Nathaniel M. Glasser, a Member of the Firm in the Labor and Employment practice, in the firm’s Washington, DC, office, was quoted in “Experts Discuss Big Data’s Effect on Hiring, Bias Claims.” The Bloomberg BNA Daily Labor Report article reviewed the Industry Liaison Group National Conference, where Mr. Glasser recently spoke.
Following is an excerpt:
“You can reduce the number of candidates that you are originally screening. Big numbers are bad numbers in terms of statistical analyses for adverse impact. When you have a large data set to work with, it’s a lot easier to find statistical significance,” Glasser said.
During the selection process, the predictive analysis and models can be utilized to limit the subjectivity in the selection process, he said. This makes it a level playing field for all candidates, which “can lead to some good results and protect you against claims of unintentional discrimination, Glasser said. Still, he advised employers to review predictive analytics and models for encoded biases.