In light of the recent election, it is more important than ever to look at how and where we are responsible for perpetuating prejudice. In a previous article, DataCrunch introduced the concept of “Weapons of Math Destruction,” which are data models built from a limited or biased sample of data that result in toxic feedback loops. Since this explanation is most often attributed to artificial intelligence, there is little discussion about how this description could also illuminate the workings of the human mind. While many might want to think of this narrow-mindedness as below the mental capacity of human beings, such a viewpoint is dangerous in that makes having a conversation about prejudice difficult. Like artificial intelligence, humans create internal models in their minds, which often lead to the creations of ideals such a stereotypes. The flaw of these models is that they are based on the past, and if not updated or addressed they will continue to run off of the same data they were originally fed – even if times have changed.
At an individual level, racism is a toxic feedback loop. People want to be able to predict how other people will behave, and it can be far too easy to create “a binary prediction that all people of that race [or gender, sexuality, religion, political group, etc] will behave that same way,” (O’Neil, 23). If an issue like this develops in a technical model, it isn’t too difficult to go back and manually adjust the data input or change the important factors. But people with racist beliefs “don’t spend a lot of time hunting down reliable data to train their twisted models,” (23) They will continue to gladly absorb the data that seems to confirm their beliefs, and will refute data that tests them.