AI has the potential to transform environmental management, especially for Indigenous communities like New Zealand’s iwi and hapū. These groups, often burdened with safeguarding natural resources, could use AI to streamline complex datasets and enhance their environmental planning capabilities AI could revolutionise environmental planning – if we don’t get trapped in the ‘iron cage of rationality’. However, adopting AI must be done carefully to avoid perpetuating existing inequalities or falling into the “precision trap,” where AI’s outputs are taken as absolute truths without questioning their underlying assumptions Artificial intelligence and its ‘slow violence’ to human rights.

Figure 1. Research on precision agriculture has identified risks in mistaking a high volume of data for high accuracy. An agricultural robot working in a smart farm, spraying fertiliser on corn fields

One of the main concerns is the historical gaps in environmental data, especially in Indigenous communities, that can result in AI tools making flawed predictions. To avoid this, AI systems must be built in collaboration with these communities, incorporating principles of Indigenous data sovereignty Artificial Intelligence for Climate Change Mitigation. By integrating Indigenous knowledge, such as mātauranga Māori, AI can promote more equitable and culturally informed solutions.

At the same time, AI itself presents environmental challenges. The rise of AI-driven technologies like ChatGPT has led to significant increases in energy consumption, carbon emissions, and water use. Data centers powering AI systems require enormous electricity and water for cooling, leading to greater environmental strain. Companies like Google and Microsoft have reported spikes in their carbon footprints due to AI development. While some firms are initiating “water positive” projects to mitigate this impact, the tech industry as a whole must adopt better sustainability practices Power-hungry AI is driving a surge in tech giant carbon emissions. Nobody knows what to do about it.

These environmental challenges mirror those faced by other industries. Air New Zealand, for instance, recently abandoned its 2030 emissions reduction goal due to difficulties in obtaining sustainable jet fuel and efficient aircraft Air NZ becomes first big carrier to drop climate goal. Like the aviation sector, the tech industry faces obstacles in aligning its growth with sustainability goals, even as both sectors push for greener futures.

Ultimately, AI offers immense potential for environmental planning and management, but its growth must be balanced with efforts to reduce its environmental footprint and ensure that marginalized communities are not left behind. By integrating diverse knowledge systems and addressing AI’s energy and resource demands, we can create a more sustainable, equitable future for both technology and the planet.