Automated decision-making and predictive analytics using AI, in combination with rapid progress in technologies such as sensor technology and robotics, are likely to change the way individuals, communities, governments and private actors perceive and respond to climate and ecological change. Methods based on various forms of AI are already being applied in a number of research fields related to climate change and environmental monitoring. Investments into applications of these technologies in agriculture, forestry and the extraction of marine resources also seem to be increasing rapidly. Despite a growing interest in and deployment of AI technologies in domains critical for sustainability, few researchers have explored possible systemic risks in depth.
In addition to their overview, the authors also identify possible systemic risks in these domains, including a) algorithmic bias and allocative harms; b) unequal access and benefits; c) cascading failures and external disruptions and d) trade-offs between efficiency and resilience.
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