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With research staff from more than 70 countries, and offices across the globe, IFPRI provides research-based policy solutions to sustainably reduce poverty and end hunger and malnutrition in developing countries.

researcher spotlight

David Spielman

David Spielman is the director of IFPRI’s Innovation Policy and Scaling Unit and has been with the institute since 2004. His research agenda covers a range of topics including agriculture and rural development policy; agricultural science, technology, and innovation; plant genetic resources and seed systems; agricultural extension and advisory services; and community-driven rural development.

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Since 1975, IFPRI’s research has been informing policies and development programs to improve food security, nutrition, and livelihoods around the world.

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IFPRI currently has more than 480 employees working in over 70 countries with a wide range of local, national, and international partners.

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TOPIC

Artificial Intelligence (AI)

Artificial intelligence (AI) is poised to play a transformative role in advancing sustainable, resilient, and equitable food systems. AI refers broadly to models trained on data that can detect patterns, make predictions, generate insights, and support decision-making. This large umbrella includes methods ranging from machine learning and natural language processing to generative AI.

For agricultural research and policy, AI brings both opportunities and risks. It can expand the evidence base for decision-making, unlock new ways of analyzing complex systems, and improve how producers, researchers, and policymakers interact with data and models. Yet, without careful stewardship, AI can exacerbate inequalities, embed biases, or divert resources away from proven approaches.

As a global research organization, IFPRI has an obligation to improve access to data and research findings to emerging AI knowledge systems, while strengthening its research capacity and ensuring that these technologies are used responsibly to support inclusive and sustainable development.

IFPRI’s role is fivefold:

  • Building competencies and research skills. IFPRI applies AI across disciplines, from foresight modeling, econometrics, and natural language processing to remote sensing, data collection, and qualitative analysis. Building AI literacy among researchers and staff is key to strengthening institutional capacity.
  • Demonstrating use cases that center people. IFPRI explores AI applications across food systems—from farm-level decision support to policy analysis. We apply human-centered participatory design that augments rather than replaces trusted processes and institutional knowledge through transparent and explainable AI approaches.
  • Promoting responsible stewardship and investment. IFPRI analyzes how AI funding and investments shape food systems. Through strategic partnerships with governments, nongovernmental organizations, and the private sector, we help direct resources toward inclusive, evidence-based, and scalable applications.
  • Advancing digital public goods and open knowledge systems. IFPRI develops and shares FAIR (findable, accessible, interoperable, and reusable) datasets and open-access publications that serve as foundational resources for the global food policy research community. These digital public goods enable AI ecosystems to develop more relevant and context-appropriate AI applications for food systems.
  • Advancing ethics and responsible governance. IFPRI examines the ethical, legal, and social dimensions of AI in food systems. Our work informs policy frameworks and promotes innovation that is equitable, transparent, and accountable.

Illustration created using MidJourney AI

topics

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Journal Article

Geospatial analysis enables combined poultry–fish farm monitoring in the fragile state of Myanmar

2025Belton, Ben; Fang, Peixun; Liu, Shuo; Zhang, Kaifeng; Zhang, Xiaobo
Details

Geospatial analysis enables combined poultry–fish farm monitoring in the fragile state of Myanmar

Food security is challenging to measure in fragile contexts. Here we combine data from previous field surveys with remotely sensed images and apply deep-learning techniques to estimate changes in the number and area of chicken houses on integrated chicken–fish farms and the supply of chicken meat and eggs from 2010 to 2023 in Yangon region, Myanmar. Yangon’s poultry sector grew ~10% annually from 2010 to 2020 but contracted ~8% annually from 2020 to 2023.

Year published

2025

Authors

Belton, Ben; Fang, Peixun; Liu, Shuo; Zhang, Kaifeng; Zhang, Xiaobo

Citation

Belton, Ben; Fang, Peixun; Liu, Shuo; Zhang, Kaifeng; and Zhang, Xiaobo. 2025. Geospatial analysis enables combined poultry–fish farm monitoring in the fragile state of Myanmar. Nature Food 6(July 2025): 664-667. https://doi.org/10.1038/s43016-025-01192-1

Country/Region

Myanmar

Keywords

Asia; South-eastern Asia; Fish Farms; Food Security; Poultry Farming; Spatial Data; Fish Culture; Fragility

Language

English

Access/Licence

Open AccessCC-BY-4.0

Links

https://doi.org/10.1038/s43016-025-01192-1 Source record

Project

Digital Innovation

Record type

Journal Article

Publications

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Journal Article

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

2026Jones-Garcia, Eliot; Singaraju, Niyati; Davis, Kristin E.; Koo, Jawoo
Details

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.

