Here’s an article titled Math is Racist, which is a misleading name.
Essentially profiles a professional mathematician (sounds like a data analyst to me) who trucks with the Occupy Wallstreet crowd. She claims that mathematics is being used to hurt poor people on loan applications, criminal sentencing, and so on.
A few thoughts:
1) It’s crazy easy to hurt poor people. Want to not live by minorities? Move somewhere with high property taxes. Want to enmesh them in the criminal justice system and feel good about yourself at the same time? Enact usurious vice taxes on things like cigarettes and alcohol and outlaw cheap vices like marijuana. It’s not like you need to be a statistician to think of ways to hurt poor people.
2) One of the things they make you learn when you become a statistician is something called discriminant analysis, which is a fancy way for coming up with mathematical rules for separating things into groups. The classic example is that you have a bunch of different flowers that look alike but are different flowers. You create a mathematical model based on the size of the petals and sepals and it classifies them.
You don’t always get perfect rules to tell them apart, but you can do a lot better than random chance. So, for example, if you had four types of flowers in a hat, picked one out and then randomly said it was one of the four types of flowers, you’d have a 25% chance of being correct. Using discriminant analysis, you might be able to move that up to a much higher rate of accuracy (maybe 75 or 85%).
When talking heads talk about computer algorithms to predict our behavior, what they’re really talking about is discriminant analysis. When you buy some stuff on Amazon, it uses discriminant analysis to figure out what “type” of person you are and then selects other stuff that your “type” might want to buy.
Sometimes it works, sometimes it doesn’t. But it’s not supposed to be perfect. Amazon has an almost infinite number of products–if it randomly picked something to suggest, it would have a negligible chance of picking something you’d want. But if it can improve that chance to even a few percentage points, it’s a success.
When you get turned down for a loan or face harsher penalties for crimes based on your zip code, credit score, and other things, that’s discriminant analysis.
3) My problem with the title of the article is that the profilee is clearly not anti-science. She’s anti-a-particular-application-of-science, which is a very different thing. She doesn’t not believe that discriminant analysis is a real mathematical tool, she believes that employing it in loan applications or criminal sentencing is wrong.
A better way of looking at this is that she’s anti-scientism, which I’d define as the belief that “Science” and the scientific method is the only reliable guide for human understanding.
In a sense, anti-scientism is the entire underpinning of books like Frankenstein or Jurassic Park, which are essentially reframings of the question “Science tells us we can do this, but should we?”
4) We have a big problem politically (on both sides–but not with enlightened people like me who are moderates), wherein each claims that the other is “anti-science.” (Liberal friends, you may not know that that conservatives think that you are the anti-science ones, but, like, it’s a thing. You need to read more NRO).