Artificial intelligence, systemic risks, and sustainability
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 ecol...
| Autores principales: | , , , , , , , , , , , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Elsevier
2021
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/115075 |
| _version_ | 1855513817661833216 |
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| author | Galaz, Victor Centeno, Miguel A Callahan, Peter W. Causevic, Amar Patterson, Thayer Brass, Irina Baum, Seth Farber, Darryl Fischer, Joern Garcia, David McPhearson, Timon Jiménez, Daniel King, Brian Larcey, Paul Levy, Karen |
| author_browse | Baum, Seth Brass, Irina Callahan, Peter W. Causevic, Amar Centeno, Miguel A Farber, Darryl Fischer, Joern Galaz, Victor Garcia, David Jiménez, Daniel King, Brian Larcey, Paul Levy, Karen McPhearson, Timon Patterson, Thayer |
| author_facet | Galaz, Victor Centeno, Miguel A Callahan, Peter W. Causevic, Amar Patterson, Thayer Brass, Irina Baum, Seth Farber, Darryl Fischer, Joern Garcia, David McPhearson, Timon Jiménez, Daniel King, Brian Larcey, Paul Levy, Karen |
| author_sort | Galaz, Victor |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | 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. |
| format | Journal Article |
| id | CGSpace115075 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | CGSpace1150752025-12-08T09:54:28Z Artificial intelligence, systemic risks, and sustainability Galaz, Victor Centeno, Miguel A Callahan, Peter W. Causevic, Amar Patterson, Thayer Brass, Irina Baum, Seth Farber, Darryl Fischer, Joern Garcia, David McPhearson, Timon Jiménez, Daniel King, Brian Larcey, Paul Levy, Karen artificial intelligence climate change sustainability resilience automation risk analysis inteligencia artificial cambio del clima sostenibilidad education 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. 2021-11 2021-09-21T16:20:04Z 2021-09-21T16:20:04Z Journal Article https://hdl.handle.net/10568/115075 en Open Access application/pdf Elsevier Galaz, V.; Centeno, M.A.; Callahan, P.W.; Causevic, A.; Patterson, T.; Brass, I.; Baum, S.; Farber, D.; Fischer, J.; Garcia, D.; McPhearson, T.; Jiménez, D.; King, B.; Larcey, P.; Levy, K. (2021) Artificial intelligence, systemic risks, and sustainability. Technology in Society 67: 101741. 10 p. ISSN: 0160-791X |
| spellingShingle | artificial intelligence climate change sustainability resilience automation risk analysis inteligencia artificial cambio del clima sostenibilidad education Galaz, Victor Centeno, Miguel A Callahan, Peter W. Causevic, Amar Patterson, Thayer Brass, Irina Baum, Seth Farber, Darryl Fischer, Joern Garcia, David McPhearson, Timon Jiménez, Daniel King, Brian Larcey, Paul Levy, Karen Artificial intelligence, systemic risks, and sustainability |
| title | Artificial intelligence, systemic risks, and sustainability |
| title_full | Artificial intelligence, systemic risks, and sustainability |
| title_fullStr | Artificial intelligence, systemic risks, and sustainability |
| title_full_unstemmed | Artificial intelligence, systemic risks, and sustainability |
| title_short | Artificial intelligence, systemic risks, and sustainability |
| title_sort | artificial intelligence systemic risks and sustainability |
| topic | artificial intelligence climate change sustainability resilience automation risk analysis inteligencia artificial cambio del clima sostenibilidad education |
| url | https://hdl.handle.net/10568/115075 |
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