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AI for Conservation / Feed

Artificial intelligence is increasingly being used in the field to analyse information collected by wildlife conservationists, from camera trap and satellite images to audio recordings. AI can learn how to identify which photos out of thousands contain rare species; or pinpoint an animal call out of hours of field recordings - hugely reducing the manual labour required to collect vital conservation data.

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WILDLABS TECH HUB Showcase

WILDLABS Team
Join us at the Tech Hub Showcase event ot hear how our winners are using technology to scale their solutions to the illegal wildlife trade. The event will take place at Digital Catapult, 101 Euston Road, London, on the...

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Meet the WILDLABS TECH HUB Winners

WILDLABS Team
In February, we released an open call for the WILDLABS TECH HUB, offering 3 months of support for solutions using technolgy to tackle the illegal wildlife trade. We were overwhelmed by an incredible 37 submissions,...

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Huge appetite for data trusts, according to new ODI research

Open Data Institute
To realise the potential benefits of data for our societies and economies we need trustworthy data stewardship. We need to establish different approaches to deciding who should have access to data, for what purposes and...

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discussion

Conserving the Sumatran and Javan Rhino

Save Indonesian Endangered Species (SIES) will be building a machine to identify individual Indonesian rhino.  This will be challenging due to low data numbers.... Sumatran...

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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]

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

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

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discussion

Responsible AI for Conservation?

AI is booming in conservation, with almost daily news articles on how it will solve problem X with algorithm Y. Indeed, there's huge potential here. But, as the old adage goes...

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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

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

 

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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funding

The Ecosulis Rewilding Tech Challenge

Ecosulis
With the aim of advancing rewildling-related technology in the UK and introducing new talent and ideas into the field of rewildling, Ecosulis is thrilled to announce the launch of their first ever Rewilding Tech...

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WILDLABS Virtual Meetup Recording: Big Data in Conservation

WILDLABS Team
The WILDLABS Virtual Meetup Series is a program of webinars that bring leading engineers in the tech sector together with conservation practitioners to share information, identify obstacles, and discuss how to best move...

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Tusk Conservation Lecture 2018: Ted Schmitt

Tusk
Tusk are delighted to announce that their Tusk Conservation Lecture 2018 speaker will be Ted Schmitt of Vulcan Inc, Paul G Allen Philanthropies. He will speak about advancing Innovation in conservation, a talk that will...

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Ocean Hack: San Francisco, 10-11th September, 2018

One Ocean Collab
A 48 hr pop up innovation lab for the ocean, bringing together a mix of designers, strategists, technologists, engineers, scientists, marine conservationists, educators, artists and buisness talent to co-create...

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funding

$90K in grants from the Con X Tech Prize

Looking to prototype or pilot a new conservation tech idea or approach? Conservation X Labs is running an idea competition for teams to create a first draft (i.e. prototype) of their conservation solution. 20 finalists...

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HWC Tech Challenge: Thermopile Sensor Project

Arribada Initative
Conflict between humans and wildlife is increasing as human communities expand and wild habitats are destroyed, prompting need for new mitigation techniques.  As a winner of the Human Wildlife Conflict Tech Challenge,...

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#Tech4Wildlife Photo Challenge 2018: Our Top 10

WILDLABS Team
Hundreds of people joined our #Tech4Wildlife photo challenge this year, showcasing all the incredible ways tech is being used to support wildlife conservation. We've seen proximity loggers on Tasmanian Devils in...

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Congratulations to Zoohackathon winners, team ODINN!

Zoological Society of London
Following the UK Government’s landmark announcement of plans to introduce a complete ban on the domestic trade in ivory, it was fitting that a new machine learning product designed to tackle the supply end of this...

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FIT Cheetahs

Larissa Slaney
A new research project is looking to investigate whether technology combined with the ancient skills and knowledge of Namibian trackers can help save cheetahs from extinction. Called FIT Cheetahs, the research project...

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