Year published

2026

Authors

Jones-Garcia, Eliot; Singaraju, Niyati; Davis, Kristin E.; Koo, Jawoo

Citation

Jones-Garcia, Eliot; Singaraju, Niyati; Davis, Kristin E.; and Koo, Jawoo. 2026. Asking the right question: Toward a research agenda for responsible GAI in agricultural extension. Advancements in Agricultural Development 7(2): 35-49. https://doi.org/10.37433/aad.v7i2.633

Keywords

Gender; Women Farmers; Smallholders; Artificial Intelligence; Agricultural Extension; Evaluation

Language

English

Access/Licence

Open AccessCC-BY-4.0

Links

https://doi.org/10.37433/aad.v7i2.633 Source record

Record type

Journal Article

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Brief

PROBES snapshot: Longa, automated speech recognition for Bantu languages

2025Jones-Garcia, Eliot; Benavente, Grecia; Jimenez, Daniel Ricardo
Details

PROBES snapshot: Longa, automated speech recognition for Bantu languages

This one-page brief, developed by the Digital Transformation Accelerator (DTA) team at the Alliance of Bioversity International and CIAT, is based on the Longa probe led by Eliot Jones-Garcia, Senior Research Analyst at IFPRI. The probe explores the use of automatic speech recognition (ASR) for Bantu languages to enable voice-based interaction with digital agricultural services. Longa tests whether low-resource ASR models can accurately capture farmers’ spoken input in real-world conditions and convert it into usable data for digital extension and advisory systems. Implemented as a safe-to-fail, early-stage experiment, the probe focuses on learning how voice-first technologies can reduce literacy and language barriers, improve inclusivity, and strengthen farmer engagement. The brief synthesizes key insights on accuracy, usability, and scalability to inform future development and potential integration of speech-based tools within CGIAR digital pathways.

Year published

2025

Authors

Jones-Garcia, Eliot; Benavente, Grecia; Jimenez, Daniel Ricardo

Citation

Jones-Garcia, E.; Benavente, G.; Jimenez, D.R. (2025) PROBES snapshot: Longa, automated speech recognition for Bantu languages. 1 p.

Keywords

Information and Communication Technologies; Artificial Intelligence; Digital Inclusion; Speech Recognition; Decision Support Systems

Language

English

Access/Licence

Open AccessCC-BY-4.0

Source

Source record

Record type

Brief

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Report

AI licensing: Pricing guidance for publishers and non-profits

2025Haynes, Zachary
Details

AI licensing: Pricing guidance for publishers and non-profits

Academic and non-profit publishers, societies and research institutions’ portfolios of intellectual property and copyrights include books, journals, major reference works, factsheets, databases, and online resources covering vast subject areas and fields of expertise. They are trusted sources of subject-specific material, with a wealth of experience, expertise and value to offer the emerging AI (models, products, services and applications) training ecosystem. There are any number of heretofore unknown AI applications and AI-enabled tools, at commercial, non-commercial, institutional, organizational and individual levels that may benefit from academic and research publications, and the digital data that is cultivated and curated in pursuit of that scholarship. The copyright holders need to find a sustainable and strategic approach for pricing their knowledge bases and repositories, to meet the market expectations of these opportunities that are simultaneously business prudent, ethical and mission-based. Therefore, we want to consider and determine a pricing strategy that is multipurpose and multifocused, considerate of various factors and axes, while also aligning the appropriate market and value expectations across a variety of use cases, customers and users. This document offers an investigation into: -The potential to create a license pricing framework in order for publishers to contribute their curated digital and analog assets into GenAI tools. -The variety of commercial AI opportunities that may be presented to copyright, IP holders and creators.

