@article{965185633dc9403a900ce43f308ee1db,
title = "Artificial intelligence, systemic risks, and sustainability",
abstract = "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.",
keywords = "Anthropocene, Artificial intelligence, Automation, Climate change, Digitalization, Resilience, Social-ecological systems, Sustainability, Systemic risks",
author = "Victor Galaz and Centeno, {Miguel A.} and Callahan, {Peter W.} and Amar Causevic and Thayer Patterson and Irina Brass and Seth Baum and Darryl Farber and Joern Fischer and David Garcia and Timon McPhearson and Daniel Jimenez and Brian King and Paul Larcey and Karen Levy",
note = "Funding Information: We would like to thank the Beijer Institute of Ecological Economics (Royal Swedish Academy of Sciences) , and the Princeton Institute for International and Regional Studies (Princeton University) for funding and hosting the workshop {"}Human-Machine-Ecology: A Workshop on the Emerging Risks, Opportunities, and Governance of Artificial Intelligence{"} at Princeton University on January 11th-12th, 2019, and the Consulate General of Sweden in New York for hosting the second workshop “Artificial Intelligence, People, and the Planet{"} in New York, on October 15th, 2019. We would also like to thank participants of these events for their valuable input, the four anonymous reviewers for their constructive comments on earlier versions of this article, and Emilia Arens for supporting the work with data extraction and analysis for Figure 1A and B.V. Galaz's work was funded by the Beijer Institute of Ecological Economics ( Royal Swedish Academy of Sciences ) and the Stockholm Resilience Centre (Stockholm University) with support from Zennstr{\"o}m Philanthropies. D. Garcia{\textquoteright}s work was supported by the Vienna Science and Technology Fund (Grant No. VRG16-005 ). K. Levy{\textquoteright}s work was supported by Microsoft. D. Farber{\textquoteright}s work was supported by the College of Engineering, Penn State University. T. McPhearson was supported by the U.S. National Science Foundation through grants #1444755 , #1934933 , and #1927167 as well as the SMARTer Greener Cities project through the Nordforsk Sustainable Urban Development and Smart Cities grant program. Publisher Copyright: {\textcopyright} 2021 The Author(s)",
year = "2021",
month = nov,
doi = "10.1016/j.techsoc.2021.101741",
language = "English (US)",
volume = "67",
journal = "Technology in Society",
issn = "0160-791X",
publisher = "Elsevier Limited",
}