- NLP models learn from data fed into them. Any biases in the training data are generally compounded and made worse.
- Many vendors will train their models using ratings provided by human evaluators for each interview. Unfortunately, this perpetuates the same biases we want to remove.
- Existing cognitive or game-based assessments claim to promote diversity by eliminating bias. In reality these assessments create misleading results since they contain limitations for predicting job performance and increasing diversity.
- Knockri goes beyond “good psychometrics" and effectively drives DEI metrics for your organization.
- While structured behavioural interviews are most accurate in predicting top diverse talent, they are traditionally very costly and time-intensive which makes them difficult to deploy at scale
- Knockri makes these assessments accessible with our automated behavioural identification and analysis system
- This makes it possible to deploy a well-designed structured behavioural interview at a fraction of the cost.
- While these efforts have pushed the needle, they do not eliminate bias from the hiring process.
- Knockri avoids all of these biases by fully automating a structured behavioural interview process from job analysis to scoring. Full automation ensures that none of the typical limitations of interviewer ratings are present in the assessment administration or scoring.
