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Journal article

Artificial intelligence, systemic risks, and sustainability

The authors present a global overview of the progress of artificial intelligence (AI) and related technologies in sectors with high impact potential for sustainability like farming, forestry and the extraction of marine resources. They explore emerging risks, identify critical questions, and discuss the limitations of current governance mechanisms in addressing AI sustainability risks in these sectors.

Amar Čaušević / Published on 17 September 2021

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Galaz, V., Centeno, M.A., Callahan, P.W., Causevic, A., Patterson, T., Brass, I., Baum, S., Farber, D., Fischer, J., Garcia, D., McPhearson, T., Jimenez, D., King, B., Larcey, P. and Levy, K. (2021). Artificial intelligence, systemic risks, and sustainability. Technology in Society 67:101741, DOI:

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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