How AI Is Impacting the World of HR (For Better and For Worse)

Artificial intelligence (AI) is a blooming field in the tech sector.

While the concept of artificial intelligence is nothing new, the unveiling of ChatGPT led to a flurry of AI investment early in 2023. IDC (International Data Corporation) forecasts that the influx of cash could reach as much as $154 billion within the year.

In other words, while it’s always been there, lurking in the background, AI is having its moment. It has exploded into the limelight, for better or worse.

Human Resources professionals are using artificial intelligence to parse through applications, search databases, conduct background checks, evaluate candidates, and much more. This growing dependency has several upsides. However, the largely uncurbed use of AI in HR is also attracting growing skepticism.

AI Is a Bit of a Wild West Scenario at the Moment

As already mentioned, artificial intelligence has countless applications (both existing and potential) in the field of HR. The issue lies in the fact that AI solutions in hiring and talent management are all relatively new. Many have minimal data to vet their effectiveness—even though, if something goes wrong, the fault typically lies with the employer, not the tool that they’re using.

There are pushes for AI legislation to overlook the use and impact of AI in the workplace on both a federal and state level, but much of this is still in development. New York is in the midst of deploying a law to regulate AI in employment. California is grappling with how to implement similar restrictions. The Biden Administration’s National Artificial Intelligence Research Task Force recently released its “Final Report” on the future of AI and a roadmap for the federal government’s involvement therein.

Why the push to fetter AI tools that have so much potential? Because as is the case with most technological tools, the impressive positives that come from using AI in a field like HR also come with some dark negatives. One of the biggest of these concerns is algorithmic discrimination.

The Potential for Indirect Bias and Other Issues With AI in HR

Algorithmic discrimination, algorithmic bias, machine learning bias, AI bias—these are all terms that refer to the same thing. It’s a concept that is just beginning to emerge as a major concern. This is particularly true in areas like HR, where AI is categorizing and making decisions between different human beings.

The consultants at PwC define this unique form of discrimination as “AI that makes decisions that are systematically unfair to certain groups of people.” In practice, this bias takes place when machine learning and AI tools classify candidates through the lens of traditional societal biases like gender, age, or ethnicity.

A good example of this is using AI to identify your high-performing candidates. This is a normal and wise thing to do. After all, you want to figure out what traits to look for in future recruitment efforts. When an AI tool does this, though, it can begin to pick up on stereotypes that are pre-existing in your workplace, such as a predominance of men or of middle-aged workers.

AI has other potentially negative side effects as well. For instance, it can exacerbate the issue of accessibility. An AI tool used in the hiring process or to make assessments may automatically rule out certain candidates, such as those who are disabled, simply because they can’t access a test or function within its parameters.

Privacy is another concern. AI has the ability to scour the internet, including very personal areas, such as deep down an individual’s private Facebook threads or personal blog posts. This may seem like an excellent way to fully understand an individual. In practice, though, the sheer expanse of knowledge AI can take into account is begging to unleash Murphy’s Law on every HR interaction.

Transparency and Human Judgment Are Important In AI

As with any new technology, guidelines and overarching standards are critical requirements when using artificial intelligence—especially in the Human Resources department.

This starts with greater transparency. Any time an AI tool influences an HR interaction, either with a candidate or an employee, the person interacting with the tool should be aware of that fact. HR personnel should inform them (not just of the tool, but what it is and how it works) and ask them to give their consent beforehand.

Along with transparency, basic human judgment and oversight are clearly needed with AI solutions in HR. This can come through federal and state legal systems but is also desperately needed within each organization.

“Along with transparency, basic human judgment and oversight are clearly needed with AI solutions in HR”

This is where investing in quality C-suite leaders, including CHROs, is important. The individuals guiding an organization must be aware of the potential for AI solutions to run off the rails. They must be instrumental in setting up oversight and ongoing evaluations of how they use AI within their HR departments. They must also stay up to date with the latest laws and legal guidelines.

If you’re using AI in your HR department—and chances are, that’s true—it’s imperative that you hire visionary HR leadership to guide you through the evolving use of machine learning in talent acquisition. The Stanton Chase team can help, too. We understand the importance of finding CHROs with the skills to both optimize the good and guard against the bad as they navigate the use of evolving technology.

AI is clearly here to stay. HR departments must find ways to use their tech safely and securely so that they can maximize its benefits without falling into its pitfalls over time—starting with protecting against AI bias in the hiring process.

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About the Author

William Brewer, CCP, is a Director at Stanton Chase Los Angeles. He is also Stanton Chase’s Global Human Resources Practice Leader. Prior to moving into executive search, Bill had 25 years of experience in corporate human resources. In addition to his executive search career, Bill is an adjunct Professor at the University of Redlands. Bill also serves as a mentor for the MBA program at the Paul Merage School of Business at the University of California, Irvine (UCI) and has been a mentor with the School of Business at the University of Redlands.