With new technologies revolutionizing data collection, wildlife researchers are becoming increasingly able to collect data at much higher volumes than ever before. Now we are facing the challenges of putting this information to use, bringing the science of big data into the conservation arena. With the help of machine learning tools, this area holds immense potential for conservation practices. The applications range from online trafficking alerts to species-specific early warning systems to efficient movement and biodiversity monitoring and beyond.
However, the process of building effective machine learning tools depends upon large amounts of standardized training data, and conservationists currently lack an established system for standardization. How to best develop such a system and incentivize data sharing are questions at the forefront of this work. There are currently multiple AI-based conservation initiatives, including Wildlife Insights and WildBook, that are pioneering applications on this front.
This group is the perfect place to ask all your AI-related questions, no matter your skill level or previous familiarity! You'll find resources, meet other members with similar questions and experts who can answer them, and engage in exciting collaborative opportunities together.
Just getting started with AI in conservation? Check out our introduction tutorial, How Do I Train My First Machine Learning Model? with Daniel Situnayake, and our Virtual Meetup on Big Data. If you're coming from the more technical side of AI/ML, Sara Beery runs an AI for Conservation slack channel that might be of interest. Message her for an invite.
Header Image: Dr Claire Burke / @CBurkeSci
Explore the Basics: AI
Understanding the possibilities for incorporating new technology into your work can feel overwhelming. With so many tools available, so many resources to keep up with, and so many innovative projects happening around the world and in our community, it's easy to lose sight of how and why these new technologies matter, and how they can be practically applied to your projects.
Machine learning has huge potential in conservation tech, and its applications are growing every day! But the tradeoff of that potential is a big learning curve - or so it seems to those starting out with this powerful tool!
To help you explore the potential of AI (and prepare for some of our upcoming AI-themed events!), we've compiled simple, key resources, conversations, and videos to highlight the possibilities:
Three Resources for Beginners:
- Everything I know about Machine Learning and Camera Traps, Dan Morris | Resource library, camera traps, machine learning
- Using Computer Vision to Protect Endangered Species, Kasim Rafiq | Machine learning, data analysis, big cats
- Resource: WildID | WildID
Three Forum Threads for Beginners:
- I made an open-source tool to help you sort camera trap images | Petar Gyurov, Camera Traps
- Batch / Automated Cloud Processing | Chris Nicolas, Acoustic Monitoring
- Looking for help with camera trapping for Jaguars: Software for species ID and database building | Carmina Gutierrez, AI for Conservation
Three Tutorials for Beginners:
- How do I get started using machine learning for my camera traps? | Sara Beery, Tech Tutors
- How do I train my first machine learning model? | Daniel Situnayake, Tech Tutors
- Big Data in Conservation | Dave Thau, Dan Morris, Sarah Davidson, Virtual Meetups
Want to know more about AI, or have your specific machine learning questions answered by experts in the WILDLABS community? Make sure you join the conversation in our AI for Conservation group!
Neuroscientist & engineer transitioning to conservation tech. I have experience working with large imaging datasets, pose estimation and positional tracking, and machine learning. Looking to get involved with GIS, remote sensing, and AI for conservation.
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PhD in Ecology, Nature's sound lover.
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- @bioNathan
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Innovation Design Engineer studying at MSc + MA level. Previously a Robotics engineer with specialisms in remote sensing, control systems & electronics design. Transitioning to ecological contexts. I use bioinspiration to inform tech design, both product & infrastructure.
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Tech 4 Conservation
President, Tech 4 Conservation
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Botswana Predator Conservation Trust
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Quantitative ecologist @ Biotope
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Savanna Ecologist, Field Station Director and Head of Conservation Tech Projects for Organization for Tropical Studies (OTS).
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Ecologist & Conservationist. Women for the Environment, Africa Fellow. National Geographic Explorer.
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Description | Activity | Replies | Groups | Updated |
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No worries! I'll be trying the other one to see how it works. Thank you for your help! |
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AI for Conservation | 2 minutes 39 seconds ago | |
Fantastic!! |
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Acoustics, AI for Conservation, Biologging, Build Your Own Data Logger Community, Community Base, Early Career, Ethics of Conservation Tech, Marine Conservation, Open Source Solutions | 5 seconds ago | |
The camera can be aimed at the greenhouse background, which is like a huge green screen. Inside the greenhouse there's only a few flying insects, and they would all have to fly... |
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AI for Conservation | 3 days 10 hours ago | |
Hi David - have you seen this opportunity? It may be a good one to apply to for support (the Darwin Initiative). |
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AI for Conservation, Drones, Emerging Tech, Human-Wildlife Conflict, Wildlife Crime | 5 days 4 hours ago | |
Hi everyone! I’m sending some information for a paid user study about Explainable AI and bird identification that may be of interest:Our... |
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AI for Conservation, Citizen Science | 5 days 16 hours ago | |
I am also commenting for future notifications - very interested to hear some responses.While not directly related to AI, here in Canada there's quite a conversation around data... |
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AI for Conservation | 2 weeks 2 days ago | |
Yes, this system is designed to be installed near farms. We also have the repeller system with audio & light, that is battery & solar powered. This system is a "last line... |
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AI for Conservation | 4 weeks ago | |
Undoubted things will quickly evolve from just "straight" ChatGPTn, BARD, ClaudeAI, etc "standard" models, to more specialized Retrieval Augmentation Generation (RAG) , where... |
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AI for Conservation, Emerging Tech | 1 month ago | |
This is so cool! I am 1000% going to see if they want to come talk about it at Variety Hou! |
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AI for Conservation, Citizen Science | 1 month ago | |
Hi Sol,If the maximum depth is 30m, it would be worth experimenting with HydroMoth in this application especially if the deployment time is short. As Matt says, the air-filed case... |
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Acoustics, AI for Conservation, Data management and processing tools, Emerging Tech, Sustainable Fishing Challenges | 1 month ago | |
Online citizen science platforms like iNaturalist and Macaulay Library contain a wealth of images but are hard to search using text. We are... |
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AI for Conservation, Citizen Science | 1 month 1 week ago | |
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AI for Earth Innovation Grant (extended)
4 June 2019 12:00am
CogX Festival of AI and Emerging Technology - free tickets for WILDLABS members
16 May 2019 12:12pm
3 June 2019 4:53pm
Are there any free tickets left for CogX?
