Publication Type : Conference Proceedings
Publisher : IEEE
Source : 2024 Fourth International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)
Url : https://doi.org/10.1109/icaect60202.2024.10468754
Campus : Coimbatore
School : School of Engineering
Year : 2024
Abstract : Artificial Intelligence (AI) and Machine Learning (ML) are rapidly emerging technologies that augur revolutionary changes in developing nations. AI and ML can help address challenges in critical areas such as agriculture, healthcare, education, and employment. The challenges and barriers to the widespread adoption of AI and ML technologies in Indian villages were analyzed through participatory approaches from a livelihood perspective. AI implementations were proposed for a real-world case study conducted as part of the Live-in-Labs® program in Malkhanpur, a rural village in the Indian state of Uttar Pradesh, addressing the community challenge of low income. The challenges were evaluated at different dimensions - community level, household level, and individual level, using Participatory Rural Appraisal (PRA) and Human-centered Design (HCD) approach. This paper explored the application of AI to drive employment to achieve income generation and overall well-being. A generative AI-based platform, ’JobConnect: AI-based Rural Job Seeker-Provider App with ChatGPT Assistance’ is proposed with AI-based virtual assist with NLP, location-based Job listing, and matching algorithms. The platform is designed to be user-friendly and accessible to rural community with varying levels of digital literacy and connectivity.
Cite this Research Publication : K. B. Bharath Suhas, A. P. Sri Krishna, Karishram B., Maddina Sai Roopesh, Sachithanantha Jothi S., Kondepati Teja, Anu G. Kumar, Krishna Nandanan, Generative AI for Community Empowerment: Transforming Livelihood Opportunities in a Rural Indian Village, 2024 Fourth International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT), IEEE, 2024, https://doi.org/10.1109/icaect60202.2024.10468754