Some of the largest employers in the world are increasingly, and in some cases controversially, relying on AI-based technologies to hire new workers. Companies like Tesla, Accenture and LinkedIn are using technology from Pymetrics to better vet qualified candidates and reduce the time and resources required for what has traditionally been a labor-intensive hiring process. The company, which boasts more than 80 global clients, uses a blend of data science and I/O psychology to create its "people recommendation engine." The Pymetrics platform is designed to improve employee retention while also increasing efficiency and diversity throughout the recruiting process. The results are parsed by AI to generate measurements related to candidates' problem-solving skills, ability to multitask and even their levels of altruism.
Pymetrics today announced it has raised $40 million to expand its work using a combination of neuroscience and artificial intelligence to help companies recruit the right job candidates. The funding will allow Pymetrics to continue its product development and expansion in markets outside the United States. More than 60 companies use Pymetrics in their hiring practices today, including Unilever, Hyatt, and Accenture. In some instances, companies using Pymetrics have seen a 20 percent increase in the diversity of hires and a 65 percent increase in retention rates. The $40 million funding round was led by General Atlantic, with participation from Salesforce Ventures and Workday Ventures, as well as existing investors Jazz Venture Partners and Khosla Ventures.
Identify the traits of your top performing employees and hire people like them, but without the discrimanatory bias of traditional recruiting. That's the promise of Pymetrics, an artificial intelligence startup that today announced $8 million in new funding onstage at TechCrunch Disrupt SF. Pymetrics' goal is "making the world a fairer place" by dismantling hiring discrimination like sexism, racism, ageism and classism. Anyone can play the Pymetrics test games and get scored on different hireable traits, plus see suggestions for job types they'd be great at. You can watch my interview with Pymetrics' CEO Frida Polli below: A company's all-star employees play Pymetrics' set of games that assess things like memory, emotion detection, risk-taking, fairness and focus.
A growing number of tech companies are placing their bets on algorithms to reinvent talent acquisition and create a more inclusive workforce. In some cases, this might mean entirely removing traditional aspects of the hiring process. Introduced in the nineties, applicant tracking systems (ATS), were created to help HR professionals organize the surge of applications that resulted from the growing use of the internet. Over the last several decades, ATS became increasingly advanced, using algorithms to sift through thousands of resumes based on various data. The promise was efficiency and blind hiring, but the algorithms have proven to perpetuate structural inequities in hiring.
A recent survey found that 31% of new hires quit within their first six months on the job. According to the U.S. Bureau of Labor Statistics, during the last half of the year from April 2017 to April 2018 over two million people left their jobs each month -- for the first six months, it was over 3 million. All of this churning points to a major headache for businesses seeking to identify and hire the right people. The traditional paradigm of HR personnel digging through stacks of paper resumes clearly isn't working that well -- and there's nothing to suggest that digital resumes are any better. And this is more than a mere annoyance for companies: Filling open positions costs money and time that's lost when the wrong person is hired.