Automated decision making and predictive analytics through artificial intelligence, 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 artificial intelligence are already today 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 have explored possible systemic risks in depth. This article offers a global overview of the progress of such technologies in sectors with high impact potential for sustainability like farming, forestry and the extraction of marine resources. We 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. We explore these emerging risks, identify critical questions, and discuss the limitations of current governance mechanisms in addressing AI sustainability risks in these sectors.

NATO's current security doctrine needs to change. It needs to enhance its political will and institutional capacity to manage climate change threats, both within the alliance itself and within the area most vulnerable to its southern flank: the Middle East. NATO will need to evolve into a CATO, a Climate Alliance Treaty Organization, that deals with the security implications of potential tipping points and develops policies in response. A case study as to how NATO can assume this role can be seen in how the organization dealt with environmental issues in Iraq, in the aftermath of war with the Islamic State.