Uncertain Boundaries: Multidisciplinary Approaches to Copyright Issues
  in Generative AI
Jocelyn Dzuong Zichong Wang Wenbin Zhang
In the rapidly evolving landscape of generative artificial intelligence (AI),
the increasingly pertinent issue of copyright infringement arises as AI
advances to generate content from scraped copyrighted data, prompting questions
about ownership and protection that impact professionals across various
careers. With this in mind, this survey provides an extensive examination of
copyright infringement as it pertains to generative AI, aiming to stay abreast
of the latest developments and open problems. Specifically, it will first
outline methods of detecting copyright infringement in mediums such as text,
image, and video. Next, it will delve an exploration of existing techniques
aimed at safeguarding copyrighted works from generative models. Furthermore,
this survey will discuss resources and tools for users to evaluate copyright
violations. Finally, insights into ongoing regulations and proposals for AI
will be explored and compared. Through combining these disciplines, the
implications of AI-driven content and copyright are thoroughly illustrated and
brought into question.