This was on NPR yesterday and was pertinent to the week 2 discussions about surveillance tech. The LAPD is using data analytics to predict who will commit crimes where, but this part was pretty troubling:
the formula for determining whether someone’s on the Chronic Offenders Bulletin is based partly on how often someone is interviewed by the police. But that’s something that’s simply more likely to happen in those places with heavier police presence.
and also this
You probably know about license plate readers in cars. As the squad cars drive around, they’re just gathering up all the license plates that they spot. It gets stored. You can recreate on a map where a car has been. It turns out they’re keeping that indefinitely… someone in the LAPD could reconstruct where you’ve driven over the last few years
Apologies if this has already been recommended elsewhere, but Weapons of Math Destruction by Cathy O’Neil is perfect for anyone who wants to learn more about the types of algorithms this article discusses. The book is thorough and engaging and not overly technical (key! she is a mathematician but I am very much not), which I love because it means I can recommend it more widely. And I recommend it all over the place because it’s such crucial information.
This part of the article stuck out for me:
What they’re trying to call science is really pseudoscience. The bias is still very much inherent in the data that’s being used, and the same communities are being impacted.
This idea that science (broadly, so also tech and big data) is unbiased is so dangerous, but also seems to be so readily accepted. There’s such a long and sordid history of science being used for political ends, or to provide a veneer of respectability for racism/domination etc., yet here we are again with tech and big data.
@sjbrown Thanks! I will check out that book.
thanks for starting this convo! we’ll talk even more about some of this stuff in week 7 with Freddy Martinez. it’s such a great point regarding the so-called “objectivity” of these tools. it is indeed pseudoscience, rife with bias. Kathy O’Neil’s book is great on this point as is Virginia Eubanks’ Automating Inequality. One of these days I’ll post the booklist that I’ve been making and we can add more titles like these to it.