The author, an Occupy Wall Street clown (who happens to have a degree in math), should know better.
Denied a job because of a personality test? Too bad -- the algorithm said you wouldn't be a good fit. Charged a higher rate for a loan? Well, people in your zip code tend to be riskier borrowers. Received a harsher prison sentence? Here's the thing: Your friends and family have criminal records too, so you're likely to be a repeat offender. (Spoiler: The people on the receiving end of these messages don't actually get an explanation.)Do the models work? Are they accurate predictors? If so, then you can't blame people for using them. If not, then there's no justification for using them at all. The author doesn't like the results and uses that dislike to try to make her point; her lack of determining if the models are valid or not severely weakens her point.
The models O'Neil writes about all use proxies for what they're actually trying to measure. The police analyze zip codes to deploy officers, employers use credit scores to gauge responsibility, payday lenders assess grammar to determine credit worthiness. But zip codes are also a stand-in for race, credit scores for wealth, and poor grammar for immigrants.
Hat tip to reader MikeAT for the link.
Update, 9/7/16: Perhaps I was wrong, perhaps there is something to this "math is evil" belief:
Meet the little-known statistician behind the Democratic nominee's most important strategic decisions.