Does AI Reduce or Amplify Biases in Recruitment?

Artificial intelligence has quickly become part of how companies hire, from scanning resumes to scheduling interviews and even predicting candidate success. For HR teams pressed for time, these tools promise efficiency and objectivity. But there’s a growing question that can’t be ignored: does AI reduce bias in recruiting or amplify it?

The answer is: it can do either. It all depends on how it’s built, used, and monitored.

Using AI in Candidate Recruiting

On the surface, AI is an appealing solution for some of recruiting’s biggest challenges.

• Speed: AI-powered tools can sort through hundreds of applications in seconds

• Consistency: Unlike humans, algorithms don’t get tired or distracted, applying the same criteria every time

• Scalability: Companies can use AI to quickly screen large applicant pools without overloading recruiters

Theoretically, AI also has the potential to remove human bias. If people tend to make decisions based on names, schools, or gut instincts, an algorithm can instead be programmed to focus purely on skills and qualifications.

But, in reality, the way AI works is more complicated. AI is only as unbiased as the data it’s trained on. And historically, hiring data reflects human decisions - decisions that often include bias.

For example, if a company has traditionally hired more men for leadership roles, an algorithm trained on that data may “learn” that men are more likely to succeed. If resumes from certain schools or geographic areas were more often advanced in the past, the AI may prioritize those applications even if they don’t represent better candidates.

Instead of reducing bias, poorly designed AI can actually make it harder to detect and can repeat it at scale.

But that doesn’t mean AI has no place in hiring.

When used thoughtfully, AI can support bias reduction in several ways:

• Blind Screening: AI can be programmed to ignore names, addresses, and other personal details, focusing only on skills, experience, and relevant qualifications

• Consistent Criteria: Instead of relying on subjective judgments, AI applies the same standards to all candidates, reducing “gut feeling” hiring

• Highlighting Overlooked Talent: AI can flag candidates who may not have traditional credentials but show relevant skills or transferable experience

• Reducing Initial Human Bias: By handling the first round of screening, AI can prevent unconscious bias from creeping in early in the process

The key to using AI in recruitment lies in transparency and monitoring, rather than blindly trusting it to make the best decisions.

Best Practices for Using AI Responsibly in Recruiting

If organizations want to leverage AI without falling into the trap of amplifying bias, HR teams need to take a proactive approach.

1. Audit the Data

Ask: What data is the AI trained on? Does it reflect diverse hiring decisions, or does it reinforce old patterns? Diverse training data is essential to avoiding biased outputs.

2. Keep Humans in the Loop

AI should never be the final decision-maker. Recruiters should use AI as a support tool, not a replacement for human judgment.

3. Demand Transparency

When selecting AI tools, prioritize vendors who can explain how their algorithms work. If you can’t understand the decision-making process, you can’t identify potential bias.

4. Regularly Monitor Outcomes

Track who is being advanced or eliminated by the AI. Look for patterns such as consistently filtering out candidates from certain backgrounds and adjust accordingly.

5. Prioritize Skills-Based Hiring

Instead of relying on credentials or pedigree, use AI to assess skills and competencies. This shifts focus toward actual ability, not just resume polish.

The Human Side of Hiring

At its best, AI can help recruiters focus more time on meaningful human interactions like interviews and ensuring a strong candidate experience. But AI will never replace the human responsibility to create fair, inclusive hiring practices.

AI should be seen as a tool to enhance HR, not a shortcut to avoid bias training or accountability. Human oversight, empathy, and judgment will always be the core of ethical recruiting.

Left unchecked, AI can quietly reinforce the very inequities HR teams are working to dismantle. But with intentional design, ongoing monitoring, and human oversight, AI can support fairer, more inclusive hiring.

It’s important to remember that the future of recruiting isn’t AI versus humans, it's AI and humans. When technology is paired with people-first leadership, organizations can hire faster, smarter, and more equitably.