Video interviewing software has taken Talent Acquisition by storm, and the market is buzzing with excitement about future capabilities.
Early adopters of specialized recruiting tech found a secret weapon in video interviewing software. Finally! Interviews could be done in a structured and scalable way, in less time, across a broader and more diverse candidate pool.
Today, more than 60% of companies use video interviewing, according to an OfficeTeam survey, and adoption is on the rise. Hiring teams are jumping at the chance to connect with more candidates, and put the more time-consuming, monotonous screening methods behind them.
While video chat and video conferencing make it easy to meet virtually, even more powerful is the ability to do pre-recorded video interviews. Hiring teams can review at least 3 pre-recorded interviews in the time it would take to conduct one 30-minute phone screen.
That’s an efficiency boost of 3X! But, employers know that today’s technology can do more than boost efficiency.
Enter AI
Technology that can accelerate outcomes is good. Technology that can anticipate and influence outcomes is even better. That’s what makes AI such a powerful tool.
So what’s the future for AI and video interviewing?
According to a Harvard Business Review article, AI algorithms are being used to mine data – including tone of voice, gestures, and facial expressions – from video interviews to make predictions about a candidate’s job potential.
Humans are constantly interpreting body language and social cues, and in just a few seconds, we can learn a lot about a person’s communication style. AI is taking it even further in an attempt to tie these cues to other aspects of job performance.
The goal of using AI in this way is to solve the age-old struggle of talent identification, which continues to be a challenge for organizations everywhere. Just ask Amazon: they tried to solve this problem with an AI recruiting tool that turned out to be biased against women.
Critical questions
Before employers allow voice and facial recognition in their talent selection tools, there are three critical questions to answer.
1. What’s the connection to job success?
Experts can train algorithms to recognize anything, including voices, gestures, and facial expressions. In doing so, they have to train the algorithms on what these cues mean, either explicitly or by letting the AI learn through data sets that are fed in.
Here’s the problem: the market does not have a shared understanding, or even a hypothesis, about how these cues are connected to job success. What does it mean if someone looks down, speaks quickly, or pauses to think? Do these behaviors make someone more or less capable of doing the job?
What if, due to a disability, a candidate doesn’t emote like others do? And what about candidates from different cultural backgrounds, where different expressions mean different things?
Using AI to help answer these questions is fine, but until there’s a clear job-relatedness link, we’re not ready to deploy algorithms that evaluate candidates in this way.
2. Will AI reduce bias in hiring, or perpetuate it?
It’s true that AI does not have an ego or agenda, but that doesn’t make it error-proof. In fact, the biggest advantage of AI – that it’s not influenced by human moods or emotional whims – is also its biggest weakness. Humans, at least, can gut-check each other. AI is completely unaware when outcomes are unfair.
Also, for AI to learn, it needs humans to tell it what to learn from. We feed data in, and our human biases go in with it. If a training set includes mostly white male faces and voices, for example, then the algorithm will likely favor this demographic. Which could be why Google’s speech recognition is 13% more accurate for men than it is for women.
So scratch the assumption that AI will free us from bias. Without careful oversight and fairness in hiring, AI will be just as biased as humans, and on a frighteningly larger scale.
3. How will candidates react to us data-mining their expressions?
The best HR tech on the market is not only transformative for internal teams, but it also makes the company look great to the outside world. Sleek, beautifully branded experiences say to the candidate, “We care about you and want you to feel at ease.”
This is where video interviewing software shines. Through video, candidates get to showcase themselves in a way that’s not possible on paper or over the phone. And with each interaction, they get to connect with the people and teams they might soon be working with.
But what happens when candidates find out they’re being evaluated by AI, not on the content of their answers, but on how well they speak and what their faces look like? You can bet this will create more nerves and awkwardness on camera. Some candidates may try to beat the algorithm by playing to what they think the AI is looking for.
For candidates who agree to complete this type of video interview (because opt-outs will soon become a requirement), they probably won’t show their real, authentic selves. And what good is that in your screening process?
The right solution
The HR tech market will continue pushing the bounds, and AI will surely be a player in solving the talent identification problem. But, is voice and facial recognition the right solution?
It depends on how you plan to use it. If you allow AI to screen out candidates based on a black-box analysis of voice, gestures, and facial expressions, then you could have a moral dilemma on your hands. Do you know how the AI is making decisions and what the adverse impact is?
While AI may be able to place your next grocery order or recommend a show you’ll love on Netflix, job decisions are a high stakes game. A flaw in the underlying logic of a talent selection tool could derail countless lives, preventing qualified people from getting jobs they deserve.
Wherever AI takes us, humans will still play an important role in the evaluation of candidates. After all, interviewing exists so that people can get to know each other before working together. AI, then, shouldn’t replace us, but be used to sharpen our skills, scale our efforts, and make our interactions more productive.
Schedule a demo to see how you can use Harver’s AI and automation to increase productivity for your recruiters and hiring managers.
