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WCC Researcher Talks Red Wolves and AI at NJIT Conference


The New Jersey Institute of Technology hosted an event last week called “Women Designing the Future: Artificial Intelligence/Real Human Lives,” which focused on the ways that AI is shaping our future and in what ways humans might be able to use AI to tackle some of the problems of today and tomorrow. AI has the potential to revolutionize many aspects of our society and shape the future in significant ways, and you may have heard a lot about it in the past few months, with some calling tools like ChatGPT the “death of creativity” and others speaking about how these tools can streamline processes that used to take hours so people can focus on more important tasks.

Several of the speakers at the event brought up other concerns, like AI systems reflecting and amplifying the biases of their creators, leading to discrimination against certain groups of people. This could exacerbate existing inequalities in society. Others had optimistic viewpoints about education enhancement, economic opportunities, and various other improvements that AI tools can bring to organizations fighting for a brighter future.

Technology And Wolves?

The obvious question that follows is how can AI tools help wolf conservation? That’s precisely what WCC Research Associate Sunny Murphy and her collaborator, Dr. Margarita Vinnikov, an assistant professor in the Department of Informatics at NJIT, set out to explain in their segment of the conference last week. With a focus on critically endangered red wolves, Murphy explained how AI could expedite and economize several tedious tasks within the conservation effort as well as reach a wider net of people.

The pair also demonstrated how other technologies, like Virtual Reality (VR) and Augmented Reality (AR) can teach a wider range of folks about parts of the world they’d never be able to experience firsthand. While we recommend getting out to the WCC for hands-on experiences with wolves, we also realize that’s not always practical, so using VR/AR to simulate the experience could be a crucial way to expand the depth and breadth of people we could reach about the importance of this keystone species and continue to dispel myths about the big bad wolf.

Why Red Wolves Specifically?

These tools could likely be used across several different animal conservation efforts and certainly aren’t only limited to red wolves, but the reason that Sunny, along with Senior WCC researcher, and red wolf expert, Joseph W. Hinton, are currently focused on red wolves has to do with their specific predicaments and just how critically endangered they are.

Before the red wolf population in North Carolina was decimated by shooting deaths and motor vehicle fatalities, there were as many as 120 wolves on the Albemarle Peninsula in 2012. As of the last count, there are only 14 known red wolves in the wild, and the individual wolves are closely related to each other and share a lot of the same genetic background.

A population of red wolf-like canids found along the Gulf Coast of Texas and Louisiana could serve as a potential source of genetic diversity and help bolster red wolf recovery. Red wolves are genetically similar to these Gulf Coast canids because the founders used to establish the captive-breeding program and the wild North Carolina population were originally captured from this region in the 1970s.

As Murphy put it for the patrons of the NJIT conference, “Being able to research the (Gulf Coast) population will help us to clarify their taxonomy, get better protections for them, and we also need to investigate the stability and distribution of their genetics. All of this can help us not only protect that population (along the Gulf), but also the population in North Carolina, and the red wolves we are breeding in captivity for recovery in the SAFE (Saving Animals From Extinction) program, which the Wolf Conservation Center is a part.”

Using AI To Streamline Research

There is a bit of a time crunch to do this work as well. As Sunny pointed out correctly, sea levels are rising, and the Gulf Coast will be one of the first impacted areas. One of the key areas that AI can help is by analyzing large swaths of photos very quickly to filter down where these canids might be. This process is called “camera trapping” which is a process that allows you to use remote camera stations to collect data 24/7 and the cameras are less invasive and theoretically induce less avoidance behavior from your target species than if you were camped out doing the observations directly. Camera traps are not necessarily just for identifying where wolves are, although they certainly can confirm their presence. Instead, they are mostly for monitoring behavior, getting population estimates, identifying individuals, etc.

This process, along with collaring, helps create a fuller picture of these Gulf Coast canids, and the more details researchers get, the more likely they find helpful data that could be used in red wolf recovery. Most of the cameras capture tons and tons of useless images, which an individual could spend hours going through before ever seeing a match. AI allows researchers to streamline this process, saving countless hours of time and money spent in order to optimize the whole enterprise. Then the human researchers can focus in on all the photos containing wolves without having to sift through all the empty ones first.

At the moment, this is still an imperfect process, but as we continue to feed these algorithms fresh data, they’ll continue to learn and get better over time. This is just one of the many ways that the WCC and our researchers are continuing to look to the future to aid wolves. Want to help fund that research? Consider donating to the WCC today! Every dollar you can donate helps us protect wolves, both on-site at the WCC and in the wilds across North America.