In the realm of environmental planning, the convergence of affordable environmental sensors with AI-driven analytics promises quicker and more insightful decision-making. This urgency is underscored by legislative changes requiring expedited assessments under the Fast-track Approvals Bill.
Kuaha Matahiko, a collaborative initiative, has identified a growing interest in AI among iwi and hapū groups, offering potential solutions for integrating fragmented environmental data and bolstering analytical capabilities. This development marks a turning point where tailored AI solutions are becoming feasible even for smaller kaitiaki organizations.
However, caution is warranted. Previous experiences reveal that algorithmic systems can perpetuate existing inequalities in data collection and constrain imaginative outcomes. The "precision trap" is exemplified by the misconception that larger data volumes inherently ensure accuracy, despite warnings from New Zealand’s Parliamentary Commissioner for the Environment about the country’s patchy and under-resourced environmental data systems.
Moreover, the opacity of AI algorithms poses risks, fostering unwarranted confidence in their precision and potentially eroding checks and balances in decision-making processes. This issue is exacerbated when AI outputs become the foundation for governance and policy decisions.
To mitigate these risks, a proactive approach is needed. Drawing from principles like FAIR (findable, accessible, interoperable, and reusable), there is a call for inclusive and transparent AI governance frameworks that acknowledge and rectify historical data gaps and biases.
Furthermore, indigenous data sovereignty movements advocate for frameworks such as CARE (collective benefit, authority, responsibility, ethics), asserting rights over community data governance. In Aotearoa New Zealand, initiatives like Te Kāhui Raraunga Māori exemplify these principles in action, emphasizing empowerment and ethical stewardship of data.
Looking ahead, expanding AI development beyond a "WEIRD" standpoint (western, educated, industrialized, rich, developed) is crucial. This includes integrating diverse worldviews, such as mātauranga Māori, to enrich AI's ethical and cultural foundations, thereby avoiding the pitfalls of an overly rational and exclusionary approach.
In navigating the future of AI in environmental stewardship, it is imperative to embrace inclusivity, transparency, and ethical responsibility, ensuring that AI serves human well-being and environmental sustainability equitably.
