WORKFORCE DEVELOPMENT
Using Neuroscience and AI to Match Candidates to Careers
By Sarah Lai Stirland F
rida Polli, a neuroscientist and en- trepreneur, disputes the idea that there’s a shortage of talent in tight
labor markets: Recruiters simply aren’t looking in the right places often because of their innate biases and habits, she said. That’s a foundational thesis for her re-
cruiting startup Pymetrics in New York City. Polli and co-founder Julie Yoo have created a company that aims to both broaden the talent and labor pool for employers at the same time as making the search process quicker and more cost-effi cient. They start- ed the company in 2013 after having met as postdoctoral fellows at MIT, both studying brain imaging. The idea came to Polli when she was studying for an MBA at Harvard Business School. There, she saw friends and fellow MBA students land coveted intern- ships and jobs—only to discover later on that they weren’t suited for the roles. That’s when she saw an opportunity to apply her background in neuroscience to the recruit- ing process.
How it works Pymetrics changes and refi nes the criteria used to search for initial round candidates. Instead of fi ltering this round of job appli- cants using resumes containing information about universities attended and work expe- rience, hiring managers would use Pymet- rics’ cognitive and emotional assessments emerging from the 12 online games that those initial applicants play. The games, designed by neuroscientists, don’t measure IQ. They examine candidates’ thought pro- cesses. They assess aspects of candidates’ personalities, such as how they read some- one else’s emotions, tendency to learn from a situation, short-term memory, impulsivity, and strategic thinking, among other things.
38 SENIOR LIVING EXECUTIVE MARCH/APRIL 2018 In all, Pymetrics assesses 78 traits. Com-
panies can use these assessments to decide whether to move forward in the interview process with the candidates, and which roles they would likely best serve. Pymetrics asks companies using its product to require its top 100-performing staff ers for each role that they’re hiring for to participate in the games. This allows its algorithms to learn which personality attributes the hiring com- panies most value. (Pymetrics’ internal staff audit its algorithms to ensure that they’re not biased in any one direction.)
Creating a Netfl ix for recruiting In eff ect, Pymetrics wants to act as a kind of Netfl ix for recruiters by using artifi cial intelligence to sort through large numbers of candidates. “We’re at the Blockbuster stage [of
recruiting],” said Polli at the World’s Fair Nano, a technology and arts fair that took place this March in San Francisco. “We need to move to the Netfl ix stage, where the system knows you better than you know yourself.” At the same time, the idea behind Py-
metrics’ approach is that a semantically blind initial search will surface candidates that humans might not initially consider for a position because of unintentional innate biases. “We need to think of technology as an
unbiasing tool,” Polli said at another talk in 2016 in New York City. “How it may or may not be used today may be perpetuat- ing some of the bias that already exists in the system.”
Change Agent Profi le
Frida Polli CEO and Co-founder Pymetrics
A case study in success Pymetrics’ clients include Accenture, LinkedIn, Unilever, and Tesla, among more than four dozen others. The startup points to Unilever as a case study in success: Pymetrics helped Unilever assess 280,000 applicants in 68 countries in 15 languages. A 2017 Wall Street Journal profi le shared a template for how the process worked: A candidate for a position in information technology at Unilever had gone through two rounds of video interviews and assessments and had fi nally landed an in-person interview because the algorithms had recommended her. The article said that at that time, Unilever had hired some 450 people this way. The company said that 80 percent of the applicants in the fi nal round of interviews received job off ers, and that the process had reduced its recruiting costs. Pymetrics isn’t the fi rst to use technology
to upend the way companies recruit can- didates, but Polli’s company distinguishes itself from the current crop of emerging technology companies with its grounding in, and application of neuroscience, artifi cial intelligence, and algorithm auditing.
For more information on how the system works, reports on its work, and the system’s compliance with various laws, visit
pymetrics.com.
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