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The Power and Pitfalls of AI in Music - WR #158
Weekly Roundups
April 21, 2023

The Power and Pitfalls of AI in Music - WR #158

This week, we cover a pretty wide range of topics from the latest updates on AI to the significant economic contribution of the music streaming industry. As per usual, there's plenty to catch up on!

#1. The copyright claim from Universal on an AI-generated track

It’s been a few weeks, even a few months, that we’ve been discussing the limitations of AI. Should they be implemented to guard human creativity and the workforce in the industry? Or be used in a completely other capacity regarding creativity? Should it just be another tool or do we need to keep it away from creative prospects? These are valid inquiries, and a recent event has further prompted us to consider both the potential and danger of AI.

AI-generated fake vocals imitating Drake and The Weeknd went viral with over 600 000 streams on Spotify and 15 million views on TikTok. It then got removed due to a copyright claim from Universal Music Group (UMG). The AI-generated song called "Heart On My Sleeve" was uploaded to various streaming platforms, including YouTube and Apple Music.

The incident raises questions about the use of AI in music production, and UMG has urged streaming platforms to block AI companies from accessing their label's songs for training purposes.

#2. The real advantage AI can provide for music businesses

A new article from MIDiA Research highlights the importance of datasets in the next battleground for AI technology. While functionality has been a major focus in the development of AI, the quality of datasets used to train AI systems will become increasingly important in the future.

As AI features take up more and more space in various industries, the accuracy and comprehensiveness of datasets will be a critical factor in determining the effectiveness and success of AI.

This shift in focus inevitably presents an opportunity for companies that specialize in collecting and curating high-quality datasets. But it will also pose a challenge for those who may struggle to access or generate sufficient data to train their AI systems. So the ability to effectively use datasets will be a key competitive advantage for companies looking to leverage AI technology in the coming years.

#3. Music Streaming represented $14 Billion in the US

Fair contribution of streaming has been shown for the year 2021. According to a study by the Digital Media Association (DiMA), music streaming contributed more than $14 billion to the US economy in 202. The study also found that the music streaming industry supported more than 100 000 jobs and generated over $2.7 billion in tax revenue.

These numbers reflect the significant economic impact of the music streaming industry in the United States. This is why the study emphasizes the importance of policies that support the growth and innovation of the music streaming industry, which has become an increasingly important part of the music business in recent years.

#4. BMG becomes the first to reconsider catalog

BMG is shifting its focus to catalog and frontline recordings after a successful year, which saw a 21% revenue increase and a 34% increase in earnings.

BMG plans to prioritize investments in music catalogs and frontline recordings. How are they going to pull that off? Well, BMG is now the first main publisher in music to remove the concept of back catalog altogether in their release strategies. As a reminder; tracks which pass the limit of 18 months since their release are considered back-catalog. Now, that limit is not considered in BMG’s strategies. Maybe there’s a trend to keep an eye on here.

#5. Spotify’s algorithm explained

Have you ever been curious about how Spotify's algorithm works? If so,The Wall Street Journal recently published a video that could pique your interest, diving into details of how Spotify's algorithm uses mapping technology to generate personalized playlists for its users

Additionally, this features an interview with a Spotify data scientist who explains how the company utilizes user behavior data to create a "taste profile" for each listener. By mapping a user's preferences to a vast music library, the algorithm generates custom playlists that cater to each user's unique taste. This video offers an interesting glimpse into the technology that powers Spotify's popular music discovery features.

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