Can AI driven data save our whales? Emily Charry Tissier, Co-Founder Whale Seeker

In my part of the world, North Atlantic right whales are a critically endangered species with an estimated population of fewer than 360 remaining individuals. 

Most of these deaths in New England and along the East coast are human-induced, overwhelmingly driven by vessel strikes and entanglement in commercial fishing gear. Over 85% of right whales are estimated to be entangled in fishing gear at least once in their lives, and whales are frequently struck by boats of all sizes.

Managing this situation has been challenging for all. But could AI powered data solve the problem? Our guest today, Emily Charry Tissier thinks so. 

Emily is a data specialist who hails from Montreal, Canada. In this episode, she describes how her company, Whale Seeker, harnesses the power of AI to analyze captured marine mammal data, improving marine navigation, and protecting these vital and beloved animals.

Emily Charry Tissier

Whale Seeker

Transcript

Abigail 0:11

Welcome to the podcast where we celebrate innovation for a happy planet. I am your host, Abigail Carroll. In my part of the world, north Atlantic right whales are a critically endangered species with an estimated population of fewer than 360 remaining individual. Most of these deaths in New England and along the East coast are human-induced, overwhelmingly driven by vessel strikes and entanglement in commercial fishing gear. In fact, over 85% of right whales are estimated to be entangled in fishing gear at least once in their lives, and whales are frequently struck by boats of all sizes. These collisions. Managing this situation has been challenging for all. But could AI powered data solve the problem? Our guest today, Emily Shari thinks so. Emily is a data specialist who hails from Montreal, Canada. In this episode, she describes how her company, whale Seeker, harnesses the power of AI to analyze, captured marine mammal data, improving marine navigation, and protecting these vital and beloved animals. But let's hear it from Emily. welcome to the podcast, Emily.

Emily 1:37

Hi Abigail. Thanks for having me.

Abigail 1:39

I'm delighted to have you here. You have a business that is all about, marine mammals. What problem is whale seeker trying to solve?

Emily 1:50

I'm a community ecologist who married a marine biologist. So it the reason that I started Whale Seeker was really because I saw that marine biologists. Have such a huge amount of work to do and interpretations to do and deciding is a population healthy, not healthy? Where is its range? And they need to decide all of these really complex things and they don't have very much data to do it with. And all the decisions that, that they make, they're really the first domino in a series of business. Ecological events, political events. And we're really concerned with the downstream ones. So for example can a port get expanded? Are we allowed to drill for oil? Here are, where are the shipping lanes going? Is this marine protected area doing its job or not? And. What I saw was that in using aerial images to detect the presence or absence of whales, what species are they, how are they using the habitat? Are they in a group? Are they not in a group? Are they adult? Are they juvenile? What species are they? All of that data was taking a really long time to get through. And then the marine biologists really didn't have very either they had a small amount of timely data or a large amount of data that was really outdated. And and that was happening in all of those different verticals that I mentioned. And so I thought if we could just solve this one problem, this one data problem, and we would be able to help a lot of different. Areas that are impacting the ocean and the blue economy and conservation and climate because we know that every other breath that we take is thanks to the ocean. And if we don't have a healthy ocean, we have no hope in tackling the climate problem. And so because I love data so much, I thought, there probably are a lot of people who should be doing this instead of me. I had huge imposter syndrome, but I thought, why am I just do it until someone else does it better? And then I'll pass the torch onto whoever that is and they can do a better job. And it, I'm still here. So I just, I found a lot of people to collaborate with, but no one who's doing this one piece the way that I think it needs to be done to have the most impact. And so that's why in 2018. We, my husband and I, and our third co-founder created Whale Seeker to really tackle this one issue of visual marine mammal detection. can we do it better? How can we do it more cheaply? And we saw too that the way the arc of technology was going in terms of ai, we knew it was only gonna get better and more powerful. And we knew that the hardware was only going to get more powerful and cheaper as well. And so we thought if we could just set things up now in 2018 when AI was not a thing yet how can we make sure that we do it and we do it right from the beginning? And which is also why we always intended to be a certified B Corp. And really. Really do things differently. So that's why it's because I had to bug up my butt about bad data and

Abigail 5:35

With good reason.

Emily 5:37

yeah.

Abigail 5:38

Also'cause the ocean is so vast and it's like most of the planet is ocean, and yet we know so little about it compared to what's on land because it's so much harder to access.

