By Alexandra Levit
Leaders are always concerned with securing the best talent, and attrition being what it is, this is not an issue that ever goes away. Just as they have improved our organizational cultures and the overall employee experience, 21st-century technologies now allow us to source, recruit and onboard candidates in more effective ways. And most importantly, they help us do it without falling prey to human frailties.
Unconscious bias means automatic attitudes about gender, age, race and so on that we are unaware we have and act upon. Some up-and-coming companies and technologies that are making hiring more of an exact science include the following:
Scoutible. While candidates play this adventure-themed video game, the system collects millions of data points used to measure a candidate’s various attributes, like problem-solving abilities and risk aversion. It then produces a numerical assessment of how likely he or she is to excel at the role in question. For certain roles, like salespeople and customer service representatives, Scoutible has established baseline metrics that can then be lightly tweaked from employer to employer. For positions with less established blueprints for success,
Scoutible works with the company to collect data from workers who have excelled in the same or similar roles
in the past. Scoutible’s current clients range from startups to large corporations, including tech companies, retailers and hedge fund managers. For one 101-person sales department, Scoutible’s game predicted job performance with 4.5 times the accuracy of traditional job interviews.
GapJumpers. GapJumpers tackles implicit bias – the prejudice we don’t realize we have – through an online blind-audition process. Applicants are given a job-related assignment – for example, web developers are asked to create a web page – and then hiring managers assess the completed task without seeing any personal identifiers, including name, gender, work experience or educational background. According to the Society for
Human Resource Management blog, GapJumpers and clients from organizations like the BBC and The Guardian have seen a 60 per cent jump in applicants from traditionally underrepresented groups who make it through to interviews compared to resume-based screening.
Textio. This company created an AI system currently used by Nvidia, CVS and Evernote that examines 40 million job listings and considers the outcomes: how many people applied, how long the job stayed open, the demographic groups the description did or didn’t attract. Based on the data, a predictive engine provides feedback on how likely a job description is to draw diverse candidates along with suggestions for how to phrase descriptions using more neutral language.
lSAP Success Factors. Success Factors identified nine key decision points where unconscious bias can affect managers’ thinking about hiring, promotions and other key points in the employee life cycle. The company used AI and machine learning to build nudges into its technology to make leaders more aware of their actions.
lADP. The global payroll company’s Pay Equity Explore service gives leaders tools to analyse employee compensation data and identify inequities. With more companies interested in supporting gender identity and LGBTQ support networks, ADP is testing a separate service on its own employees that identifies sexual orientation in advance of offering it to customers.
Unbias.io. Many studies have shown that we have biases based in names. Resumes and application materials labelled with typically male names like James are rated more highly than those with typically female names like Jane. Research has also uncovered significant discrimination against African-American sounding names: white sounding names receive 50 per cent more callbacks for interviews. Unbias.io, which is a Google Chrome extension, removes names and photos on LinkedIn,
in both standard and recruiter account searches and profile views, to help reduce the effects of unconscious bias.
Blendoor. Similarly, Blendoor captures candidate data from a company’s existing applicant tracking systems and/or online job boards. Candidate profiles are ‘blendorized’ – or displayed without name, photo or dates. Blendoor also collects EEO demographic data to enable talent pipeline analytics based on race, gender, LGBTQ, veteran and disabled identities and uncover bias as it’s happening in real time so that leaders can be held accountable. A number of high-profile tech companies including Apple and Intel are already using it.
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Alexandra Levit is a Business/Workplace Author, Speaker, Consultant, and Futurist. Follow her on Twitter @alevit