How Hiring Algorithms Are Used in Background Checks

Everywhere you look, people are talking about AI and algorithms. Whether it’s new apps that can “predict” changes in the stock market or innovative medical technology that seeks to incorporate AI into cancer screenings, there appears to be little that it can’t do. 

Yet, one area we are tiptoeing gingerly around is using AI and algorithms during the hiring process, particularly to conduct background checks. It sounds like a great idea, but several potentially major drawbacks have appeared in recent years. Is this the future? Or are we pushing too far hard for the technology we have right now?

How Do AI Hiring Algorithms Work?

Hiring managers can incorporate AI into various stages during the hiring process, but to understand how it works, it helps to understand what AI is.

Artificial intelligence describes any ability of a machine to perform the cognitive functions typically associated with human beings. It includes reasoning, task performance, synthesis, and more.

We’re not yet to the point where machines do all the work of selecting candidates and extending job offers, but machine learning is part of the screening and recruitment process. AI can tweak job advertisements to appeal to as broad a reach of quality candidates as possible and match ads to the right kind of people. 

Screening potential candidates can be time-consuming, but AI can do it in a fraction of the time. It can check qualifications, work history, past employment patterns, and experience in minutes.

Interviews are generally where most hiring decisions occur, and AI algorithms might have a relatively limited input right now. However, it can be useful for facial recognition and sentiment analytics. During the selection process, AI can help recruiters conduct background checks and quickly scan public and private records to confirm the information given and search for inconsistencies.

What Are the Benefits of Hiring Algorithms?

There are plenty of positives that explain how this technology is quickly becoming standard practice.

Quickly Find Applicants Who Stand Out

As mentioned above, hiring algorithms can ensure that the right advertisement is visible to the right type of candidate for the job. 

While traditional job advertising can be hit-and-miss, AI makes the process significantly more targeted. As a result, the applications you’re looking for come in much faster. 

Increased Intelligence 

As the saying goes, a machine is only as intelligent as its creator. AI may never compete fully with the human brain, in part because its limitations are for the specific tasks it is programmed to do. 

However, artificial intelligence comes with massive processing power with which humans can’t compare. It can make split-second yes or no decisions in a fraction of the time a human could. 

That can only be positive for recruiters since machines can enhance intelligence in the selection and screening process. 

Removes the Subjective Bias

Subjective bias is a topic that concerns all employers, and the objectivity of AI is one of the reasons it has become so popular in recruitment. At least in theory, algorithms should be able to reduce recruitment bias from the early stages of the process. 

AI doesn’t care or even know about race, ethnicity, or gender, meaning it will focus only on the points relating to the candidate’s employment prospects.

Increases Efficiency 

Hiring can be a slow, tedious process that can drag on for months if you’re determined to find the right person. Using algorithms can dramatically reduce that time.

Algorithms can work through the screening steps much faster than any human—or even team of humans—could ever hope to achieve. Increased efficiency leads to an excellent return on investment and boosted productivity levels for human workers. 

Fast Response Times

With AI significantly speeding up the initial screening stage, candidates can get faster updates about whether they’ve progressed to the next step. There’s nothing worse than putting together a great application and waiting for months on tenterhooks only to be told you didn’t even get past the first step.

What Are the Drawbacks of Hiring Algorithms?

With hiring algorithms quickly gathering pace, there are several drawbacks to consider. 

Lengthy Set-Up Times

Good-quality AI algorithms don’t appear overnight. They must be carefully programmed to align with your recruitment requirements. It will undoubtedly save you time in the long run but comes with lengthy set-up times, which can also be expensive.

Algorithmic Bias

Recruitment bias is a major problem whether algorithms are being used or not. While AI might be objective, its developers might not be. Programmers can introduce bias into the data leading to algorithmic bias.

Data Accuracy 

Algorithms are only as good as the data they base their decisions on—which require imputing in the first place. Incorrect or outdated data can affect employment prospects in the current hiring window. Also, because AI is always learning, it will incorporate those mistakes into its algorithms, becoming its usual way of operating. 

Algorithm Errors

AI is still a relatively new technology that is far from error-free. As with incorrect data, algorithm errors can become ingrained, meaning mistakes get passed down throughout future hiring processes.

Pushback from Recruiters & Hiring Managers

Like other forms of automation, we’re already seeing pushback from recruiters and hiring managers who see AI algorithms as the beginning of the end for their jobs. 

While we’re still decades away from computers doing the whole process, the potential loss of work is a significant concern for those within the recruitment field. 

3 Must-Dos When Implementing Hiring Algorithms

There are plenty of understandable concerns about the use of hiring algorithms, but here are three must-dos that can help:

Be Transparent About Using AI in Recruitment

People are nervous about AI, so being as transparent as possible is essential. Explain to potential candidates exactly what stage algorithms are involved in, how they work, and how recruiters will base their decisions on AI data.

Be Upfront About Data Collection

Using sensitive data makes many people nervous, but most seem to feel better when a human is involved—they can assume some common decency among most people. Placing such data in the hands of AI can take fears up a notch, so it’s important to be completely upfront with data collection processes, including data use and disposal. 

Disclose Decision-Making Based on Algorithms

Candidates must know who makes the final decision and that a computer isn’t running the whole show. They’ll feel much better about the process when they understand algorithmic decision-making—both who uses it to make decisions and during which stages.

Final Thoughts

While it may feel inevitable that AI algorithms will become part of our lives, it’s an area that still makes many feel uneasy. As with any new technology, there is much hesitation and fear around using AI, especially within the hiring process. 

Recruiters should approach the process with transparency so that candidates are fully aware of how AI works and what it does. Candidates will want to know how it affects everything from resume scanning to background screening. 

Background checks are a crucial part of the hiring process. ScoutLogic proudly leads the way, offering a range of search types to ensure checks are fast, accurate, and thorough.

Contact ScoutLogic today for background screening the intelligent way.

David Garcia

David Garcia, co-founder and CEO of Scout Logic, is an industry leader in the bulk background check world. With his strategic acumen and expertise in the HR sphere, specifically in hiring, recruiting, legal compliance, background checks, and resume screening, he’s an invaluable asset and consultant.

David's counsel extends across the boards of ScoutLogic, YipitData, and Supplier.io, drawing from his impactful stints on the boards of Infutor and Avetta. With an extensive 25-year journey, he champions unparalleled B2B commercial leadership within data & analytics, significantly shaping the HR landscape.