Despite risks, tool has ‘enormous potential’ for good, a Conservation International expert says.

In her own words, Ali Swanson is a “tech skeptic.”

Conservation News spoke with Swanson to unpack the perils and promise of integrating AI with conservation.

Conservation News: What problems can artificial intelligence solve for conservation?

Second, AI can help us both optimize — and future-proof — our decisions. A lot of conservation is about maximizing our impact with limited resources and information. Broadening the scope of information will help increase certainty, which is something funders covet. AI lets us not only consider so many more variables in our calculations but also predict what might happen in the future —
so we can make the best decisions today that last for generations to come.

And then the third piece, and this is something I’m really excited about, is thinking about how we can help democratize conservation action —
putting our science into the hands of the people who can put it into practice.

Tell me more about that.

AS: Let’s take . There are dozens of different ‘nature credit’ methodologies out there, and they’re all over the map on what they ask you to measure and report on — even the goals.

So far, we’ve discussed hypotheticals. Where is Conservation International already embedding AI into its programs, and what have we learned?

AS: Historically, we’ve used machine learning or deep learning to process large volumes of data much faster — like camera trap images in the Wildlife Insights program, or satellite data in our Climate Smart Shrimp program.

But we’re looking to dramatically increase the sustainability and accessibility of AI tools. We have an incredible opportunity with funding from the Patrick J. McGovern Foundation to pursue AI innovation. With this support, we are building out a dedicated AI curriculum at CI to upskill our staff and empower them to use AI strategically and responsibly. We are also partnering with AI developers to prototype AI agents that can help stakeholders make better conservation decisions, such as with nature credits or restoration.

One of those challenges is AI’s massive environmental footprint. The average American datacenter uses roughly 17,000 showers’ worth of water each day, for example. How do you think about the tradeoff of potential long-term progress at a real short-term environmental cost?

AS: There’s no easy answer here, but I think the first step is visibility. Just over the state line from my house sit two coal-fired power plants that feed data centers. It makes visible for me a cost that is otherwise invisible just sitting at a computer prompting a chatbot.

In the big picture, I do think the benefit of doing our work faster, bigger and better will outweigh the costs of our AI use, in part because we’re leveraging a tool that has largely been built and developed already.

But at Conservation International, we have a unique opportunity — and therefore, a responsibility — to bring different actors to the table, including major tech partners, other NGOs and world leaders to have this discussion. How can we, as a conservation sector, harness this tool for good, recognizing the costs that it creates? It’s one of the most important questions of our generation.

Max Marcovitch is a senior writer at Conservation International. Want to read more stories like this? Sign up for email updates. Also, please consider supporting our critical work.

Source: www.conservation.org