Dive Brief:
- To boost diversity in the workplace, one proposed solution is to remove existing biases with a systematic analysis of data...in other words, use an algorithm, according to an article at The Atlantic.
- Basically, employers give pre-hiring personality tests to candidates then use data analysis to determine its ideal hires. While the algorithm depends on what an employer is looking for, common outcomes include using the data to predict whether a candidate will quit or steal on the job.
- Algorithmic hiring has been on the rise, says The Atlantic. One study of algorithmic hiring found that a simple equation was significantly better than humans at identifying high-performing employees.
Dive Insight:
Infor Talent Science is reporting that algorithmic hiring can also improve diversity. It provides software that helps employers hire by collecting behavioral information using a survey, then makes a predictive model based on top performers.
In Infor’s forthcoming report, they found that using an algorithm to help with hiring increased their wholesale clients’ Hispanic hires by 31%. For their restaurant clients, African American hires increased by 60%
Will algorithms be the secret sauce for boosting diversity? Some academics warn that big data’s supposed objectivity can mask other biases built into the algorithms. But while the early results seem to indicate that algorithmic hiring can help reduce biases, an employer has to care about doing so, says The Atlantic.
