Assigning Jobs Using An Algorithm
DEIDiversityTransformation InnovationTechnologyTechnology, Data, and DigitalInnovation, Research, and DevelopmentDiversity, Equity, and Inclusion Advisory
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November 14, 2020
DEIDiversityTransformation InnovationTechnologyTechnology, Data, and DigitalInnovation, Research, and DevelopmentDiversity, Equity, and Inclusion Advisory
This article quoted Russell Reynolds Associates Consultant Cecyl Hobbs on how technology and artificial intelligence can be used to boost diversity in organizations.
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Global Finance

The Global Finance article, "Assigning Jobs Using An Algorithm," quoted Russell Reynolds Associates Consultant Cecyl Hobbs on how technology and artificial intelligence can be used to boost diversity in organizations. The article is excerpted below. 

On September 30, California Gov. Gavin Newsom signed legislation requiring publicly traded companies based in the state to have at least one racially, ethnically or otherwise demographically nontraditional director on their board by 2021. While 11 states, as well as some countries, have enacted or are considering board diversity legislation, these focus on disclosure, without instituting quotas. Even so, “the expectation is by taking the lead, California-based companies will set the standard that becomes expected by a lot of other publicly traded companies,” says Cecyl Hobbs, consultant at Russell Reynolds Associates.... 

Being thoughtful and creative with technology can eliminate bias, proponents claim. Algorithms can ensure job descriptions encourage a broader swath of applicants. Algorithms optimize for multiple criteria that are predictive without showing gender or ethnic differences. Training algorithms with data that’s more common across groups—like math scores versus engineering degrees— and evaluating soft skills like cognitive, social and emotional aptitudes rather than proxy variables for gender or race—produce a more diverse candidate pool. 

“AI is only good as the data that gets fed into it—if the underlying data only feeds in experienced-based criteria, you may miss candidates that may have unconventional experience sets,” says Hobbs. 

There’s no question that when humans interview candidates, bias is an issue. There are ways to overcome this, like anonymizing resumes or evaluating candidates with a rubric focused on skills rather than education and experience. Comprehensive referencing helps fill in the gaps for candidates with unfamiliar backgrounds 

“There’s hard work to be done around diversity but there are incredibly rich rewards in terms of the performance of the companies willing to embrace this,” Hobbs believes. 

​To read the full article, click here