Interview/bias training effectiveness is pretty low and research conducted in this field throughout the years is showing mixed results at best.

This makes sense due to several reasons:

1. The forgetting curve: 60% of the information that is taught in training is forgotten after 72 hours.

2. Resistance to change: people tend to default back to their baseline behaviors unless there is a system in place that reinforces the expected behaviors.

3. Lack of immediate feedback: even if people want to change their ways, biases tend to be unconscious. Unless they are made aware of the bias immediately or shortly after it occurred, it will be hard to act on.

4. Hard to track improvement: companies struggle with quantifying and measuring interview training effectiveness. When they do, it’s usually at an aggregated level (team, business unit, etc.), making it impossible to draw conclusions on how an individual interviewer (or a specific group of interviewers) can improve.

5. The future of training is more "micro-learning" and "learning at the point of need". Interviewers' training needs to be the same - directed, individualized feedback on individual biases, when they occur. This is almost impossible to do by humans since it requires so many resources.

So what should you do to reduce interview bias and increase accuracy and fairness?

The answer is in our Interview intelligence technology.