AI psychotherapists and positive psychology : a systematic literature review of current literature and future directions

Abstract

This thesis summarizes the state of the art concerning the integration of artificial intelligence (AI) with positive psychology. The main contributions include: (1) analysis of the existing literature to classify relevant research in terms of technological advancements and their applications, identify the key AI technologies such as machine learning, natural language processing, and robotics that support positive psychology interventions, highlight the primary domains where these integrations have been most impactful, such as education, mental health, and organizational development; (2) identification of gaps and open issues that emerge from the analysis, offering a theoretical framework for future research and development by addressing key areas of improvement, including personalization through the use of NLP and machine learning algorithms, scalability via cloud-based infrastructure, cultural adaptability with multilingual datasets, ethical compliance through GDPR-aligned practices, emotional sensitivity using multimodal sentiment analysis, real-time feedback mechanisms, iterative improvement informed by user feedback, hybrid human-AI collaboration for high-risk cases, cost-effectiveness through experimental designs, and cross-domain applications to integrate mental health interventions across diverse fields such as education, healthcare, and workplace environments; and (3) This targeted approach aims to provide insights that are directly relevant to the development of AI systems tailored for positive psychology.