Those people in the classroom that get on everybody's nervesIdentifies both annoying teachers and studentsI was brainstorming with some of my friends and we came up with a pretty good
list of those people in the classroom who get on everybody’s nerves. This list
is mostly students, but we realized that some of the most annoying people were
teachers, so we threw them in there, too.
10. Kid who eats in class.
The kid who always brings in a huge
bag of chips when you’re always super hungry and eats the whole thing in front
of you and doesn’t share.
9.
Teacher’s pet.
It’s almost painful to watch this
kid try to suck up to the teacher without realizing that it won’t boost his
GPA.
8. Professor who answers his/her own questions. Every question asked by this teacher
is rhetorical. They don’t expect you to answer. They just talk the entire class
time and make it seem like it’s dragging on forever.
7. Kid who sleeps in class.
None of us get enough sleep. We’re
in college. What makes this person think it’s alright to make the classroom
their new bedroom. They took nap time out of the curriculum after fourth grade. Get
over it.
6. Student who complains about how hard a class is, but has the best grades.
Student: Dude, I hate going to this
class. It’s so hard.
Me: Yeah, dude, I know what you mean.
I’m barely passing.
Student: Oh, I’ve got 100. This is my
hardest class.
Me: Don’t talk to me.
5. Student who answers every question
There’s a participation grade that
I’m failing because one kid knows the answer to every question and the teacher
always picks him.
4. Kid Who Answers Every Question Wrong.
This is the exact same situation as above. The only difference is that this one is always picked, and they have never
gotten a single answer right. Every time they open their mouth, I get a little
dumber.
3. Guy who shows up to class drunk. Just imagine how annoying drunk people
are and then put them in a classroom. The party ended hours ago for everyone
else, but it didn’t end for this bro until he realized he had to go to class.
Hopefully, he’ll keep his head down as he stumbles to his desk.
2. Student who never quite left high school. They always want me to know what
sport they played in high school despite not playing any sports, now. They have no cool college stories so they think that their high school
stories interest us. “Back when I played varsity football…” Shut up. I’m
watching real football.
1. Teacher’s pet whom the teacher dislikes.
This is the student who tries to
answer every question to become the teacher’s favorite. They don’t understand
that the teacher is deliberately looking for another student to answer their
question. I would answer their question, it’s just that I never seem to know
the answer. Hopefully, someone else can before I lose my mind.
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This article has not been reviewed by Odyssey HQ and solely reflects the ideas and opinions of the creator.
StableDiffusion
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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