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How To Balance AI With Decision-making In HR

Some artificial intelligence (AI) tech companies would have you believe that you no longer need to make any decision after purchasing their product—let the AI run and figure everything out for you; take the decision out of decision-making and out of human hands. That doesn’t sit well with most people; after all, the sum total of the HR manager’s knowledge is important to any company. The fears that technology can replace the HR team arise from the rapid change over the last decade in available AI-assisted platforms. But the key when dealing with AI technology is to create an appropriate balance between AI and your team’s decision-makers.

What Is Decision-Making?

The language we use to discuss AI serves us well to understand its power as similar to human intelligence, but can often be misleading when we consider necessary human qualities important to decision-making—like judgment. We, as humans, value the “gut-check” decision, the decision that feels right based on all the given information; we often “read” people and may make the best hiring decision based on the interview. When HR managers engage in “decision-making,” they assemble facts or differing opinions and ultimately use their experience, knowledge, and judgment to make a decision. Decision-making in AI operates on a similar model. Rather than possessing experience, AI may factor in historical data points to assess the effectiveness of a decision. Rather than considering differing opinions, AI may calculate the various scenarios and “predict” the best outcome based on data.

Decision-making in AI works best when the technology has more data to collect when it “learns” to change course given new data. But it’s important for HR teams to discover where AI technology can best assist them in the hiring process. After all, AI is a program. Someone needs to tell the program what to do. The overarching decision-making of long-term goal setting and strategy, and where to apply AI technology, lies squarely in the hands of top decision-makers in your organization.

Combining Lots Of Data With A Final Human Touch

Remember, AI works best with lots of data. Let’s look for example at resume screening. If you have ten applicants for an open position, your AI platform could narrow the field down to one final candidate by making connections between applicant resumes cross-checked with the job description and requirements. It can ultimately make an assessment of the best choice based on the facts. But there’s not a lot of data to read in this example. The decision on who to hire out of ten applicants is best left to a member of the HR team.

We have to think bigger and on a scale of an excess of information. AI can read all the information of successful hires at a company and assess which candidate is most likely to replicate that pattern of success—or AI can look at data from thousands of companies within a particular industry to make a prediction on the most successful candidate.

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The use of AI tech is best applied when you have a lot of information. AI will be able to read one thousand applications and assess the best candidates by narrowing the field down to ten in a fraction of time it takes the HR team to do the same busywork. That kind of decision-making, based on data, is a smart use of AI technology. When it comes to the final decision of who to hire among top-tier candidates (in a smaller data set of ten applicants), this important decision-making is best left to the HR team.

Ad Posting Can Lead You To The Best Candidates

Another key area where AI can assist the HR team is in navigating the vast digital landscape of job advertising: where to post, how to post, how long to keep an ad going, how much spending a particular ad needs based on the over job ad budget. All of these factors that we consider “decision-making” that helps garner top-quality candidates comes down to numbers: cost, page clicks, and the number of applications necessary to collect in order to get a top-quality hire. All of these factors are digital and can, therefore, be read and assessed with AI technology.

Platforms that measure job ad performance in real-time can help the HR team create a smarter budget allocation and get better quality candidates more quickly. There is no “gut check” decision about which website is the best place to post an ad. Navigating the excess of data when it comes to ad posting and reaching the top tier candidates is best left to AI technology.

The Bottom Line

There are other key areas where AI can help assist the HR team, like reducing unconscious bias in resume screening. But AI can also replicate biased decision-making by following a pattern of hiring at a company that has engaged in unconscious bias. Ultimately, it is most important for decision-makers in your organization to assess the use of AI technology, set the long-term strategies and goals, and learn the best applications of AI for your organization. Sometimes there are “gut” decisions; sometimes it has to be based on the numbers. The key is for the HR team to understand the capabilities of their technology and when to steer the course of their decision-making in concert with the data.

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