{"id":254047,"date":"2026-09-29T23:18:28","date_gmt":"2026-09-29T21:18:28","guid":{"rendered":"https:\/\/tropica-verde.de\/interview-with-frauke-fischer\/"},"modified":"2026-09-29T23:21:35","modified_gmt":"2026-09-29T21:21:35","slug":"interview-with-frauke-fischer","status":"publish","type":"post","link":"https:\/\/tropica-verde.de\/en\/interview-with-frauke-fischer\/","title":{"rendered":"Can AI Save Nature? \u2014 An Interview with Dr. Frauke Fischer"},"content":{"rendered":"
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Can AI Save Nature?<\/strong><\/h2>\n

Artificial intelligence (AI), designed to map the night sky, suddenly starts recognizing whale sharks in Instagram photos. It sounds like science fiction, but it\u2019s actually an example of how AI is used in nature conservation. Dr. Frauke Fischer\u2019s new book explores this intersection.<\/p>\n

Frauke Fischer, who holds a Ph.D. in biology, founded the agency \u201cauf!\u201d in 2003, which advises companies on their commitment to sustainability, climate protection, and the preservation of biodiversity. She is the co-author of the book \u201cPlanet 3.0 \u2013 Climate.Life.Future,\u201d published by oekom Verlag, as well as \u201cThe Palm Oil Compass,\u201d \u201cWhat Has the Mosquito Ever Done for Us?\u201d and \u201cWhales Make the Weather.\u201d In October 2025, oekom Verlag will publish her book \u201cCan AI Save Nature? How Artificial Intelligence Can Protect Animal Species and Ecosystems and Revolutionize Environmental Protection\u2014Opportunities and Risks of the Technology for Our Planet,\u201d which she co-authored with environmental economist Dr. Hilke Oberhansberg (216 pages, \u20ac26.00, ISBN 978-3-98726-163-3).<\/p>\n

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She has a long history with Tropica Verde: As a student in Frankfurt, she witnessed the founding of our association by her fellow students. Today, she is a member herself.<\/p>\n

We\u2019re giving away three signed copies!<\/strong><\/h2>\n

Frauke Fischer is providing us with three copies of \u201cCan AI Save Nature?\u201d signed by her, which we\u2019ll be giving away to our subscribers. <\/em><\/p>\n

Send us an email by October 25, 2026, with the keyword \u201cAI\u201d to Presse@tropica-verde.de. The decision is final.<\/p>\n

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AI in Nature Conservation: Dr. Frauke Fischer in Conversation with Tropica Verde<\/h2>\n

You've been a member of Tropica Verde for a few years now. Maybe you could briefly tell us what connects you to the organization and where you see overlaps with your research.<\/strong><\/span><\/p>\n

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First of all, my connection to it, of course, is that I witnessed its founding, so to speak, firsthand. When I was a student, Tropica Verde was founded by some of my fellow students who were a few semesters ahead of me. I think Stefan Rother was there at the founding, too, wasn\u2019t he?<\/p>\n<\/blockquote>\n

Yes, exactly.<\/strong><\/p>\n

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Exactly, and that\u2019s why it was naturally a topic of discussion at our university back then\u2014I was there myself, after all. That\u2019s how I found out about it. And since I\u2019m a tropical biologist myself, I\u2019m very well aware of how important it is to protect tropical ecosystems. And what I like about Tropica Verde, of course, is that they\u2019re actually doing things on the ground there. And obviously, they\u2019re doing things that make sense, because some of the projects have been around for a very, very long time.<\/p>\n<\/blockquote>\n

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In your new book, you posed the question: Can AI save nature? Could you tell us a little bit about that\u2014perhaps how you came to choose this topic?<\/strong><\/p>\n

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I actually came across this topic because I have colleagues and friends who founded a company in the U.S. that provides AI-based tools\u2014not only for conservation organizations, but also for businesses and government agencies\u2014to help identify human impacts on nature more quickly and better protect intact natural areas. And another friend of mine is conducting research on this topic. That\u2019s why I found it really interesting to combine this technical topic with the issue of nature conservation.<\/p>\n

And at the same time\u2014as we all know\u2014our goal must be to reach as many people as possible with this issue. And of course, that made me think once again that a topic like AI can reach more people\u2014or even additional people\u2014who might not be at the very top of the list for conservation organizations or conservation and wildlife biologists. I personally find it very, very exciting because you can really do some pretty cool things with it.<\/p>\n<\/blockquote>\n

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Could you share a few examples of that\u2014some standout examples?<\/strong><\/strong><\/p>\n

