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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

Eliot Jones-Garcia

Eliot Jones-Garcia is a Senior Research Analyst with the Natural Resources and Resilience Unit based in Washington, DC. His research focuses on human-AI interaction, user-centered design, and the ethical and responsible development of AI. Eliot is currently finalizing a PhD on the digitalization of agricultural advisory services at Wageningen University & Research.

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Natural Resources and Resilience

Eliot Jones-Garcia

Senior Research Analyst

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Bio

Eliot Jones-Garcia is a Senior Research Analyst with the Natural Resources and Resilience Unit based in Washington, DC. His research focuses on human-AI interaction, user-centered design, and the ethical and responsible development of AI.

At IFPRI, he explores the conceptual and methodological advancements of AI, the skills and governance structures needed to responsibly integrate AI into agricultural research, and the socio-technical barriers that shape its effectiveness in extension and advisory services.

Eliot is finalizing a PhD on the digitalization of agricultural advisory services at Wageningen University & Research. He holds a master’s in Rural Development and Innovation from Wageningen University and a bachelor’s in International Agriculture from the University of Greenwich.

Languages spoken: English, Functional Spanish

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Publications

Resource thumbnail

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

Resource thumbnail

Report

Longa: An automated speech recognition tool for Bantu languages

2023Mganga, Nelson; Jones-Garcia, Eliot; Monsalue, Andrea Gardeazabal; Koo, Jawoo
Details

Longa: An automated speech recognition tool for Bantu languages

Farm Radio International (FRI) and the CGIAR Research Initiative on Digital Innovation have col laborated on the development of an end-to-end, automatic speech recognition pipeline for the tran scription, translation, and analysis of Swahili and Luganda. This task is particularly challenging due to the number of languages used by FRI’s clients and the limited training data available for speech recognition in African languages. The tool is named ‘Longa’, or ‘Let’s chat’ in Swahili. Longa will be used to answer the surplus of phone calls currently being received from smallholder farmers asking questions about radio programs which FRI does not presently have the capacity to address. When fully implemented, Longa should allow FRI to design their broadcasts more intricately in line with the needs of farmers and better deliver insights to those most in need, such as female and youth farmers. Key results from the collaboration include a series of design principles iteratively and col laboratively developed to reflect the common values and goals of FRI and the CGIAR, a proof of concept for Longa, building on open-source models and open access corpora, to be shared with the developer community upon completion of the final tool, a 10% improvement upon the state-of-the art automatic speech recognition in Luganda radio-speech performance and accuracy, some im provement in performance with audio enhancement processes using real-world data, and proof that fine-tuning is an effective approach to expanding Longa to new languages. The next steps of the collaboration will focus on the analysis and interpretation of an aggregation of farmer phone calls and integration with the existing FRI workflow and software.

Year published

2023

Authors

Mganga, Nelson; Jones-Garcia, Eliot; Monsalue, Andrea Gardeazabal; Koo, Jawoo

Citation

Mganga, Nelson; Jones-Garcia, Eliot; Monsalue, Andrea Gardeazabal; and Koo, Jawoo. 2023. Longa: An automated speech recognition tool for Bantu languages. Digital Innovation Technical Report December 2023. Washington, DC: International Food Policy Research Institute (IFPRI). https://hdl.handle.net/10568/137177

Keywords

Africa; Artificial Intelligence; Innovation Adoption; Languages; Farmers

Language

English

Access/Licence

Open AccessCC-BY-4.0

Source

Source record

Project

Digital Innovation

Record type

Report

Blogs

Asking the right questions: A stakeholder dialogue on generative AI in digital extension
IFPRI Blog
 | 
October 07, 2025

Asking the right questions: A stakeholder dialogue on generative AI in digital extension

By Eliot Jones-Garcia, Kristin Davis, and Niyati Singaraju

Balancing new technology with local needs.

Grounding AI in practice: What extension gets wrong, what extension gets right, and what AI can learn
IFPRI Blog
 | 
August 26, 2025

Grounding AI in practice: What extension gets wrong, what extension gets right, and what AI can learn

By Kristin Davis, Eliot Jones-Garcia, and Niyati Singaraju

Exploring how emerging tools can help farmers.

Beyond the hype: Centering humans in CGIAR’s genAI research
IFPRI Blog
 | 
May 14, 2025

Beyond the hype: Centering humans in CGIAR’s genAI research

By Eliot Jones-Garcia

Realizing the potential and minimizing the risks of a promising new technology.

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Events

From Foundations to Field: Lessons from Microsoft and Reply’s Work in Agriculture
IFPRI Program/Country Event

 | 

January 29, 2026, 9:30 – 10:30 am

From Foundations to Field: Lessons from Microsoft and Reply’s Work in Agriculture

As large language models (LLMs) and generative AI systems evolve, understanding how these technologies work—and what they can realistically achieve—has become essential for researchers and practitioners alike. Over the past year, many of us have had the chance to experiment with these systems in a “sandbox” environment. Today, we move from experimentation to brass tack with a […]

AI and Remote Sensing for Agricultural Insights: From Satellite Imagery to Decision Support 
IFPRI Program/Country Event

 | 

November 20, 2025, 9:30 – 10:30 am

AI and Remote Sensing for Agricultural Insights: From Satellite Imagery to Decision Support 

How can advances in AI and remote sensing improve agricultural decision-making, particularly in contexts where timely, accurate data is difficult to obtain? This webinar explores the intersection of machine learning and satellite imagery, focusing on innovations that enhance monitoring, planning, and climate resilience in food systems.  Ambica Paliwal will share insights on how remote sensing […]

IFPRI @ 30th UN Climate Change Conference of the Parties (COP30)
IFPRI at External Event

 | 

November 10 to 21, 2025

IFPRI @ 30th UN Climate Change Conference of the Parties (COP30)

IFPRI is pleased to participate in the 30th UN Climate Change Conference of the Parties (COP30) being held in Belém, Brazil from November 10 to November 21, 2025. COP30 builds on progress of previous COPs to turn the ambitions of the Paris Agreement into reality. Hosted in the Amazonian city of Belém, the topics of […]

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News

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.