When we were younger, what was considered normal? Being like everyone else. Till this day, normal was just blending in with what everyone else does. What we find abnormal is being different or in other words, marching to the beat of your own drum. At what point were we taught that being normal was blending in with everyone around you. How long does it take us to become our own and not be so worried to not be different, but to be ourselves? It takes so many people a lifetime to finally be themselves and not care about what other people thing. One of my moments where I did something a little different from people around me was when I decided to take some time off after I graduated high school. At first I was so nervous to tell anyone because I was afraid of what they were going to think, but as time went on I told myself, everyone is different and people take different paths in their lives and that's okay. I can do my thing and people can do theirs and that's the beauty of the world, how different everyone is and how many different perspectives we have of the world. Its not meant to be alarming, it's suppose to be a wonderful and amazing thing. What makes this world so complex is all the different personalities we have around us. Do you think things and life would be so dull and boring if everyone was the same? It would be like living in a black and white world, no color or life to it. All the different cultures and people are what make this world so interesting and such a beautiful place to be. If we all took time to except people how they are and embrace difference, this world would be a happier place.
Recommended for you
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
Trending Topics
Trending Stories
Best of Student Life![Jenna Pizzi and her mom smiling by a waterfront with a historic ship in the background.]()
![Cristina Yang and Meredith Grey in scrubs sit against a wall, smiling and enjoying a break.]()
![Towson University]()
![Woman in field with a red heart-shaped balloon under a colorful sky.]()
