How Pymetrics is using AI and Neuroscience to change the hiring process?<\/strong><\/h3>\n\n- \n
Gamified Neuroscience –<\/p>\n<\/li>\n<\/ol>\n
Pymetrics developed games based on years of well-established neuroscience research. They have a set of 12 neuroscience mini-games that take less than half an hour to measure 90 cognitive, social and emotional traits of candidates. While many traits are said to be acquired while on the job, Pymetric focuses on measuring the intrinsic traits that do not change over time.<\/p>\n
Some of the games are filling animated balloons with water without them bursting, clicking the space bar every time a green dot appears and weighing how much money to trade with an imaginary partner ina scenario akin to the prisoner\u2019s dilemma. There are no victories in this game, but rather they serve to measure the candidate\u2019s various behavioral traits to help map them to the best-fit job. ![](\"https:\/\/lh3.googleusercontent.com\/7wt_kmsVmLK9UAQ7P5SzTOBEVLGq-lQseRvO7vFUfg8HEP4oBHFuSbinw8DrcrFHgKpcX6qQySIW0LPHHtaDbO8tmJfLiBKiayzOBZh8wLUyTkbb67aRvDz5gJgI1vCOYrZnjeyS\")
<\/p>\n
Pymetric Game #1<\/em><\/p>\nWhen the multi-trait games are over, candidates receive a report which will let them know pymetrics’ evaluation of 90 different traits including –\u00a0 attention duration, processing consistency, flexibility, creativity, decision making, learning from mistakes and more. ![](\"https:\/\/lh5.googleusercontent.com\/QqxQoUNPmBzensgtv8X0az7K5zy8_PRyFYDszALjjk_ahM30_l3nwMeVG9to61owQhUvc6BGdmtjvMoPspTeb5wsmZvMACDnhci4nicE0ADC7PgTZCg50gaXzIvttXtrAngVEY-S\")
<\/p>\n
Pymetric Game #2<\/em><\/p>\n\n- \n
Custom AI Trained Model on Top Performers –<\/p>\n<\/li>\n<\/ol>\n
Pymetrics makes custom algorithms for companies by running their mini-games on at least 50 of the organization\u2019s top performers. It then uses this model to compare and find applicants with similar traits. Job seekers play different games when applying for a job and a matching algorithm is used to select the one which would be the best fit for the role or have similar skills as the top performers at the company. This model has been mostly employed by companies to recruit for standard entry and midlevel corporate positions.<\/p>\n
![](\"https:\/\/lh3.googleusercontent.com\/ghnlfdfOIyqqLu5yqFAQmw9wbhjsznhk1WuweOWsmnbarqjn7dAHp5vItdhuoG1IU9htUHjQKDVECEwn68hs_C8akzB-rj28vulPU6D4KXsWBhQe6eDH3gXpyGhtamdTvA6tp5P2\")
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Ethical AI: De-Biased Algorithms –<\/p>\n<\/li>\n<\/ol>\n
Resume reviews lead to women and minorities being at a 50-60% disadvantage. [2]. Pymetrics works to create a more ethical AI-enable de-biased algorithm. The games played by the candidates are conducted in the form of a blind audition for job candidates. Candidates move through the platform anonymously, and the prediction algorithm does not use any demographic information to assess career fit. With AI that doesn\u2019t see race or sex, underlying skills specific to the job can shine through. Before any algorithm is deployed, pymetrics checks each algorithm and removes any bias through their open-sourced algorithm auditing tool, Audit-AI<\/a>.<\/p>\nEmploying statistical methods to actively de-bias the dataset and validate the method, on which the predictive models lie, is imperative to ensure the selection procedure is promoting fairness rather than perpetuating barriers. Only then is the final result of a bias-free prediction model that recommends future best performers.<\/p>\n
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Saves resources spent on recruiting –<\/p>\n<\/li>\n<\/ol>\n
Recruiters typically spend an average of six seconds on a resume; often arbitrarily cutting many candidates out of this phase. Pymetrics can help companies to screen candidates in a more systematic way based on matching skills required for the job using their games, rather than traditional CV, cover letters and self-reported questionnaires. Recruiters can spend time on outreach to improve their candidate pool, rather than haphazard resume-scanning.<\/p>\n
