Last Reviewed on April 2, 2020, by eNotes Editorial. Word Count: 1262
Chapter 6: Ineligible to Serve: Getting a Job
The chapter begins with the story of a student whose application for a minimum-wage job at a supermarket was rejected on the basis of a personality test. He later found that all the other companies to which he applied also turned him down based on the same test. O’Neil uses this example to introduce the question of “how automatic systems judge us when we seek jobs and what criteria they evaluate.”
The Supreme Court has ruled that companies cannot use intelligence tests to select employees, so many have taken to using personality tests instead. Since simple personality tests can be easy to “game,” as the answers the employer wants are obvious, more complex tests have been developed, often featuring questions in which prospective employees are asked to admit to one of two faults. These tests are opaque and have no feedback mechanism, since no one tracks what happens to the candidates who are rejected. This is why personality tests for hiring employees are WMDs. They are even more unfair than the old-fashioned hiring practices based on personal contacts and first impressions: these, at least, varied from company to company, but the prejudices embedded in tests are scaled across entire industries.
Human resources departments are increasingly reliant on automatic systems to screen applications. Applicants who know the particular terms for which these systems search, therefore, have a built-in advantage. The systems are often designed to replicate procedures that human beings have previously followed, meaning that the computer learns “from the humans how to discriminate.” O’Neil cites the case of St. George’s Hospital Medical School in London. The people who screened applications tended to discard those with poor grammar or spelling, many of which were from overseas. The computer therefore learned to assign lower scores to applicants from Africa and Asia.
The complexity of recruiting and retaining good employees with any degree of consistency has so far proved too much for both old-fashioned and mathematical models. O’Neil compares companies’ imprecise use of data to the pseudoscience of phrenology, which claimed to make authoritative pronouncements about personality based on bumps and indentations in the subject’s skull. The Big Data models that claim to assess personality are often, like phrenology, “little more than a bundle of untested assumptions.”
Chapter 7: Sweating Bullets: On the Job
The data economy helps companies to tailor employees’ schedules to better serve the needs of the business. However, the needs of employees are generally disregarded—including such basic requirements as childcare, transportation, and sleep—as schedules change at the last minute to eliminate inefficiency and save the business as much money as possible. The technology used in scheduling is rooted in a branch of applied mathematics known as “operations research,” or OR. This was used during World War II to track the “exchange ratio” of “Allied resources spent versus enemy resources destroyed.” OR was developed and refined after the war by the Pentagon, and then by large companies. Technology which was first used to manage the supply of parts for car assembly lines now manages the supply of low-paid workers in the service sector.
These scheduling programs, O’Neil argues, are some of the worst WMDs. They are entirely opaque to workers, who often don’t know their schedules in advance, and they create a vicious feedback loop, since the uncertainty and stress prevent employees from finding better jobs or improving their prospects through education. The children of workers are also severely affected by the lack of routine and stability. As is always the case with WMDs, the model...
(The entire section contains 1262 words.)
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