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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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experts

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
Research Post
 | 
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
Research Post
 | 
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
Research Post
 | 
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

Farmer-Centric AI for Livestock Systems: Design, Explainability, and Responsible Innovation
IFPRI Program/Country Event

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March 26, 2026, 9:30 – 10:30 am

Farmer-Centric AI for Livestock Systems: Design, Explainability, and Responsible Innovation

As AI tools begin to influence livestock production, health management, and advisory services, ensuring these technologies are farmer-centric, explainable, and context-appropriate is essential. This webinar brings together researchers working at the intersection of livestock systems, digital innovation, and responsible AI to explore how AI can be designed and deployed in ways that genuinely serve livestock keepers.  We begin with Karen […]

Large Language Models for Policy Makers: Exploring RIAPA-AI and PEPA-AI
IFPRI Program/Country Event

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March 12, 2026, 9:30 – 10:30 am

Large Language Models for Policy Makers: Exploring RIAPA-AI and PEPA-AI

As large language models (LLMs) begin to influence how evidence is generated, synthesized, and communicated, new opportunities are emerging for policymakers and analysts working in food systems. This webinar explores how generative AI tools can support policy design, analysis, and dialogue—bridging technical modeling and real-world decision-making.  Askar Mukashov, Research Fellow at IFPRI, will introduce RIAPA-AI, an extension of the Rural Investment and […]

Two Sides of the Data Governance Coin: AI Innovation and Regulation for Producers and Users 
IFPRI Program/Country Event

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February 26, 2026, 9:30 – 10:30 am

Two Sides of the Data Governance Coin: AI Innovation and Regulation for Producers and Users 

Responsible AI and data governance are often framed as constraints on innovation—but what if they are essential to it? This webinar explores why ethical, well-regulated systems are not at odds with innovation, but rather foundational to its legitimacy, sustainability, and impact.  Bringing together perspectives from both technology producers and users, this session examines how policy, design, and governance […]

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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.