Maybe I'm lacking imagination, but how do you account for the renter and Airbnb having vastly different sets of information to work from? Also your sample size would have to be huge to rule out coincidental outcomes, which I dare say would rarely be found for the average property.
For example my property gets about 100 customers per year. I'm guessing in the last 4 years I've had 3 black customers, all accepted by the way, but if I rejected all 3 can an algorithm reasonably rule out coincidence having such a low sample size? It just seems like it would be the kind of algo doomed to fuck it up.
It's like spam filtering. It may be hard to imagine but it can work. Algorithms look at multiple signals and produce a confidence score.
Consistently rejecting the one black customer you get every year would probably raise your score enough to prompt an investigation, and the outcome of that (like a fake white test booking) would give more confidence that it's not just coincidence.
Maybe I'm lacking imagination, but how do you account for the renter and Airbnb having vastly different sets of information to work from? Also your sample size would have to be huge to rule out coincidental outcomes, which I dare say would rarely be found for the average property.
For example my property gets about 100 customers per year. I'm guessing in the last 4 years I've had 3 black customers, all accepted by the way, but if I rejected all 3 can an algorithm reasonably rule out coincidence having such a low sample size? It just seems like it would be the kind of algo doomed to fuck it up.