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This friend of mine who runs a company in the U.S.\u2014for example, they recently awarded a major prize for research on how to detect wildfires as early as possible. And that\u2019s also kind of the focus of my colleague, who\u2019s conducting scientific research on this, because animals know a lot of things that we don\u2019t. For example, there are certain species of beetles that always lay their eggs in trees that have just burned\u2014as soon as the tree has cooled down, they lay their eggs inside. And these animals are extremely good at detecting fire, because, of course, they have to make sure they\u2019re the first ones on the scene. Modern, very, very small sensors\u2014the smallest ones weigh just 0.2 grams\u2014might already be able to help us, through these large insects, detect forest fires in the future earlier than we would have been able to using technical smoke detectors or optical methods. Or here\u2019s another example I think is really cool: an AI that was originally designed to analyze the starry sky was trained to recognize the skin patterns of whale sharks. <\/p>\n<\/blockquote>\n<\/div><\/div>\n<\/div>\n\n

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It\u2019s important to know that the whale shark wasn\u2019t scientifically described until the mid-19th century, and up until 1986, we had only 300 recorded sightings of whale sharks. Most of these were animals that had become entangled in fishing nets or were found dead on the beach. And now, all kinds of recreational divers have cameras and are taking photos of whale sharks. They no longer have to send these photos to any scientific institution\u2014instead, they post them on Instagram, TikTok, or wherever. And the AI has been trained on these images of whale sharks and scans social media accounts for photos of them. AI is very good at pattern recognition. This specific AI has created a database in which the whale sharks are assigned individual numbers and, in effect, a data sheet. And that\u2019s why we now know 3,000 whale sharks individually. We know where they are, what routes they swim, and so on.<\/p>\n

And that, in turn, can be put to use: If you let the AI cross-reference this data with all kinds of other information on ocean parameters, food availability, temperature, current direction, etc., then the AI can predict where the whale sharks will be in the near future. And one of the main causes of death for whale sharks is certainly still collisions with ships or getting entangled in fishing nets. And this could actually be prevented: If this data were made available to fishermen or shipowners, they could prevent such encounters with whale sharks\u2014which are, after all, also detrimental to them\u2014in the future. That\u2019s actually a really cool application for nature conservation.<\/p>\n

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And when we go to the tropics or tropical rainforests: There, you can work with soundscapes\u2014in other words, you can hang up these sound boxes. You train the AI beforehand with what we might call a \u201cbackground noise\u201d in German, and provide it with information about the forest\u2019s health. And from there, it can determine on its own: Okay, based on what I\u2019ve heard here, the forest is in such-and-such a condition. And that\u2019s, of course, pretty cool, too.<\/p>\n

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Of course, the example involving the tropics is particularly interesting for us as well. The examples you mentioned are often very specific AI applications tailored to the respective use case, and they are usually based on proprietary data.<\/strong><\/p>\n

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Yes, well, that can be infinitely complex. Perhaps this already brings us close to the threats posed by AI. What we\u2019ll certainly have to do in the future\u2014as nature conservation organizations, but also in research\u2014is ensure that AI operates within clearly defined and secure data environments. After all, AI is actually \u201cdumb.\u201d And of course, it can only generate information based on the data made available to it. And if you let it roam freely on the internet, where we know that the majority of the information is now false\u2014if AI generates its knowledge based on this false information, then naturally, what comes out is also false. And that\u2019s why, especially in nature conservation, we need to ensure that when we use AI in such sensitive areas, we ideally have data sets that contain only data we know to be accurate. Otherwise, the AI will naturally spit out all kinds of nonsense.<\/p>\n<\/blockquote>\n<\/div><\/div>\n\n

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Of course, the example involving the tropics is particularly interesting for us as well. The examples you mentioned are often very specific AI applications tailored to the respective use case, and they are usually based on proprietary data.<\/strong><\/p>\n

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Yes, well, that can be infinitely complex. Perhaps this already brings us close to the threats posed by AI. What we\u2019ll certainly have to do in the future\u2014as nature conservation organizations, but also in research\u2014is ensure that AI operates within clearly defined and secure data environments. After all, AI is actually \u201cdumb.\u201d And of course, it can only generate information based on the data made available to it. And if you let it roam freely on the internet, where we know that the majority of the information is now false\u2014if AI generates its knowledge based on this false information, then naturally, what comes out is also false. And that\u2019s why, especially in nature conservation, we need to ensure that when we use AI in such sensitive areas, we ideally have data sets that contain only data we know to be accurate. Otherwise, the AI will naturally spit out all kinds of nonsense.<\/p>\n<\/blockquote>\n

That would have been part of my question: the data. But on the other hand, there are also some systemic issues, because large generative AI models are always very closely linked to questions of energy and water consumption, which might then conflict with nature conservation goals. So my question is, how did you shed light on this\u2014including from the perspective of: Where are these large models actually needed?<\/strong><\/p>\n

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This is, of course, a huge problem, because all AI applications are, by their very nature, harmful to the environment. They consume enormous amounts of water, enormous amounts of energy, and enormous amounts of mineral resources\u2014which is leading to crises, particularly in tropical ecosystems. My argument for using AI in nature conservation, however, is that nature conservation applications make up a tiny, tiny, tiny fraction of the total. In other words, even if we were to stop using AI for nature conservation, AI would still be just as harmful globally as it would be without its use in nature conservation. So what we need to do is this: We mustn\u2019t dismiss its use in nature conservation as pointless; instead, we need to be smarter overall\u2014and yes, more cautious in our use of AI.<\/p>\n

