mlsanityData to 7 Oct 2026

"Sora is Incredible and Scary": Emerging Governance Challenges of Text-to-Video Generative AI Models

arXiv 2406.11859 ↗First posted 10 Apr 2024cs.CY cs.AI cs.ETcited by 3

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Abstract (arXiv)

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. We collected and analyzed comments (N=292) under popular posts about Sora-generated videos, comparison between Sora videos and Midjourney images, and artists' complaints about copyright infringement by Generative AI. We found that people were most concerned about Sora's impact on content creation-related industries. Emerging 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 labeling of AI content and AI literacy education for the public. 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.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 6 of its 42 references that are in the map. First posted on arXiv 10 Apr 2024.

Builds on

6 of 42 references.

References · 6

  1. 2024Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Modelscited by 467
  2. 2024World Models for Autonomous Driving: An Initial Surveycited by 79
  3. 2023Watermarking Conditional Text Generation for AI Detection: Unveiling Challenges and a Semantic-Aware Watermark Remedycited by 45
  4. 2024Sora Generates Videos with Stunning Geometrical Consistencycited by 31
  5. 2024Sora OpenAI's Prelude: Social Media Perspectives on Sora OpenAI and the Future of AI Video Generationcited by 8
  6. 2024The Machine Can't Replace the Human Heartcited by 1

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Citing papers per year: 2024: 1; 2025: 2.

3 papers.