Public perceptions towards ChatGPT as the Robo-Assistant
Kris Jangjarat, Tanpat Kraiwanit, Pongsakorn Limna, Rattaphong Sonsuphap
Abstract
The widespread adoption of digital technologies in various economic activities paves the way for the establishment of a unified digital space. ChatGPT, an artificial intelligence language model, can generate increasingly realistic text, with no information on the accuracy and integrity of using these models in scientific writing. This study aims to investigate factors influencing public perceptions toward the acceptance of ChatGPT as the Robo-Assistant, using a mixed method. The quantitative approach in this study employed convenience sampling to collect data through closed-ended questionnaires from a sample size of 1,880 respondents. Statistical analysis software was used for data analysis. The researchers used binary regression to examine the relationship between various independent variables (such as score, gender, education, social media usage) and the acceptance of ChatGPT, as dependent variable. As part of the qualitative approach, in-depth interviews were conducted with a purposive sample of six participants. The qualitative data was analyzed using the content analysis method and the NVivo software program. Findings show that ChatGPT awareness and usage are influenced by variables like score, gender, education, and social media usage. Occupation and monthly income were not significant factors. The model with all independent variables was able to predict the use of ChatGPT as the Robo-Assistant in Thailand with an accuracy rate of 96.3%. The study also confirms acceptance of ChatGPT among Thai people and emphasizes the importance of developing sociable robots that consider human interaction factors. This study significantly enhances our comprehension of public perceptions, acceptance, and the prospective ramifications associated with the adoption of ChatGPT as the Robo-Assistant. The acquired findings offer indispensable guidance for the effective utilization of AI models and the advancement of sociable robots within the domain of human-robot interaction.