Artificial intelligence amps up HR effectiveness

Could a robot do your job? Probably not, says futurist and HR consultant Josh Bersin. But software that uses artificial intelligence to facilitate decision-making will probably soon affect how you do your work.

“AI is the new form of automation,” Bersin says. Several HR-related AI software packages are making great leaps in automating the hiring and management process.

That worries some HR pros. In a survey by CareerBuilder last year, 35% of HR managers said the thought of AI makes them nervous, in part because it could threaten their jobs.

Bersin, head of Bersin Deloitte Consulting, says the anxiety is misplaced: “AI is creating jobs, not eliminating them.”

Some examples of how artificial intelligence is improving HR functions:

Tough Talks D

Recruiting: AI programs can read résumés, compare them to job descriptions and separate well-qualified applicants from online also-rans. It promises greater objectivity than managers can bring to the process. Some AI packages can identify prime candidates who haven’t even applied for a job.

Promotions: Deciding who to promote can be handled in the same dispassionate manner.

Retention: Several AI products promise to increase retention by analyzing employee emails to identify disgruntled staff or those who may benefit from more challenging tasks.

Discipline: Software can become a policy enforcement tool. It can track computer usage and report how much time an employee spends browsing social media or shopping.

Compliance: Can AI reduce bias? Federal and state laws make it illegal to discriminate on the basis of protected characteristics (age, race, sex, disability) in hiring, firing and promotions. In theory, letting software take the lead could minimize the chance for unlawful bias.

What could possibly go wrong?

First, it’s relatively new tech. Most AI algorithms are based on past experience, which may pull from a small sample size. Second, AI collects lots of data. Not every manager will know how to use it.

It’s a mistake to rely solely on algorithms to reduce hiring bias. For example, an outdated job description could cause AI programs to seek unqualified applicants.