Identifying the Public's Beliefs About Generative Artificial Intelligence: A Big Data Approach

Managerial Relevance Statement:
This study provides engineering managers and policymakers with actionable insights into public perceptions of generative AI (GenAI). Understanding these public beliefs enables managers to develop targeted strategies that address concerns such as job displacement, ethical AI development, and public trust. Investing in workforce reskilling and encouraging human-AI collaboration can enhance innovation and maintain a competitive edge. Establishing ethical guidelines and engaging with the public can build trust and facilitate smoother integration of AI technologies. Implementing these action plans based on our findings can lead to increased public acceptance, sustained productivity, and long-term business sustainability.
Abstract:
In an era where generative AI (GenAI) is reshaping industries, public understanding of this phenomenon remains limited. This study addresses this gap by analyzing public beliefs about GenAI using the Technology Acceptance Model and Diffusion of Innovations Theory as frameworks. We adopted a big-data approach, utilizing machine-learning techniques to analyze 21,817 public comments extracted from an initial set of 32,707 on 44 YouTube videos discussing GenAI. Our investigation surfaced six pivotal themes: concerns over job and economic impacts, GenAI's potential to revolutionize problem-solving, its perceived shortcomings in creativity and emotional intelligence, the proliferation of misinformation, existential risks, and privacy decay. Emotion analysis showed that negative emotions dominated at 58.46%, including anger (22.85%) and disgust (17.26%). Sentiment analysis echoed this negativity, with 70% negative. The triangulation of thematic, emotional, and sentiment analyses highlighted a polarized public stance: recognition of GenAI's transformative potential is tempered by significant concerns about its implications. The findings offer actionable insights for engineering managers and policymakers. Strategies such as awareness-building, transparency, public engagement, balanced communication, governance, and human-centered development can address polarization and build trust. Ongoing research into public opinion remains essential for aligning technological advancements with societal expectations and acceptance.