The Perils of Algorithmic Hiring and Title VII
posts included a large number of posts about caring for sick relatives during work days is becoming a reality .
The initial push for use of big data analytics in employment has been spearheaded largely by departments comfortable with work with data analysis such as marketing and operations . 34 Marketing departments have long been familiar with segmenting the population and identifying groups of people for targeted advertisements . An employer wants to know its target audience and find effective ways of reaching them . 35 The most famous example is Target ’ s “ Pregnancy Prediction Score ,” which Target used to predict if a customer was pregnant , and successfully estimate the due date within a small window . 36 This allowed Target to send coupons to customers at specific stages of pregnancy using nothing more than the shopping habits for items like lotion and cotton balls . 37 Applied to a potential applicant pool , these same innocuous criteria , easily buried in the noise of 100,000 or more possible factors , could be used to completely exclude potentially pregnant women from consideration were a company worried about an applicant taking maternity leave shortly after being hired . In terms of bringing a claim , it would be difficult for an applicant to prove they were discriminated against based on pregnancy at the time the applied , especially if they did not themselves even know they were pregnant at time of application .
Employers will want to use this algorithm power to improve their resources in regards to hiring , retention , and promotion . However , employers must be mindful not to discriminate against employees , or potentially employees based on protected characteristics . Discrimination based on race , color , religion , sex , national origin , 38 disability , 39 genetic information , 40 or pregnancy 41 is forbidden by law . How each cri-
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