Emily 5:50

It is true. It's so expensive. It's really hard to access. There are just these sort of black holes of data and, but what I love about the ocean community, whether it's just, research or the blue economy innovation, is that they're so collaborative because I think everyone feels like they're really up against this giant of a task, and we need all hands on deck. And and what we've seen since we've started it is, underwater gliders going everywhere and providing underwater acoustic data to, in the depths to that we really had no idea about. And so technology, and we are dealing with satellite imagery. So technology has done its job in the ways that everyone knew that it would go. And so it's, yeah, it's a different ecosystem now than when, than we started Than's for sure. Yeah,

Abigail 6:48

Why are marine mammals so important to this data about the ocean?

Emily 6:55

think a few different reasons, marine mammals, so people don't tend to. Really care about things that they don't understand or they don't wanna save, things that they don't care about. And so all those charismatic mega fauna, they're a way to hook people in. And they're a way that, that people can understand, families, we, I have a family. The seals have family, the walrus have family, the whales have family. It's a way, I think, for us and some people who are maybe not very connected to the ocean, to feel some kind of connection to the ocean. And then we can talk about the habitat and everything like that. And the other thing that's so important about marine mammals is, by and large, they're a long-lived species. They use a lot of the ocean basin, and they have they're a real part of human history too. And on top of being indicator species for how well the ocean is doing. It can really track big trends in the way that the health of the ocean.

Abigail 8:06

And aren't they fertilizers of the ocean

Emily 8:10

Yeah. So specifically Satans Yeah. So specifically whales. Yeah. They really are in really interesting ways too. Regarding using, some species use the whole ocean basin and some species don't move at all. And so there, there are some species, like the beluga in the St. Lawrence there they stay within the St. Lawrence area. In the St. Lawrence Seaway. And there are some species that migrate really a far ways. And so what I think is so interesting is areas like in the Arctic that is nutrient poor. The whales, when they come to migrate to certain areas, their feces provides a lot of fertilization for the primary producers in the ocean. All the plankton. The phytoplankton. And then very interestingly too, when they migrate closer to the Caribbean, they're not contributing that much to the, to fertilizing because they're not really eating at that time. They're having their babies and they're in a safe place. And so the way that they're using the habitat and the way that they contribute to the ecosystem is really dynamic spatially and temporally as well.

Abigail 9:27

Wow. Fascinating. So you started this in 2018 and it is 2026. Last I

Emily 9:35

Yeah.

Abigail 9:36

The world's changed a lot since then, and technology has evolved a lot since then. What are the tools available to you today and how have they evolved over the last sort of eight years?

Emily 9:50

Yeah, so the main tools we had when we started were manned aircraft, aerial surveys. So cameras strapped to an airplane with biologists in the airplane. And the photographs were used to support, mainly to support the human detections. Human detections, humans are detection, are detecting the marine mammals. And since then. Because of drones that are able to operate in more extreme conditions, go further offshore have autonomous systems in them the payloads being much lighter too and much more powerful than they were back in 2018. There's a lot more versatility. There's also different types of imagery besides electro optical. So there's infrared, there's all kinds of, there's very powerful in infrared. But then you don't have a very wide field of vision. You can have a less powerful infrared camera to increase your field of vision. So you're always doing trade-offs. And what I, and I think one of the disconnects that, that I think will always exist is humans are looking for one. One golden ticket, one, one solution that's gonna solve everything. But what we're seeing is we have more tools in our toolkit. So like a carpenter has more tools now to do their job more efficiently in building a cabinet and building a house. How do biologists and ecologists and politicians and economists, what tools did they have at their disposal to be able to make better decisions and gather data in different ways depending on different environmental conditions, different budgets different questions that you're trying to answer. And I think the wealth of solutions is what we have now that we didn't before, and the tech integration. Now the, I think one of the biggest things that we have now is there's so many opportunities to leverage AI with no code, and so how are we gonna optimize the way that we work? How do we optimize the way that we communicate? And in using ai I, I don't want to you to have to read between the lines. We absolutely must use our thinking caps. We cannot toss common sense out the window. We need to be involved. We need to use our critical thinking now more than ever, and we need to act on our critical thinking now more than ever. And so AI is a very good tool to help humans do their job in a faster way, a more powerful way, more effective way.

