Your examples are not inherent rights that copyright law explictly grants to rights holders. They are clever side effect of how the holder licenses out their monopoly on reproduction.
Holders rarely grant unrestricted reproduction rights to anyone. Reproduction rights licenses always come with a bunch of explicit restrictions, for example: "You may reproduce this novel, in print, unmodified, only for retail sale, in North America, on this quality of paper, for the next 5 years" and so on.
The party has the license to reproduce the song as a standalone audio recording, but attaching it to a video and reproducing the combined work isn't covered and the party must enter into negotiations with the rights holder for a new license. Such licenses often only grant the rights to reproduce it with that exact video and not a different one later, which allows the rights holder to gain control over which videos their song is attached to.
Same thing with holding morality over political events. The rights holder was careful to add a bunch of restrictions to that public performance license they sell. Sure, the politician might have bought a licence, but they forgot to check the small print that blocks their type of event from actually using it.
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Machine learning is kind of like compression, yes... It can be a useful analogy at times.
But it is absolutely nothing like lossy video compression. It's not compressing a single file or object. The only way you could train it on a 4k video and get a 420p video out is if that model was extremely over-fitted. The resulting model would likely be bigger than a 420p h264 video file and useless for anything else.
The way that machine learning is like a compression is that it find common patterns across it's entire training set and merges them in very lossy ways.
And it's actually very much like how a human brain works. Your brain doesn't start from scratch for every single human face you recognise. Instead, your brain has built up a generic understanding of the average human face, grouping by clusters of features. Then to remember a given human face it just remembers which cluster of features it's close to and then how it differs... Which is a form of lossy compression.
> No person can produce a 420p video just by consuming a 4k video
But many people do remember entire songs, complete with lyrics and music. And people with musical skills can (and often do) reproduce that song from memory as a cover... Which is copyright infringement if preformed publicly or otherwise distributed.
> nor can any machine learning model gain the emotional constructs and social contexts that human brains get from learning.
There are many things which large LLMs like chatgpt are absolutely incapable of doing. People do over hype their capabilities.
But in my experiments, chatgpt is actually quite good at tasks that require interpreting emotions and social contexts. Does it actually understand these emotions and social contexts? shrug. But if it doesn't actually understand that just proves that true understanding isn't actually needed to preform useful tasks in those areas.