2023/04/02 by Baihan Lin, Lin, Baihan, Djallel Bouneffouf +5 · 1 voice · 2 citations
Computer Science · Medicine · Psychology · #Artificial Intelligence (cs.AI) #Artificial Intelligence in Healthcare and Education #Computation and Language (cs.CL) #Computers and Society (cs.CY) #Digital Mental Health Interventions #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Machine Learning (cs.LG) #Mental Health via Writing #cs.AI #cs.CL #cs.CY #cs.HC #cs.LG
paper · pdf · doi:10.48550/arxiv.2304.00416
openalex publication_date 2023/04/02 · arxiv published 2023/04/02 · arxiv updated 2023/04/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Recent advances in large language models (LLMs) have led to the development of powerful AI chatbots capable of engaging in natural and human-like conversations. However, these chatbots can be potentially harmful, exhibiting manipulative, gaslighting, and narcissistic behaviors. We define Healthy AI to be safe, trustworthy and ethical. To create healthy AI systems, we present the SafeguardGPT framework that uses psychotherapy to correct for these harmful behaviors in AI chatbots. The framework involves four types of AI agents: a Chatbot, a "User," a "Therapist," and a "Critic." We demonstrate the effectiveness of SafeguardGPT through a working example of simulating a social conversation. Our results show that the framework can improve the quality of conversations between AI chatbots and humans. Although there are still several challenges and directions to be addressed in the future, SafeguardGPT provides a promising approach to improving the alignment between AI chatbots and human values. By incorporating psychotherapy and reinforcement learning techniques, the framework enables AI chatbots to learn and adapt to human preferences and values in a safe and ethical way, contributing to the development of a more human-centric and responsible AI.