Integrating new HR technology can be confusing and frustrating. Greg Moran, president & chief executive officer of OutMatch, writes on how to identify tech that will help prevent workplace bias and help your business grow.
2020 is a big year of growth for your organization, and the HR department needs help reducing time spent on repetitive tasks so it can focus on recruiting the right candidates and strengthening the team.
Integrating new HR technology can be confusing and frustrating. Vetting HR software with buzzwords like machine learning and artificial intelligence (AI) and finding the right solution â€“ whether you’re looking for a chatbot, a video interviewing tool, an onboarding assistant, or a performance management platform â€“ can be a daunting task.
You don’t have to be a software engineer to know the right questions to ask about how these products leverage machine learning and AI. Understanding the differences between â€œblack boxâ€ and â€œgray boxâ€ technology will guide you in making the right decision.
Understanding HR Technology
To be able to make smart investments in HR tech, you must first be able to understand what it is and what it does. The first step in knowing how to invest in new technology is knowing how employees are using current technology.
HR must be able to collect data about how employees are using tools such as HR apps, dashboards, and learning platforms to accomplish this. It’s valuable to know what is being used and not used, as well as what services employees find most beneficial, so the new technology can be useful even though the changing needs of employees and the organization.
When determining how to use technology accordingly in the hiring process, avoid â€œautomation biasâ€ â€“ the impulse to believe that technology is more suitable than humans in performing various functions.
What You Need to Know About HR Technology: â€œBlack Boxâ€ vs. â€œGray Boxâ€
Because machine learning and AI rely on the data inputs used to generate answers, even the most sophisticated algorithms are subject to human error and bias. Also, even if you have no personal bias while dealing with HR tasks, it still may slip through reporting, sampling, latent, and interaction bias. Simply put, if the data going in is biased, the results may be as well (which is what happened with Amazon’s AI recruiting toolOpens a new window in 2015). Here’s a look into some key information that will help guide your conversations as you dig deeper into different software providers.
Beware of the black box
Black box technology is prescriptive and claims it can make decisions on behalf of the experts in your department. Black box technology got its name from people not being able to understand how the algorithm accomplishes what it does, and that it’s difficult to understand the purpose of the multiple factors in a machine learning model.
In a human-first industry like HR, it’s critical to avoid solutions that (a) remove humans from decision-making, and (b) don’t provide transparency into how decisions are made. Considerations like diversity and inclusion may fall to the wayside without human oversight. Just because an algorithm’s job is to process the information, it doesn’t mean the results won’t be biased. This is why it is essential to move away from black box technology and focus on the gray box.
Stay in the gray
Gray box technology is suggestive and delivers recommendations rather than final answers. This keeps humans in the loop and helps avoid unintended bias that can occur in black box technology. While using gray box technology, you know its functionalities, as well as a general understanding of its internal mechanisms without being able to access the source code.
Coupling recommendations with insights into the data and what the algorithm was looking for, gray box solutions arm your team with powerful knowledge to make more informed decisions with a personal touch.
As you begin conversations with HR technology vendors, remember that utilizing AI and machine learning isn’t a magic bullet capable of solving all your HR problems. A product merely arms the talented people on your team with information to help them make data-driven decisions and manage their processes more efficiently.