Meet ‘Tengai,’ the job interview robot who won’t judge you, read the headline of a recent Business Story on the BBC. I read it again… it just didn’t sound right! The usage of ‘who’ instead of ‘that’ seemed to be a typo. With ‘Who’ typically used to denote people and not objects…did BBC just elevate Bots to Human status?? Yes, I may be nitpicking on a typo, but I guess I am resisting the imagery of a bot that can judge me but has chosen not to! Tengai promises interviews without bias, and any technology that claims a bias-free outcome leaves me wondering if they are overrated or just a classic half-truth!

The Pet Peeve

‘Hiring Bias’ has been HR Tech’s pet peeve for a while now. Interviewers have labeled the problem child with a huge, incurable bias. Bot builders swear by the interviewer’s inability to carry out ‘unbiased’ hiring. With all fingers pointing at the problem child, the popular fix to eliminate bias seems to be to eliminate the interviewer! If not a complete elimination, the attempt is to at least distance the interviewer far enough from the interviewee to reduce the bias!

To HR Tech’s excitement, Gartner’s recommendation to neutralize Hiring Bias was more “HCM Technology.” The report summarised that organizations should establish data-driven decision-making to mitigate the effect of bias. In short, it said throw more Technology and kill the Bias! After all, hasn’t Technology often turned up as the magical stone to kill the complicated bird?

Ok…Let’s Engineer it!

Can’t deny the strange fact that fixing the Hiring Bias is now approached as a technology challenge rather than an HR challenge. And don’t techies love challenges that are technically not theirs? They’ve jumped neck-deep en masse, and two large schools of Engineering have emerged with contrasting philosophies to fix the Bias:

• One that proposes to replace the human element with data-neutral Robotic Process Automation. This school produces tools and bots that (claim to) do everything from writing bias-free JDs to triggering bias-free Welcome emails!
• The second stream proposes to anonymize hiring data to remove bias-inducing identifiers. This school churns out solutions that ‘neutralize’ hiring data at each stage of the process. From sourcing to screening to interviewing and selection, their tools just ride on anonymous recruitment.

Both schools have created a massive lineup with the likes of Debra, Mya, Olivia, Ari, and a bunch of bots to make recruitment bias-free in their own ways. Well, don’t ask me about the gender bias in naming Bots!

Oops! Stalemate?

While both Schools remain convinced of their capabilities, there are blatant exposés of their Achilles’ heels. There are high-stakes use cases and scenarios emerging that they just can’t seem to tame.

• Amazon shut down its secret AI Recruiting Tool, as it showed bias against women, and they couldn’t help it unlearn the Gender Bias.
• 65% of recruiters in a study declared that it is a struggle to recruit meaningfully with anonymized resumes.
• A HBR study revealed that minorities who “whitened” their résumés, by removing racial cues, got more interview callbacks than those who did not.

With failing Bots, resisting Recruiters, and candidate-manipulated data, engineering a pure-tech remedy to hiring bias seems to be stepping into a stalemate.

Divide and Rule!

Every touchpoint between an interviewer and a candidate or a candidate’s data has been marked as a potential spot for unconscious bias. The seemingly sure-shot (a.k.a short-sighted) fix is to distance the stakeholders. Introducing buffer layers between stakeholders helps moderate the exchanges and dilutes the bias. A huge arsenal of tools has hence been built on this Divide and Rule principle. There are options for every step in the recruitment workflow to either be tech-assisted or tech-validated or directly executed by a bot.

Tengai, for example, denies a direct connection between the interviewer and the candidate. It interviews the candidates, records their responses, and converts them into text. The anonymized text transcript is what the recruiter gets to review and make the selection choices. That’s a quintessential Divide and Rule in action!

Time for a Pause

All said it would be archaic to cry foul for everything in this space. Technological advancements are non-negotiable and no doubt keep us moving ahead with our efficiency. However, not maintaining a balance between human and artificial capabilities is a concern. Specific to recruitment, solutions seeking to automate entirely may have to slow down. Touting them as replacements for high-cognitive human tasks will have to be carefully reviewed. Putting interviewers on standby while technology does the work is bound to backfire in the long term.

Technology as a sole remedy for Hiring Bias is just another case of solving the symptoms and not the cause. If Hiring Bias is real, it’s time that the humanities, social sciences, behavioral, and management sciences took the lead on this.

After all, can we move humans out of human interactions?