It uses a software-as-a-service model, and charges based on the number of applicants a company receives each year.<\/p>\n
Results of these shifts:<\/h3>\n
Pymetrics has managed to become a part of the hiring process for many high-profile companies like Unilever, LinkedIn, and Accenture to name a few. Polli says that some companies have more than doubled the percentage of candidates they hire out of those they invite for in-person interviews. She also noted that the platform also has helped companies increase their diversity. She says Pymetric’s algorithms constantly test for and remove ethnic or gender biases that arise, leading to more women and minority hires. It also helps companies expand their scope beyond just those who can afford expensive college educations. [3]<\/p>\n
Challenges and future:<\/h3>\n
Pymetric has adopted an interesting model of using games to collect large sets of data about candidates. Despite, it having a large set of high-profile clients there are some challenges which it might face in the future:<\/p>\n
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Most companies would still have an interview process after the shortlist using pymetric where human judgment would be used, cause biases to play out. Polli agrees with this point – \u201cWe offer another data point that’s free of bias and subjectivity, and hopefully people will trust it as an objective data point.” [4]<\/p>\n<\/li>\n
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The algorithm developed would need to be job-specific for companies to hire for a specific role. Where do you keep getting data sets of high-performance candidates?<\/p>\n<\/li>\n
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It is difficult to have a de-biased dataset. Datasets usually replicate a company\u2019s existing setup and they have some form of bias.<\/p>\n<\/li>\n
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Would the usage of pymetrics cause the diversity of ideas to decrease due to the skill set and personality traits of employees hired being similar?<\/p>\n<\/li>\n
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People might start gaming the system, by developing, playing and practicing such games to get a higher score on the traits required for the job role they want.<\/p>\n<\/li>\n<\/ol>\n
Pymetrics has $17 million in funding from VC firms including Khosla Ventures and Jazz Venture Partners. The startup has about 70 employees based in New York, London, and Singapore. [5]<\/p>\n
They have decided to tackle a problem where there is friction but only time will tell if they will be able to deliver all that they promise.<\/p>\n
References:<\/p>\n
[1] https:\/\/www.pymetrics.com\/<\/a><\/p>\n[2] Ibis<\/p>\n
[3] https:\/\/www.inc.com\/kevin-j-ryan\/pymetrics-replacing-resumes-with-brain-games.html<\/a><\/p>\n[4] https:\/\/www.inc.com\/jeremy-quittner\/neuroscience-brain-personality-tests-recruiting.html<\/a><\/p>\n[5] https:\/\/www.inc.com\/kevin-j-ryan\/pymetrics-replacing-resumes-with-brain-games.html<\/a><\/p>\n
Gamified Neuroscience –<\/p>\n<\/li>\n<\/ol>\n
Pymetrics developed games based on years of well-established neuroscience research. They have a set of 12 neuroscience mini-games that take less than half an hour to measure 90 cognitive, social and emotional traits of candidates. While many traits are said to be acquired while on the job, Pymetric focuses on measuring the intrinsic traits that do not change over time.<\/p>\n
Some of the games are filling animated balloons with water without them bursting, clicking the space bar every time a green dot appears and weighing how much money to trade with an imaginary partner ina scenario akin to the prisoner\u2019s dilemma. There are no victories in this game, but rather they serve to measure the candidate\u2019s various behavioral traits to help map them to the best-fit job.
