Summary of Uncertain Boundaries: Multidisciplinary Approaches to Copyright Issues in Generative Ai, by Jocelyn Dzuong et al.
Uncertain Boundaries: Multidisciplinary Approaches to Copyright Issues in Generative AI
by Jocelyn Dzuong, Zichong Wang, Wenbin Zhang
First submitted to arxiv on: 31 Mar 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Artificial Intelligence (cs.AI); Computers and Society (cs.CY)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper presents a comprehensive survey on copyright infringement in generative artificial intelligence (AI), focusing on detecting and preventing unauthorized use of copyrighted content by AI models. It covers methods for identifying copyright violations in text, image, and video, as well as existing techniques for safeguarding copyrighted works from generative models. The survey also discusses resources and tools for evaluating copyright infringements and explores ongoing regulations and proposals for AI-driven content. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper talks about a big problem with artificial intelligence (AI) that can copy things without permission. It’s like when you copy someone else’s work without giving them credit! This survey looks at how AI models are getting better at creating new content, but also how they’re copying copyrighted stuff like movies and songs. The researchers want to find ways to stop this from happening and make sure people get the credit they deserve for their ideas. |
