Also videos from gender criticals. It’s so incredibly upsetting. One thing I’ve noticed is that there is simultaneously a claim that we are being lied to, and yet when trans content creators talk about their surgery complications it’s used as ammunition against us and our care. Which is it? I have always found that trans creators are fully open about the risks and complications that can happen from surgery and yet I still desperately yearn to have it even though I know recovery is going to suck. I have to hear this GC rhetoric from my parents and it breaks my heart. I just want to live my life as the woman I was always meant to be. To grow old and die as a woman. To finally have a chance at happiness. Why do we have to justify our existence? Why can’t they just leave us alone?
If it makes you feel better, I watch a few shorts from a woman who talks about talking through your relationship problems to make it healthier instead of mining it for clout on TikTok and immediately I got a flood of right-wing MRA type videos
YouTube recommendations are like gifts from an inattentive spouse but somehow way worse. It’s like if you said “I love dogs” and your spouse was like “I know you love dogs so I gathered up all the uncollected dog shit in the neighborhood and put it in the front seat of your car.”
The reason Youtube is getting absolutely fucking demolished by tiktok is that tiktok actually serves you recommended content that is like what you engage with and actually watch whereas Youtube recommends you the exact fucking opposite.
nah they both have documented issues funneling people towards fascist content.
the notion of the recommendation algorithm is inherently flawed, especially in the absence of standards or moderation. you’re always going to be using metrics that are poor proxies for actual interest.
Agreed. Expressed vs revealed preference is the devil in the details of building useful recommendation models that seems to always have this catch. It’s worsened by a hugely unaccounted for spread of experience among users. Anyone training models daily takes for granted the often subtle but unusual ways they’re careful to avoid miscommunicating preferences. Slow-scrolling past content without pausing to lessen interest capture weighting, for example, or using statistically associated concepts for steering. Neither is average user behavior, yet developers often assume it.
In the end, did the user actually tell you their preference? or did you simply attempt to give them one [at any cost]