“A peels an apple, while B kneels to God,C telephones to D, who has a handOn E’s knee, F coughs, G turns up the sodFor H’s grave, I do not understandBut J is bringing one clay pigeon downWhile K brings down a nightstick on L’s head,And M takes mustard, N drives to town,O goes to bed with P, and Q drops dead, R lies to S, but happens to be heardBy T, who tells U not to fire VFor having to give W the wordThat X is now deceiving Y with Z, Who happens, just now to remember A Peeling an apple somewhere far away.””
“As odd as it may seem, there also are constructive uses of biases against certain groups (Q2 in figure 1.1). They can benefit us in many ways. We determine that people who have aggressive personality types might not be the best fit for a customer service job. Or that people who don’t have certain technology skills and background won’t be a good match for a job that requires computer proficiency. If we didn’t have these filters, hiring would be almost oppressive, because we would start with a huge number of résumés and have to look at all of them more carefully than time might allow. I know that many people would say those are “qualifications,” and that looking for qualifications is not the same as having biases. In fact, qualifications are simply biases that we have agreed upon and codified. There are hundreds of examples of people who have performed in extraordinary ways who do not have the normal qualifications for their roles. If qualifications were the only measure of success, than college dropouts such as Steve Jobs and Bill Gates would still be unknown. However, understandably, we have determined that while there are occasional creative eccentrics like Jobs and Gates, it just doesn’t make good sense to look at 150 résumés and not take education into account. So we use biases against the lack of those characteristics to “filter out” certain people who we might have determined are not a good fit for the job.””
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