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Comment by jdminhbg | Hacker News Reader

I see the same thing on a completely uncontroversial subject: music videos. If I watch e.g. a Beatles video, the recommendations aren't [Rolling Stones, Kinks, Badfinger, ...], they're always [Beatles, Beatles, Beatles, ...]. I don't know if it's naive and bad or if it's actually good for engagement and I'm just an outlier in what I expect to get.

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I only wish I would get songs by the same band... It sort of seems like Youtube tries its darndest to steer me away from the current band. I'd be happy if it just cycled between hits from the same artists, but I've never seen it do this recently.

I think what's most frustrating about it is I don't know what game they're playing. Recommendations used to be logical, now they're almost a waste of screen real estate. What even happened?

Dislikes and "not interested" are important.

I've noticed the same in my usage across almost all google services at this point. My speculation is that this is due to them now being so heavily dependent on neural networks these days vs the previous mix of algorithms. The old approaches seemed to be better at not presenting false positives / creating a rediculous mish-mash of previous trains of thought in an effort to recommend something, anything... no matter how wrong.

For example: older versions of the google keyboard were pretty good about not recommending/autocorrecting non-words. So I'd type things like function/variable names (which often use camel case) and it would either suggest valid English words or perhaps a non-word used earlier in the message. These days, my use of camel case names in technical emails spills over so that emails to family now pop up with bizarre camel case recommendations. I seeing similar things happening to YouTube recommendations and elsewhere.

My guess is the system creator think a lot about making the best recommendations for situations where they have enough information but seldom think much about the consequences of making recommendations where they don't have the information to make a recommendation and both users and developers underestimate how information is needed for a decent recommendation.

Edit: And the situation seems very much a product of youtube (and all the content providers, basically) stripping any user content controls from their UI. The user has no easy way to tell youtube what they want besides choosing between video that youtube offers them and those become more circumscribed as the process progresses.

There's a myth of the content providers doing magic to give the user what they want and the results seem to be this, ie, just terrible.

For episodic content it actually works ok, recommending videos on the same series, even if it's not the same channel

Ideally it would know how to predict order from title but that doesn't always work

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