Abigail 12:43

AI seems to be very helpful at processing data and finding patterns that would take us maybe longer.

Emily 12:53

That's right. Yeah. So computers are good at doing like the heavy lifting and going through a lot of monotonous data. And so what computers are really good at doing in our use case, for example, is going through mountains of data and saying, okay, there's no whales in these, and then there's something in these images, and these are whales. And then what it will flag for human review are those judgment cases where it's not sure what is a whale in an image. That wasn't real, that's not defined very often. And when we talk about human expertise, oh I'm an expert. What does that mean? Have you spent decades in an aircraft and in a boat on the water? Observing these animals from different angles, or did you just graduate with your master's and maybe have been in the field three months? What is, what does an expert mean exactly. And so I think we need to we need to define things a little bit more. And that's where, without these definitions, AI's not very good because it needs to be really hemmed in and told, this is a target. This is not a target. This is a target that looks like what it is, but it's not right. And then there's different environmental conditions. And so we knew back in 2018 that AI was the only. Statistical tool that could go through the amount of really messy real world data that's out there, especially with the ocean. So detecting targets in the ocean is a very different approach than detecting targets from terrestrial images.'cause we're not necessarily looking for shadows. We're not necessarily looking at a static image and what moves between one frame and another, and the ocean. Everything's moving all the time. So how do you detect it then? So there's some really fundamental questions in what are we looking for? What is the question that we need to answer? And then those AI tools can evolve from there. But a lot of that fundamental work hadn't been done only because we didn't have, we didn't need to, we didn't have that luxury either to spend a lot of time on those. First dominoes I like to call them. Really, people needed to know, let's get our people up in the air and are there animals here? Is the population healthy? Do your best. Now that we have more tools, we can back up and say, okay, what are we really looking at? How are we using these tools? Does this make sense? I assume that in using Chachi PT and Claude and Gemini now, we've all seen mistakes. And so we know that we can't trust it with our eyes closed and we know what it's good at. And so we need to always be reviewing the data. Does this make sense? Should there be a whale in the middle of this lake? Probably not. So

Abigail 16:05

It's an inflatable,

Emily 16:06

That's right. Yeah.

Abigail 16:08

I'm interested to know, it sounds like you're getting a lot of visuals from the sky, but a lot's happening underwater, is what's happening on the surface enough of an indicator so you can project what you think is happening under the water? Or do you have a way of tracking what's under the water or does that not matter because your applications like shipping are more surface related anyhow.

Emily 17:09

that's a great question. Is it good enough? That depends on what question we're trying to answer. A lot of times we're fighting against. We don't have much here anyhow, so anything more is better than what we have right now. And so I think it's, I know that especially working in the world of ai, everyone is looking for perfection when and not accepting of any errors, when really what we're just trying to do is do better than what we have right now. And what we have right now oftentimes is very little ocean data. And so how can we move the dial forward? And so the good thing about marine mammals is that they're mammals and they need to breathe. And that happens at the surface. So we know that they need to come up for air and it is a good way to detect marine mammals. It's not the best standalone solution. And I don't know that there are any great standalone solutions that will work for all scenarios. The North Atlantic right? Whale is a very good example of that. So because it's such a slow animal and it's so vulnerable, one of its mechanisms for avoiding predation is to be silent. And especially when it's a mother with its calf spending so much time at the surface, extra vulnerable, they don't vocalize very much. And so having a suite of hydrophones off the eastern seaboard of Canada and the US is very good. And when they're vocalizing. I hope they will be detected, but it's not the best way to detect that species. Whereas some of the more vocal the whales that hunt that have teeth like we have, that are not the filter feeders they echo locate. And so they're much more vocal. And so hydrophones are a more powerful tool for detecting those animals. And so it's really a trade off. And what I love about what we're doing is we're not trying to solve everything. And so we collaborate with with researchers and with different companies that do have an underwater acoustic component to it. So we can do the top down imagery, they can give us the underwater noise. And so we can, in combining all these tools together. We can get a much more accurate idea of what's going on in the ocean.

Abigail 19:46

it sounds absolutely amazing. So what is this? How does this present? What is the product and like what does the market look like?

