AI-based hiring tools: Pymetrics

19

September

2021

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By this time next year, most of you will have graduated from the master’s programme and made yourselves available on the job market. In this blog I want to shed some light on a gamified assessment called pymetrics games that you may possibly encounter during the assessment stage of a job application process.

For those of you who are not familiar with assessments or applying for jobs in general, the traditional job application process (as I have experienced it) generally looks something like Figure 1.

Figure 1. Traditional job application process (via Sierrasoln). Note: steps may vary depending on the type of job or sector.

The traditional (online) assessment stage will generally consist of:

  • ability tests measuring your performance when it comes deductive, numerical and logical reasoning;
  • personality test (questionnaire)

This is where Pymetrics comes in, a company that specialises in developing gamified assessments for recruitment purposes. Companies have opted to fully replace their aforementioned assessment stage with Pymetrics’ patented pymetric games. Some of the most notable companies being: Boston Consulting Group (BCG), JP Morgan, Accenture and Unilever.

What do these pymetric games entail?

The pymetric games are Pymetrics’ core product. It is an online gamified assessment in which candidates have to play through a series of 12 minigames that take two to three minutes each. The assessment uses neuroscience and AI in order to assess a broad range of 91 different cognitive traits. An example of one of the minigames is depicted in Figure 2.

Figure 2. Balloon minigame in which candidates can earn money with every balloon pump. Pumping too much will cause the balloon to explode and make you lose all your money for that respective balloon.

How does it work (in a nutshell)?

Pymetrics creates a custom algorithm for a company by having at least 50 top performers of said company play the pymetric games. Subsequently, this model is used as a benchmark when evaluating applicants’ results. Pymetrics markets its algorithm as entirely bias free, having succesfully subjected the algorithm to extensive AI audits in order to prove their claim.

So what’s the catch?

As my fellow peers Andrew Tan and Tamas Vincze have already explained in great detail: algorithms are inherently biased. In addition, an independent AI audit of Pymetrics’ algorithm found that although it passed the formal checks, the audit itself did not prove that the tool is bias free nor that it actually picks the most qualified candidates for a job.

This brings me to my question: how do you feel about an AI-based hiring assessment being put into practice? Would you much rather prefer the traditional online assessment? Having personally experienced both types of assessment, I am curious to see where my fellow peers stand, especially as you prepare yourselves for your job search.

References

Did this blog pique your interest? Please refer to the used sources below for more in-depth coverage on this topic:

  • https://www.technologyreview.com/2021/02/11/1017955/auditors-testing-ai-hiring-algorithms-bias-big-questions-remain/
  • https://digital.hbs.edu/platform-digit/submission/pymetrics-using-neuroscience-ai-to-change-the-age-old-hiring-process/
  • https://www.graduatesfirst.com/pymetrics
  • https://hackingthecaseinterview.thinkific.com/pages/bcg-pymetrics-test
  • https://www.jobtestprep.com/pymetrics-games#balloon-game
  • https://sierrasoln.com/hiring-process/


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