Unconscious bias is a threat to any process that requires objective decision-making, and candidate selection is no exception. With the proper data-led approach to assessment, recruiters can increase efficiency and improve the quality of their hires.
Bias is hardwired into almost all of our day-to-day decisions, including those related to making new hires. That doesn’t mean we’re incapable of making rational decisions, but it does mean we have to remain aware of and address these latent tendencies.
Recruiters, just like everyone else,are subconsciously drawn to or repelled by specific human qualities. For example, a candidate's stated interests, physical appearance or tone of voice can influence a reviewer's scoring decisions without them even realising it. Attractiveness, cultural similarities and outgoing personalities all similarly affect candidate selection.
Often, the person who best showcases their skill is the one hired, regardless of who might actually be the best fit. And thus, thanks to our ingrained biases, evaluating a candidate’s true aptitude and acumen can be incredibly tricky.
The main question here is whether we can we systematically overcome these biases and psychological barriers. Yet before we talk about solutions, we first need a better understanding of the problem at hand.
The science behind human decision-making is a study in missed connections, lack of collaboration and avoidable biases. Based on approximately two million data points drawn from more than 500,000 video interviews, we discovered a troubling pattern: 45% of all candidate scores were affected by reviewer discrepancies by a margin of two or more points.
This disconnect suggests that candidates aren't being judged based on pre-established criteria. This may be the result of unconscious bias, or even a misunderstanding of the criteria itself. Either way, it's an indication that the process needs to be reassessed and possibly adjusted.
According to leading researchers and psychologists, humans simply aren’t effective at accurately judging the abilities of others. This holds particularly true in face-to-face interviews, as a higher level of intimacy between interviewer and interviewee only further clouds objectivity.
While most hiring professionals today know better than to rely solely on gut instinct or first impressions, unconscious bias can’t be eradicated quite so easily. As a result, says Behavioral Economist Iris Bohnet, it may be time to do away with the in-person interview altogether.
Bohnet notes that the long-presumed value of meeting with a candidate might be totally unfounded. She suggests that the practice is actually among “the worst predictors of actual on-the-job performance” and less reliable than even general aptitude or personality tests.
So if we can’t trust our instincts, what are we to do? We enhance them! Many believe the future of recruitment will involve “co-bots” — tech platforms that leverage a combination of machine learning and predictive analytics to effectively collaborate with human recruiters. When you consider the alternatives — continuing to press on with our biases firmly entrenched or being replaced altogether by robots — this imagined future sounds incredibly promising.
In this sunny marriage between human and machine, data is the tie that binds. By collecting information at every stage throughout the candidate journey, we can leverage machine learning algorithms to boost the objectivity and accuracy of our recruitment decisions.
Specifically, LaunchPad’s VERIFY platform addresses the issue of bias by 1) establishing a baseline measurement of candidate aptitude and fit; and 2) identifying biases as they manifest themselves. This in turn allows hiring managers to review potentially discriminatory processes and adjust accordingly.
Many of our deepest psychological barriers to objectivity may be unconscious and deeply ingrained, but by leveraging data-led insights provided by recruitment technology, we as an industry will move closer to objective hiring across the board.