Public Perception of Generative AI on Twitter: An Empirical Study Based on Occupation and Usage

• URL: http://arxiv.org/abs/2305.09537v1
• Date: Tue, 16 May 2023 15:30:12 GMT
• Title: Public Perception of Generative AI on Twitter: An Empirical Study Based on Occupation and Usage
• Authors: Kunihiro Miyazaki, Taichi Murayama, Takayuki Uchiba, Jisun An, Haewoon Kwak
• Abstract summary: This paper investigates users' perceptions of generative AI using 3M posts on Twitter from January 2019 to March 2023. We find that people across various occupations, not just IT-related ones, show a strong interest in generative AI. After the release of ChatGPT, people's interest in AI in general has increased dramatically.
• Score: 7.18819534653348
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The emergence of generative AI has sparked substantial discussions, with the potential to have profound impacts on society in all aspects. As emerging technologies continue to advance, it is imperative to facilitate their proper integration into society, managing expectations and fear. This paper investigates users' perceptions of generative AI using 3M posts on Twitter from January 2019 to March 2023, especially focusing on their occupation and usage. We find that people across various occupations, not just IT-related ones, show a strong interest in generative AI. The sentiment toward generative AI is generally positive, and remarkably, their sentiments are positively correlated with their exposure to AI. Among occupations, illustrators show exceptionally negative sentiment mainly due to concerns about the unethical usage of artworks in constructing AI. People use ChatGPT in diverse ways, and notably the casual usage in which they "play with" ChatGPT tends to associate with positive sentiments. After the release of ChatGPT, people's interest in AI in general has increased dramatically; however, the topic with the most significant increase and positive sentiment is related to crypto, indicating the hype-worthy characteristics of generative AI. These findings would offer valuable lessons for policymaking on the emergence of new technology and also empirical insights for the considerations of future human-AI symbiosis.

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