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Preventing AI Bias in Hiring: 7 Tips for a Fair and Inclusive Process

Artificial intelligence (AI) is revolutionizing employee hiring, making the process more efficient, thorough and data driven. According to a 2022 Society for Human Resource Management (SHRM) survey, one in four companies embraces AI when hiring.

Used responsibly, AI can help businesses quickly identify and secure top talent like never before. But with these advantages comes a growing threat: AI bias creeping into the recruiting and hiring process. Here, you’ll learn 7 smart strategies for preventing AI bias in hiring to support a fair and inclusive workforce.

What is AI Bias?

Unfair hiring is a legitimate concern for many organizations, where unconscious bias (or favoritism) can influence decisions based on a candidate's gender, ethnicity or age, and even their name or address. While AI is designed to prevent these issues by removing human bias from the equation, AI systems can inherit and perpetuate biases in other ways, which can lead to questionable hiring practices. The potential for AI bias occurs through:

  • Data bias – If historical hiring data is skewed toward one demographic, AI algorithms trained on this data may prefer candidates from that group.
  • Language and terminology – AI may unintentionally favor certain types of language or terminology used in resumes or interviews, eliminating candidates who express themselves differently.
  • Pattern recognition – AI systems can create patterns based on historical data. And if these patterns reflect biased decisions, the AI may perpetuate these biases, consistently selecting similar candidates.

Under these influences, AI bias may occur as selection bias (favoring certain candidates based on irrelevant factors), confirmation bias (emphasizing data that supports preconceived notions about candidates), performance bias (assessing candidates based on criteria that isn’t relevant to job performance) and stereotyping bias (assigning certain traits or preferences to candidates based on group characteristics or stereotypes).

For example, Amazon was an early adopter of AI for recruitment. Unfortunately, a gender bias emerged from the company’s reliance on historical data from existing employees. Basically, it was determined that the AI program discriminated against female applicants because of this skewed training data.

While AI in hiring offers great potential, it also raises questions about fairness and accountability. It is crucial for employers to adopt ethical AI practices and prevent bias in their algorithms.

7 Tips for Preventing AI Bias in Hiring

When adopting AI tools in the hiring process, organizations must be diligent about ethical considerations. Guarding against algorithmic bias and discrimination is crucial to upholding fairness and diversity. Here are 7 tactics to support your efforts:

  1. Utilize diverse training data – Ensure your AI system is trained on a diverse dataset that includes a wide range of demographics and backgrounds. This can help reduce bias by exposing the AI to various hiring scenarios.
  2. Aim for transparency and fairness – Select AI models that provide transparency in their decision-making process. Understand how the system reaches its conclusions and be prepared to challenge any unjust bias.
  3. Monitor and evaluate regularly – Carefully monitor your AI system's performance and analyze its results for potential bias. Frequently review its decisions and adjust the model as necessary to align with your organization's diversity goals.
  4. Conduct fairness audits – Perform fairness audits to ensure the AI system does not favor or discriminate against specific groups. Take corrective actions when you identify disparities.
  5. Prioritize human-AI collaboration – Use AI as a tool to aid your HR managers and recruiters, not replace them. Final hiring decisions should involve a human element, especially when assessing soft skills, cultural fit and nuances that AI might miss.
  6. Run regular re-training – AI models can drift in their output over time. Periodically retrain your AI system using up-to-date and diverse data to prevent it from becoming outdated and biased.
  7. Use inclusive language and policies – Review and revise job postings, interview scripts and hiring-related company policies to ensure they are inclusive and unbiased. Encourage a diverse candidate pool to apply.

Leverage AI as a Powerful Tool for Hiring Diversity and Inclusion

As a final precaution, it’s important to keep current with legislation and guidance concern AI in the workplace. For example, employers in New York City must notify job candidates that AI is being used – and allow them to request details on the data being collected. Employers must also conduct annual audits of AI tools to ensure they don’t discriminate against or disproportionately impact specific groups. Understanding emerging laws will be vital for using AI appropriately (and protecting your business) in the coming years.