>There's no way to indicate, “I’m engaging with this, but I hate myself for doing it.”

that would be a thumbs down if it exists. The system already knows you're engaging with it, they checked that you stopped scrolling and did all sorts of stuff around the thing you are engaging with.

What's being referenced here is maybe the tip of the iceberg in terms of inadequacies of current recommendation systems.

I suspect there's a range of indices related to content interaction that companies use poorly or even maybe nefariously — for example, are they motivated to present what you want, or what will keep you engaged with the site? Are their assumptions about why, say, you're spending a lot of time on a video correct? This post is focused sort of on options to communicate with the recommendation system, but there's a lot that could be said in terms of mismatched system-user goals in the system, and poor assumptions being made by the system in general.

I wondered too as I was reading it whether it's worth making the distinction between "different features of user experience with the content" and "metaresponse". That is, I can feel positively and negatively about the same video, or like it for one reason but not another; at the same time I can want to provide a response explaining a response. There's a difference between providing information about how I feel about some content, and information about how I want that information to be used.

We've already forgotten the hype train that Netflix orchestrated when they held a paid contest for who can build the best recommendation engine. What was it - a million dollar prize?

It was shit back then, and it is still shit today. It just got worse over time.

To me, the "best of the best" is its own thing. I do not watch romance movies in general, but I've had good experiences watching what people call the best of the best of the genre. Similarly for a lot of genres, media types, etc. Even just the "best of the best" of "cute animal video" can be fun every once in a while.

But I have to keep a heavy hand on the YouTube watch history and remove many things that I may have enjoyed as an exception, but don't want to see endlessly offered up forever. Some of the strange attractors in the algorithm are very, very powerful, like the aforementioned "cute animal videos". Another problem I hit is situations like, I watched the video because, say, a parrot was doing a very good impression of Captain Picard (just making this up, sorry) which was given due to general sci fi interest, but the algorithm sees "a ha! another hapless human who likes cute animal videos! Après cette vidéo, le déluge!"

At least YouTube has that knob, and does generally seem to honor it. The algorithms that don't are very hard to keep from degenerating into the lowest common denominator, because the slightest hint that you like some extremely popular thing or have an interest in a very lucrative ad keyword almost immediately swamps my actual interests.

This is an unexpected yet welcome application of the fundamental attribution error: https://en.wikipedia.org/wiki/Fundamental_attribution_error