it's not just that people start to suck when they get in groups. But it's also that individual incentives are almost always productive. And collective goals have never worked. And I don't know what it is about the human.

Pablos: Software. I think people working together has accomplished a lot of great stuff. I don't mean to. Collective, large scale collective.

Kevin: It's not for lack of knowledge that vexing global problems persist. It's that there's no specific will to just solve these problems on their own merit for our collective outcome. That's tragic. But it's also, I think you have to start there and say that that's true. This is the game on.

Pablos: The field right now.

Kevin: This is true. And that the approaches of policy have always been around, well, this is clearly in the collective good. And it's it is clearly in the collective good. It's also clear that bad actors or selfish actors, let's put it that way, selfish actors don't act in the collective good. then the question is, how do you create something that isn't the collective good by appealing to the individual incentives on all sides?

I think that's the trick.

Pablos: We have done that. We have done more and more of that. I agree. There is no ozone hole panic anymore. We made the right. We are. And I have this, I don't know, my belief is that humans have done a better and better job over time. Not as fast as we'd it's so easy to vilify people from 100 years ago the way people 100 years from now are going to vilify us.

But for not acting faster, more logically on these things. I think that there's a but the trend is correct and the trend is great. And you could imagine maybe in a century or two, humans will be able to get organized and be hey, let's stop with this emissions crap. let's stop some of this other bullshit that we've been doing make things, because maybe they'll be free to do that because they won't have, to have the same kinds of jobs filing TPS reports that our generation has.

And so I think it's exciting to see, that we can lay the groundwork. We can set the future generations up for greater success than we were able to achieve. Yeah. That's how I think about.

Kevin: It. I agree. I think that. think that what's interesting that the solutions that we all have to come up with, the most difficult part is in this part around the incentives for to actually grow be deployed in a way that it has a consequential effect. it's the problems to solve aren't how do we how does this work?

Yeah. the problem is, how do we get everything and everyone.

Pablos: Behind it?

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Recorded on August 13, 2026