If the numbers show that poor people are more likely to respond to payday loan advertisements, then that's what the numbers show. If the businesses are truly predatory then they should be regulated. It doesn't make sense to show ads for them to people who are statistically unlikely to respond to them, nor does it make sense to show poor people ads for institutions that are statistically unlikely to grant them loans. Algorithms aren't the problem here, the nature of the businesses is.
And in fairness, I notice that when I watch certain tv shows late at night I'm much more likely to see payday loan ads than when I watch during prime time. I've long suspected that this is because the kind of person who is watching "30 Rock" re-runs at 1am is less likely to be employed and more likely to need a payday loan. So if it's fair for a media buyer to select audiences that are most likely to purchase a product, why is it unfair for an algorithm to do it?
The article makes the point that algorithms are opaque and people often can't explain exactly why a decision was made. That's fine, as long as the results can be shown to be accurate with out of sample testing. It's good to understand why, but it isn't always necessary. The point of using advanced statistical modelling is to expand our level of capability beyond what our brains can easily perceive. The ability to draw reliable inferences from tens of millions of data points is a very powerful and wonderful thing, quite a leap for evolved monkeys who use lobes of fat to perform calculations. It's new, it's different, and it's definitely worrying. But the sooner we can adapt, the better off we'll be as a society.
[1] in this case "large" probably means two or three orders of magnitude larger than you were thinking