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April 14, 2017

AI Moves Deeper Into HR

Among the emerging uses of artificial intelligence is the processing and interpretation of large volumes of data in order to spot patterns. Machine learning tools are surfacing to automate time-consuming business processes, in theory freeing users to connect the dots and make better decisions.

The latest AI application is a recruiting tool designed to make the hiring process more efficient and transparent, with the laudable goal of “creating deeper human connections.” On a more practical level, the tool addresses the concerns of a recent survey of human resources specialists that found 52 percent saying the hardest part of recruitment is identifying the right candidate from a large pool of applicants.

With those issues in mind, San Francisco-based SmartRecruiters this week unveiled a new recruiting tool that applies data science techniques to detect patterns related to applicants’ work experience to quickly weed out unqualified candidates and come up with a short list of prospects.

The “Recuiting AI” platform applies machine-learning technologies to spot, screen and ranked applicants with the goal of speeding a hiring process that has become a time sink. “Tens of thousands of recruiters worldwide miss out on great hires because they’re overwhelmed with manual tasks that could easily be automated through AI technologies,” SmartRecruiters’ Kristopher Osborne noted in a statement.

The AI-based recruiting software also is billed as a replacement for first-generation applicant tracking systems, the company noted.

The goal is to use machine learning to score candidates so employers can spend less time shuffling job applications and more time “interacting with candidates and colleagues to make better decisions,” Osborne added.

Along with analyzing résumés and ranking candidates based on both “hard” and “soft” skills that match the job description, a “smart feedback loop” feature is designed to help recruiters match the emerging candidates and their particular skill sets to the appropriate position. That feature also includes the ability to screen internal candidates as a way of promoting employee development and retention.

Such capabilities could prove useful in areas such as data science, where companies are scrambling to fill vacant positions.

The Recruiting AI tool also seeks to address the sticky issue of employer bias, SmartRecruiters noted. “While recruiters may be biased, usually unintentionally, artificial intelligence is not,” the company asserts. It further argues that the use of predictive analytics provides an unbiased assessment of the best candidates for a specific job while boosting workplace diversity.

Predictive analytics has been used with mixed results in related areas such as college recruiting. Several U.S. universities have used these emerging tools to spot students with a higher risk of dropping out. Others employed analytics to identify students on the bubble and encouraged them to drop out—thereby boosting a university’s retention rate.

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