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Youtube has content moderators https://www.theverge.com/2018/3/13/17117554/youtube-content-moderators-limit-four-hours-sxsw https://www.theverge.com/2018/3/13/

Youtube has content moderators https://www.theverge.com/2018/3/13/17117554/youtube-content-moderators-limit-four-hours-sxsw https://www.theverge.com/2018/3/13/17117554/youtube-content-... And, if anything, github is almost all text, and most of the interesting stuff is structured. That should be relatively straightforward compared to raw video and freetext on Youtube.

realusername 7y ago
I'm aware of those but realistically, what's the percentage of youtube videos really reviewed by moderators? I'd put it in the single digit percentage in the best case scenario. To me it's more a legal excuse of "we are doing something" than actually impacting videos.
- killjoywashere 7y ago
  What fraction of videos are actually problematic? What if it's one in a thousand, and they're reviewing 10x over that? I mean, they also have $120B in the bank. If they thought more reviewers would fix things, I'm pretty sure they'd get more reviewers.
  - Godel_unicode 7y ago
    Those numbers only matter if you're very good at finding the problematic videos via some automatic means. You are vastly underestimating the size of the problem. See also: https://en.m.wikipedia.org/wiki/Base_rate_fallacy https://en.m.wikipedia.org/wiki/Base_rate_fallacy
    - killjoywashere 7y ago
      How do you know I'm vastly underestimating the size of the problem? Do you have a source? Random sampling from the ingest stream sounds like a good start for your base rate. Once you have some metadata about bad actors, you can also start hunting their videos and compare your random sample collection stream to the ever-improving bad-actor collection stream.
      - Godel_unicode 7y ago
        To be clear, "size" here refers not to the volume of undesirable content, but rather to the total volume of videos submitted to YouTube. In order to use automatic classification, one needs to examine every new video submitted. YouTube gets (last I heard) double-digit hours of video submitted per second. You have to scan an appreciable portion of the video to determine if it's objectionable. Edit: the common suggestion that you can just ban the few bad actors effectively ignores decades of research into spam detection. Accounts are too easy to create, you have to go after content.
        killjoywashere 7y ago
        Let's say I have a river. I can only examine 1 drop under a microscope at a time. How do I find the cholera in the river? I take drops and look at them under the microscope. Over and over. I may not sample the whole river, but I can definitely build a representative sample. I can buy more microscopes and hire a bunch of microscopists and increase the sampling rate. Eventually, I'll figure out the amount of cholera per cubic liter, or accept that it's below the limit of detection. In this case, you're arguing that the bad thing is above the limit of detection, so I should be able to find some using random sampling. The metadata I refer to could be all sorts of things. Fingerprints of key frames in the videos, patterns of IP addresses, cities where those streams are coming from, browser fingerprints, etc. If the videos are drops of water, then you can imagine they start as rain. Every drop falls from the sky, somewhere in the river's basin. You can't possibly examine every drop before it gets to the ground. But you can sample them in the river. In this case, I bet Google does, in fact, monitor the browser fingerprints of uploaders. Monitors all sorts of data around the upload event. Every single time. And does use all sorts of fancy algorithms to aid in assessment. And, and, they sample the river, with actual human microscopists/moderators, because they surely assume new patterns of plague are continuously evolving.
        Godel_unicode 7y ago
        First, the goal here isn't to find the cholera. We know there's cholera in this river, the goal is to remove it before it gets to the village and drunk by the town's people. Same method though, you can only remove one dropper of water per person sampling. Now imagine you have not a river, but the bering strait. As Napoleon said, quantity has a quality all it's own. Please, please read about the base rate fallacy.

realusername 7y ago

I'm aware of those but realistically, what's the percentage of youtube videos really reviewed by moderators? I'd put it in the single digit percentage in the best case scenario. To me it's more a legal excuse of "we are doing something" than actually impacting videos.

killjoywashere 7y ago
What fraction of videos are actually problematic? What if it's one in a thousand, and they're reviewing 10x over that? I mean, they also have $120B in the bank. If they thought more reviewers would fix things, I'm pretty sure they'd get more reviewers.
- Godel_unicode 7y ago
  Those numbers only matter if you're very good at finding the problematic videos via some automatic means. You are vastly underestimating the size of the problem. See also: https://en.m.wikipedia.org/wiki/Base_rate_fallacy https://en.m.wikipedia.org/wiki/Base_rate_fallacy
  - killjoywashere 7y ago
    How do you know I'm vastly underestimating the size of the problem? Do you have a source? Random sampling from the ingest stream sounds like a good start for your base rate. Once you have some metadata about bad actors, you can also start hunting their videos and compare your random sample collection stream to the ever-improving bad-actor collection stream.
    - Godel_unicode 7y ago
      To be clear, "size" here refers not to the volume of undesirable content, but rather to the total volume of videos submitted to YouTube. In order to use automatic classification, one needs to examine every new video submitted. YouTube gets (last I heard) double-digit hours of video submitted per second. You have to scan an appreciable portion of the video to determine if it's objectionable. Edit: the common suggestion that you can just ban the few bad actors effectively ignores decades of research into spam detection. Accounts are too easy to create, you have to go after content.
      - killjoywashere 7y ago
        Let's say I have a river. I can only examine 1 drop under a microscope at a time. How do I find the cholera in the river? I take drops and look at them under the microscope. Over and over. I may not sample the whole river, but I can definitely build a representative sample. I can buy more microscopes and hire a bunch of microscopists and increase the sampling rate. Eventually, I'll figure out the amount of cholera per cubic liter, or accept that it's below the limit of detection. In this case, you're arguing that the bad thing is above the limit of detection, so I should be able to find some using random sampling. The metadata I refer to could be all sorts of things. Fingerprints of key frames in the videos, patterns of IP addresses, cities where those streams are coming from, browser fingerprints, etc. If the videos are drops of water, then you can imagine they start as rain. Every drop falls from the sky, somewhere in the river's basin. You can't possibly examine every drop before it gets to the ground. But you can sample them in the river. In this case, I bet Google does, in fact, monitor the browser fingerprints of uploaders. Monitors all sorts of data around the upload event. Every single time. And does use all sorts of fancy algorithms to aid in assessment. And, and, they sample the river, with actual human microscopists/moderators, because they surely assume new patterns of plague are continuously evolving.
        Godel_unicode 7y ago
        First, the goal here isn't to find the cholera. We know there's cholera in this river, the goal is to remove it before it gets to the village and drunk by the town's people. Same method though, you can only remove one dropper of water per person sampling. Now imagine you have not a river, but the bering strait. As Napoleon said, quantity has a quality all it's own. Please, please read about the base rate fallacy.