Directing focus at "people who drink a lot of beer" means considering people who who drink a lot of beer at home as guilty by association, ultimately due to the subjective priorities of whomever pushed for that model.
Obviously in the expected value sense, charging on correlations is lucrative for the company (as is any justification for raising prices on a set of customers if your competitors do it too). But in the exact same way as saying certain zip codes are more likely to default on a loan, which we rightfully reject.
Why would we reject that zip codes are more likely to default on a loan? Seems like information I would like to be aware of if I was a home lender.
I certainly look at crime rates of a community before I live there. While a bad crime rate certainly doesn't make potential neighbors "guilty by association", it certainly increases the likelihood that one of my neighbors might be actually guilty.
Nope. Because it's flawed reasoning. If many people who get into accidents were driving drunk and everyone who drives drunk buys beer it might seem logical to increase rates for everyone who buys beer, but people who drive drunk are only a small percentage of the people who are beer buyers. That kind of reasoning seems more likely to be a weak justification to raise rates for a large number of people than a reasonable response to a trend.
If the insurance companies could arbitrarily raise rates due to a trend that doesn't exist, than they would have already done so. These companies know their margin and they don't bid above that if they want to be competitive.
that assumes that all companies involved aren't doing the same thing. Corporations figured out a long time ago that when one of their competitors does something that makes them more money at the expense of their customers they could start doing the same thing to their own customers and profits increase for everyone without risking prices being driven down by a truly competitive market. The insurance industry in particular is has a long history of shady practices from good old fashioned collusion and price fixing to new techniques like data mining to charge customers different rates depending on where they live, what jobs they have, or how often they're willing to change insurance companies.
In my view, the insurance industry looks competitive, which means that even though these shady practices happen they can't effectively dictate the entire market.
One of the tendencies of the neo-puritanism that has become prominent in the last decade is a real willingness to abandon any boundaries that have kept corporations from using certain kinds of information against individuals -- boundaries that were in large part legislated during the civil rights era.
It's the job of the insurance company to accurately assess risk and charge me that plus their margin. If the companies can more accurately assess risk, than that makes insurance a less volatile and therefore cheaper market.
Insurance companies don't have access to the actual root causes of accidents. They have no measure of my driving skill or risk tolerance or attention span. They just estimate based on some really primitive data they have about me. What's the harm in including more data?
Is it just supposed to be self-evident that those inferences are unreasonable?
I've always thought that this was an interesting argument. If there is some form of correlation with beer consumption and and car accidents, wouldn't it make sense to adjust your estimated risk based on that information?
I do find it self-evident that that would be a bad thing, but I also have a hard time putting my finger on why.