Workplace Diversity: 5 Benefits of an AI Recruitment Process

With workplace diversity a key theme of this year’s Black History Month, the spotlight is on recruitment and how recruiting leaders can implement processes to foster progress.

David Bernard, founder of behavioural assessment firm AssessFirst, outlines how digital recruitment brings societal and commercial benefits that guarantees better workplace diversity.

When Goldman Sachs announced it would no longer take a company public if they have all-white, straight, male boards, it was greeted with both praise and criticism.

Those that praised the move saw it as both a sound social and business move. “It’s what big investors are looking for these days”, said Fred Foulkes, professor at Boston University Questrom School of Business.

According to reports by CNBC and Glassdoor, diversity is overwhelmingly what employees want too. 76% of personnel told Glassdoor that a diverse workforce is important when evaluating job offers. 80% of workers told CNBC of their preference to work for a company that values diversity.

These numbers, for many, are not surprising. A modern workforce that doesn’t want to reflect diversity and equality would be a peculiar thing to admit to.

Issues arise when we talk about the motivations that often sustain recruiting for diversity. When employers enforce policies to have a predetermined demographic of a workforce or board, they risk criticism that undoes what are well-meaning intentions.

Criticism of Goldman Sachs claimed that this new policy was born of financial pragmatism rather than a desire for progressive social change. As Foulkes said, diversity is the direction that investors are moving in, and a canny company like Goldman Sachs can follow that direction and appear progressive in the process.

Critics pointed out that a quarter of all directors of S&P companies are female, with over half of all new board appointments in 2019 going to females, a year before Goldman Sachs announced its new policy. Goldman Sachs, they said, were simply appropriating the new boardroom culture as their own procedure.

Then there are the assumptions and demands that interventionist policies make. Is a board regressive simply because of its composition? And what of the backgrounds of those boards? Is it progressive to assume advantages that some of those board members may not have had?

When we make assumptions, we are not truly pursuing diversity and equality. When we make tokenistic gestures that assume too much about ‘target’ groups, we give with one hand but take away with another. We could after all, be patronising marginalised groups by having them fill designated places on boards.

At the time of the Goldman Sachs announcement, the Cognitive Psychologist and science author Steven Pinker summarised this good-intentions-bad-process feeling: “Yes, group-based bigotry and exploitation exist, but at the same time there are poor white males who are horribly disadvantaged, women of colour born into privilege, and every other combination. To shame or disempower an entire category of people violates the principle of fairness and can have repercussions, such as the election of President You-Know-Who.”

Benefits of Artificial Intelligence in recruitment

If we are to pursue diversity with a fair and equal process, we must completely remove bias. Unfortunately, humans are not good at this, such is the deep-rooted nature of cognitive predisposition.

At AssessFirst, our AI powered recruitment solution can do what the human brain is simply incapable of – objectively assess a candidate’s suitability for the role, especially if we are ranking them against multiple other candidates.

We have seen how this organically and fairly creates workforces that are diverse and representative of the societies in which we live. There are three ways we help companies with recruitment:

  • Remove common biases

Hundreds of cognitive biases have been identified, several of which have commonly agreed theoretical origins. Using advanced and user-friendly psychometric testing, combined with AI, we can find the required skills for the available role, unburdened by these biases.

As recruiters, we tend to over-estimate our intuition, adding another unintentional obstruction to fair, diverse hiring.

By neutralising potentially discriminatory factors and by calibrating each of the criteria used in our algorithms, we generate reliable information that is free of bias and obstruction.

  • Discover soft skills

When you focus on the candidate’s actual ability instead of the quality of their CV or qualifications, you can break it down into three parts:

  • The way they reason and learn (their cognitive agility)
  • What sets them in motion (their motivations)
  • The way they behave (their personality)

Once identified, these three behavioural skills can be matched to the available position and company culture.

A common flaw in the recruitment process is the assumption that staff in similar positions have similar motivations. Our behavioural science proves that this is not the case, candidates are in fact much more nuanced – and that diversity of motivation and thought can help an entire business.

Behavioural potential is distributed among the general population much more equally than is reflected in the current workforce. When we researched and isolated these factors, we found that there is virtually no distinction between groups of people regardless of ethnicity, gender and age.

  • Predict success 

Our AI technology can use objective and unbiased data to quicky find people who can succeed and thrive in open positions.

Proprietary predictive algorithms analyse hundreds of criteria related to people’s personality, motivations and cognitive skills.

Predictive models can build the candidate profile you are looking for by analysing the best performers from within your existing workforce. You can customise this model. Finding candidates that complement the skills and behaviours of your existing personnel will help to increase diversity.

Leveraging automation and artificial intelligence to see human behaviour more clearly, provides a data-led solution that ensures diversity whilst making commercial success a more reliable constant.

Author: Editorial Team

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