> It seems like the only solution that would work at a large enough scale to handle that kind of demand
It doesn’t work. These automated systems are flagging a (presumably) benign site and an article yesterday regarding their $5M lawsuit for running a scam ad on their SERP for “Coinbase support” suggest the automated systems can be bypassed too.
I’m not saying automated detection can’t be a part of it, but we shouldn’t accept companies automating away decision making as if computer-derived errors are acceptable.
The larger point is that Google isn’t exactly strapped for cash. They could hire an army of reviewers. They just don’t.
Point taken; it "works" for certain values of "work."
> They could hire an army of reviewers. They just don’t.
They may actually do that too, but perhaps there are thresholds that must be met for something to reach a reviewer. I have some sympathy for Google here as I work on email security in a high-volume environment. ML is one tool in the box, and human reviewers are another. Everything is a tradeoff between resources, false positives, and false negatives.
At least my organization's customers can contact support if something is going wrong, but for people trying to legitimately use Google Ads, it can be an extremely frustrating situation of shouting into the void. (And getting boilerplate support answers back from the void.)
It doesn’t work. These automated systems are flagging a (presumably) benign site and an article yesterday regarding their $5M lawsuit for running a scam ad on their SERP for “Coinbase support” suggest the automated systems can be bypassed too.
I’m not saying automated detection can’t be a part of it, but we shouldn’t accept companies automating away decision making as if computer-derived errors are acceptable.
The larger point is that Google isn’t exactly strapped for cash. They could hire an army of reviewers. They just don’t.