Copyright of Training Data in the AI Era: Practical Analysis Based on Case Studies of Representative AI Companies
TL;DR
The fundamental issues of copyright infringement in AI training data are identified, the negative effects of such infringement on the copyright owner and the digital content value chain are provided, and specific regulations for AI companies, copyright regulators, and governments are provided.
Abstract
Currently, one of the elements of generative artificial intelligence that is rapidly advancing, is the training of AI using existing resources like text, images, audio, and video. Most of the training data are copyrighted resources that were collected without the rights holder's consent, and using such resources has resulted in an unprecedented and mass infringement of copyright. This has resulted in a global copyright crisis, and the legal and commercial challenges posed by this situation are foremost in the era of artificial intelligence. This paper analyzes the copyright infringement risks and the governance dilemmas of AI training data. Within this scope, it examines the lawsuits of media companies, content creators, and AI technology companies. The author employs a combination of methodologies such as case study, comparison, documentation, and normative legal study. Accordingly, the paper aims to identify the fundamental issues of copyright infringement in AI training data, the negative effects of such infringement on the copyright owner and the digital content value chain, and provide specific regulations for AI companies, copyright regulators, and governments.
