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Avoiding the Shortcuts: Best Practices with AI in Hiring FAQ

Erin Iafelice
AI in Hiring

Artificial intelligence (AI) is being used more and more in modern hiring processes, leading to positive and negative perception in the market. How can recruiters evaluate AI in a hiring platform? How can TA leaders make their case for AI-enabled hiring tools? What do candidates think about non-human input being used for hiring decisions? Here are answers to some of the most frequently asked questions about AI in hiring.

Q: How is AI being applied effectively to hiring these days?

A: It’s being used in many different areas to improve the hiring process. Modern Hire uses AI in assessments to bring data together and model out what drives the prediction of candidates’ performance. Advanced analytic techniques like machine learning are being used to model out data. 

AI can also be used to understand structured and unstructured data. With the advances in natural language processing, AI applications can understand human language. Modern Hire’s models have been tuned to understand the language in an interview environment. As a result, it’s possible to take the content of what a candidate says in an interview and score it against the job’s key competencies, much the way recruiters do today. 

AI is used to automate hiring processes, too. For instance, AI reduces the time and effort it takes to schedule interviews. AI tools can look at multiple calendars and find a time that works for everyone.

 

Q: How are concerns about a lack of transparency with AI being addressed?

A: Transparency is missing in today’s environment regarding how AI is being applied to hiring. It’s often like a black box that prevents recruiting teams from knowing what’s going on. Transparency starts with understanding what is going on: The platform collects this data because it will tell this about a candidate and predict this outcome. 

Modern Hire takes a Glass Box approach to be transparent and help recruiters and TA leaders understand what is going on. Our team of scientists understands what’s going into the box to begin with because we’ve designed it that way, so when we do automatic scoring of our interviews, we can tell candidates what we are doing. The Modern Hire platform does not use facial recognition or look at the candidate’s image or listen to the candidate’s voice. Instead, we’re focused on the content of the candidate’s response. Our platform compares that to a massive database with millions of data points from others who’ve answered this same job-specific question, and scores candidates on that core competency required for that specific job. When attention is paid to the kind of data collected, how AI uses that data becomes explainable. That’s important for recruiters who evaluate AI-enabled platforms and for TA leaders making the case bringing AI-driven platforms into their hiring. 

 

Q: What are the best practices around the types of data used in hiring?

A: There’s a shortcut that’s frequently used: modeling against data that is convenient and readily available rather than against what matters. What really matters is the hiring outcomes, knowing if the candidate turned out to be a good hire, if he or she is performing, and stayed with the organization. All too often shortcuts are taken by using data around whether or not the candidate was hired, and the recruiter’s impression of the candidate. That type of data is out there, it’s available, but being able to model a recruiter’s hiring decision isn’t necessarily indicating what organizations really want to know, which is whether the candidate was ultimately an effective hire.

If you’d like to learn more about this topic, search “Artificial Intelligence” in our Resources, or download our white paperThe Future Is Fair: How AI Is Eliminating Bias.