User Negotiations of Authenticity, Ownership, and Governance on AI-Generated Video Platforms: Evidence from Sora
Bohui Shen, Shrikar Bhatta, Alex Ireebanije, Zexuan Liu, Abhinav Choudhry, Ece Gumusel, Kyrie Zhixuan Zhou

TL;DR
This study explores how users on AI-generated video platform Sora negotiate authenticity, ownership, and governance, revealing complex dynamics of realism evaluation, creative participation, misinformation concerns, and platform regulation challenges.
Contribution
It provides a qualitative analysis of user comments to uncover how users interpret and contest authenticity, authorship, and moderation in AI-generated video environments.
Findings
Users critically evaluate realism through micro-details.
Users shift from passive viewers to active creators.
Users contest platform moderation and share evasion tactics.
Abstract
As AI-generated video platforms rapidly advance, ethical challenges such as copyright infringement emerge. This study examines how users make sense of AI-generated videos on OpenAI's Sora by conducting a qualitative content analysis of user comments. Through a thematic analysis, we identified four dynamics that characterize how users negotiate authenticity, authorship, and platform governance on Sora. First, users acted as critical evaluators of realism, assessing micro-details such as lighting, shadows, fluid motion, and physics to judge whether AI-generated scenes could plausibly exist. Second, users increasingly shifted from passive viewers to active creators, expressing curiosity about prompts, techniques, and creative processes. Text prompts were perceived as intellectual property, generating concerns about plagiarism and remixing norms. Third, users reported blurred boundaries…
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Taxonomy
TopicsEthics and Social Impacts of AI · AI in Service Interactions · Hate Speech and Cyberbullying Detection
