Transforming Community Engagement with Generative AI: Harnessing Machine Learning and Neural Networks for Hunger Alleviation and Global Food Security
DOI:
https://doi.org/10.48047/w6a74w66Keywords:
Generative AI, Community Engagement, Hunger, Food Security, Neural Networks, Machine Learning, Global South, Sustainable Development Goals, UN Collaboration, Technology for Good, Convention on Biological Diversity, Biotechnology, Ethical Considerations, Social Benefits, Case Studies, Policy Implications, Stakeholders, Impacted Communities, International Norms, Technology Development, Real-World Examples.Abstract
This essay examines the intersection of generative artificial intelligence (AI) with community engagement practices, which are designed to address hunger and food security. It draws on a wide range of stakeholders and collaborators and is supported by a literature review.
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References
Ravi Kumar Vankayalapati, Dilip Valiki, Venkata Krishna Azith Teja Ganti (2025) Zero-Trust Security Models for Cloud Data
Analytics: Enhancing Privacy in Distributed Systems . Journal of Artificial Intelligence & Cloud Computing. SRC/JAICC-436. DOI:
doi.org/10.47363/JAICC/2025(4)415
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