Emily 19:57

So we have three products that we've developed over the years. So our first is our flagship solution. It's called Mobius named after the Mobius Loop where it's, so it's a human in the loop. AI plus a human is what the solution is. And so this is a non-real time bulk aerial image analysis solution where. One of our clients does a big aerial survey, for example, for environmental impact assessment, maybe some baseline studies or yearly yearly surveys that need to be done. They send us those hundreds of thousands of images. We analyze them. We have biologists in house, and what gets sent back to them are the locations of the detections and a spreadsheet that is ready for analysis.

Abigail 20:52

Yeah.

Emily 20:53

So we just detect what's in the images. We don't interpret what does that mean and what should be done because of that, because there are so many people who are experts and much better placed to, to do that than us. So that's our first and we collaborated with Fisheries and Oceans Canada and we. Looked at, going back to we need to do better than what exists now. We looked at a completely manually annotated data set from Fisheries and Oceans Canada and blindly. We analyzed that same data set and then we compared metrics. So how long did each take? What were the detections? How many animals were detected? And so are we as good? Yes, we were as good. We were much faster. We used less energy than doing it all manually as well. So it's also an example of ai, not being generative, AI being more analytical AI and actually having an energy cut because of it. And so it's important for us to be working with regulators so that we can prove that we are at regulatory level and that. People can, they, if they're trusting humans to do this job, they can trust this AI plus humans to do this job. And then our second solution that we developed is called C dus. And it's detecting marine mammals from very high resolution satellite imagery. And satellite imagery has come a long way since 2018 as well. Happily so that's also been exciting. And those two solutions have been recognized by UNESCO as some of the top AI projects in the world to meet the sustainable development goals. And we know that SDG 14 life underwater is the most underfunded on this blue planet. So we are doing our best to show that there's really rigorous scientific and ethical. Tech work that's being done to tackle this so that we can do this at scale.

Abigail 23:05

Yeah.

Emily 23:06

And then the solution that we are ready to launch in our beta testing in the field with some partners right now is called Mobius Observer. And it's our Mobius algorithm, Mobius light where it's for marine mammal observers to work on a laptop in the field using a drone. And so it's an algorithm that flags the presence of whales and then the human MMO needs to say, yes, I accept this detection. No, this is a false positive. And then they take all the notes, accordingly. And, but what's great there too is that you can audit those those data, which is also something that. It doesn't happen very often for visual observers. Oftentimes there isn't any photographic proof because of the angle that you're looking at, or, it's just a blow and you missed it with the camera, yeah. So those are the three solutions that we have. How is the market looking? It has been really rock and roll in the past year and a half, Abigail

Abigail 24:19

am so happy to hear

Emily 24:20

yeah, it has, it's been really wild. Because environmental impact data and doing things faster and better is something that, offshore, renewable energy is very interested in, and it's been offshore energy is the future. Offshore energy kills whales. Offshore energy is necessary. Oil, drill, baby drill and so it's been like, it just been so volatile, I would say more than any other time. And at the same time, because we've seen geopolitics really rock the AI world, rock, the DEI world valuing, valuing nature, what I am really hopeful about is everything that came out of the United Nations Oceans Conference and the Blue Economy and Finance Forum this past summer. And, really getting the multinationals. Invested into de-risking and scaling these solutions, collaborating blended finance. So getting the World Bank to work with the VC to work with with a state or with a a conservation organization. And so these sort of unconventional pairings is what came out of, by and large what came outta these meetings. And so we're seeing interest in we know we need to create something and we, and, but how do we do that really is the next step, so now everyone's at the table saying, yes, we need financial less institutions and we need governments and we need international regulatory bodies involved. Okay. Now how do we do that exactly? And there are some great examples of there are some great examples of that. At a I say small scale, but it's not small for a nation to use it's blue capital for a debt for nature swap. That's revolutionary. But I would like to see it happen on a larger scale. And the point that gives me hope is that none of these new investment mechanisms or insurance solution insurance solutions can happen without good data. And that's the space that we're in. We're back to the first domino again, and how can we be sure these data are trustworthy and accurate? Yeah.

Abigail 27:05

It sounds like you've got, you're covering the bases. We just need everybody to come and play and invest. Is that happening? Are people like coming and saying, we need to do this, like this is this is part of our mission. Are corporates doing that?

Emily 27:23

I have seen a decline in corporates doing it. So I think as, as soon as the ESG rigor and the DEI rigor was taken off the table, all of the companies who didn't truly have that as a core value, it, they tossed it to the curb as soon as they could.

Abigail 27:41

The fakes.

