Hiring Without Bias: Is It Possible?

Imagine a hiring process where every decision is free from bias, fair, and purely merit-based. Sounds perfect, right? But let's be honest: Even the best of us are prone to bias. It's human nature! We all have preferences that can shape our perceptions and influence our decision-making, consciously or unconsciously.

In this article, we'll uncover the reality behind bias in recruitment and explore practical steps to minimise its impact. It's a journey towards making your hiring process fairer, more inclusive, and less susceptible to common pitfalls.

FOLLOW ME ON TIKTOK

Headed Towards Diversity and Inclusion

Diversity, equity, and inclusion (DEI) are hot topics in recruitment. More companies are publicly committing to creating a diverse and inclusive workforce. But here's the truth: studies show a considerable gap between the theory and reality. While most companies express a desire for diversity, their hiring practices often tell a different story.

Why the Disparity?

• Lack of clear DEI goals and accountability.
• Unconscious biases influencing decision-making.
• A preference for hiring people similar to the existing workforce.

To bridge this gap, recruiters must recognise their biases and implement more structured, bias-reducing hiring processes.

Put Your Personal Preferences Aside

Bias is like a pair of tinted glasses—it changes how we see things without us even realising it. There are two main types:

1. Conscious Bias: Also known as explicit bias, it's intentional and can be controlled if recognised.
2. Unconscious Bias: The trickier one. It affects our decisions without us even being aware of it.

Example Scenarios:

• Affinity Bias: You discover that a candidate named Lisa went to your high school and is about the same age as you. This connection makes you feel a sense of affinity towards her, influencing your judgement.
• Horn Effect Bias: You notice a few typos in Lisa's CV and instantly assume she needs to be more meticulous and reliable, even though typos don't necessarily reflect her competence.

These examples highlight just two of the many biases that could affect recruitment. It is crucial to recognise and acknowledge these biases.

Unintentional Bias is Still Bias

We're all products of our backgrounds and experiences. Our instincts have helped us survive and thrive. But they can also lead us astray. Unconscious biases can sneak in even when we aim to do the right thing.

Think About This:

• Isn't looking for candidates who fit your definition of diversity also a form of bias?

Systemic Bias is Deeply Rooted in the System

Studies worldwide indicate that personal details like gender, race, and age significantly affect whether candidates receive callbacks. Systemic bias is like a hidden thread woven into the fabric of society. It's everywhere and affects recruitment decision-making.

Examples:

• Name Bias: A candidate named John might be viewed positively if you have fond associations with the name. Alternatively, a negative past experience with someone named John could lead to a biased evaluation.
• Education Bias: Assumptions based on where candidates attended school or worked before can influence our judgement.

Clearly, systemic bias exists, but tackling it requires more than just good intentions.

Can Anonymised Screening Entirely Reduce Bias?

One popular solution is anonymised screening, which removes personal information like name, photo, age, and gender from CVs at the initial stages. It helps overcome unfair assumptions but doesn't eliminate bias altogether.

Limitations:

• Delayed Bias: Eventually, candidates will be met face-to-face, and biases may creep in at later stages.
• Residual Clues: Education and experience can still lead to biased assumptions.

Anonymised screening is a step in the right direction, but it's not the ultimate solution.

Moments When AI Failed

Artificial Intelligence (AI) in recruitment has been praised for its potential to remove bias. But, believe me, it hasn't always worked perfectly.

Examples:

• Amazon's Biased Algorithm: Amazon's automated talent search programme was found to rate candidates in a gender-biased way, so the project was scrapped.
• HireVue's Face-Scanning Technology: HireVue used facial analysis to score candidates based on their interview responses. Following concerns over fairness, they shut down this feature.

These cases show that AI is not infallible. Algorithms can inherit biases from the humans who create them, especially if trained on biased data.

Illegal or Not, It's a Dangerous Play

Using AI for recruitment is a legal grey area. The Equal Employment Opportunity (EEO) laws prohibit discriminatory job practices, but rapid technological advancements have outpaced legislation. The New York Times noted that under federal law, employers can define what qualities constitute a "cultural fit," which could hide bias in automated hiring.

Key Risks:

• Unregulated Technology: AI-driven assessments are mainly unregulated, making them susceptible to reinforcing biases.
• Exclusionary Criteria: Companies can set hiring criteria that exclude certain groups under the guise of finding the right "fit."

AI is a Helping Hand, Not a Magical Solution

Technology can help us make data-driven decisions but isn't a cure-all. Many recruiters need to realise the limitations of AI in recruitment.

Consider This:

• AI offers the promise of finding hidden data patterns that predict candidate success.
• Critics warn that biased data can reinforce existing biases, making it harder for women, Black candidates, and others from non-traditional backgrounds to get hired.

We can't solely rely on technology to solve bias issues, but it can certainly help recruiters make fairer decisions.

What Should You Do After All?

Hiring a human is a very human process, and human interactions involve emotions. It's natural to have instincts and opinions. But it's crucial to recognise and reduce biases.

Steps to Minimise Bias:

1. Acknowledge: Admit that everyone has biases.
2. Standardise: Use structured interview questions and scoring rubrics.
3. Diversify Panels: Include diverse interviewers to balance perspectives.
4. Use technology Wisely: Employ AI tools carefully and understand their limitations.
5. Train: Regularly train hiring teams on recognising and mitigating bias.

Ultimately, reducing bias in recruitment is like navigating a minefield. It can't be entirely eliminated, but it can be significantly reduced with the right tools and mindset.

Call to Action

Ready to tackle bias in your recruitment process? Here's what you can do next:

• Review Your Process: Analyse each step of your recruitment process for potential bias.
• Implement Anonymised Screening: Introduce anonymised CV screening for the initial stages.
• Invest in Training: Train your team to recognise and minimise unconscious bias.
• Explore Technology: Consider using AI tools like TalentLyft to help streamline and improve your hiring process.

Resources

1. How to Avoid Bias in Recruitment
2. Increasing Diversity and Inclusion with AI
3. More Evidence That Company Diversity Leads to Better Profits
4. Research: How Companies Committed to Diverse Hiring Still Fail
5. HireVue Discontinues Facial Analysis Screening

Connect and Share

Believe me, tackling bias isn't easy, but sharing experiences can make a world of difference. Connect with fellow recruiters, comment on your challenges, and share your success stories in reducing bias.

Trending Hashtags

1. #InclusiveHiring
2. #DiversityInRecruitment
3. #UnconsciousBias