Year published

2025

Authors

Haynes, Zachary

Citation

Haynes, Zachary. 2025. AI licensing: Pricing guidance for publishers and non-profits. CAB International. https://hdl.handle.net/10568/181438

Keywords

Artificial Intelligence; Agriculture; Price Formation; Private Sector Engagement

Language

English

Access/Licence

Open Access

Source

Source record

Record type

Report

Blogs

How AI can help reduce food loss and waste in Nigeria’s tomato value chain
Research Post
 | 
March 25, 2026

How AI can help reduce food loss and waste in Nigeria’s tomato value chain

By Futoshi Yamauchi, Aoi Fukuhara, Dauda Bawa, Caleb Olanipekun, and Olufemi Popoola

Using photos to analyze when and where produce goes bad.

Co-designing AI agents for agricultural policy
Event Post
 | 
March 04, 2026

Co-designing AI agents for agricultural policy

By Kristin Davis, Eliot Jones-Garcia, Hlamalani Ngwenya, Arielle Rosenthal, Amanda Grossi, and Mia Speier

Generating insights for a rapidly-changing world.

How natural language processing and AI can help policymakers address global food insecurity
Research Post
 | 
February 12, 2026

How natural language processing and AI can help policymakers address global food insecurity

By Marieke Meeske

Scaling up data analysis to meet SDG2.

View all Blogs

Events

When Data Is Everywhere: Digital Research Methods Transforming Food Systems Science
IFPRI Program/Country Event

 | 

May 14, 2026, 9:00 – 10:00 am

When Data Is Everywhere: Digital Research Methods Transforming Food Systems Science

In an era of data abundance, novel digital research methods are reshaping how we study and improve food systems. Building on earlier sessions focused on speech-based AI and farmer-generated data, this discussion broadens the lens, bringing together two researchers who are applying cutting-edge digital tools to address complex questions in the food domain.  First, Soonho Kim (Senior Data Manager, IFPRI) will introduce how Agentic AI […]

Leveraging Automatic Speech Recognition and Farmer-Generated Data for Insight, Inclusion, and Impact
IFPRI Program/Country Event

 | 

May 1, 2026, 9:30 – 10:30 am

Leveraging Automatic Speech Recognition and Farmer-Generated Data for Insight, Inclusion, and Impact

As speech recognition and mobile data collection tools mature, increasing attention is turning to a critical next question: how can farmer-generated data be meaningfully used to inform research, programs, and policy? This session builds directly on earlier discussions of Automatic Speech Recognition (ASR) for agriculture by focusing on the applications, utility, and downstream impacts of […]

Breaking the Silence: Deploying Automatic Speech Recognition for Agricultural Advisory
IFPRI Program/Country Event

 | 

April 9, 2026, 9:30 – 10:30 am

Breaking the Silence: Deploying Automatic Speech Recognition for Agricultural Advisory

Speech-based interfaces are increasingly central to agricultural advisory systems, particularly in low-resource and multilingual contexts where oral communication remains the primary channel for accessing information. Automatic Speech Recognition (ASR) is therefore a critical—but still under-examined—component of AI-enabled agricultural extension.  This webinar presents emerging research on the state of the art in ASR for agriculture, with a focus on real-world deployment for low-resource […]

View all Events

News

February 17, 2026 | Press Release

IFPRI and Farm Radio International collaborate to give a voice to the most vulnerable farmers by advancing AI tools for African languages

Introducing Longa, an AI-powered speech recognition tool designed to strengthen agricultural communication and inclusivity across sub-Saharan Africa.

November 12, 2025 | Press Release

IFPRI and Digital Green expand collaboration to test AI innovations for smallholder farmers

Building on years of joint research on digital extension, the collaboration will now focus on user testing of Digital Green’s FarmerChat application as part of IFPRI’s Generative AI for Agriculture (GAIA) initiative.

October 06, 2025 | In the News

Agriculture Ministry and LIFAAS host generative AI workshop to strengthen extension services (Ministry of Agriculture, Liberia)

With support from IFPRI, the workshop brought together diverse stakeholders to explore how generative AI can close extension gaps and enhance the reach and impact of agricultural advisory services in Liberia.

View all News

Our experts

Pushkar Gaur

Pushkar Gaur

Research Analyst, Natural
Resources and Resilience

Aulo Gelli

Aulo Gelli

Senior Research Fellow, Poverty,
Gender, and Inclusion

Soonho Kim

Soonho Kim

Senior Data Manager, Markets,
Trade, and Institutions

Jawoo Koo

Jawoo Koo

Senior Research Fellow, Natural
Resources and Resilience