Business

Can AI Solve Your Hiring Problems?

In April, the number of job openings hit a record 9.3 million, according to data from the Labor Department. With the pandemic fading away, there has been a scramble to hire new employees and this has become a major challenge for companies.

So then can AI (Artificial Intelligence) help out? Well, it definitely can. The irony is that many companies are using the technology—and don’t even realize it! The reason is that AI is built into the top online job sites. 

“For example, when you type in a search for a job title, say with the phrase ‘job manager,’ the LinkedIn engine will not only look for the title itself, but also people with relevant skills like time management, team coordination, risk assessment and so on,” said Sakshi Jain, who is the Engineering Manager on LinkedIn’s Responsible AI team. “This means that a recruiter gets more results than just the people who already have the exact title or role.”

One of the key powers of AI is that it can detect complex patterns in huge data sets.  In a way, this can simulate the capabilities of a recruiter. And this is definitely important when it comes to finding passive job candidates. 

“In a study we recently published, 74% of talent leaders told us they’ve increased outreach to passive candidates in the past year,” said Hari Kolam, who is the CEO of Findem. “AI greatly speeds up the passive recruiting process–one where it can take upward of ten hours to fill a single role. It can index and surface information on people from hundreds of sources as passive candidates typically aren’t on job or career sites, and many people tend to only include piecemeal information on their LinkedIn and other profiles.”

AI can also help with personalization. This can be a good way to create a good first impression with candidates.

“Currently, there are many hiring workflows that are incredibly inefficient, including the scheduling of interviews and follow-up emails for candidates,” said Vivek Ravisankar, who is the CEO of HackerRank. “With the use of automated scheduling and email follow-ups, AI can help free up valuable time and solve the major pain point of extensive back-and-forth coordination with candidates and interviewers.”

Yet AI is not without its risks. After all, there is inherent bias in datasets and this can result in outcomes that are unfair and discriminatory. 

“AI-driven HR software that is using years old data on previous hires to determine ideal candidates for job openings is a perfect example of where algorithms can go wrong,” said Ingrid Burton, who is the Chief Marketing Officer at Quantcast. “This is especially true in roles that have historically been dominated by men, such as software engineers, which would risk the hiring algorithm to arbitrarily exclude most women and minorities from advancing during the hiring process.”

To guard against this, there must be good governance as well as explainability of the AI models. There also needs to be people in the loop for critical parts of the process. 

“It is never acceptable to set up an AI process and simply leave it to run,” said Ian Cook, who is the Vice President of People Analytics at Visier. “While there is no need to inspect every transaction or process run by the AI, there is a need to constantly review the performance of the AI steps to ensure that the outputs are in line with expectations. Validation, updating and retraining are constant requirements of running any AI process.”

Tom (@ttaulli) is an advisor/board member to startups and the author of Artificial Intelligence Basics: A Non-Technical Introduction, The Robotic Process Automation Handbook: A Guide to Implementing RPA Systems and Implementing AI Systems: Transform Your Business in 6 Steps. He also has developed various online courses, such as for the COBOL and Python programming languages.



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