zlacker

>>benhur+(OP)
This happens again and again. I have had that happen to my twitter account. I see this regulary on HN.

My suspicion is that this is mostly happening because platforms that big like google or twitter rely very heavily on machine learning and other AI related technology to ban people. Because honestly, the amount of spam and abuse that are likely happening on these platforms has to be mind boggling high.

So I get why they would try to automate bans.

But after years and years of regular high profile news of false positives, one would think they eventually would change something.

I mean the guy had direct business with Google going on....

Why would they continue like that. Isn't there one single PR person at Google?

>>p410n3+Y2
Shows the bias in machine learning. One simple parameter isn't added and the whole model is bullshit.

One parameter would be: Amount of money this customer has spend on our products.

Another would be: Active time since signup.

I'm pretty sure if "money spend > 0" is actually a legitimate threshold to remove a lot of spam, although not all. "money spend > 200" might to the trick though.

>>WA+A6
This can be gamed. There are so many stolen credit card numbers and/or payments using Apple/Google pre-paid cards out there, so it's not difficult to automatically build accounts with this kind of 'reputation'.

Unfortunately the best way to do KYC is (still) human intervention (and use of data).

>>HenryB+5g
It can be gamed. But if the average value of a fake account is $100 and you set the threshold to be $200 it is no longer profitable.

Of course this still isn't a perfect metric. But it seems that banning people with accounts that have spend thousands of dollars and been active for many years should probably be avoided and this will significantly help that.

I mean if the account has spent >$50 you can probably afford a human review at the very least.