Humanizing Hiring with Technology? Yep, That Works.
Part Five of Our "Talent and the Future of Work" Series.
If you imagine artificial intelligence to be as coldly neutral as HAL in 2001: A Space Odyssey — “I’m sorry Dave, I’m afraid I can’t do that” — then you might stumble over the idea of using AI technology to humanize hiring.
To realize AI’s full purpose in talent acquisition and human resource practices, it’s essential to identify the difference between automation — artificial intelligence making current practices (which are often biased and unpredictive) more efficient and automatic — and augmentation, i.e. “helping humans do countless complex tasks that are either beyond human cognition and/or inefficient for human beings to do.” In other words, AI that’s smarter. AI that utilizes augmentation over automation is often referred to as Expert Automation & Augmentation Software (EAAS).
This blog recently suggested AI needs to be used for more than simply streamlining processes. By “proceeding with care,” professionals can actually add a human element to talent acquisition and hiring practices and strategic workforce planning.
But when we used the word “care,” we didn’t mean gently. Instead, genuine attention should be paid to the lessons you’re teaching the machines sifting through the data or the AI making decisions. If these are trained to make choices in the same way humans would — i.e., automation — this simply perpetuates a flawed system. It’s up to talent and HR professionals to augment the AI software with their expertise, drawing from lessons already learned to check validity and try to remove risk by considering in detail how algorithms are structured or the data input is classified.
61% of CEOs do not believe they are recruiting fast enough, and the process has become enormously complex.
Augmenting with I/O Psychology
To truly gain AI’s advantages, look to also incorporate the hard work of the global community of Industrial/Organizational Psychologists. Scientists at the likes of Harvard, Northwestern, MIT and Columbia, have dedicated decades of research to identifying more predictive and objective hiring methods. Today, the work of I/O psychologists help organizations glean valuable information from big data based on knowing the questions to ask, best ways to analyze data, and how to interpret results to inform important decisions.
This can take the practice of, for instance, automated resume scanning — which can’t distinguish truth from fiction, perpetuates racial bias, and doesn’t predict on-the-job performance — up a notch. Marrying the advancements of I/O Psychology and augmented AI technology helps prepare for the future of work by focusing on core traits that are transferable to the new jobs on the horizon. This is looking beyond the hiring stage to find process value that will translate to long-term success in strategic workforce planning.
While the move to chatbots and video interview facial screens represents adoption of AI for efficiency, augmenting AI tools with I/O psychometrics offers both efficiency and predictability. Instead of automating human faults into the hiring process, an enlightened AI approach works better, not just faster.
Plum’s talent platform matches potential employees based on 10 different core talents. Rather than focusing on skills and educational background, which don’t actually predict that candidate’s ability to innovate or be an agile problem solver who communicates effectively, Plum’s assessments focus on bringing candidates into an organization for the right job. With an augmented AI, based in I/O, focusing on talents, the HR and TA professional can better identify growth opportunities and see possible paths to advance and retain employees for long-term success.
The Human Touch Remains Essential
Note that augmented AI doesn’t automate you out of a job. Ultimately, the human touch is necessary for augmented AI to succeed. Machine learning that incorporates human oversight (called human-in-the-loop machine learning) is the best way to avoid “black box” AI that makes decisions without a traceable explanation or reasoning. Bring a diverse group of business stakeholders together to determine AI objectives and outcomes. This can help program an AI algorithm to ask the right questions and make the best judgement calls and decisions, which pays off in more nuanced insights.
Machine learning needs to complement rather than replace human expertise. HR and TA professionals know their stuff; machine learning can’t do all the thinking for them. As a CA Technologies blogger noted, “While machine-driven decisions may be right 80% of the time, the (sometimes disastrous) consequences of being wrong 20% of the time wipe out the productivity gains.”
Simply incorporating AI automation risks turning human resources into a process-driven machine that manages people as a binary batch to be shifted from one process or department to another. With the right augmented AI tools in place, hiring and talent professionals can get to better know candidates and employees and offer more personalized attention to each unique human in the company.
Next, we’ll go deeper into the ways in which AI can develop talent pipelines that are dynamic, reactive, and identify great candidates for today and tomorrow. With augmented AI you can build on your great talent acquisition practices to do smarter strategic workforce planning too.