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How AI Boosts Diversity and Inclusion in Recruitment


The business scenario these days is highly competitive, and organizations look for anything that can give them the edge. A diverse workforce is one such approach to stay ahead of competitors, given how it helps in attracting the most talented people, signing on more clients, or getting funding to go public.

And corporates are on board – Goldman Sachs, the biggest Wall Street underwriter of IPOs in the US, announced its support for diversity and inclusion in January 2020 by saying it would not take a company public in Europe or the US unless it had a director who was diverse or female.

How does diversity help?

The benefits are many, and measurable. For companies with above-average diversity, earnings are 9 percent higher and innovation revenues 19 percent (before tax and interest), as per 1,700 organizations surveyed in eight countries. Companies that ranked in the top 25 percent for ethnic and racial diversity outscored the median financial returns for their respective countries by 35 percent, making this something HR leaders must focus on.

What is unconscious bias?

The problem is that humans intrinsically are biased. Subjectivity is built into the core of a human being, try as we might to be very objective. To be successful in making fact- and competency-based pure objective decisions, something must change.

Unconscious bias refers to individuals forming social stereotypes outside their conscious awareness, when it comes to select groups of people. free-quick-and-safe-instagram-auto-liker.html Several studies and research have shown that such biases:

  • Affect real-world behavior
  • Develop at early ages, such as during middle childhood, and continue to develop across childhood
  • Can be minimized by taking proper steps

Unconscious bias training has become a popular tool for HR leaders to minimize biases across departments in organizations. The effect of such training is to make people aware of the standpoints they take implicitly, and guide them on how to reshape their thinking.

Leaders look at how they can create inclusive, fair, and ethical workplaces by shaping their organizational cultures properly, and by personifying the very moral and prosocial values they would like to see practiced across their own organizations.

Does it help to bolster recruitment with artificial intelligence?

At the end of the day, the human factor still does creep in, which is why it helps to have artificial intelligence (AI) incorporated into recruitment, such as in applicant training systems (ATS).

These rank individuals objectively after looking only at their individual competencies, which makes them very powerful. Incorporating smart HR technology into candidate sourcing and selection is a great way to redefine HR practices and strategies, giving companies an edge in the market while making the process cheaper and more productive.

Here are the specific advantages of how AI helps HR leaders in recruitment and other aspects of managing talent:

  • Trouble-free process: Time constraints, narrowed candidate sets, or other typical characteristics of traditional recruitment methods are no longer a concern.
  • Large candidate pools: Reduced impacts of human biases in bigger candidate groups enhance the chances of more diversity.
  • Zero emphasis on appearance: Eschewing manual candidate searches saves a lot of time and negates any bias. No longer can a person see the face, nation, or other profile details of a candidate, and the software selects a candidate just by using Boolean operators to evaluate the skill match.
  • Negation of preferences: Parsing technology matches candidates with the right job descriptions, by looking for matching elements in a job description and CV. AI-supported platforms transform CVs into sentences without elements that could have any bias or irrelevant elements.
  • Unbiased ranks: Only relevant candidate characteristics are evaluated to create an objective ranking, with top rankers being those whose skills match most closely with the job description.
  • Reduced compensation bias: Predicting pay as per market demand and making for a fairer pay environment

How do you properly bring AI into recruitment?

Realizing the aforementioned advantages requires strong evaluation algorithms and well-drafted, robust questionnaires. Algorithms cannot for instance be based on past hiring practices, as those could be biased by favoring specific genders or ethnicities. AI cannot be the sole operator or driver of bringing diversity and inclusion into the process, and the emphasis is on collaboration between technology and humans with the right checks build in.

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