Australian artists and representative bodies are urging AI companies to pay for the use of copyrighted works scraped for training data [1].
This push for compensation highlights a growing conflict between the generative AI industry and the creative sector. As AI models become more capable of mimicking human art and music, creators argue that the unauthorized use of their portfolios undermines their livelihoods and legal rights [3].
Representative bodies, including APRA AMCOS, have called for formal licensing deals to ensure creators are compensated when their work is used to train models [2]. The organization said investigations into AI practices demonstrate that companies have plundered the life's work of songwriters from Australia and New Zealand [2].
Musicians and authors argue that big-tech firms are profiting from their intellectual property without permission [1]. They describe the scraping of their work as a copyright breach that requires a financial remedy [1].
Despite these demands, some creators face significant hurdles in seeking redress. Reports indicate that while many Australian musicians oppose the use of their songs by AI, they currently have little legal protection to prevent such activity [3]. This gap in legislation has led to calls for updated copyright frameworks that specifically address the capabilities of machine learning.
The movement seeks a shift toward a licensing model where AI firms pay a fee to access high-quality, human-made data. Such an arrangement would mirror existing music licensing structures, where songwriters receive royalties when their music is played in public, or broadcast [2].
“Australian artists and representative bodies are urging AI companies to pay for the use of copyrighted works.”
This dispute reflects a global tension between the rapid scaling of AI and existing intellectual property laws. If Australian creators successfully secure licensing deals, it could establish a regional precedent for how 'training data' is valued, potentially forcing AI developers to move away from open-web scraping toward paid partnerships with content owners.



