Decoding hiring AI: myths, value, and answers to FAQs

When you hear “hiring AI” what comes to mind? 

Excitement? Questions? Confusion? 

AI in hiring is a big topic with a lot of opinions—but when 75% of workers admit their negative perception of AI in hiring is due to lack of understanding, it’s safe to say education on the topic is needed. 

Hiring AI is not a mystery box open to interpretation—it’s rooted in decades of scientific research and data. 

Below we break down the explanation and science behind ethical recruiting AI.

How is AI used in hiring?

Ethical AI can enhance hiring by providing data that aids human decision-making. Available AI solutions include automation, conversational AI, and assessments, varying in complexity and impact. Deployments like chatbots streamline candidate interactions, while complex solutions like AI-driven assessments, integrated with an ATS, evaluate skills and fit for roles, offering significant benefits.

The benefits of AI in hiring:

• Supports decisions with data
• Creates a fairer candidate experience 
• Support DEI initiatives
• Unlocks candidate potential by assessing skills and competencies for roles 

Top myths

• Myth: AI decides who gets the job. 

  AI solutions, including assessments, provide important decision-support for hiring teams. HireVue algorithms are built to support human decision-making in a structured and consistent way that mitigates human bias. HireVue believes our solutions empower smarter decision-making—and should never be the decision maker.

• Myth: AI replaces a face-to-face interview.

  AI-assisted recorded interviews actually get you to the live interview faster! On-demand interviews typically replace the resume review or phone screen phase —speeding the process along.

• Myth: AI is changing in uncontrollable ways, so you can’t trust the results. While AI algorithms can certainly be learning “online,” that is not the standard in hiring assessments. HireVue assessment models are trained and tested in the “lab” then locked for deployment. It wouldn’t make sense to use a different algorithm day-to-day when evaluating candidates for a role. And with the spreading use of Generative AI, it’s worth noting that these algorithms should be deterministic, meaning the same input should produce the same output every time. 

Read more about AI myths and facts in our AI in Hiring Hub.

The value of bias mitigation

Hiring teams have a responsibility to create candidate experiences that treat and evaluate all candidates equally—relying on data-driven evaluation instead of subjective resume reviews. 

A resume review does little to prove a candidate’s value as an employee, and the process invites unconscious bias to creep in. Bias isn’t just discriminatory behavior towards those with certain names, alma maters, or age. It can also present as familiarity bias—an affinity for people from the same hometown, who cheer for the same team, or even have similar interests. 

Incorporating AI into your evaluation process offers a more objective analysis of the skills and competencies that best predict success. For example, an assessment built specifically for a product manager, can evaluate candidates on the skills that make successful employees for that specific role.

HireVue data and algorithms are audited to check for bias and mitigated accordingly. In addition  to third-party audits, HireVue rigorously tests every algorithm before it’s put into production to minimize bias. Once live with our customers, they’re checked regularly to monitor for bias and assist with diversity hiring efforts.

Hiring and employment are already well-regulated, but creating clearer regulations at the intersection of AI and hiring will take some of the pressure off companies who have to try to make sense of multiple standards when vetting potential partners and vendors. Computers allow us to formalize fairness/bias requirements that we define in an automatic way. Rather than simply incentivizing an algorithm to predict an outcome (in this case, a job-related competency), we simultaneously penalize it for having significant demographic group differences in the outcome.

Read HireVue’s industry first AI Explainability Statement here. 

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