Earlier quoted context omitted.
I think they meant (and I am interested in hearing about) appealing a "block" decision that was made by your automation. If I'm a real human and trying to post a "good" post, but the model classifies it as bad and automatically blocks it, how do I appeal that decision? Can I? Or is my post totally blocked with no recourse?
Oh got it. Thanks for clarification. When a post gets published, it will be send to machine learning image via REST. If bad, the post will be kept as Draft. A new record gets created in another database table to keep track them, the accuracy rate was recorded as well. This was made to make sure no irreversible action was done on the good content. Blogs with more than 1 year of history would not go through moderation…
And there's a lot of overlap between how that system acted and what you're describing. It makes we wonder if there's space for a company that offers this sort of model training + content tagging + review tooling capability as a service, or if there's too many variation on what "good" and "bad" input is to make it generalizable.