Jawoo Koo

Asking the right question: Toward a research agenda for responsible GAI in agricultural extension

This study explores how generative AI (GAI) tools for agricultural extension can be designed and evaluated more responsibly. While current GAI systems offer scalable, personalized advice, they often ignore the lived realities of smallholder farmers—especially women—by relying on generic datasets and rigid evaluation metrics. We investigate three complementary methods: adversarial testing to expose gendered and contextual blind spots in model outputs; deliberative stakeholder engagement using the C-H-A-T framework, which focused on Collective knowledge, Human insight, Augmentation, and Trust, to surface value tensions and design trade-offs; and field-level insights from extension officers to uncover trust-building, diagnostic reasoning, and social intelligence absent from static GAI interactions. Together, these approaches reveal that responsible GAI requires more than technical accuracy. It demands participatory design processes that foreground user realities, surface stakeholder assumptions, and account for social and institutional context. We recommend developing gender-responsive benchmarks, embedding reflexive, participatory design methods, and modeling advisory reasoning based on real-world extension practice. The findings contribute to a growing agenda for responsible AI development—highlighting the importance of aligning GAI tools not only with technical goals, but with the social, cultural, and political contexts in which they operate.

What do we know about the impacts of the next El Niño on agrifood systems?

As of June 2023, the U.S. National Oceanic and Atmospheric Administration (NOAA) declared that El Niño conditions were present and consensus existed among climate prediction centers that El Niño would likely persist from November 2023 to February 2024. El Niño is typically associated with seasonal climate anomalies and extreme weather events throughout the developing world, especially across sub-Saharan Africa, but the economic impacts caused by these events are difficult to disentangle from those of other climate shocks, natural disasters, and economic cycles. Additionally, the strength and consistency of El Niño’s agroclimatic impacts vary by region. El Niño’s unique slow onset, periodic pattern, and lead times of prediction (from a few months to a year) make it possible to design anticipatory policies and prepare emergency responses in advance. Policymakers should closely monitor the evolution of El Niño-Southern Oscillation (ENSO) phases and the potential impacts of El Niño and be prepared to coordinate policy responses quickly as the situation unfolds. As global warming continues and climate extremes occur more frequently, actions to foster climate-resilient agrifood systems should be broadly prioritized.

Statistics from Space: Next-Generation Agricultural Production Information for Enhanced Monitoring of Food Security in Mozambique – Progress report (January-June 2025)