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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?

Author

Listed:
  • Wiebe, Keith D.
  • Mosnier, Aline
  • Mason-D'Croz, Daniel
  • Petsakos, Athanasios
  • Svensson, Johannes
  • Zurek, Monika

Abstract

“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.

Suggested Citation

  • Wiebe, Keith D. & Mosnier, Aline & Mason-D'Croz, Daniel & Petsakos, Athanasios & Svensson, Johannes & Zurek, Monika, 2025. "What do we know about the future of foresight modeling related to food systems?," IFPRI book chapters, in: What do we know about the future of food systems?, chapter 37, pages p. 223-22, International Food Policy Research Institute (IFPRI).
    • Handle: RePEc:fpr:ifpric:175535
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    File URL: https://hdl.handle.net/10568/175535
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    References listed on IDEAS

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    1. Amber Geurts & Ralph Gutknecht & Philine Warnke & Arjen Goetheer & Elna Schirrmeister & Babette Bakker & Svetlana Meissner, 2022. "New perspectives for data‐supported foresight: The hybrid AI‐expert approach," Futures & Foresight Science, John Wiley & Sons, vol. 4(1), March.
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