TheraGen: Therapy for Every Generation
Project Overview
The document explores the integration of generative AI in education, emphasizing its potential to enhance learning experiences and support mental health. A key application highlighted is TheraGen, an AI-powered mental health chatbot designed to provide accessible and personalized support to students and educators. Leveraging the LLaMA 2 7B model, TheraGen operates around the clock, utilizing a comprehensive dataset to engage users in meaningful conversations. The chatbot has garnered impressive user satisfaction, with 94% of participants reporting improvements in their mental well-being, illustrating its effectiveness as a complementary resource rather than a replacement for traditional therapy. The findings suggest that generative AI can play a significant role in addressing mental health challenges within educational settings, ultimately bridging gaps in service accessibility and enhancing overall student support systems.
Key Applications
TheraGen, an AI-powered mental health chatbot
Context: Accessible mental health support for individuals with mental health issues
Implementation: Utilized the LLaMA 2 7B model fine-tuned on a dataset of 1 million conversational entries, deployed on cloud infrastructure for scalability and availability
Outcomes: 94% user satisfaction, improved mental well-being for users, high accuracy in response generation (BLEU score of 0.67 and ROUGE score of 0.62), significant reduction in response time
Challenges: Not a replacement for professional therapy, ethical considerations regarding privacy and accuracy, maintaining user engagement and trust
Implementation Barriers
Ethical
Ensuring user privacy, transparency about AI capabilities, and addressing stigma associated with AI mental health support
Proposed Solutions: Implement strong data privacy measures, inform users of AI's role, and emphasize the complementary nature of AI support to professional therapy
Engagement and Trust
Users may be skeptical about the efficacy of an AI-based mental health tool compared to traditional therapy
Proposed Solutions: Provide consistent, high-quality interactions and demonstrate the value of AI over time
Accuracy and Reliability
Ensuring the accuracy and reliability of responses to maintain user trust
Proposed Solutions: Integrate advanced natural language understanding techniques and regularly update based on user feedback
Project Team
Kartikey Doshi
Researcher
Jimit Shah
Researcher
Narendra Shekokar
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Kartikey Doshi, Jimit Shah, Narendra Shekokar
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