AI in Wildlife Conservation.

Why, in my opinion, it's a double-edged sword for nature.

I remember the first time I discovered/heard about ChatGPT: I was sitting alone, once again, in the graduate office of my old University. It was lunch time, and I was eating my sandwich and scrolling through the news when I was suddenly barraged by article after article of this latest artificial intelligence (AI) concept. Since then, it feels like AI has taken on a life of its own, a beast we created without pausing to think if we should’ve done that in the first place (or if it was at all ethical to maintain).

Like it or not, it has rapidly emerged as a powerful tool in many fields, including wildlife conservation. From analyzing vast amounts of data to automating labor-intensive tasks, AI has the potential to revolutionize how we protect the planet’s most vulnerable species. But as with any technology, it’s not without its pitfalls.

Let’s go over “the good,” first.

1. Smarter monitoring of wildlife
   AI excels at processing and analyzing massive datasets, and in conservation, this is a game-changer. Machine learning algorithms can quickly sift through camera trap photos or audio recordings to identify species, behaviors, or population trends. This automation saves researchers hundreds of hours and allows for more accurate assessments of biodiversity. I’ll give you an example using one of my fave big cats (mainly a fave because it’s inked across my husband’s arm and he lets me color in the black-and-white tattoo whenever I want): AI can distinguish between a tiger’s roar and other jungle sounds, helping track these elusive predators without disrupting their habitats.
   

2. Protecting species in real-time
   AI-powered tools, such as drones equipped with thermal imaging cameras, can monitor protected areas for illegal poaching or habitat destruction. Real-time alerts from these systems allow rangers to respond swiftly, potentially saving lives — both human and animal. (For more information on drones vs poachers, I found this article to be eye-opening)
   

3. Predictive analytics for habitat management
   By analyzing historical and current data, AI can forecast future changes to habitats due to climate change, human activities, or natural disasters. These predictions help conservationists implement proactive measures, such as relocating species or restoring ecosystems before it’s too late.
   

4. Community engagement and awareness
   AI is also improving how we communicate about wildlife conservation. Chatbots, augmented reality apps, and AI-driven educational tools are making it easier for people to engage with and learn about wildlife, fostering a global community of conservation advocates. Trust that if I had the money to film some incredible dives, get some VR headsets, and travel around Australia showing kids in land-locked towns what awaits them in the ocean, I would. (Anyone know any investors?)

Alright, so those are some of the good. What about the bad?

Let’s talk about some concerns about AI.

1. Technology isn’t neutral
   No matter what anyone says, AI systems are only as good as the data they’re trained on. That means biased or incomplete datasets can lead to skewed conclusions (here’s an example for healthcare). If certain species or habitats are underrepresented in the data, AI might inadvertently prioritize the wrong conservation targets. I read a really interesting article titled, “AI chatbots contribute to global conservation injustices,” that I suggest browsing!
   

2. High costs and accessibility issues
   Working with this sort of cutting-edge technology often means it’s expensive to implement, leaving underfunded conservation efforts and organizations at a disadvantage. This gap can further widen inequalities in global conservation efforts, with wealthier nations benefiting while others struggle to keep up.
   

3. Privacy and ethical dilemmas
   The use of AI-powered drones and surveillance systems raises concerns about privacy — both human and wildlife. While tracking endangered species is essential, the power of this tech raises significant privacy issues for local communities living near conservation areas as the cameras can inadvertently capture images or data about people without their consent. Yikes! This raises questions about who owns the data, how it will be used, and whether it could harm the communities involved. And animals deserve their privacy, too. I know, I know, the concept of “animal privacy” is unusual, but there’s evidence that some species alter their behaviors when they sense surveillance or human presence. This disruption can interfere with natural behaviors like mating, feeding, or migration, potentially causing unintended harm to the very species we’re trying to protect!

4. The environmental toll no one remembers
   Training AI models requires immense computational power. Large-scale models, like those used for image recognition or predictive analytics, rely on data centers filled with servers that consume significant amounts of energy. Data centers already account for about 1-2% of global electricity consumption — and this is projected to grow as AI adoption increases. And, AI generates vast amounts of data that must be stored and accessed, often in cloud servers that further contribute to energy use. Already AI's projected water usage could hit 6.6 billion m³ by 2027, meaning we need to think about its water footprint, too! (Some say that last fact alone should dissuade anyone from using it.) The list goes on and on about the environmental impact this technology has and will have on our planet.

Can we find a balance?

While AI offers immense promise for wildlife conservation, it’s not a silver bullet. To maximize its potential while mitigating its risks, we need to approach it with care:

• Collaborate Across Fields: Conservationists, technologists, and ethicists must work together to ensure AI is used responsibly.

• Diversify Data Sources: Incorporating data from a wide range of habitats and communities can help make AI tools more equitable and effective.

• Invest in Accessibility: Lowering the cost of AI technologies and training local communities in their use can help level the playing field.

• Prioritize Ethics: Clear guidelines on privacy and environmental impact should be a cornerstone of AI deployment in conservation.

I’m often inspired by how technology bridges gaps between human ambition and nature’s resilience. AI holds extraordinary promise, but it’s a tool we must wield wisely. Currently, it’s a sword, helping some win battles against dragons (aka tackling those large datasets) while being fatal for others who wield it (ahem, environmental cost). At the end of the day, yes, I see the irony of using resource-intensive AI systems in conservation work. But I believe AI is neither inherently good nor bad — it’s a tool. The question is: How will we use it to protect the wild places we love?