Interestingly, I don't think I really found dislike counts to be very useful, though I do go for negative reviews on books first.

Negative reviews tend to be a bit more articulate and specific about what they didn't like, and why they didn't like it. Pain points tend to stand out a lot more than positive things, especially if you go into an experience with the expectation that you'll enjoy it.

That said, there's also plenty of occasions where I've found nothing useful in the negative reviews, but found some positive reviews compelling enough to try a book.

Movies, TV shows and music I tend to ignore specific reviews altogether, and just go by the description and overall positive/negative average from ratings. There are so many more dimensions that short form reviews generally aren't useful at all.

I wonder how useful it would be for a dislike button to require a brief statement explaining why. I'm not a fan of dislike/downvote buttons in general because there are so many different reasons why something could be perceived as negative, and what might be considered negative by one person might be a positive for somebody else. It just feels like noise to me.

Eh, tbh dislikes on YouTube were more of a popularity contest for the outrage du jour or a sign that some streamer told his followers to brigade something.

I’m still disappointed that YouTube/Google didn’t find it worthwhile to figure out brigading and render it useless.

Wouldn’t that be an entirely solvable problem? Or am I expecting too much from machine learning?

Given the gigabytes of data that just viewing the content generates for them, I'm sure they could correlate those actions. But given it took them many months to deal with extremely obvious comment spam... I have low expectations.