To recruit diverse talent, we need emotionally intelligent AI. But how?

Recruiting stand-out, creative talent poses a challenge. In the wake of the pandemic, we need creativity more than ever. The Harvard Business Review says, “Imagination may seem like a frivolous luxury in a crisis, but it is actually a necessity for building future success. Now is not the time for only executing a practiced recipe.”

Artificial Intelligence (AI) designed for recruitment can build an ‘ideal candidate profile’ using historic data from your business, but is that enough? Can the best creative talent be so easily defined?

Using any candidate profile automatically creates bias, whether positive or negative, because it’s then used to source candidates and identify those most likely to succeed in the role. Algorithms even exist that can recommend candidates based on interview attributes, like facial expressions, body language and word choice.

If you’re recruiting based on who’s been successful with your company before, can those with different kinds of experience and viewpoints have a fair chance to shine? To find the best free-thinking talent, we may need an AI with emotional intelligence that can go against bias.

AI mirrors our best and worst traits

Is AI itself biased? Frida Polli, a former academic neuroscientist at Harvard and MIT, and CEO of Pymetrics talent matching platform, doesn’t think so. She told Wired magazine, “AIs are learning from the origins of bias – the human brain.”

Stephanie Allcock, tech industry HR specialist, echoes the sentiment. “In theory, AI should reduce unconscious bias in recruitment, but it depends on how you program it. Their success is down to the data you feed it.”

The World Economic Forum warns, “Past hiring decisions are used to train the algorithm to evaluate who is most likely to be the ‘right’ applicant. Often this approach inherently replicates the same biases present before the arrival of AI recruiting tools.”

And it happens. Amazon was forced to scrap a secret AI recruiting tool that showed bias against women because it “taught itself” male candidates were preferable.

Whether using machine or human judgment, without frameworks in place, it’s easy to hire those who fit your workplace culture, leading to a team without diverse experience. A Wall Street Journal report said, “Employers often aim to hire people they think will be a good fit, but their efforts can easily veer into a [situation] where new hires all look, think and act alike.”

Unconscious bias and why it matters

If questioned, most of us would say (and believe) we don’t have prejudice. But unconscious bias is the assumptions we hold that we’re unaware of. It may include preconceptions about people based on, for example, sex, race, disability or age that seep into our decision-making without our knowing.

Solving unconscious bias is not as simple as alerting workers that they may have it. It can make the team defensive and unreceptive to coaching. Myra LalDin, CEO of diversity training start-up Vectre, told Workflow magazine, “From a neuroscience perspective, your brain automatically starts trying to defend itself, and you don’t hear the content being presented.”

Using VR to reduce unconscious bias

International professional services giant PwC predict VR and AR could boost the global economy by 1.5 trillion US dollars over the next 10 years, with one-fifth coming from its use in training.

Traditionally used for job skills simulation like flight simulators, safety procedures and equipment operation, a recent PwC study shows impressive potential for using VR for soft skills training, like empathetic leadership and problem-solving.

‘V-learners’ (learners using a 3D virtual environment) found the simulations so realistic that they made decisions the same as they would in real life. 75 percent reported a ‘wake-up call moment’ that helped them identify times in their past when they had not been as inclusive as they’d thought.

V-learners were up to 275 percent more confident to act on what they learned after training. This is significant because when it comes to soft skills, confidence is key to success. Confidence builds employee satisfaction, leads to better employee retention. It also helps to improve work quality and reduce mistakes.

At scale, v-learning would likely be more cost-effective than classroom or e-learning. Most participants said they preferred it to traditional approaches too.

The study goes so far as to call a ‘blended approach’ to learning “the future.” It suggested VR is best for practicing what you learn in a safe environment, e-learning is great for academic activities such as learning how to use software, and classroom training is best for working collaboratively and discussing with peers.

The path to AI with emotional intelligence

AI and algorithms can be blamed for many things, such as unfair exam results or secretly ranking Tinder users based on their ‘desirability’ and ruining the chronological timeline of Instagram. It doesn’t create unconscious bias but reinforces prejudices present in its source data.

This is where skills training comes in. With immersive technology like VR, we can reduce unconscious bias in ourselves before we feed our recruitment choices into automated programs using AI.

Automated recruitment technology is useful, but it shouldn’t replace human judgment. Otherwise, the best talent may get missed because they don’t have the right keywords in their application. Emotionally intelligent AI will help us find the best talent, not just the most obvious fit, just as soon as we can train ourselves to make more emotionally intelligent choices.