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> I imagine companies like Meta have such good automated moderation that what remains to be viewed by a human is practically a firehose of almost certainly dist

> I imagine companies like Meta have such good automated moderation that what remains to be viewed by a human is practically a firehose of almost certainly disturbing shit. On the contrary I would expect that it would be the edge cases that they were shown - why loop in a content moderator if you an be sure that it is prohibited ont he platform without exposing a content moderator? In this light, it might make sense why they sue: They are there more as a political org so that facebook can say: "We employ 140 moderators in Kenya alone!" while they do indifferent work that facebook already can filter out.

Retric 2y ago
Even if 1% of images are disturbing that’s multiple per hour, let anyone across months. US workman’s comp covers PTSD acquired on the job, and these kinds of jobs are rife with it.
aoanevdus 2y ago
Content moderation also involves reading text, so you’d imagine that there’s a benefit to having people who can label data and provide ground truth in any language you’re moderating. Even with images, you can have different policies in different places or the cultural context can be relevant somehow (eg. some country makes you ban blasphemy). Also, I have heard of outsourcing to Kenya just to save cost. Living is cheaper there so you can hire a desk worker for less. Don’t know where the insistence you’d only hire Kenyans for political reasons comes from.
pizza 2y ago
> They are there more as a political org so that facebook can say: "We employ 140 moderators in Kenya alone!" while they do indifferent work that facebook already can filter out. Why assume they're just token diversity hires who don't do useful work..? Have you ever built an automated content moderation system before? Let me tell you something about them if not: no matter how good your automated moderation tool, it is pretty much always trivial for someone with familiarity with its inputs and outputs to come up with an input it mis-predicts embarrassingly badly. And you know what makes the biggest difference.. is humans specifying the labels.
- tossandthrow 2y ago
  I don't assume diversity hires, I assume that these people work for the Kenyan part of Facebook and that Facebook employs an equivalent workforce elsewhere. I am also not saying that content moderation should catch everything. What I am saying is that the content moderation teams should ideally decide on the edge cases as they are hard for automated system. In turn that also means that these people ought not to be exposed to too hardcore material - as that is easier to classify. Lastly I say that if that is not the case - then they are probably not there to carry out a function but to fill a political role.

Retric 2y ago

Even if 1% of images are disturbing that’s multiple per hour, let anyone across months. US workman’s comp covers PTSD acquired on the job, and these kinds of jobs are rife with it.

aoanevdus 2y ago

Content moderation also involves reading text, so you’d imagine that there’s a benefit to having people who can label data and provide ground truth in any language you’re moderating. Even with images, you can have different policies in different places or the cultural context can be relevant somehow (eg. some country makes you ban blasphemy). Also, I have heard of outsourcing to Kenya just to save cost. Living is cheaper there so you can hire a desk worker for less. Don’t know where the insistence you’d only hire Kenyans for political reasons comes from.

pizza 2y ago

> They are there more as a political org so that facebook can say: "We employ 140 moderators in Kenya alone!" while they do indifferent work that facebook already can filter out. Why assume they're just token diversity hires who don't do useful work..? Have you ever built an automated content moderation system before? Let me tell you something about them if not: no matter how good your automated moderation tool, it is pretty much always trivial for someone with familiarity with its inputs and outputs to come up with an input it mis-predicts embarrassingly badly. And you know what makes the biggest difference.. is humans specifying the labels.

tossandthrow 2y ago
I don't assume diversity hires, I assume that these people work for the Kenyan part of Facebook and that Facebook employs an equivalent workforce elsewhere. I am also not saying that content moderation should catch everything. What I am saying is that the content moderation teams should ideally decide on the edge cases as they are hard for automated system. In turn that also means that these people ought not to be exposed to too hardcore material - as that is easier to classify. Lastly I say that if that is not the case - then they are probably not there to carry out a function but to fill a political role.