Large Language Models (LLMs) like GPT-3 offer the potential to create more human-like and helpful chatbots. This paper presents a case study evaluating the feasibility of a GPT-3-based chatbot designed for improving mood and mental well-being. A randomized factorial experiment with 945 Mechanical Turk participants tested three prompt design dimensions: identity, intent, and behavior. Quantitative and qualitative analyses of conversations and user perceptions are presented, offering insights into prompt engineering for GPT-3 chatbots and providing a methodology for HCI designers and researchers to build upon.
Publisher
ACM
Published On
Aug 22, 2022
Authors
Harsh Kumar, Ilya Musabirov, Jiakai Shi, Adele Lauzon, Kwan Kiu Choy, Ofek Gross, Dana Kulzhabayeva, Joseph Jay Williams
