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With research staff from more than 60 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

Elodie Becquey

Elodie Becquey is a Senior Research Fellow in the Nutrition, Diets, and Health Unit, based in IFPRI’s West and Central Africa office in Senegal. She has over 15 years of research experience in diet, nutrition, and food security in Africa, including countries such as Burkina Faso, Chad, Ethiopia, Ghana, Kenya, Mali, and Tanzania.

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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 600 employees working in over 80 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.

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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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Opinion Piece

Beyond the human touch: Can generative AI transform Uganda’s agricultural extension and advisory services?

2025Asiimwe, Elizabeth; Davis, Kristin E.
Details

Beyond the human touch: Can generative AI transform Uganda’s agricultural extension and advisory services?

Generative Artificial Intelligence (Gen AI) is a type of artificial intelligence that can create new content such as text, images, audio, video, or even computer code, based on the data it has been trained on. Generative AI is trained on huge amounts of data (like books, images, and conversations), and it learns patterns. When prompted, it uses the learned patterns to generate something new that fits the request.

Year published

2025

Authors

Asiimwe, Elizabeth; Davis, Kristin E.

Citation

Asiimwe, Elizabeth; and Davis, Kristin E. 2025. Beyond the human touch: Can generative AI transform Uganda’s agricultural extension and advisory services? UFAAS Blog Post. https://ufaas-ugandacf.org/beyond-the-human-touch-can-generative-ai-transform-ugandas-agricultural-extension-and-advisory-services/

Country/Region

Uganda

Keywords

Africa; Sub-saharan Africa; Eastern Africa; Artificial Intelligence; Agricultural Extension; Advisory Services; Digital Technology

Language

English

Access/Licence

Open Access

Source

Source record

Record type

Opinion Piece

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Training Material

Ethical use of artificial intelligence in food, land and water systems research: A guide for equity and inclusion

2025Jones-Garcia, Eliot; Malapit, Hazel J.; Magalhaes, Marilia; Go, Ara; Bryan, Elizabeth
Details

Ethical use of artificial intelligence in food, land and water systems research: A guide for equity and inclusion

This document aims to support CGIAR researchers and their partners by providing guidance, recommendations and resources on ethical considerations in using artificial intelligence (AI) in food, land and water systems (FLWS) research and practice with attention to equity and inclusion dimensions. This toolkit complements the GENDER Impact Platform Ethics and Standards Toolkit and aligns with CGIAR’s core ethical values outlined in the CGIAR Ethics Framework and the CGIAR Research Ethics Code. In response to the rapid development and adoption of emerging AI technologies, the toolkit presents key issues and practical recommendations for researchers to consider across the research cycle, drawing on a comprehensive literature review and interviews with experts in AI ethics and social inclusion. AI systems, as used in this context, refer to technologies that mimic aspects of human cognition and behavior—interpreting real-world data, generating predictions, and adapting through continuous learning (Benefo et al. 2022; Fu 2022; Manning et al. 2022). These systems are increasingly central to a suite of AI and agricultural technologies poised to transform FLWS research: not only in how we conduct research and generate insights, but also in how we define best practice for gender-related research and understand the downstream impacts of our research outputs.

Year published

2025

Authors

Jones-Garcia, Eliot; Malapit, Hazel J.; Magalhaes, Marilia; Go, Ara; Bryan, Elizabeth

Citation

Jones-Garcia, E., Malapit, H., Magalhaes, M., Go, A. and Bryan, E. 2025. Ethical use of artificial intelligence in food, land and water systems research: a guide for equity and inclusion. Nairobi, Kenya: CGIAR Gender Equality and Inclusion.

