Rui Benfica is a Senior Research Fellow in the Innovation Policy and Scaling Unit. Prior to joining IFPRI in 2019, he worked with the Research and Impact Assessment Division at the International Fund for Agricultural Development (IFAD), where he undertook research in areas relevant for the overarching goal of overcoming poverty and achieving food security and nutrition, development and dissemination/outreach of policy research outputs, the design and implementation of impact assessments of the Fund’s interventions in client countries in Asia and Latin America, and economy-wide modeling analysis to inform IFAD’s Country Strategies. He was also Associate Professor of International Development at Michigan State University and worked on research in South Asia and sub-Saharan Africa with the Food Security Group (FSG) on a wide range of issues including policy analysis and evaluation of development interventions aimed at promoting income diversification, reducing poverty, fostering gender equality and women’s empowerment, and promoting food and nutrition security. Early in his career, he worked at the World Bank as an Economist with the Gender and Development Group and as Poverty Economist in the Africa Region, Mozambique Country Office, where he engaged in research and policy dialogue with the Ministries of Planning and Development and of Agriculture and Rural Development, undertaking poverty assessments, impact evaluations, and poverty and social impact analyses.
Rui holds a PhD in Agricultural Economics from Michigan State University, with a focus on International Development, Commodity Market Analysis, and Quantitative Development Policy Research. He is a member of several professional organizations, has published extensively in peer-reviewed journals, and served as founder and co-editor of the IFAD Research Series.
Speaker: Rajesh Veeraraghavan (Georgetown University)
Responsible AI is a widely discussed topic these days, but what does it really entail? In this session, Rajesh Veeraraghavan, a recently tenured Associate Professor at Georgetown University’s School of Foreign Service and an affiliate of the Massive Data Institute, will explore this question. He will offer a comprehensive overview of responsible AI, focusing on the ethical challenges and design complexities of AI systems. Rajesh’s ICT4D research focuses on creating technology solutions that are not only advanced but also ethically responsive to the needs of global, often marginalized, populations.
Moderator: Jawoo Koo (IFPRI)
Panelists: David Spielman (IFPRI), Jona Repishti (Digital Green), Patricia Zambrano (IFPRI), Caitlin Corner-Dolloff (USAID)
AI holds exciting potential for addressing challenges faced by agriculture. However, regulatory frameworks are needed to ensure that AI does not inadvertently harm farmers and other agricultural stakeholders. While the concept of responsible AI is frequently emphasized, there is no universally accepted definition or clear implementation guidelines. Panelists in this session will explore what it means to develop and use AI solutions responsibly in agriculture, particularly for small-scale producers in the global South. They will also discuss how to balance fostering innovation with safeguarding stakeholders from potential risks.
Moderator: Charlotte Hebebrand (IFPRI) Panelists: Andres Ferreyra (Syngenta), Rui Benfica (IFPRI), Jeehye Kim (World Bank)
The potential of AI in agriculture is very promising, but will AI actually help farmers increase their income, and if so, how? This session will address unanswered questions about AI’s prospects for enhancing farm income, particularly in light of the declining profitability of agriculture globally in recent years. Can advanced technologies, especially AI-powered ones, reverse this trend? Panelists will share their experiences working with farmers and other agricultural stakeholders, highlighting the areas of farming where AI can potentially reduce costs and improve profitability over the next 5 to 10 years. Additionally, they will discuss the risks associated with technology failures, including the implications of AI liability and the necessary safeguards.
New Delhi, India
Texcoco, Mexico
Washington, D.C., United States