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Here\u2019s an example I always give: When I was in college, there was no internet yet, and no smartphones either. If you wanted to know something, you\u2019d first go to the library, pick up a book, and read it. Or you\u2019d ask someone who might know the answer. And if we take something as mundane as, \u201cHow do I make a pancake?\u201d\u2014back then, I would have called my grandma, or I would have gone to the library to see if I could find a cookbook that explained it. Then, at some point, we reached a stage where you\u2019d definitely have Googled it. And today, people ask AI five times a day if it could quickly list the ten best pancake recipes for them again. And the information you get is always the same. In the end, you always know how to make a pancake\u2014but the resource consumption varies enormously between these three models. And yes, we have to learn this somehow: that we shouldn\u2019t always turn to AI for every little thing. But of course there are also nonsensical applications in nature conservation\u2014for meaningful applications in nature conservation, however, I\u2019d still be in favor of using it, and I\u2019d prefer that we use less AI for other things.<\/p>\n<\/blockquote>\n

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And here\u2019s what you might have been getting at: Since most questions are so trivial, you can now essentially add an intermediate level. Instead of having the AI analyze all available data sources worldwide to figure out how to make pancakes, you can introduce these intermediate levels so that the AI knows: \u201cAh, this is about cooking\u2014I\u2019ll just look in this tiny data space where all the recipes are.\u201d And of course, that requires less energy, water, and raw materials.\u201d<\/p>\n<\/blockquote>\n

You\u2019ve already mentioned a few examples that you also discuss in your book. Where do you see\u2014perhaps with an eye toward Tropica Verde as a tropical conservation organization\u2014specific applications for us as an organization or for similar organizations?<\/strong><\/p>\n

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I was in Kenya last year and helped train game wardens there on how to use these smart camera traps and sound boxes. And both these camera traps and sound boxes are now extremely affordable. So it doesn\u2019t cost much, and you can reuse them over and over again\u2014they\u2019re not disposable products. I can definitely see how this could be useful, for example, in reforestation programs\u2014and once you\u2019ve gotten the hang of how to assess forest health based on these soundscapes\u2014I think it could be an interesting tool for Tropica Verde. Also because it\u2019s obviously a great way to communicate: because you can still give people who can\u2019t travel to Costa Rica a very, very close look at the work being done there. And of course, you can do that with these camera trap photos, and you can do it with these soundscapes.<\/p>\n

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And, of course, purely theoretically, we could also involve members or interested parties through a citizen science approach like this. So when we look at these camera trap photos, the AI can be trained to recognize jaguars, for example. But it\u2019s still a good idea to have a human observer take another look at them. So let\u2019s say you have 40,000 photos; you train the AI to say, \u201cPlease look for jaguars in these.\u201d Then the AI comes back and says, \u201cHere, there\u2019s a jaguar in number 100.\u201d And those 100 photos could then be reviewed by citizen scientists, so to speak, to confirm whether there really was a jaguar in that one.<\/p>\n<\/blockquote>\n

The interview was conducted and edited by Paul He\u00df, a volunteer with Tropica Verde e.V. <\/em><\/span><\/p>\n<\/div><\/div>\n<\/div>\n<\/div>\n\n

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Make a donation!<\/h3>\n<\/div><\/div><\/div>
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Become a member!<\/h3>\n<\/div><\/div><\/div>
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Compensate for CO2!<\/h3>\n<\/div><\/div><\/div>
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Be active as a volunteer!<\/h3>\n<\/div><\/div><\/div><\/div>\n<\/div>","protected":false},"excerpt":{"rendered":"","protected":false},"author":5,"featured_media":254048,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[146,188,209,246],"tags":[],"class_list":["post-254047","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news-ngo","category-be-active","category-educational-work-germany","category-knowledge-animals-plants"],"_links":{"self":[{"href":"https:\/\/tropica-verde.de\/en\/wp-json\/wp\/v2\/posts\/254047","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/tropica-verde.de\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/tropica-verde.de\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/tropica-verde.de\/en\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/tropica-verde.de\/en\/wp-json\/wp\/v2\/comments?post=254047"}],"version-history":[{"count":4,"href":"https:\/\/tropica-verde.de\/en\/wp-json\/wp\/v2\/posts\/254047\/revisions"}],"predecessor-version":[{"id":254057,"href":"https:\/\/tropica-verde.de\/en\/wp-json\/wp\/v2\/posts\/254047\/revisions\/254057"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/tropica-verde.de\/en\/wp-json\/wp\/v2\/media\/254048"}],"wp:attachment":[{"href":"https:\/\/tropica-verde.de\/en\/wp-json\/wp\/v2\/media?parent=254047"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/tropica-verde.de\/en\/wp-json\/wp\/v2\/categories?post=254047"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/tropica-verde.de\/en\/wp-json\/wp\/v2\/tags?post=254047"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}