Human Chatbot

Human-chatbot interaction research focuses on improving chatbot design and evaluation, aiming to create more engaging, helpful, and trustworthy conversational AI. Current research emphasizes evaluating chatbot performance through both online user interactions and offline assessments, utilizing large language models (LLMs) for automated evaluation and analysis of vast conversation datasets. Key areas of investigation include mitigating biases, enhancing privacy protections, and developing methods for personalized and contextually relevant responses, ultimately impacting the development of more effective and ethical conversational AI across various applications.