Coming off an incredible freshman year, I expected sophomore year to be just the same, if not better than freshman year. A part of me probably should’ve known that having such a good freshman year would make it hard to have an equally good sophomore year, but many people said that sophomore year was their favorite: your friends are sorted out, you have a general knowledge of the university and your bearings and yet there’s still so much that’s exciting and fresh. If college is the best four years of your life, that means every year is perfect right? Wrong. What was excluded in the conversation was the fact that while you may have more steady friends sophomore year, you lose a lot of friends; this is due to a lack of proximity, classes together or just by having a more mature understanding on who your real friends are. Also, unlike freshman year where everything is new and every experience becomes a memory, you aren’t exposed to as many new experiences and not everything becomes a memory. Keep in mind—these are just my own experiences; there are people who despised freshman year and created more memories sophomore year with the greater stability. It’s different for everyone and those who are adventurers will constantly find themselves in new territories.
Though I questioned whether or not this was a shared sentiment, I soon found out that a lot of sophomores felt the same way. Many of them agreed that this year holds higher standards and greater pressures. Whereas freshman year you could use the excuse “I’m a freshman” for pretty much any mistake, that unfortunately isn’t true for sophomore year; you are expected to know better. You can and should still make mistakes—they are important learning experiences and the best mistakes you can make are the ones you make before entering the “real world” (college years and earlier). Just remember: you are only a freshman once, and there is no shame in doing “freshman-y” things; learn how to use the equipment in the gym, go to the orientation events and own that lanyard around your neck. #yofo (you’re only a freshman once).
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