Emily 27:43

yeah. It was a real easy way to see who was greenwashing after all, and so what we've seen is real serious engagement from the corporates who, who have held onto that and said no, this is really who we are, and this is a way for us to be resilient in this economy and this landscape that's happening right now, but. I, what I've seen is investors and corporates and governments, everybody's holding their breath, and I understand because they don't know what's gonna happen next. And it's a time of a lot of financial, a of economic volatility. And so I don't really blame them, but it's hard because it's been, a year and a half of everyone holding their breath and we just need to move. Like we need, someone needs to go, okay, I'll jump in the pool first and let's do something brand new, and I think that's especially hard because even before the geopolitics got to this point, blue investment was really hard because. VCs wanted the same quality of metrics as the terrestrial economy has, and the blue economy didn't have that luxury. And so the blue economy and blue innovation and blue startups were very much building the plane on the way down off the cliff. And that doesn't meet the financial ethos of venture capital. And so what's another way for, we know that and we knew that venture capital wasn't the cure all solution for blue innovation and for the blue economy, which is why the blended finance was such a very big thing to come out of these, conferences this past summer,

Abigail 29:37

No.

Emily 29:38

but what does that new, what does that look like now? I'm not really sure. And so it's hard because I feel like we haven't been able to go all in yet. There hasn't just been, yeah, I don't know. How do you feel about that?

Abigail 29:53

I it's such an interesting subject and, I've been doing this podcast now for quite a few years and I've been doing a little bit of angel investing too, and I have this sort of gripe of we call everything a startup

Emily 30:08

Ugh. Yeah.

Abigail 30:09

and it's so loaded with these like connotations of a Silicon valley.com kind of styles or whatever, crypto startup that's gonna give you a hundred time multiples and things like that. And I, and then we have all these accelerators, which put even more pressure on it. And I love these accelerators. I think it's, they're so great, but the, but they're all enshrouded in these fantasies about what the outcome is supposed to be.

Emily 30:36

Yeah.

Abigail 30:36

maybe the outcome for some of these companies is just like a solid income for a handful of people. And that's okay. And I think we just need to be really mindful that not everything is a startup and we shouldn't be looking through this startup lens at everything. And there's gotta be a different, I think, vocabulary, like even because the, language matters. And and I think, and this focus on as you said, I think we need a different funding. Maybe dividends are okay for some investors in some situations. Like, why are we always looking like the exit can't be the holy grail because not everything's gonna exit,

Emily 31:18

yeah. That's right.

Abigail 31:19

in a hundred years, and

Emily 31:21

And how do we operate outside of a four year fund or like a 10 year fund, or how do we operate outside of an election cycle? Because I feel like all those decisions are made very strategically. Oh, these two years I can be riskier, then I can't be risk. And I feel like some of the organizations that are doing the most meaningful work are the ones that are just privately family owned or an NGO, and they don't have to worry about the ups and downs of this as much as we do. What do you think that, what vocabulary would you use? What have you been kicking around in your brain?

Abigail 31:58

I don't know that I have a solution, but I do think there's like a, there is something, I think very special about these sort of activists, entrepreneurs, these mission-driven. Companies. And what I think is so interesting is that a lot of them probably could just come out as non-profits. So I think it's like a bold choice to come out as a for-profit. And I think that's good.'cause I like, I'm still hopeful that there are, profits to be made. I don't know if there's like massive investor multiples, but, even on an investment basis, I think there should be some profits to be made in investing in these businesses that are really like B Corp and trying to do helpful things to the planet because the. They have a different role too. If you're a nonprofit, you're not contributing taxes, you're not, there, there is a, an advantage to our communities to have these companies be for profit companies. But but I, it's a conundrum, but I don't think we should be calling them,

Emily 33:06

startups.

Abigail 33:08

Or we just really need to have a little bit of an exorcism of the word startup and pull out like the high tech ideas in it, which is, these fantasies about multiples. And I see it sometimes in these, showcases where they showcase a bunch of startups and then there's there's one that's clearly gonna make massive multiples and others that are worthwhile, but they don't get the attention because they're not they're just, isn't that lever to

Emily 33:35

Yeah.

Abigail 33:36

crazy multiples.

Emily 33:37

Yeah.

