SUKHSANDESH: An Avatar Therapeutic Question Answering Platform for Sexual Education in Rural India
Project Overview
The document discusses S UKH SANDESH, an innovative AI-driven Question Answering platform designed to deliver sexual education to vulnerable rural communities in India. Utilizing generative AI and avatar technology, it effectively tackles cultural stigmas surrounding sexual health by providing accessible information in regional languages. The platform prioritizes user safety through protective measures that ensure privacy and mitigate exposure to harmful content. Furthermore, the empathetic avatar feature enhances user engagement, particularly benefiting individuals with limited literacy skills by fostering a more relatable and supportive learning environment. Overall, the application of generative AI in this educational context demonstrates its potential to improve access to vital information and promote informed decision-making among underserved populations.
Key Applications
S UKH SANDESH - AI-based Question Answering platform
Context: Rural Indian population seeking sexual education
Implementation: Multi-staged system using information retrieval and generative AI (LLMs) with avatar therapy for real-time audio responses.
Outcomes: Improved access to sexual education, enhanced user engagement through empathy, and support for regional languages.
Challenges: Cultural stigma around sexual education, lack of labeled data, ensuring data quality, and ethical considerations regarding user privacy.
Implementation Barriers
Cultural Barrier
Stigmas and taboos surrounding sexual education in rural India hinder open communication and data acquisition due to cultural norms related to sexual topics.
Proposed Solutions: Ground-level awareness programs and partnerships with local organizations (e.g., Gram Vaani) to build trust, along with collaboration with local organizations to gather anonymized user queries and responses.
Technical Barrier
Quality issues in data due to potential biases, lack of representation in training datasets, and a shortage of skilled personnel in AI for model training and deployment.
Proposed Solutions: Implement rigorous data validation processes, utilize diverse data sources, and invest in training programs to build local AI expertise.
Resource Barrier
High energy consumption associated with training large language models leading to a significant carbon footprint.
Proposed Solutions: Explore energy-efficient AI models and practices to mitigate environmental impact.
Project Team
Salam Michael Singh
Researcher
Shubhmoy Kumar Garg
Researcher
Amitesh Misra
Researcher
Aaditeshwar Seth
Researcher
Tanmoy Chakraborty
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Salam Michael Singh, Shubhmoy Kumar Garg, Amitesh Misra, Aaditeshwar Seth, Tanmoy Chakraborty
Source Publication: View Original PaperLink opens in a new window
Project Contact: Dr. Jianhua Yang
LLM Model Version: gpt-4o-mini-2024-07-18
Analysis Provider: Openai