The Risks of AI in Biodiversity Management

While AI offers unprecedented tools for conservation, its rapid rise also brings serious risks. Like any powerful technology, AI is only as wise as the goals it serves—and biodiversity isn’t always at the top of the agenda.

One concern is data bias. Most ecological AI models are trained on data from regions with robust monitoring—North America, Europe, parts of Asia. But many of the world’s most biodiverse and vulnerable ecosystems, such as the Congo Basin or the Mekong Delta, lack adequate datasets. This can lead to skewed predictions and underrepresentation of threatened regions in global strategies.

AI can also be co-opted for harmful purposes. Satellite and drone imagery paired with AI are sometimes used by mining or agricultural corporations to identify “underutilized” land, which often includes biodiverse forests or Indigenous territories. What starts as environmental data can become a tool for extraction.

Additionally, the infrastructure behind AI—data centers, rare minerals for chips, vast energy consumption—has its own ecological footprint. Training large models consumes immense electricity, sometimes powered by fossil fuels. The global AI boom fuels demand for cobalt, lithium, and rare earths—resources often mined in environmentally destructive ways.

There are also ethical concerns. Should we allow AI to automate decisions about which species to prioritize for protection? Who controls the models that dictate conservation funding or enforcement? The risk is that AI could shift biodiversity management away from field ecologists and Indigenous stewards toward tech companies and centralized authorities.

Finally, there’s the broader philosophical question: is AI reinforcing a technocratic relationship with nature—one where we see the Earth as a dataset to be optimized rather than a living system to be in relationship with?

To harness AI’s potential without deepening ecological harm, we must develop not just better algorithms—but better values, better politics, and better accountability systems. Conservation in the digital age must remain grounded in justice, context, and humility.