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Notes -
I think critic scores have also become a less accurate predictor of my enjoyment over the years. I would attribute this to my taste being in a sort of inchoate state until my mid-20s or so. I was still trying to figure out what I enjoyed, and was a lot more susceptible to suggestion. There were cases where I forced myself to 'enjoy', say, Bjork, or Henry James, or The Night of the Hunter, because I felt like they were things I ought to like, for reasons of tribal identification. Liking works that were critically acclaimed was a way to signal my erudition. As I've gotten older, I've become less insecure. I like what I like. Some of what I like is "trash", and that's fine. I'm not trying to impress anyone with my Letterboxd.
But the whole idea of giving cultural artefacts numerical scores (and aggregating them into a single Metacritic/RT average) sort of hinges on the simplifying assumption that these works vary along a single axis of "goodness", and that your enjoyment of a work is a function of where they fall on this scale. This has always been a laughably crude simplification. Consider the category of the cult classic, a work which turned off most audiences but which has a small group of ardent admirers. How do we account for why I love the critically panned Mommie Dearest? Maybe we just need to add a noise term to our linear model to account for these sorts of random fluctuations? Except these deviations don't occur uniformly at random. If you know that I love Mommie Dearest, you should greatly increase your predicted probability that I love Showgirls, and Valley of the Dolls, for example.
The qualities that affect your enjoyment of a work of art are many-dimensional, and different people differ widely in terms of which regions of that high-dimensional space they enjoy.
The role of reviewer is becoming outmoded now that we have technology to move past the simplifying assumption of a universal, one-dimensional scale of quality. For example, we have collaborative filtering algorithms driving the ubiquitous "Users who liked X also liked..." feature, and other, more complex recommendation algorithms. Social media has also made word-of-mouth transmission a lot more efficient. No matter how niche your tastes, you can always find people who share them somewhere on the internet.
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