What do we know about the future of foresight modeling related to food systems?
“Foresight modeling” is thinking about the future using a simplified representation of reality to inform choices we make today. Quantitative foresight modeling is increasingly used to inform decision-making related to food systems by analytically exploring alternative possible futures in a world th...
| Autores principales: | , , , , , |
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| Formato: | Capítulo de libro |
| Lenguaje: | Inglés |
| Publicado: |
International Food Policy Research Institute
2025
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/175535 |
| _version_ | 1855525753665355776 |
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| author | Wiebe, Keith D. Mosnier, Aline Mason-D'Croz, Daniel Petsakos, Athanasios Svensson, Johannes Zurek, Monika |
| author_browse | Mason-D'Croz, Daniel Mosnier, Aline Petsakos, Athanasios Svensson, Johannes Wiebe, Keith D. Zurek, Monika |
| author_facet | Wiebe, Keith D. Mosnier, Aline Mason-D'Croz, Daniel Petsakos, Athanasios Svensson, Johannes Zurek, Monika |
| author_sort | Wiebe, Keith D. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | “Foresight modeling” is thinking about the future using a simplified representation of reality to inform choices we make today.
Quantitative foresight modeling is increasingly used to inform decision-making related to food systems by analytically exploring alternative possible futures in a world that is becoming more complex and uncertain.
Foresight modeling is improving in coverage and resolution, but various technical and institutional gaps remain.
Artificial intelligence can help gather and synthesize information to improve foresight modeling, but it cannot replace the role of human expertise and foresight in testing assumptions and helping to shape the future.
To be most effective, quantitative foresight modeling needs to be better linked with qualitative foresight approaches and complemented by engagement with decision-makers in an ongoing and systematic process. |
| format | Book Chapter |
| id | CGSpace175535 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | International Food Policy Research Institute |
| publisherStr | International Food Policy Research Institute |
| record_format | dspace |
| spelling | CGSpace1755352025-11-06T04:01:22Z What do we know about the future of foresight modeling related to food systems? Wiebe, Keith D. Mosnier, Aline Mason-D'Croz, Daniel Petsakos, Athanasios Svensson, Johannes Zurek, Monika artificial intelligence food systems modelling climate models growth models econometric models decision-support systems “Foresight modeling” is thinking about the future using a simplified representation of reality to inform choices we make today. Quantitative foresight modeling is increasingly used to inform decision-making related to food systems by analytically exploring alternative possible futures in a world that is becoming more complex and uncertain. Foresight modeling is improving in coverage and resolution, but various technical and institutional gaps remain. Artificial intelligence can help gather and synthesize information to improve foresight modeling, but it cannot replace the role of human expertise and foresight in testing assumptions and helping to shape the future. To be most effective, quantitative foresight modeling needs to be better linked with qualitative foresight approaches and complemented by engagement with decision-makers in an ongoing and systematic process. 2025-07-21 2025-07-07T20:58:47Z 2025-07-07T20:58:47Z Book Chapter https://hdl.handle.net/10568/175535 en https://hdl.handle.net/10568/175019 Open Access application/pdf International Food Policy Research Institute Wiebe, Keith D.; Mosnier, Aline; Mason-D'Croz, Daniel; Petsakos, Athanasios; Svensson, Johannes; and Zurek, Monika. 2025. What do we know about the future of foresight modeling related to food systems? In What do we know about the future of food systems? eds. Keith Wiebe and Elisabetta Gotor. Part Four: What Do We Know About the Future of Foresight Data and Analytical Tools? Chapter 37, Pp. 223-229. Washington, DC: International Food Policy Research Institute. https://hdl.handle.net/10568/175535 |
| spellingShingle | artificial intelligence food systems modelling climate models growth models econometric models decision-support systems Wiebe, Keith D. Mosnier, Aline Mason-D'Croz, Daniel Petsakos, Athanasios Svensson, Johannes Zurek, Monika What do we know about the future of foresight modeling related to food systems? |
| title | What do we know about the future of foresight modeling related to food systems? |
| title_full | What do we know about the future of foresight modeling related to food systems? |
| title_fullStr | What do we know about the future of foresight modeling related to food systems? |
| title_full_unstemmed | What do we know about the future of foresight modeling related to food systems? |
| title_short | What do we know about the future of foresight modeling related to food systems? |
| title_sort | what do we know about the future of foresight modeling related to food systems |
| topic | artificial intelligence food systems modelling climate models growth models econometric models decision-support systems |
| url | https://hdl.handle.net/10568/175535 |
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