While AI models for generating opinions are advancing in the realm of music, their main expertise remains in manipulating text and images. Music presents a distinct challenge due to the critical discernment of listeners compared to viewers or readers. Moreover, the landscape is complicated by copyright laws, which increasingly pose obstacles for AI-created music.
Training these AI systems involves emulating human behaviors using extensive datasets, often gathered from diverse content platforms. However, the music industry, especially record labels, is diligent in safeguarding intellectual property rights. Legal disputes, such as Universal Music Group’s lawsuit against Anthropic for alleged lyric plagiarism, underscore the contentious nature of AI-generated music.
The rise of AI-generated tracks like “Heart On My Sleeve” by Ghostwriter, which imitated the styles of renowned artists such as Drake and The Weeknd, highlights the potential of neural networks in music composition. Nevertheless, the proximity of AI-generated content to existing works raises concerns about potential copyright violations and legal consequences.
Developers encounter challenges in training AI models with copyrighted material and justifying the transformative aspect of their creations. Instances like OpenAI’s ChatGPT summarizing news articles or Midjourney’s replicated images have sparked discussions on intellectual property rights concerning AI-generated content.
The future of AI in music creation relies on overcoming legal hurdles, obtaining licensing agreements, and promoting ethical collaborations among technology giants, startups, musicians, and developers. Resolving issues related to copyright regulations, fair competition, and commercial feasibility will be pivotal in shaping the landscape of AI-generated music.
