In addition you do not factor in significant complexities like the ones below:
You are incorrect about your assumptions in many respects. Let me list out a few:
1) There is a big difference between watching a 15 min video at 2X for fun vs watching 8 hours of videos a day while having to follow laid down policy with complexity. Videos are not taken down only for one reason and there is a lot of complexity involved with edge cases. Humans are not robots and this is not a task we are inherently good at. Give it a shot yourself for a day and see how easy it is.
2) Your overhead does not consider any additional complexity in terms of languages, specialty, regional expertise etc. This is not a simple problem either. Sure maybe you can hire 1000 reviewers in lets say Indonesia but you cannot find a native Kswahili speaker there. Its not cheap to setup an office for 2 people in Kenya. Scale this to the world which has 193 countries and 6,500 languages.
3) People dont work without any management overhead. You need frontline reviewers. Then you need a layer of experts above them. The you need managers to take care of the operations. The managers to manage those managers. Then recruiters to hire those people. Then HR to deal with their issues.
4) Turnover is a big deal. Very few people in the world can watch beheadings 40 hours a week. An even smaller proportion can handle child safety material. What happens when those people need to take time off? You need additional people. If you want a humane operation then you might have to get them to work only 2 hours a day.
Here is some more reading if you are interested in understanding this from the moderators / reviewers view: https://www.theverge.com/2019/12/16/21021005/google-youtube-...
It continues to amaze me how some of the smartest and technically savvy people on HN either do not recognize or refuse to admit how complicated a problem planet scale moderation is. If it was a problem that could be solved by spending a few tens of million dollars a year, it would have been solved.
Obviously, just watching every video in real-time a single time is not an adequate review process. Things can be missed, misunderstood, or just take more time to process, so it is likely that more review would be necessary for non-obvious cases. But, on the other hand, it is not necessary to review literally every second of every video. If they only reviewed reported videos and reports were required to specify the timestamp, they would probably instantly reduce this total burden by a factor of 10x-100x (assuming they filter out obvious spam reports). This would allow them to allocate more independent reviewers to the actual non-obvious cases resulting in reasonable accuracy with a human appeals process while reducing their overall cost burden significantly lower than the previously stated ~50%. They could then tier their review process based on the amount of views to allowing them to limit how many resources they spend on unpopular and irrelevant videos to focus on more visible and profitable videos while still providing a base level of review. And, all of this is assuming that they do not have any automated mechanism to directly decide on cases that are trivially obvious, thus reducing their burden even lower to only the contentious cases where the automated systems can not create a clear-cut answer. Frankly, I could go on about various other potential mechanisms they could do to reduce costs while increasing efficiency and avoiding bad actors, but what I have already said should already be sufficient to handle the basic problem.
All in all, they could probably institute a reasonable human review process that could handle all reasonable cases for <5% of yearly revenue and frankly I would be shocked if it were anywhere near the high end of that estimate. Even without any automated systems I would put my median cost prediction at 1% of yearly revenue and with even basic automated systems probably close to 0.2%.
[1] https://www.businessofapps.com/data/youtube-statistics/