If it is incorporated, its definitely not effective. Clickbait dominates Youtube's recommendations and search despite consistently low thumb ratings. An easy example would be a procedurally generated channel such as this one:

https://www.youtube.com/@futureunity5129/videos

Sort by "Popular" and you'll see that their most watched videos have consistently low like/dislike ratios yet are still being actively recommended. If you use Youtube's search feature, these same channels and videos will come up long before the actually informative channels do.

You could argue it's been helping Youtube by wasting viewer's time and making them watch extra ads but its certainly not helping the viewers find what they're looking for. Even mass reporting the channels doesn't seem to stop them.

Doubtful that they can do this in a way that accurately and effectively helps the user compared to showing the dislike count.

YouTube is plagued by low quality content with clickbait titles, descriptions, and images. Often they outright lie about the content. The recommendation algorithm prioritizes these videos first.

Users can't determine in advance that these videos are poor quality, so they'll be forced to watch those poor quality videos until they find a good one. YouTube wants it to be like this because it increases time on the platform and their advertising revenue.

Along the way, users can dislike these videos but that video still gains views which helps push itself upwards in the recommendation algorithm. Particularly videos with clickbait titles, descriptions, and images tend to amass large numbers of views in short periods of time, which YouTube may recognize as "going viral" and give it an additional push in its recommendations when searching for important keywords.

Furthermore, many users are also watching these videos whilst not logged in or don't care to click dislike, which is another lacking signal to help tune YouTube's ranking algorithm correctly.