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#video#recommendations#don#youtube#more#watch#shit#recommender#best#things
Discussion (40 Comments)Read Original on HackerNews
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.
[Watches video on WWII]
Youtube: Congratulations on becoming a Nazi, here's instructions on how to join a supremacy group in your area.
If I watch a bunch of Nazi videos over a long period of time, yes, gradually start shoving them into my suggestions.
People are avoiding listening to anything outside of their bubble because they're afraid their bubble will get totally shattered, and they won't be able to find their way back in. People like their bubbles, and they like venturing outside of them every once in a while. If leaving my house to go to a party at someone's house I just met destroyed my house, I'd never leave.
Also, seeing all the giant shit videos getting recommended reminds you that on a backend somewhere some shit-lover flag has been flipped, and now your government, your insurance company, your boss, and people who sell shit pornography are now being sold your information.
https://en.wikipedia.org/wiki/Emotive_conjugation
https://hn.algolia.com/?dateRange=all&page=0&prefix=true&que...
I think we need to start building intermediary feeds for all of our services (presumably via AI or something) that lets us customize how much we get of each type of content (e.g. no more than 5% about bad the economy is, no more than 5% about a new AI trick, 0% about 'drama of the day', 40% educational)
In my experience at least cultivating recommendations this way has worked really well for me on YT, I get consistently recommended a mix of stuff I want to watch and stuff that is at least theoretically interesting to me even if I don't want to watch it.
I wish other social services had the same mechanism (and wish it was more ergonomic on YT).
YouTube and Amazon are some of the very worst. I regularly watch a video or song on YouTube (/Music) and explicitly say "I enjoyed that but don't want YouTube to focus on recommending me things like that so I'm not going to hit like".
Amazon, there are entire classes of links I won't click or products I won't search/buy because I don't want them filling my recommendations forever.
And no, having to manually dig through settings and find a list of my entire history to manually delete entries isn't a good workaround. Too much effort, easier to just not give the platforms the data in the first place.
It's like if I go for a walk, metaphorically, and I see a giant pile of shit, and that's a genuinely interesting thing to see, because Jesus Christ that is huge. Then the algorithm notices I stopped to look at that, and the next time I go for a walk everything is filled with shit. That's what my Instagram feed is right now, metaphorically speaking. A never-ending field of shit.
This happened to me with youtube and feral hog trapping. A two-minute video of that showed up in my feed, and yeah, it was interesting to see how and why it was done. But my feed was full of that for a long time, and even now, years later, one will pop up just desperately trying to get me to re-engage.
It was interesting as a one off, not as a way of life.
I use a custom filter in uBlock Origin to hide the recommended sidebar in YouTube (all except the video of what’s next). Even so, there will occasionally be a video in search results with a topic that might be interesting from a channel I don’t normally watch.
I’ve learned to right click and open the link in a private browsing window so that my search results (and that one remaining sidebar thumbnail) do not become poisoned by that one channel/topic.
It’s insane that clicking on one video makes YouTube think that I’m now obsessed with that channel. And, it’s going to fixate on that for the next few weeks.
I work in streaming recommendations and basically no one voluntarily gives extra feedback, and most initiatives that aren't machine learning based on true behavior fail on A/B tests.
1.) I don't want to give companies more information about me.
2.) I don't trust that that information will be used to primarily benefit me, I trust that it will be used primarily to keep me on the platform somehow. Ick.
3.) As others have suggested in other comment chains, the way the algorithms have responded to "feedback" I've given it in the past has been so godawful and off-base that I have zero faith it will be of any benefit to contribute my sentiments.
"People who liked this also liked this" is already a pretty good way of discovering things. The problem is when the catalogue is crap. I get plenty of good recommendations on Prime Video and Criterion Channel, which both have a substantial number of great films available to watch.
I don't want "recommender systems", I just want easily-browsable catalogues that start out being sorted by their actual genre (looking at you, Netflix homepage with a bunch of bullshit 'categories'). I want to be able to look through things at my own pace and in my own way. I want to browse through movies/shows the same way I browse for records in a record store.
I'm happy to take recommendations from friends and family members who know what my nuanced tastes are, I don't want recommendations from some unknown algorithm built by someone for the purpose of keeping me on the platform.
https://www.bfi.org.uk/
https://theyshootpictures.com/
But what's a "recommender system"? Are my friends and family who understand my tastes at a deeper level than an algorithm not a "recommender system"? Is your approach to finding comedies via BFI/They Shoot Pictures not a form of a "recommender system" for you?
If recommender systems truly depend on a deeper level of nuance that they likely won't ever be able to get without people giving up even more privacy than they already do, shouldn't we look at alternative forms of recommendations as a form of improvement, rather than sticking to altering what's already there?
I'd argue that using algorithmic recommendations limits exploration and agency and doesn't allow us to develop our taste beyond our taste's current horizons. Without them, serendipity can be genuinely serendipitous if not moreso, our effort can increase attachment/pleasure when it pays off, and we have more opportunities to build knowledge along the way.
I might be digressing just a bit here, but I fundamentally believe that the answer to broken algorithmic feeds, or recommendation systems, or whathaveyou, isn't going to be found in more algorithms.
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.
So when reviewing reviews, care is needed. Simply picking the product that maximizes stars and number of reviews is a bad metric for the quality of a product, that is, for what your perceived quality of that product will be.
That's why I look at two things: 1) distribution of reviews; if frequency of stars decreases monotonically with star number, it is probably a good product, and I look at 3/4 star reviews for pro and cons; 2) if the distribution has a spike in the 1 or 2 stars, I further investigate to see what the problems are, regardless of number of reviews or how many five star the product has.
So far has worked great on Amazon.
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.
Why would they? They do not care, why you engage, they want you to engage as much as possible.
It was shit back then, and it is still shit today. It just got worse over time.
It was shit back then, it is shit today, but it improved a lot over time before it started to worsen.