Recruitment has come and gone leaving the best of us with fond memories and glitter on all parts of our body. Sorry not sorry, I had a Kate Spade bid day theme! For those of you who found your home, I am proud to say I am super happy for you and hope for the best in the four years you will become close and come to love your sorority. For those of you who thought your home was elsewhere but ended up in your second choice, it’s okay.
You know the saying, no matter the letters we are all Greek together? It is definitely true. The system is in place because it will match you correctly with the house you are meant to be with. It’s okay to feel cheated at first. It’s okay to feel like you aren’t at home. Recruitment is only 4 days long meaning you can’t fall in love in just only 4 days. For some, we have that instant I know where my home is moment while others don’t realize that until the very end of their new member period. The house you originally fell in love with probably loved you too but knew that your home wasn’t with them but somewhere else. We have been through this many times and know where you will fit in, even if you yourself don’t know as of yet. Don’t walk away so soon, stay a while at your second choice. Get to know the girls who loved you so much that they extended an invitation to you to see their passions for the sorority, the bonds they cherish and the transitions that make their sorority special. You may not get the burning desire most us originally felt but maybe your candle is slow burning for now, maybe you need a jolt of something special or a the makings of new memories to ignite the fire we all feel.
You never know when your second choice may finally become your first choice. No matter the letters we are all Greek together. We all love, we all share, and most of all we each have something that makes us unique tying us perfectly together. Take a leap of faith and see what you can do to change your frown into a smile when you think of your second choice house.
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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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