Abigail 33:38

so I do think you're, all of this about financing is really hitting the nail on the head about some of the things that are keeping the ocean economy and a lot of just the green economy

Emily 33:52

and

Abigail 33:52

a little bit, in, in LA Cold,

Emily 33:56

yeah. And one of the big in terms of funding, we meet a lot of the philanthropic funding goals in terms of what's your scale? How are you working, what are your values? But the way that our legal structure is, we're structured as a for-profit, therefore, we're not eligible for the philanthropic funding. Is there a way that philanthropy can maybe rejig their distribution? Like how can some of the outside of VC'cause VCs aren't all the devil. What how, what other ways do you think this blended finance can, the, this partnership and this risk sharing can look like, what other unconventional sort of ways do you think that can happen?

Abigail 34:50

There are organizations that have done really smart things like Schmidt Schmidt Marine. They were on the podcast and they are basically fostering and putting money into these marine programs. These projects, which are all, most of them are profit based. So there are examples of this being done in a very smart, thoughtful way. And I think that comes down to, again, activist investors need to meet the activist entrepreneurs. And maybe that's just the word. Maybe the hot word is activist

Emily 36:07

I like that.

Abigail 36:08

and maybe there's more debt financing,

Emily 36:10

yeah.

Abigail 36:11

If you're not gonna get a multiple, you might be able to get your money out sooner if you're just gonna give somebody a debt. Debt at a decent rate,

Emily 36:20

Yeah. It's true. Yeah. It doesn't have to be maybe more complicated. Yeah. One of the, one of the things that we've been working on is so we have all these different technical solutions and we see them. Being used in, energy and government and conservation and, all this stuff. what we're seeing is that there's missing a scaffolding for the, for all of this data to fit into that makes it a carrot instead of a stick. So it's not, it doesn't have to be a law because we know that governance lags behind technology, which is normal even though I wish it was accelerated. But how can we make nature visible to the market and engage insurance and engage these large regulatory bodies like the IMO and the IHO. And how can we grease the wheels for the TNFD to really dive deeper into the ocean economy? So I'm curious about all of that. So we've created whale seeker certified routes where we did a case study looking at a Panamax a Panamax vessel going from Montreal to so it's going, it's crossing non-negotiable water that hit is full of critically endangered species. So two, at least,

Abigail 37:56

which are those? The north, the

Emily 37:58

so the. That's right. North, north Atlantic, right Whale and the St. Lawrence Belugas. And so those are two of the critically endangered ones that are within Canada at least. And so what we looked at was what's the normal trajectory? What's the normal path that they would've taken at, going as fast as you can across the ocean. And then we provided them some data layers and said, okay, these are the legal slowdown areas. These are important marine mammal habitats. These are, and it's not just, they're not all just squares on the map, it's not a political boundary. They're really, they're like the messy polygons that actually show where the habitats are. And we said if you can, if it's safe to do avoid. Or slow down in those areas. And so that's what they did. And they, we looked at the difference between those two.'cause we wanted to just look at it

Abigail 39:01

Yeah.

Emily 39:02

before to say, is this even economically viable or should we just, or do we need to flip this on his head and look at it a different way and it's economically viable, it's cheaper, it's it's slower. They burn less they burn less fuel, they burn less of the dirty fuel. And so it's really this triple win. And there's so much talk around the triple threat of shipping. So decarbonization pollution, which includes noise pollution, so underwater radiated noise and biodiversity. And I was cheering a session at Monica Ocean Week a couple of years ago on this triple threat, looking at what tools do we have to address them. And the IHO was just rolling out its new electronic chart system called the S 100, and they were saying, look how exciting this is. We're gonna be able to reroute vessels into ocean currents and use ocean currents so that they don't use as much fuel, and this is gonna drop this percentage of carbon and fuel use overall. And we know that shipping has a long way to go before it reaches its decarbonization. And those are very expensive investments, retrofitting vessels, different fuel types. There's they're big, systemic expensive changes that they're doing, but they're expensive and they're not immediate just with rerouting. They could have those benefits, but not being a hydro and being an ecologist. We know what everyone learned in Find Finding Nemo is that ocean currents are biodiversity super highway. So in, in having a positive effect of what they wanted on carbon, they're having a negative effect on biodiversity. But there's no metrics to measure that biodiversity. So we can't we can't manage anything that we don't measure. And so what we have developed is a system for having a biodiversity data layer within these navigational charts. And so that didn't really have a place to live until the S 100 system got a bit more, more mature, which it is now. And now there's real there's real acceptance for it. We published this case study and now there's real economic traction. So there's the potential for insurance to get involved. There's the potential for assurance, so limited assurance and reassurance. On the flip side of this, creating new blue financial levers. So is it a blue bond? Is it a marine biodiversity, risk reduction credit? Is it like, like what are those ocean credit systems that can be created? I am, I'm not in finance, so I don't know what those financial levers and insurance leavers can be, but I know that they need good data. To exist. And I, and that's what we're building out is to say, okay, there are all of these things that are not moving because we're missing data and we don't have the scaffolding for things to latch onto and grow. And so we have interest from these multinationals. We have interest from third party reviewers. We have, all this interest, but don't know how to fund the in-between. So creating this new sort of financial structure, who funds that, when it's really creating something new. And so I think so those are some of the, those are some of the blind spots that I have in growing something that is not a traditional startup trajectory.

