Plum Co-Founder and CEO Caitlin MacGregor Breaks Down Top Strategies for Future-Proofing Your Talent Pipeline
This article was originally published in Inc.com
By the year 2034, 47% of today's jobs will be automated. 65% of today's students will be applying for jobs that don't exist yet.
After building two businesses and witnessing the repercussions of poor employee fit, I founded Plum, which automates advanced Industrial/Organizational Psychology (or, the psychology of work) to ensure companies hire, grow, and retain top talent. But as luck would have it, I became pregnant during fundraising, and my perspective on the potential impact of Plum shifted. Yes, Plum could find top talent for organizations today, but as my children enter the workforce and new jobs arise because of AI, Plum provides the ability to quantify human potential to find the right people to fill these new seats. In other words, predictive change on a massive scale - no musical chairs. As I've become increasingly invested in the future of work, here's what I've learned about preparing any organization for it.
Innovate (but learn from the past)
When IBM was founded in 1911, the company first sold scales and punch card tabulators. As we are on the precipice of a new economy, every company - including yours - will face the evolutionize-or-die moment that IBM had to navigate as they pivoted to offer software, consulting services, and IT services. Perhaps your company isn't making punch card tabulators, but you do need to set a course of innovating with a future of automation in mind - while also learning from past mistakes.
Although AI offers a level of scalability and efficiency to established hiring processes, the crux of AI is teaching machines to make decisions the same way humans would - which is often unpredictive and biased. Fortunately, while we've been continuing "gut feel" hiring processes, a global community of I/O Psychologists have dedicated decades of research to identify more predictive and objective hiring methods. Our current hiring habits are going to leave a lot of people without jobs in this new economy of automation; we have the opportunity to prepare for the future of work by marrying the advancements of I/O Psychology and AI technology.
Ditch the credentials list
Learning from the advancements of I/O Psychology means ditching that long list of requirements you post in your job ads, like a bachelor's degree or five years experience. Not only are education and past experience poor predictors of on-the-job success now, but the ever-transforming reality of the future of work is going to make a lot of degrees obsolete, and 5 years experience in one field will be nearly impossible.
We need to go beyond the resume and look at predictive indicators of employee success in new situations, such as cognitive ability, social intelligence, and personality. Focus on getting the right people in the right seats based on these indicators of adaptability, rather than getting stuck in your mindset of what the resume of an "ideal candidate" looks like.
Design for diversity
Not only are the credentials you'd find on a resume practically useless in predicting how a job candidate will perform in a new environment, resumes are ingrained with bias. Job applicants with names of Indian, Pakistani, or Chinese origin are 28% less likely to get an interview than applicants with traditionally Anglo names. Do we want AI to replicate these unconsciously biased conclusions?
We can automate processes designed for diversity. AI can be used to screen job descriptions for phrasing that isn't accessible to all applicants, or to automate assessments that pinpoint indicators of future success. The fear of the future of work is that there will be a talent shortage, but removing these barriers opens up your candidate pool to an influx of diverse and qualified talent.
If our infatuation with AI in HR only extends to automating established and familiar practices, then we aren't preparing for the future of work. If we're truly concerned with the status of our legacy, if we truly desire the best for our children in an unpredictable future economy, then we need to look outside our own limited concern with efficiency and understand how the affinity of AI and I/O can prepare us for the future of work.