Organisations have been long accused of disproportionately hiring people of a specific ethnicity and gender. For example, IT and STEM industries are almost entirely represented by men. A study by recruitment firm, Hays, shows that a given profile of the same candidate is more likely to be selected if the candidate’s name is gender-neutral or that of a man.

Why recruitment bias occurs?

After all, HR professionals are humans, and we have our underlying preferences that take over our decision making subconsciously. In a workplace setting, these preferences result in cognitive biases and prejudices during recruitment. It is because HR professionals can prefer people of a particular community or have stereotypes for or against a gender group.

Turning tide in favour of diversity

Business leaders have started to recognize the benefits of inclusive hiring practices, promoting a diverse workforce in their workplace. Diversity has now been perceived as an organisational strength and not just a form of regulatory compliance or a mere slogan. McKinsey & Company confirms these findings in their study, which indicates that businesses with gender and ethnic diversity outperform others by 25-33% in terms of profitability. A research study by Deloitte highlights that approximately 68% of leading organisations are recruiting diverse candidates and investing in technologies to reduce workplace bias.

With the increased significance of diversity and inclusion in the workplace, technologies driven by artificial intelligence (AI) have been identified as tools that can help reduce recruitment bias and select candidates on merit irrespective of their caste, ethnicity, and gender. Let’s take a look at how.

AI at your service

Eliminating biases

The toughest challenge to resolve biases during recruitment is to track them in the first place. AI technologies remove the scope of human intervention in selecting the right candidate, eliminating any distracted or cognizant bias resulting from stereotypes or personal mindset.

AI tools level the playing field by choosing applicants with skills and experience pertinent to the specific job, thereby ensuring employers that they have access to the best talent. These types of intelligent software systems are being used to scout, engage, screen, and even interview diverse and prime candidates. It has been proved that AI-driven recruitment solutions significantly reduce the duration of the entire recruitment process, hire better candidates, and improve retention rates.

Inclusive job descriptions

AI-enabled technology for reviewing the job post can detect bias in draft recruitment advertisements before they appear in the media in front of potential applicants. The tools can identify the language promoting gender, age, and ethnicity biases and allow the recruiter to reframe the post, appealing to a broader spectrum of qualified candidates. Additionally, one can improve its job posts using AI through guidance on tone, voice, and length to reduce biases.

Recruitment Smart pioneering AI-driven recruitment

As one of the leading HR tech companies, Recruitment Smart has been offering AI-driven solutions, applying data science and Heuristic AI to recognize different means of promoting diversity in the context of businesses and suggest the most efficient way to achieve it. Its advanced machine learning algorithms identify the nature of bias, if any, and then address them through an AI-based recommendation engine, engendering ethical hiring while protecting the candidate’s identity. Further, the algorithms neutralize any extant inherent bias in the system.

Recruitment Smart has helped its clients to reduce various types of biases by over 40%. It has developed Sniper AI as one of the tools to help organisations in selecting and recruiting the most eligible candidates without exhibiting any prejudice.

How Sniper AI can help you achieve your D&I goals

Recognize Potential Applicants

Sniper AI is built on a powerful matching algorithm, rendering it with advanced learning capacities. As a result, the software selects the candidate more accurately the more you use it. Every search provides more informed feedback to the system, allowing it to calculate better how to match candidates to roles.

Reducing recruitment bias

The software selects the best applicants and helps the recruiter interact with them through the entire recruitment lifecycle without showing any personal preferences or predisposition in terms of region, race, and gender, etc., thus promoting equality and inclusion of a more diverse workforce.

Selection only based on merit

Sniper AI identifies candidate’s attributes such as work experience, skills, and qualifications and compares it to qualitative factors such as length of service, employer noteworthiness, geographical location, and more. These factors are calibrated using proprietary machine learning (ML) technology, allowing the entire system to learn how to appropriately weigh and score each unique factor. The best candidate with the highest score is displayed at the top.

Accurate with no “false positives”

Sniper AI is significantly more trustworthy because of its search system that uses the most advanced keyword technology. The system ranks the most appropriate factors, generating accurate results without producing any “false positives.” In this way, recruiters can gather more information on every applicant, thereby evaluating candidates more effectively.

“Towards the growing significance of AI in recruitment”

AI reduces the scope of human intervention, thus eliminates the cognitive biases of HR professionals towards or against a particular ethnic or gender group. Using tools driven by AI, organisations gain an incredible opportunity to recruit simply the best applicants based on their genuine potential and personality.

Tools like Sniper AI will definitely prove beneficial in automatically coordinating the right application to the correct job detail, promoting inclusion. With selection happening based on merit, one can hire both male and female candidates from different ethnic backgrounds, enhancing diversity at the workplace and creating a diverse pool of talent.

Of note, it is significant to highlight that AI alone cannot help organisations become diverse. Progressive vision and values should back the usage of technology. Thus, before integrating AI-driven tech with the company’s D&I framework, managers and leaders should evaluate the existing limitations and challenges. They need to design an empirical assessment strategy by identifying the factors influencing the workplace culture and employee experiences and empowerment.