‘Sora is incredible and scary’: public perceptions and governance challenges of text-to-video generative AI models - Zhou, Kyrie Zhixuan; Choudhry, Abhinav; Gumusel, Ece; Sanfilippo, Madelyn Rose (Information Research an international electronic journal, 2025)
Introduction. Text-to-video generative AI models such as Sora OpenAI have the potential to disrupt multiple industries. In this paper, we report a qualitative social media analysis aiming to uncover people’s perceived impact of and concerns about Sora’s integration. Method. We collected and analysed comments (N=292) under popular posts about (1) Sora generated videos, (2) a comparison between Sora videos and Midjourney images, and (3) artists’ complaints about copyright infringement by Generative AI. Analysis. We employed a thematic analysis to analyse the collected comments. Results. We found that people were most concerned about Sora’s impact on content creation-related industries. Governance challenges included the for-profit nature of OpenAI, the blurred boundaries between real and fake content, human autonomy, data privacy, copyright issues, and environmental impact. Potential regulatory solutions proposed by people included law-enforced labelling of AI content and AI literacy education for the public. Conclusions. Based on the findings, we discuss the importance of gauging people’s tech perceptions early and propose policy recommendations to regulate Sora before its public release.