Up until today I have always found the people who sing out loud while they’re listening to their headphones to be slightly annoying. Especially if the singing is not any good. After class today, I came across one of these people. This woman was walking down the sidewalk on campus, belting out a song that I’ve never heard before - or maybe just couldn’t recognize. I can’t say she had an amazing voice, and all of the other students around her were giving her weird looks. As I got a little closer, I realized how happy this woman looked. She wasn’t singing to impress people. She wasn’t singing to annoy people either. She was singing for herself, and I found this to be extremely refreshing. All she could hear was the music, and it looked like she was having a great time. She didn’t care what anyone thought, and she didn’t let anyone get in the way of enjoying her day. She was truly happy because of her own self-fulfilling confidence. All I can hope is that her confidence is contagious, because there are so many people today who could use it. Not the confidence to brag, or to show off, but the confidence to be oneself. There are so many people, including myself, who can learn from this woman that it is okay to be independent, individual, and unique if it means being happy. We do not have to conform to being quiet and keeping to ourselves. We shouldn't be afraid to show our identity, and we shouldn't be afraid to put our voices out there. I'm not saying we all need to start singing and yelling out song lyrics in public - obviously that would get out of hand. But I do know that everyone has their own quirks and interests, and we shouldn't let society hinder our ability to enjoy them. If that means taking the time to do something for yourself, or by yourself, then go for it. I saw today just how happy that can make a person. If more of us can be like the woman I saw singing with her headphones in, I think we'll overall contribute to a much more positive community.
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The Illusion of Creativity
AI-generated music is often marketed as “artistic” or “educational.” But what does it really teach?
- That style can be replicated without understanding.
- That emotion can be simulated without feeling.
- That effort can be bypassed with a prompt.
For young creators, this sets a dangerous precedent. Why learn to play guitar when an algorithm can do it faster? Why study harmony when AI can generate chord progressions in seconds? The risk isn’t just laziness — it’s the loss of depth, discipline, and the tactile joy of creation.
I have listened to several AI-generated music covers. My initial reaction was one of considerable impressiveness, particularly regarding the reimagining of classic pop hits in diverse genres with novel arrangements. Here is one good example a-ha — Take On Me
However, after engaging with several such Ai generated song covers, a sense of emotional detachment emerged, attributable to the perceived absence of human artistry and genuine sentiment, resulting in a technically flawless yet ultimately soulless auditory experience.
Copyright in Crisis
What does the copyright law say about AI generated music, especially in field of music covers. Who is liable for copyright in this case, AI developers, people who used AI to generate music or people who published it on music platforms?
Recent lawsuits show that the music industry is pushing back hard:
- Universal, Sony, and Warner sued AI music platforms Suno and Udio in 2024 for allegedly training their models on copyrighted songs without permission Ars Technica The Lyon Firm.
- They’re seeking up to $150,000 per infringed song, arguing that the AI outputs resemble famous tracks and voices (e.g., Mariah Carey, Michael Jackson).
- These lawsuits target the developers of the AI tools — but they raise broader questions:The legal gray area is training data. Courts haven’t yet ruled definitively on whether using copyrighted songs to train AI counts as infringement or fair use Sites at USC.
But who’s liable?
Role | Legal Risk | Why |
AI Developers | ✅ High | For training on copyrighted material without licenses. |
Users | ⚠️ Moderate | If they intentionally recreate protected works. |
Publishers/Platforms | ✅ High | For distributing infringing content. |
The grey area lies in training data. Courts haven’t yet ruled definitively on whether using copyrighted songs to train AI counts as infringement or fair use. Meanwhile, AI-generated works themselves aren’t eligible for copyright unless a human provides substantial creative input — leaving them in legal limbo.
The Educational Mirage
Some argue that AI music helps people learn genres, production styles, or vocal techniques. But this “education” often lacks context. It’s like learning to paint by watching a printer — technically impressive, but creatively hollow.
True musical education involves:
- Struggle and iteration: Learning through mistakes.
- Emotional connection: Expressing what words can’t.
- Cultural lineage: Understanding the roots of sound.
AI shortcuts bypass all of this. And in doing so, they risk flattening the rich terrain of human creativity into a sterile landscape of algorithmic mimicry.
Why This Fight Matters
This isn’t just about music. It’s about the future of art, storytelling, and human expression. If we allow machines to dominate creative spaces, we risk turning culture into content — optimized, monetized, and devoid of soul.
We must ask: Do we want a world where art is made by machines, or one where machines help humans make better art?
5 Key Takeaways
- AI-generated music blurs the line between innovation and erosion in the creative arts
- AI-generated music raises questions about copyright, culture, education, and artistic expression
- AI-generated music can replicate style without understanding, simulate emotion without feeling, and bypass effort with a prompt
- AI-generated music sets a dangerous precedent for young creators by potentially leading to a loss of depth, discipline, and joy of creation
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