38% of HR leaders have already explored using AI in the recruitment process. And, this shouldn’t come as a surprise. Artificial Intelligence is revolutionising industries across the board, from manufacturing and logistics to big data and marketing. Of course, AI in recruitment can also add untold value. And with the funding for generative AI nearly octupling in the last 2 years to reach $25.2 billion, we’ve barely even scratched the surface.
AI is still in the very early stages of development, so there’s still a long way to go before it will “take over” in any industry. For instance, generative AI tools tend to “hallucinate”; they give false information as if it were fact. As such, all answers need to be fact-checked before they can be used verbatim.
Furthermore, human-based biases tend to sneak in as these tools learn by analysing vast amounts of pre-existing data. Consequently, ensuring fairness in recruitment practices must remain a fundamental objective moving forward.
So, how can we harness the power of AI to improve the recruitment process while avoiding biases that may have already infiltrated it?
We explore common biases that occur in AI recruitment and how your organisation can create a more equitable hiring experience by limiting bias.
What Is Bias in Recruitment?
To understand how we can avoid bias in AI recruitment, we first have to understand how artificial intelligence becomes “intelligent”.
AI, especially generative AI (artificial intelligence capable of producing text, images, videos, etc.), utilises machine learning algorithms to identify patterns within data sets. However, if the data sets are based on hiring practices that have taken place until now, surely the data would be skewed, right?
Biases of gender, age, faith, and race, among others, have historically affected recruitment and still have a hugely negative impact on the industry. So, if candidates were rejected in the past over such characteristics, the AI models that learn from these data sets must pick up these same biases.
Take Amazon. The tech giant began using an AI-driven hiring model to streamline their recruitment process. While revolutionary, a certain propensity towards male applicants became apparent. The AI learnt that male applicants had historically been chosen for more technical roles in the company. As such, it inadvertently continued this prejudice, selecting male candidates over more qualified female ones simply based on gender.
The Importance of Diverse Training Data
So, how do we effectively mitigate bias in AI recruitment? The answer lies in the data we use to train the AI models.
AI models learn from the data they are fed. Therefore, if this data lacks representation, the resulting algorithms will inherently perpetuate existing biases. As such, organisations must ensure their training data reflects the rich diversity of the workforce.
Organisations can achieve this by actively sourcing data from various demographics, ensuring a balanced representation of gender, ethnicity, age, and other relevant characteristics.
This means not only using historical hiring data (as was the case in Amazon) but also integrating broader datasets that encompass different backgrounds and experiences.
For example, an AI system trained on a diverse set of resumes can better understand the qualifications of candidates from all walks of life, ultimately leading to more equitable hiring outcomes.
Implementing Human Oversight
While AI can streamline the recruitment process, it cannot replace the nuanced understanding that human judgement provides.
Implementing human oversight is crucial to counteract potential biases that may arise during the recruitment process. Regular audits of AI outcomes can help identify patterns of bias and ensure that the system aligns with the organisation’s diversity goals.
For instance, a report from McKinsey & Company found that companies with diverse teams are 27% more likely to outperform their competitors, highlighting the business case for inclusive hiring practices.
HR teams should collaborate closely with AI systems to validate hiring decisions. This can be achieved by forming diverse hiring panels that evaluate candidate selections and provide feedback on AI recommendations.
Developing Bias Awareness and Training
Creating a culture of awareness around bias (both conscious and unconscious) is imperative for organisations seeking to improve their recruitment practices.
Training programmes for HR professionals and hiring managers can significantly enhance their understanding of bias and its implications.
One such training approach at the University of Wisconsin aimed to reduce gender bias in a STEM faculty. The departments that underwent the training saw a 15% increase in female faculty hiring over the next two years. Meanwhile, the departments that didn’t complete the training saw no change in female faculty hiring.
Organisations should incorporate regular bias training sessions and workshops to empower their teams to recognise and address their own biases.
Additionally, by creating a space for open discussions about bias, employers can help build an environment where employees feel comfortable sharing their experiences and insights. This will ultimately lead to more equitable hiring practices.
Leveraging AI Tools with Built-In Bias Mitigation Features
As AI technology continues to advance, several tools have been developed with features specifically designed to reduce bias in recruitment.
For instance, platforms like Pymetrics utilise neuroscience-based games to evaluate candidates’ soft skills, providing a more holistic view of their abilities without relying on traditional metrics that may reinforce biases.
Similarly, tools like HireVue use AI-driven video interviews to assess candidates based on their responses and behaviours, rather than their appearance or background.
Adopting these innovative solutions can help organisations harness the benefits of AI while actively working to diminish bias in their hiring processes.
By selecting AI tools that prioritise fairness, organisations can remain committed to promoting diversity and inclusion in their recruitment efforts.
Creating an Inclusive Hiring Process
To create a truly inclusive hiring process, organisations must implement practical strategies that minimise bias at every stage of recruitment.
One effective approach is standardising job descriptions to eliminate ambiguous language that may unintentionally favour one demographic over another.
A job advert inclusivity screening is another great approach that tests the language used in your job description against inclusive language checklists to ensure your job posting doesn’t contain any bias.
Additionally, employing blind recruitment techniques, where identifying information is removed from applications, can further reduce bias. This allows recruiters to focus on the candidate’s skills and qualifications without being influenced by their gender, ethnicity, or other characteristics.
By taking these steps, organisations can ensure a more equitable recruitment process that values merit over preconceived notions.
Conclusion and Key Takeaways
So, what have we learnt from today’s blog on AI in recruitment and how to avoid bias? Well, here are the key takeaways:
- AI is revolutionising recruitment but also presents challenges: AI can streamline recruitment, but it can perpetuate existing biases if not implemented carefully.
- Diverse training data is key: Training AI models on diverse datasets is crucial for avoiding bias.
- Human oversight is essential: Human judgement and regular audits are necessary to counteract potential biases in AI-driven recruitment.
- Bias awareness and training matter: HR professionals and hiring managers should receive training on bias and its implications.
- AI tools with bias mitigation features can help: There are tools available that aim to reduce bias in recruitment.
- Creating an inclusive hiring process requires practical steps: Standardising job descriptions, blind recruitment techniques, and other strategies can minimise bias at every stage of recruitment.
Ultimately, recruiters need to recognise that technology alone cannot eliminate bias; it requires a concerted effort from all stakeholders to create a fair and equitable recruitment process.
As we move forward, we must embrace the potential of AI to enhance our hiring practices while prioritising fairness and inclusivity.
Become a Diversity-Positive Employer
If you’re an employer and/or business owner looking to up their game in fair, inclusive recruitment and employment, you’re in the right place.
Here at Aspiring to Include, we believe in equal opportunities for all. As well as an inclusive job board and a free resource hub, we offer a range of employer services.
From advertising opportunities to inclusivity screening, we can support your business in building an inclusive and diverse workplace with or without AI.
Get in touch today.
