Machine learning and algorithms have the potential to completely change the hiring industry and help to eliminate the rampant issues around bias, but we believe the human element will remain an essential part of the equation. Humans will still need to apply the emotional, intuitive functions that machines will never be able to learn while machines can process data at volumes and speeds our brains never could. In this situation, man and machine are truly more than the sum of their parts. Check out this piece from GetApp Lab, a Gartner company, on how biases take shape and how Riviera, and other companies, are leading the charge to improve recruitment practices with data science.
(GetApp Lab) Hiring Bias: Why Your Recruitment Practices May Be Unfair and How Algorithms Can Help
US companies have a diversity problem. Only 14 percent of CIOs are female. At Microsoft, the representation of female employees even declined by 1 percent in 2016, despite the company’s diversity program. Meanwhile, only 2 percent of tech executives are black and 3 percent are Latino.
The question is, how much of this can be traced back to a (conscious or unconscious) hiring bias in companies’ recruitment processes?
