User Negotiations of Authenticity, Ownership, and Governance on AI-Generated Video Platforms: Evidence from Sora

TL;DR

The paper investigates how users negotiate authenticity, ownership, and governance on AI-generated video platforms, focusing on OpenAI's Sora. It employs qualitative discourse analysis of publicly available user comments to reveal four recurring dynamics: critical realism assessments, a shift from viewers to creators with prompt-centric authorship concerns, blurred boundaries between real and synthetic content, and contested platform governance with tactics to evade moderation. The study demonstrates that authenticity judgments are grounded in micro-visual cues, prompts are treated as creative capital, and governance is co-constructed by users and platforms, including informal ethical policing. These findings inform design and policy, suggesting content labeling, transparent moderation, and monetization models that balance openness with intellectual property protection in emergent generative-video ecosystems.

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 between real and synthetic media, worried about misinformation, and even questioned the authenticity of other commenters, suspecting bot-generated engagement. Fourth, users contested platform governance: some perceived moderation as inconsistent or opaque, while others shared tactics for evading prompt censorship through misspellings, alternative phrasing, emojis, or other languages. Despite this, many users also enforced ethical norms by discouraging the misuse of real people's images or disrespectful content. Together, these patterns highlighted how AI-mediated platforms complicate notions of reality, creativity, and rule-making in emerging digital ecosystems. Based on the findings, we discuss governance challenges in Sora and how user negotiations inform future platform governance.