 I'm here today to talk about, to answer the question, if crowd sourcing of data can actually make the world a better place, planet Earth better. This is something that I'm truly passionate about and I hope some of you in the audience are too. I know for sure that's one of the previous speakers, Al Gore, he definitely is. So to give a little bit of background on the company that I'm currently running and why this makes sense for my presentation today. The FishBrain is the platform for the world's by far biggest hobby, sport fishing. Globally, half a billion people fish. This is more than play golf and tennis combined. It's also a massive industry. In the US alone, it's a $48 billion industry, which is roughly three times the global music industry. And FishBrain actually almost got started here on stage at Slush because a couple of years ago we were pitching here and won the pitching competition, only a couple of months after we started the company. So I'm very happy to be back here on stage again. Now we have four and a half million users globally, three and a half million catches. Can you imagine how much fish that is? But our mission is connecting anglers to make fishing dreams come true today and tomorrow. And it's the last part of our mission statement, today and tomorrow. This speech is all about, this talk is all about, because that's about conservation. This is about sustainable fishing. We want to make sure that the fantastic sport of sport fishing is not only possible today but also for the future generations to come. So back to the topic. Why does data matter? Why is this important at all? I can tell you, data is very, very important because the researchers, they build their models and they're making predictions, but they need the data to see if the models are right, if they don't have enough data or if the error is or if there's wrong data, then the predictions will be wrong because these predictions are actually used by the decision makers when they set the rules and regulations. And you can see a couple of the graphs here are on the global warming. And what if those models were wrong? And then some politicians, unfortunately, decide to stick their heads into the sand and ignore the predictions altogether. But that's a discussion for a separate talk. I want to go through two different ways of collecting data today. The first way is this is the NOAA way. This is the National Oceanographic and Atmospheric Agency. They oversee fishing, commercial and recreational in the States. This is the form you actually have to fill in after you caught some fish. Actually, you need to figure out which form to fill in to begin with, because they have 40-something on the webpage. And they realize this doesn't work. So today, they're actually sending people to the shores, to the docks, to fill in the survey for you, which takes roughly 16 minutes. This doesn't sound very scalable to me. This is 2017 right. So let's take a look at another way. This is the fish brainway. So first of all, all anglers, they take a picture of the catch because they want to brag about the fish. Using machine learning, we can automatically detect the species. You can see in the picture here, it's not a very good picture, but we can see it with the 99% accuracy that this is a northern pike. Then the user enters the weight or the length of the fish. This we will also be able to automate when we get the depth information from the mobile cameras. Then, of course, we get the position automatically, time of the day automatically. Same with the weather. We get a ton of different weather information. High level, like it was it sunny, it was it rainy, all the way into the nitty-gritty details like air pressure, water temperature, wind speed, wind direction, tide, moon phase current, you name it. So a ton of data. And then, so the entire process takes less than 60 seconds, not 60 minutes, 60 seconds, which makes all the difference because if you ever fished, you know that you're quite busy when you try to land your dream catch. You don't want to lose your dream catch, so that process has to be dead simple. Then after you've posted your catch, the user has posted his catch. It goes out to our community and they get the social encouragement they deserve, rightfully deserve, for landing such a great catch. And this actually encouraged them to log more catches. So this is another way of doing it. I can tell, what's the difference between the two approaches? The first method, the NOAA way, they collect data points, catches in the thousands every year. Where's our method? We collect data in the millions. And this makes an enormous difference when it comes to the actual predictions you can do based on this data. The source of use difference in cost, because the first one is very expensive. You have to send people to the shores to the docks, cost millions of dollars. Ours is free because it's done by the users, our users. So let me give you a couple of example how the data that's being collected on Frisbee is actually being used. So what does this odd-looking fish has to do with making the planet better? If you don't recognize it, this is a lionfish. And it's a very popular species to have in an aquarium. And that's where the problem begins. Because a lot of people, after a while, they get pretty tired of this aquarium. And then they don't know what to do with the fish. They don't want to kill it. So they think it's a brilliant idea to take the fish and actually throw it back in the water closer where they live. I can tell you, it's a terrible idea, especially when lionfish is released in Florida. Because most of the time, it doesn't really matter because the water is too cold or they're predator fish. So the fish, poor fish, will die immediately. So then it doesn't matter. But that's not the case with lionfish in Florida because it's the perfect temperature for lionfish in Florida. And there's no predator fish going after them. And the issue is that lionfish is a carnivore. And it feeds on small and native species, like important species, like grouper and snapper, almost making these species go extinct. So it's a massive problem. So how do we help out here? So we work with the Florida Wildlife Commission. We have a ton of users already on fish bait in Florida. So we implemented this list in Fish bait. So when they log a species that we automatically identify is an invasive species, then the recommendation is not to throw it back in the water again, but actually eliminate the fish. And then also, we share this data with the Florida Wildlife Commission. So they can actually see how these invasive species, how they spread out in Florida. And they can actually take measures based on the data. They've never been able to do that before. Give you another example. This is what we do on the nationwide level in the states with US Fish and Wildlife Service. And this was big news when announced. It made it into 147 publications, including this one is from Fortune. And here, similar setup, but this is around endangered species. And fortunately, there are many of them. So we implemented this list in Fish bait. When a user logs a catch that's an endangered species, you can see some of them on the right-hand side. The list is unfortunately longer than this. We can inform the user that please do not kill this fish. Practice catch and release. Let the fish go back in the water again. Then we can inform the user this is the best way of doing it to increase the survival rate of these species. And this is working out. And then we, of course, share the data with US Fish and Wildlife Service so they can much better than before track the health of these different species. And if the population goes down, they can actually set stricter rules and regulation based on all the data that we are collecting. Before I want to give you two other examples that are not from FishBrain on how the crowdsourcing of data can make the planet better. One is from Waze. This is an app for crowdsourcing traffic information and give you recommended routes based on that. It's very, very popular used by millions of users. I'm being one of them. And this is not only saving the users a lot of time, but also cut on the CO2 emissions. And this is also an example of how it can be good business to crowdsource data because Waze got acquired by Google for $1 billion a couple of years ago. The second example here is an app called Strava, which is an app for cyclists. So cyclists, when they go out biking, they store their bike rides on Strava. So how can this data be used? Actually, in a very, very smart way, because the city planners today, they use this information when planning new bike lanes so that biking gets safer, faster, so more people can take their bicycle to work. Don't have to take the car. Again, saving CO2 emissions. So two other examples. So to answer the question, my original question, can crowdsourcing of data actually make our planet better? The answer is a big yes. And the experience. We've done this now at Fish Planet for a couple of years. Our experience is that users actually love to contribute with information, especially if they see they do it for a greater cause, what they do actually contribute to making the planet better. So they love this. And I want to end this presentation with a pledge. And this pledge, which I'm very proud of announcing on stage today, is to share our fishing data for free with nonprofits working with marine conservation initiatives. And this is a big thing. And I'm very proud of this, because as you saw, this is part of our mission statement, making sure that fishing is available not just today, but also for future generations to come. So if you know anyone working with marine conservation initiatives, send them our way. Thank you. And make sure you use Fish Planet when you're fishing, because then you may actually contribute to making the world better. Thank you.