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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

Danielle Resnick

Danielle Resnick is a Senior Research Fellow in the Markets, Trade, and Institutions Unit and a Non-Resident Fellow in the Global Economy and Development Program at the Brookings Institution. Her research focuses on the political economy of agricultural policy and food systems, governance, and democratization, drawing on extensive fieldwork and policy engagement across Africa and South Asia.

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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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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

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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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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

Blogs

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.

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.

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Events

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

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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 […]

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, 9:00 – 10:00 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 […]

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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.