Keywords

Artificial Intelligence; Agrifood Systems; Research

Language

English

Access/Licence

Open AccessCC-BY-4.0

Source

Source record

Record type

Training Material

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Infographic

PEPA.AI Generating Insights for Informing Policy Decisions: Steps

2025Mockshell, Jonathan Yaw; Mosquera Escobar, Leslie Estefany; Blanco Garcia, Maria Alejandra; Garcia Gallego, Jeffrey Steven; Franco Betancourt, Gabriel; Nielsen Ritter, Thea; Resnick, Danielle
Details

PEPA.AI Generating Insights for Informing Policy Decisions: Steps

Year published

2025

Authors

Mockshell, Jonathan Yaw; Mosquera Escobar, Leslie Estefany; Blanco Garcia, Maria Alejandra; Garcia Gallego, Jeffrey Steven; Franco Betancourt, Gabriel; Nielsen Ritter, Thea; Resnick, Danielle

Citation

Mockshell, J.Y.; Mosquera Escobar, L.E.; Blanco Garcia, M.A.; Garcia Gallego, J.S.; Franco Betancourt, G.; Nielsen Ritter, T.; Resnick, D. (2025) PEPA.AI Generating Insights for Informing Policy Decisions: Steps. xx p.

Keywords

Artificial Intelligence; Inteligencia Artificial; Policy Analysis; Análisis De Políticas

Language

English

Access/Licence

Open AccessCC-BY-4.0

Source

Source record

Record type

Infographic

Blogs

Beyond the algorithm: The need for farmer participation and data justice in digital agricultural technology
IFPRI Blog
 | 
December 02, 2025

Beyond the algorithm: The need for farmer participation and data justice in digital agricultural technology

By Ayorinde Ogunyiola

Addressing systemic disadvantages.

How accurately do the large language models (LLMs) powering chatbots respond to questions on gender equality and women’s empowerment in Indian agriculture?
IFPRI Blog
 | 
November 14, 2025

How accurately do the large language models (LLMs) powering chatbots respond to questions on gender equality and women’s empowerment in Indian agriculture?

By Marilia Magalhaes, Niyati Singaraju, and Jawoo Koo

A key issue for AI in extension services.

Generative AI’s environmental footprint poses difficult tradeoffs for agrifood systems in low- and middle-income countries
IFPRI Blog
 | 
October 24, 2025

Generative AI’s environmental footprint poses difficult tradeoffs for agrifood systems in low- and middle-income countries

By Amy Margolies

Costs and benefits of data centers.

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Events

Launching the Ethical AI Methods Toolkit: Reflections from Research and Practice
IFPRI Program/Country Event

 | 

October 23, 2025, 9:00 – 10:00 am

Launching the Ethical AI Methods Toolkit: Reflections from Research and Practice

What does it mean to design ethical AI for agricultural research and development—and how can researchers and practitioners begin to put principles into practice? Following our previous webinar on A Problem-Oriented Approach to AI Ethics in Food Systems, this event marks the launch of the Ethical AI Methods Toolkit: a practical resource developed to support […]

Making Sense of AI and Qualitative Research: Conversations on Meaning, Context, and Power
IFPRI Program/Country Event

 | 

October 2, 2025, 9:30 – 10:30 am

Making Sense of AI and Qualitative Research: Conversations on Meaning, Context, and Power

As artificial intelligence tools become more common in research workflows, qualitative researchers face both new opportunities and critical challenges. Can AI support interpretive and nuanced research? What risks might it introduce—and how can researchers remain attentive to nuance, positionality and power?  ​​​This webinar explores the use of AI in qualitative research. Drawing on her experience […]

From Principles to Practice: A Problem-Oriented Approach to AI Ethics in Food Systems 
IFPRI Program/Country Event

 | 

September 18, 2025, 9:30 – 10:30 am

From Principles to Practice: A Problem-Oriented Approach to AI Ethics in Food Systems 

This webinar offers a practical introduction to AI ethics, with a focus on how ethical principles translate into real-world decisions. As AI tools are increasingly deployed in food systems research and innovation, questions around fairness, accountability, consent, and transparency are no longer abstract—they are critical design choices with tangible implications.  Together, the speakers will explore […]

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News

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.

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Aulo Gelli

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Jawoo Koo

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Yanyan Liu

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