this post was submitted on 04 Sep 2024
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That's the thing about automation and training models.
First, they implement some sort of auto-reporting bot that requires a human to review them. In the beginning, it only about 50% accurate, but as they give it more and more examples of good and bad results through the human reviews, it moves to 80%, then 90%, then 99%, then 99.99% accuracy.
After a while, the humans on the other end are so numb to the 9999 entries they have to mark as approved that they can barely tell what's a rejection themselves, and the moderation team is asking itself just what this human review is actually doing. If it's 99.99% accurate, why not let the bot decide?
Then, the model moves on from auto-reporting to auto-moderation.