YouTube has launched two new AI-driven music creation tools, Dream Track and Music AI, to help creators make more engaging short videos and better compete with rivals like TikTok. These new tools allow users to generate original songs and instrument performances using artificial intelligence.

According to a recent report from Wired, Dream Track enables creators to generate a 30-second song simply by inputting text prompts like "a folk song about unrequited love" and selecting one of seven popular artists, such as Charlie Puth or Demi Lovato. The tool is built on Google's Lyria AI system developed by DeepMind and aims to enable creators without musical skills to quickly add high-quality, customized songs to their short videos.

Meanwhile, Music AI offers more advanced capabilities, including remixing songs, transforming music styles, creating instrumental accompaniment tracks, and converting text prompts like "melancholy" into music. Google states that the system allows for transformations such as converting hip-hop tracks into country music. The goal of this system is to enhance human creativity by making music creation faster and easier.

The introduction of these AI music tools appears to be a response to the competition from TikTok, as music and creative effects have significantly driven TikTok's growth. While TikTok allows people to easily mix songs and find inspiration for short videos, YouTube aims to provide creators with more advanced tools to capture viewers' attention.

However, the use of generative AI raises concerns about copyright, ownership, and compensation. To address this issue, YouTube plans to add watermarks to AI-generated music and, in a new initiative, share ad revenue with the artists who inspired the AI models. The company is testing how to adequately compensate artists whose styles (a key component of creativity) are imitated by AI systems.

Seven artists have collaborated with YouTube to provide their music styles for Dream Track. They hope to see AI as a new creative avenue rather than a threat. However, accurately attributing each artist and determining fair royalty payment methods still pose challenges.

As AI generation becomes mainstream, companies like YouTube face pressure to properly evaluate human creativity and intellectual property rights. Music highlights the complex legal and ethical debates involved in replicating artworks using data and algorithms. YouTube's revenue-sharing experiment can set a precedent, but it may take years to develop a system that satisfies all stakeholders.