The search process for potential job candidates used to be straightforward and low-tech: companies advertised for the open position then sorted through the resumes, or maybe they hired a search firm or put together a search committee to match the company with the best possible candidates. But the growth of data analytics has come to the human resources office and now companies can use predictive analytics to determine characteristics of candidates who would do well in a given role and isolate those in the candidate pool or in a company’s applicant databases who would do best. They also can rank applicants’ suitability by using software that analyzes interview responses or test answers.
Data analytics are appealing because they can make hiring less expensive, more efficient and, some would argue, smarter. But there is a downside, namely the threat of employment discrimination claims resulting from systems that unintentionally exclude or appear to exclude candidates with certain protected characteristics. Adding to the problem is that guidelines from the U.S. Equal Employment Opportunity Commission and Office of Federal Contract Compliance Programs still enforce standards related to disparate impact and disclosure that haven’t been updated along with modern technological realities.
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