Employing Artificial Intelligence to Mitigate Biases in Hiring Processes

It has long been known through research and even mere observation that diversity and inclusion in an organisation result in higher productivity and innovation. Equality, diversity and inclusion (EDI) have become a priority for organisations, and they are taking strategic steps to tackle the issue for several years now. The EDI teams have been rolling out several creative initiatives to tackle the problem, seeking to create awareness among their workforce, but most of these did not deliver the desired results. They are still struggling to make tangible changes in their workforce despite making it a primary HR objective due to the unconscious biases at the talent acquisition stage.

The Role of AI in Achieving EDI Goals of Organisations

Talent acquisition is the single most effective way for an organisation to increase diversity within its workforce, thus the hiring process has received a lot of attention in the last few years. As a result, human resource professionals and EDI leaders must identify and implement strategies that will increase their chances of finding and selecting more diverse candidates. With this priority in mind, it's critical to consider how we can maximise efforts to reduce bias in the hiring process.

The modern-day EDI initiatives require a holistic and long-term approach. It is prudent to incorporate strategic and technology-driven steps at the hiring stage itself for organisations to achieve their diversity and inclusion goals. Artificial Intelligence is bringing about a holistic change in the workforce by addressing the problem of diversity at the sourcing, screening, and interviewing stages of the hiring process. By deploying the power of AI that thrives on big data, HR leaders and EDI strategists can generate insights and find potential candidates that wouldn't have been found with unconscious biases of the recruiters.

As humans are inclined to function per their biases, organisations can now help reduce these biases to support objective decision-making in the hiring processes. The technology's ability to consider a larger pool of candidates enhances the chances for greater diversity.

It's Time to Choose AI-Driven Talent Acquisition Solution to Contain Recruitment Biases

SniperAI, a leading talent intelligence platform, is an AI-driven solution that uses clients' internal databases/historical data to extract only the skills required for a role and excludes other candidate characteristics such as gender, race, nationality, religion, and so on. SniperAI's Equitable Hiring algorithm creates a detailed skill map based on previous successful hires and uses that skill map to assess candidates for a similar job opening in the future.

How does our Equitable Hiring Feature Help in Achieving Diversity Goals?

To ensure that unconscious human biases are mitigated from recruitment processes, SniperAI is enabled with 3 formulations.

1. Bias Checker

The algorithm examines the job description/skill map and then analyses the historical data to determine which candidates were shortlisted and selected, as well as those who were rejected. It will further evaluate all previous candidates considered for a job and generate a fitment score. It would then create a comparative map to separate and study outliers (candidates with high fitment scores who were not shortlisted and candidates with low fitment scores who were shortlisted/selected). The system would then examine how large this outlier group is and whether there are any biases in the recruiters' selection decisions (gender, race, religion, etc.).

2. Blind Hiring

To check for prospective biases, Recruitment Smart innovated Blind Hiring technology to conceal personal identifiers such as name, phone number, age, location, previous employer, etc. The tool enables organisations in addressing a wide variety of biases substantially including gender, race, religion, etc. with varying confidence. It then assesses the skills of the candidate to make recommendations and it only reveals the name/contact details of the candidate once recruiters have decided on the candidature (shortlist/reject etc.).

3. Job Description Templatisation

With this feature, organisations can help reduce gender bias from the start of the process by creating a standardised job description with inclusive diction that lists skills in a gender-neutral manner to encourage female candidates to apply for the job.

Our Equitable Hiring Feature is designed in such a way that can be customised as per the diversity goals of an organisation. Organisations can choose to conceal the identifiers of a candidate that make a difference in the diversity vision of the organisation.

For instance, while employing Equitable Hiring at NRG Energy, a large American energy company that employs 500+ candidates annually, we offered the following identifiers that can be masked in the initial stages of hiring:

• Name (Full Name)
• Email
• Contact Number
• Gender
• Country (Optional)
• City (Optional)
• State (Optional)
• Zip/Postcode (Optional)
• Preferred Location (Optional)
• Nationality (Optional)

NRG Energy now employs Recruitment Smart's Equitable Hiring Feature on 80% of its Job Openings to address unconscious human biases in its recruitment process

Artificial Intelligence: To Help Reduce Bias in Hiring Decisions in Talent Acquisition

Humans will never be replaced by machines in the hiring and talent evaluation processes. However, when equipped with standard job descriptions and well-designed algorithms, AI can screen job candidates without biases that would normally stymie diverse hires and promotions. Furthermore, it can assist employees in developing the skills required to become more effective and open doors to advancement. When all these factors are considered together, a more diverse workforce could be the result.