The other problem with fixing it with statistics is that it’s essentially illegal, right? And that’s our way of fixing discrimination. Chief Justice Roberts famously said “the way to stop discrimination on the basis of race is to stop discriminating on the basis of race. With the high crime statistics in South Africa, theft is obviously something car insurance companies deal with on a daily basis. There are a number of local and national insurance companies willing to insure your teen, their vehicle, and anything else they may damage while driving. Your occupation: If your occupation demands a lot of driving and you use your own car for it then the car is mostly on the road and the risk of accident is high. Many insurers offer discounts for features that reduce the risk of injuries or theft. Some companies will offer a discount when more than one insurance plan is picked with a service provider. Some companies also offer deals for students who keep their grades to B average and above and, in the case of cheap auto insurance, every little bit helps. Th is was gener ated with GSA Content Generator Demoversion!
We really can’t do that because the companies have all that data so our laws need to kind of shift away from this race blind strategy that we’ve kind of done for the last, you know, 50, 60 years where like, okay, let’s not consider a race, let’s just be blind to it. Cindy: We all want a world where people are not treated adversely because of their race, but it seems like we are not very good at designing that world, and for the the last 50 years in the law at least we have tried to avoid looking at race. When looking for auto insurance you are obviously going to want to get a good deal. It may be a good idea for you to raise the deductible. And those little bits of data, may be what website we’re looking at, but it’s also things like how long you looked at a particular piece of the screen or did your mouse linger over this link or what did you click? Vinhcent: Absolutely. When they looked at discrimination and algorithmic lending, and they found out that essentially there was discrimination.
Vinhcent: Even if you’re an engineer wanted to fix this, right, their legal team would say, no, don’t do it because, there was a Supreme court case Ricci a while back where a fire department thought that its test for promoting firefighters was discriminatory. Danny: You’ve talked about how red lining was a problem that was identified and there was a concentrated effort to try and fix that both in the regulatory space and in the industry. Vinhcent: Absolutely. The Greenlining Institute where I work, was founded to essentially oppose the practice of red lining and close the racial wealth gap. So even though red lining is outlawed, these computers are picking up on these patterns of discrimination and they’re learning that, okay, that’s what humans in the United States think about people of color and about these neighborhoods, let’s replicate that kind of thinking in our computer models. Danny: One of the issues here I think is that as the technology has advanced, we’ve shifted from, you know, just having an equation to calculate these things, which we can kind of understand.
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Danny: So it’s not just about your zip code. So they look at the zip code and look at all of the data associated with that zip code, and they use that to make the decisions. The internet makes it easy to compare prices from different insurers, why not make the most of this? That why this credit limit changed. A gentleman, Wint, was traveling and he went to a Walmart in I guess a bad part of town and American Express reduced his credit limit because of the shopping behavior of the people that went to that store. So they have very specific segments that put people into different buckets. So what data brokers do is they, you know, they have tracking software, they have agreements and they’re able to collect all of this data from multiple different sources, put it all together and then put people into what are called segments.