Pymetric Game #1<\/em><\/p>\n When the multi-trait games are over, candidates receive a report which will let them know pymetrics’ evaluation of 90 different traits including –\u00a0 attention duration, processing consistency, flexibility, creativity, decision making, learning from mistakes and more. Pymetric Game #2<\/em><\/p>\n Custom AI Trained Model on Top Performers –<\/p>\n<\/li>\n<\/ol>\n Pymetrics makes custom algorithms for companies by running their mini-games on at least 50 of the organization\u2019s top performers. It then uses this model to compare and find applicants with similar traits. Job seekers play different games when applying for a job and a matching algorithm is used to select the one which would be the best fit for the role or have similar skills as the top performers at the company. This model has been mostly employed by companies to recruit for standard entry and midlevel corporate positions.<\/p>\n Ethical AI: De-Biased Algorithms –<\/p>\n<\/li>\n<\/ol>\n Resume reviews lead to women and minorities being at a 50-60% disadvantage. [2]. Pymetrics works to create a more ethical AI-enable de-biased algorithm. The games played by the candidates are conducted in the form of a blind audition for job candidates. Candidates move through the platform anonymously, and the prediction algorithm does not use any demographic information to assess career fit. With AI that doesn\u2019t see race or sex, underlying skills specific to the job can shine through. Before any algorithm is deployed, pymetrics checks each algorithm and removes any bias through their open-sourced algorithm auditing tool, Audit-AI<\/a>.<\/p>\n Employing statistical methods to actively de-bias the dataset and validate the method, on which the predictive models lie, is imperative to ensure the selection procedure is promoting fairness rather than perpetuating barriers. Only then is the final result of a bias-free prediction model that recommends future best performers.<\/p>\n Saves resources spent on recruiting –<\/p>\n<\/li>\n<\/ol>\n Recruiters typically spend an average of six seconds on a resume; often arbitrarily cutting many candidates out of this phase. Pymetrics can help companies to screen candidates in a more systematic way based on matching skills required for the job using their games, rather than traditional CV, cover letters and self-reported questionnaires. Recruiters can spend time on outreach to improve their candidate pool, rather than haphazard resume-scanning.<\/p>\n It uses a software-as-a-service model, and charges based on the number of applicants a company receives each year.<\/p>\n Pymetrics has managed to become a part of the hiring process for many high-profile companies like Unilever, LinkedIn, and Accenture to name a few. Polli says that some companies have more than doubled the percentage of candidates they hire out of those they invite for in-person interviews. She also noted that the platform also has helped companies increase their diversity. She says Pymetric’s algorithms constantly test for and remove ethnic or gender biases that arise, leading to more women and minority hires. It also helps companies expand their scope beyond just those who can afford expensive college educations. [3]<\/p>\n Pymetric has adopted an interesting model of using games to collect large sets of data about candidates. Despite, it having a large set of high-profile clients there are some challenges which it might face in the future:<\/p>\n Most companies would still have an interview process after the shortlist using pymetric where human judgment would be used, cause biases to play out. Polli agrees with this point – \u201cWe offer another data point that’s free of bias and subjectivity, and hopefully people will trust it as an objective data point.” [4]<\/p>\n<\/li>\n The algorithm developed would need to be job-specific for companies to hire for a specific role. Where do you keep getting data sets of high-performance candidates?<\/p>\n<\/li>\n It is difficult to have a de-biased dataset. Datasets usually replicate a company\u2019s existing setup and they have some form of bias.<\/p>\n<\/li>\n Would the usage of pymetrics cause the diversity of ideas to decrease due to the skill set and personality traits of employees hired being similar?<\/p>\n<\/li>\n People might start gaming the system, by developing, playing and practicing such games to get a higher score on the traits required for the job role they want.<\/p>\n<\/li>\n<\/ol>\n Pymetrics has $17 million in funding from VC firms including Khosla Ventures and Jazz Venture Partners. The startup has about 70 employees based in New York, London, and Singapore. [5]<\/p>\n They have decided to tackle a problem where there is friction but only time will tell if they will be able to deliver all that they promise.<\/p>\n References:<\/p>\n [1] https:\/\/www.pymetrics.com\/<\/a><\/p>\n [2] Ibis<\/p>\n [3] https:\/\/www.inc.com\/kevin-j-ryan\/pymetrics-replacing-resumes-with-brain-games.html<\/a><\/p>\n [4] https:\/\/www.inc.com\/jeremy-quittner\/neuroscience-brain-personality-tests-recruiting.html<\/a><\/p>\n [5] https:\/\/www.inc.com\/kevin-j-ryan\/pymetrics-replacing-resumes-with-brain-games.html<\/a><\/p>\n\n
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Results of these shifts:<\/h3>\n
Challenges and future:<\/h3>\n
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