Summary

• (30 min) Read the chapter 
• (5 min) Short videos
• (10 min) Additional readings
• (30 min) Discussion and case-study on slack
• (5 min) grading declaration

Readings

Read Chapter 5 “Civilian Casualties: Justice in the Age of Big Data” in the Weapons of Math Destruction book. 

Note: We are going to do something slightly different for this chapter than just hunting for quotes and discussing (though you are quite welcome to highlight your favorite quotes and discuss also!).  In addition to the traditional discussion on the chapter, I have a short research assignment below.

The main focus of this chapter is on predictive policing.  We want to examine the details of these a bit more.

• Take a look at the description of PredPol’s algorithm.  What do you think of the algorithmic transparency here? 
• Here is a quick article about PredPol and its biases, written in the Smithsonian Magazine.  Artificial Intelligence Is Now Used to Predict Crime. But Is It Biased?

Predictive Policing

 Image from PredPol

Minority Report

One of the movies referenced in this chapter is Minority Report.  Thought provoking especially for ethics, though it doesn’t related to AI & ethics as much as just predictive ethics (which is what this chapter is all about!).  For fun, watch the trailer and you can see what I mean.  If you have time and want to enjoy a movie, it is thought provoking!

Discussion and Assignment

This discussion will happen in the #weapons-of-math-destruction channel. Remember to use threads so that we can keep track of the conversation more easily.

We are going to do two things for this chapter.  The first is our more traditional discussion based on the chapter and quotes from the chapter.  The second is that I want you to do some research about predictive policing.

Discussion

As with previous chapters, I have a few quotes to think about and discuss.  As before, feel free to find your own quotes and discuss as well.

• “The result is that we criminalize poverty, believing all the while that our tools are not only scientific but fair.” (page 79, Chapter 5, Weapons of Math Destruction)
• “While looking at WMDs, we’re often faced with a choice between fairness and efficacy.” (page 81, Chapter 5, Weapons of Math Destruction)
• “WMDs, by contrast, tend to favor efficiency.  By their very nature, they feed on data that can be measured and counted.  But fairness is squishy and hard to quantify. … So fairness isn’t calculated into WMDs.  And the result is massive, industrial production of unfairness.” (page 82, Chapter 5, Weapons of Math Destruction)
• “Justice cannot just be something that one part of society inflicts upon the other.” (page 83, Chapter 5, Weapons of Math Destruction)
• “From a mathematical point of view, however, trust is hard to quantify.  That’s a challenge for people building models.” (page 88, Chapter 5, Weapons of Math Destruction)

Short Research Assignment/Case study

Your short research assignment for this chapter is to look into predictive policing, either here in Oklahoma or in your home towns and surrounding areas. See if you can identify if they are using predictive policing algorithms and what, if any, oversight they have on the algorithms with respect to fairness.  Report your findings to the #case-studies channel.  Note, reporting only “I did a short web search and didn’t find anything” isn’t really much of a report.  Do your homework and figure out what is happening and share!

Declarations

OU students: After you have done your reading and engaged actively in discussion, complete the grading declaration titled “Module 7: Civilian Casualties”