Popular Culture Review Volume 30, Number 1, Winter 2019 | Page 185

The Perils of Algorithmic Hiring and Title VII
Employer Wellness Programs , 45 but these same criteria could be applied against potential applicants .
In her testimony , Kelly Trindel addressed these risks . She noted : “ As an example of the type of EEO problems that could arise with the use of these algorithms , imagine that a Silicon Valley tech company wished to utilize an algorithm to assist in hiring new employees who ‘ fit the culture ’ of the firm . The culture of the organization is likely to be defined based on the behavior of the employees that already work there , and the reactions and responses of their supervisors and managers . If the organization is staffed primarily by young , single , white or Asian-American male employees , then a particular type of profile , friendly to that demographic , will emerge as ‘ successful .’ Perhaps the successful culture-fit profile is one of a person who is willing to stay at the job very late at night , maybe all night , to complete the task at hand . Perhaps this profile is one of a person that finds certain perks in the workplace , such as free dry cleaning , snacks , and a happy hour on Fridays preferable to others like increased child-care , medical and life insurance benefits . Finally , perhaps the successful profile is one of a person who does not own a home or a car and rather appears to bike or walk to work . If the decision-makers at this hypothetical firm look to these and other similar results to assist in the recruiting of passive candidates , or to develop a type of screen , giving preference to those future job-seekers who appear to ‘ fit the culture ,’ the employer is likely to screen out candidates of other races , women , and older workers . In this situation , not only would the algorithm cause adverse impact , but it would likely limit the growth of the firm .” 46
Ultimately , the relationships among the variables are exclusively correlational in nature . There is no certainty that an individual employee ’ s distance from work will increase their
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