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YouTube, Spotify, Snapchat, Google all have horrid recommendation systems. I mistakenly clicked a link to a YouTube clip of a TV show once and closed it immedia

YouTube, Spotify, Snapchat, Google all have horrid recommendation systems. I mistakenly clicked a link to a YouTube clip of a TV show once and closed it immediately before even watching 2 seconds of it, but now my home page and the "watch next" bar are filled with clips from that show. I'm convinced that the dislike button and "I'm not interested in these" option in the hamburger menu are actually defunct because as far as I can tell they have absolutely no effect. Spotify is just as bad. I once made the mistake of liking an instrumental track on one of the radio stations I listen to. Now a good 25-30% of the songs that come up are just the instrumental versions, not the songs themselves. No matter how many of them I dislike they keep appearing. The same goes for remixes. There's no notion of "nuance" in these systems and it just makes me think that they were only ever evaluated internally. The models might perform well when they're tested on all 1 billion YouTube users, but on an individual level they're really awful. As an aside, I've never given them any of my data so this is purely anecdotal, but I frequently hear (in both positive and negative contexts) about how great Facebook's recommendation systems are on both Facebook and Instagram. I think that's what investor confidence in them as an ad company has stayed so high even through their controversies. I honestly don't think I've ever heard anyone praise Google's recommendation systems, by contrast.

deleted 8y ago
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ravenstine 8y ago
> There's no notion of "nuance" in these systems and it just makes me think that they were only ever evaluated internally. The models might perform well when they're tested on all 1 billion YouTube users, but on an individual level they're really awful. Well, that is all that really matters to them in the end, isn't it? A more accurate recommendation system might be better for many individuals but not drive engagement, whereas what they are going after may be lousy for the individual but drive more engagement overall. It's the classic playing to the lowest common denominator. Getting enough people to keep viewing ads is all that matters.
- adrianN 8y ago
  There has been an explosion of Fanta flavors and canned pasta sauce because they realized that optimizing for the median consumer is a lot worse than optimizing for a small handfull of cluster centroid users.
  - joshuamorton 8y ago
    Recommender systems don't optimize for the median consumer though. They optimize for clusters, much as pasta sauces now do. That's why my recommendations probably include a lot more super smash Bros content than yours do.

deleted 8y ago

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ravenstine 8y ago

> There's no notion of "nuance" in these systems and it just makes me think that they were only ever evaluated internally. The models might perform well when they're tested on all 1 billion YouTube users, but on an individual level they're really awful. Well, that is all that really matters to them in the end, isn't it? A more accurate recommendation system might be better for many individuals but not drive engagement, whereas what they are going after may be lousy for the individual but drive more engagement overall. It's the classic playing to the lowest common denominator. Getting enough people to keep viewing ads is all that matters.

adrianN 8y ago
There has been an explosion of Fanta flavors and canned pasta sauce because they realized that optimizing for the median consumer is a lot worse than optimizing for a small handfull of cluster centroid users.
- joshuamorton 8y ago
  Recommender systems don't optimize for the median consumer though. They optimize for clusters, much as pasta sauces now do. That's why my recommendations probably include a lot more super smash Bros content than yours do.