Blind spots in recruiting
Dr. Chrysavgi Sklaveniti
4 min read
26 July 2022
How to fix blind spots in the recruiting process – and why it matters
“To ensure society’s well-being in the future, we may need to place limits on automation... We may even have to entertain an idea that’s come to be considered unthinkable, at least in business circles: give people precedence over machines” (Carr, 2015: 228).
Artificial intelligence (AI) has transformed the recruiting process with algorithms screening applications and filtering them according to predetermined criteria. Understandably, fuelling recruiting with AI brings on significant cost and time benefits. Does this result in optimal decision-making though?
While AI is impressive in scanning numerous applications in no time at all, it can bring recruiting specialists to fall into blind spots and miss out on candidates who would be ideal matches if selected with traditional human-driven processes. An international study by Harvard Business School and Accenture is revealing (2021: 22), 78% of the business leaders interviewed acknowledge that approximately half or more of middle-skilled candidates are filtered out of the recruiting process, while 80% of the interviewees noted that more than half of highly skilled candidates are left out in the same way. In this article, I zoom in on two key reasons causing blind spots and propose solutions to prevent them.
First, recruiting algorithms driven by AI cannot identify and evaluate personality cues included in applications. This idiosyncrasy is because they do not have the sensitivity or insight to read between the lines and understand the meaning behind the information presented to reach conclusions about an applicant’s suitability. Algorithms perform their screening and filtering tasks based on rules and patterns, which are however unable to assess information beyond the immediate context. As a result, they are not suitable for evaluating characteristics such as work ethic, creativity, or exposure to the task connected to the job profile.
Second, recruiting algorithms driven by AI cannot understand the work cultures an applicant has been exposed to. They cannot recognise whether an applicant has previously worked in a corporate environment, in an emerging start-up, or a non-profit organisation. However, this type of information is quite important when evaluating how prepared an applicant is for the work environment in the recruiting organisation or what work experiences accompany the applicant.
What do these blind spots furthermore signify? Their exposure is a blunt confrontation of the bias and discrimination employees deal with at the workplace. Herein lies a grand challenge. With Diversity, Equity, and Inclusion (DEI) being a top strategic priority, it is high time that companies develop appropriate responses on the one hand to help their recruiting avoid blind spots, and on the other, to ensure that all talent has access to employment opportunities. By adopting a recruiting approach focused on people, companies benefit from overall recruiting optimisation and increasing retention levels while propelling ethically towards the future (2021).
How can companies humanise their recruiting approaches? A hybrid approach that compliments AI with human intuition allows benefits from both worlds while ensuring that talent does not get lost. A necessary first step is to investigate which workforce segments tend to be filtered out of the recruiting. Herein, UBS includes a Career Comeback scheme into their recruitment to specifically ensure that applicants with career breaks are included. Another step is to make the values which are recognised as essential requirements visible and indicate how they are practiced in everyday work life. Towards the direction of visibility, Novartis puts forwards an Inspired, Curious, Unbossed culture and sees the people embodying these values as the drivers for transformative innovation. A final step is to turn to innovative channels which combine the simultaneous filtering of requirements with a humanised reading of an applicant’s profile. Such an innovation takes shape in CareerLunch which organises an informal connection between talent and employer, thereby empowering applicants and including proactiveness in the recruitment process.
In the introductory quote, Carr (2015) encourages us to re-think the limits on automation and give people precedence over machines towards societal well-being. Let us, then, be inspired by the examples described above and re-imagine recruiting approaches that carry companies forward into flourishing and human-centred workplaces.
Carr N. (2015) The Glass Cage: How Our Computers Are Changing Us: W. W. Norton & Company.
Fuller JB, Raman M, Sage-Gavin E and Hines K. (2021) Hidden Workers: Untapped Talent: How leaders can improve hiring practices to uncover missed talent pools, close skills gaps, and improve diversity. Harvard Business School.
Dr. Chrysavgi Sklaveniti is an organisational psychologist with expertise in people & organizational development and extensive experience in academic and applied projects. More information about her work can be found here.