Using Machine Learning to Select a Diverse and Effective Workforce
New machine learning techniques offer a promising way for organizations to predict employee success without compromising fairness to applicants.
New machine learning techniques offer a promising way for organizations to predict employee success without compromising fairness to applicants.
Background information in asynchronous video interviews can lead to bias in the employee selection process.
Many organizations are now conducting job interviews with a video interface that records answers for later evaluation. Are these “asynchronous” methods fair to job applicants?
New research shows that ethnic minority CEOs compared to nonethnic minority CEOs experience around half the risk of turnover.
New research investigates score differences on cognitive ability tests when taken by mobile versus non-mobile users.
Researchers demonstrate that employees who anticipate discrimination may be at risk for behaving badly at work.
New research provides evidence that diversity training and ally networks are effective interventions for improving the wellbeing of minority employees.
Researchers demonstrate how support for transgender employees can improve work engagement and life satisfaction.
New research suggests that observers of workplace abuse are more likely to legitimize the abuse when they have a strong relationship with the leader.
New research shows that Black employees face racial backlash for self-promotion that other racial groups are not penalized for.