I am on [email protected]
3 June 2019 5:04pm
yep! Drop me an email at [email protected] and I'll get you a link.
Steph
How machine learning can help fight illegal wildlife trade on social media
31 May 2019 12:00am
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21 May 2019 12:00am
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17 May 2019 12:00am
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13 May 2019 12:00am
Call for Papers: Data Mining and AI for Conservation Workshop at KDD 2019
15 April 2019 12:00am
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15 April 2019 12:00am
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26 March 2019 10:12am
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18 March 2019 12:00am
#Tech4Wildlife Photo Challenge: Our Favourites from 2019
3 March 2019 12:00am
Conserving the Sumatran and Javan Rhino
15 January 2019 7:39pm
23 January 2019 10:12pm
Hello Claire,
Engineer at Wild Me here. We would love to start a conversation about a Wildbook for rhinos.
Lets talk about citizen science and computer vision for identification possibilities. I'm curious about your current data set and the identification tools you are using as a starting point. I'm happy to talk here, or you can email our team at [email protected].
24 February 2019 1:28am
Hi Claire,
At the BearID Project, we are working on a similar problem for brown bears. We are currently using machine learning methods developed for human facial recognition (like Google FaceNet). We got some ok initial results, but now we are running up against small data issues. The method for human faces were trained with millions of images of hundreds of thousandes on individuals. We have a few thousand images of about a hundred individuals. We plan to investigate other methods in the future.
It will be great to keep in touch to see what methods you will be using.
Ed
24 February 2019 1:38am
Hi Colin,
At the BearID Project, we are working on a similar problem for brown bears. We are currently using machine learning methods developed for human facial recognition (like Google FaceNet). We got some ok initial results, but now we are running up against small data issues. The method for human faces were trained with millions of images of hundreds of thousandes on individuals. We have a few thousand images of about a hundred individuals. We plan to investigate other methods in the future.
The last time I talked to WildMe, the identification algorithms were based on matching unique patterns. We didn't think this would be directly applicable for brown bears as they don't have a lot of clearly identifiable markings. Have you developed other identification algorithms?
Ed
Responsible AI for Conservation?
11 February 2019 6:22pm
21 February 2019 8:17am
Hi Jaishanker
Absolutely - the overlap between image-based and sound-based analyses is increasing, and consistent terminology will no doubt help us share info.
Are you using ML in SODA for automated identification of sounds? If so, how are you determining if a given classifier is performing well?
Thanks
Ollie
21 February 2019 11:08am
Hello Ollie,
SODA is a recently launched suite. It is in the development phase. We have with us call libraries with multiple (40+) calls for 10- 12 species of birds. A research scholar is on the job for classifying at the species level.
Our interest is equally on separating the different sonic components (as stated in https://www.wildlabs.net/community/thread/666). It is different from the link shared in my previous reply. This is where I see the confluence of objectives.
As a TEAM, I believe, we can address the individual objectives faster.
regards
jaishanker
21 February 2019 9:13pm
Hi Ollie,
Great article, thank you! I mostly work with responsible AI in other contexts, at Doteveryone.org.uk and the Trust & Technology Initiative at the University of Cambridge, so don't have much to offer here, although I am very interested in the topic. I appreciate your point that many of the consumer data issues highlighted in the 'popular' responsible AI discourse aren't relevant to conservation (some of us have been gathering 'responsible tech' / 'ethical tech' resources in a shared doc, and there's essentially nothing there for conservation specifically - https://docs.google.com/document/d/1SN6hYeKe3eRK6x9D0Sr7GpCA4nirpyo3u68xG1A6NDs/edit ). However there might be some links with humanitarian data practices, which are touched on by the Responsible Data folks at https://responsibledata.io and https://www.fabriders.net/data-literacy-consortium/ or in this recent article https://asecondmouse.wordpress.com/2019/02/20/instability-forecasting-models-seven-ethical-considerations/
Best,
Laura
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19 April 2018 12:00am
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28 May 2019 12:02pm
UPDATE: We've had quite a few members emailing us for tickets, so I'm looking forward to meeting everyone in person! We've now been allocated some extra tickets, so if you are interested you're in luck, there is still a chance to come along.