I have learned over the years that this life is going to be difficult, and people are not always going to be what we expect. I myself have experienced my fair share of difficult and heartbreaking moments. Things I never thought would come about in my life until a later time left me thinking I was never going to get through it. Each and every hard time has made me a stronger and better person. It has also taught me that self love is so important. I have never been the most confident girl but I love me for me and I find that more important. It has taken time to let things go and not to get so down on myself for the things I cannot control. I know who I am and the big heart I have is taken for granted a lot of times. There have been people that have walked out on me, or haven't even given me a chance to show them who I really am. I may be shy and kind of awkward until I'm comfortable enough to open up. The tragedies in my life have caused so much damage I've learned my own ways to protect myself even if they aren't the best. I have often times pushed people away when that was the last thing I intended. My intentions with each and everyone in my life have always been the best and I am always willing to give more than I receive in return. There is no doubt that I miss those I was once close with but they have all taught me something, and I'm hopeful there is a day we are able to rekindle things. We are all in different places in our lives now and things are a bit more stable than they once were. I have grown to accept some aren't meant to be in our lives for a long period of time but it doesn't make me any less grateful for everyone that comes across my path. I will always try to make the best of this life as its the only one I get. We will not be loved by everyone we meet but not everybody matters.
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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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