Abigail 42:55

No, of course. You're in the middle of so many holding patterns it seems like.

Emily 43:02

That's a great way to put it. That's, yep. Absolutely.

Abigail 43:11

You are an entrepreneur and you have been at this for a long time, and you still are here. So do you have advice for other activist entrepreneurs that, that may be facing headwinds too?

Emily 43:26

I I'm sure they're all facing headwinds, especially now. I would say find your tribe, find your people. The people that you can be really vulnerable with that will give you the, maybe the ugly answer that you don't, that you don't wanna hear, that will help you really critically think about pivoting or some wacky idea that you have not considered yet. Or something that you tossed out a long time ago. I think now more than ever, is the time to surround yourself with the people who will be real with you. And that doesn't mean pessimistic. It means who really get you and will help you trudge through the sludge. It's really hard to lead in these holding pattern times. We don't know what's happening and people are looking to the CEOs for, what are we doing and what's happening. I don't

Abigail 44:20

it Annoys me at one time. I'm feeling like, oh, the government's changing their policies. And I'm like maybe this is, it's more important than ever to dig in and I'm sorry, but Trump changing environmental policy doesn't have to change how, companies ship their products across the Atlantic. Whether or not they're happy to run into a whale or a beluga or not. Come on, gimme a break. That's just more excuses. I do think it's, I do think it helps, to your point earlier, you need to have something that's economically viable, because if you're just adding costs, you're not, it's. To these companies that might feel like a luxury. And then the cost of these products, every, there's so much inflation every, anyhow, it just keeps going up. And so you're not helping consumers. I think we need to find ways that, what's good for them is good for us, deal. But I, we can't just sit around waiting for policy because,

Emily 45:17

we cannot.

Abigail 45:18

that, when, you mentioned earlier, we're just, been holding our breath for the last year and a half. Given that, as you said, even earlier than that, every other breath comes from the ocean. When you do finally decide you're gonna take that breath, you wanna make sure that the air is clean and there's actually oxygen in it to breathe. I think the time is now more than ever.

Emily 45:38

I agree. I agree. I agree. Yeah.

Abigail 45:42

So I ask everybody because the title of this podcast is Happy Planet. Are you optimistic at all?

Emily 45:52

I am optimistic. I am optimistic because it's not like with the Instagram and LinkedIn culture, but there are so many really. Smart people trudging through it right now and they're not giving up. And so just to see the real sort of invisible work that's happening and that people are really digging in, that gives me a lot of hope. daughter's nine. I want her to have a healthy planet. I want her to see whales in the wild. I don't want her to just watch documentary about what used to be. And so I have to be optimistic and I, and the pendulum can only swing so far. And let's grease the wheels for it to swing back in the other direction and be ready for it when it does. And, get all the kinks out of everything as much as we can so that when the world does shift back again, we can just scream in the other direction. That's what I'm, that's what I'm hoping for.

Abigail 46:55

You also said when,

Emily 46:57

Yeah when, yes.

Abigail 47:00

All right I'll take that.

Emily 47:01

Thanks Abigail.

Abigail 47:03

so much, Emily, for coming on the podcast today. It's really been a pleasure to hear about your venture and your and you've got a lot of grit, so that's what it takes.

Emily 47:13

Yes, it does take grit. So yeah, to everyone else, just keep it up. And thanks for talking about this stuff and being honest and asking the hard questions. I really appreciate it and I feel like we need to see people more deeply now, more than ever. So thanks for your work, Abigail.