AI in recruitment has many benefits, such as helping screen candidates, sourcing candidates in different platforms, and conducting initial interviews. But the topic of AI bias in recruitment has also been an emerging topic.
AI bias happens because of the information the system learns from. Imagine if a computer program is taught using data that shows most product designers are men. Then, it might prefer male candidates for product design jobs and overlook female candidates. Similarly, if the data used favors names that sound white, the system might show bias based on race when hiring people.
Source: Photo by Mapbox on Unsplash
In this article, we’ll help you understand what AI bias is and provide strategies to reduce the bias.
What is AI Bias in Recruitment?
AI bias in hiring means the unfair results that happen when computers and smart machines are used to pick new employees. So, AI bias in hiring can arise from a variety of factors, including:
- Algorithm design: The system may be biased due to how its algorithms were programmed.
- Data selection: The data used to teach AI systems might not include enough diverse information. Thus, leading to unfair treatment of certain groups who have faced discrimination in the past
- Lack of transparency: AI bias can occur when there isn’t clear documentation and monitoring systems.
One real-life example of AI bias in hiring is Amazon’s AI hiring platform. So, this platform was trained on different resumes for 10 years. The resumes were mostly from men and as a result, the system learned to downgrade resumes with words associated with women and hence favored men.
So, as you can see, AI bias can have negative impacts on different groups of employees. Read on to find out the strategies you can use to get rid of the bias.
Strategies for Reducing the Effects of AI Bias in Recruitment
Addressing AI bias in recruitment is important to ensuring diversity and fairness in the workplace. Here are the best practices your organization can take to reduce the effects.
1. Provide Diverse Training Data
To make AI hiring fair, we need to fix where it learns from — the data it’s trained on. So, if the data includes different kinds of people, like men and women of all races, the AI can make fair decisions when hiring.
Diversity training is as essential for AI as it is for human recruiters. Without the training, your AI hiring system gets biased.
To succeed at this step do this:
- Include global diversity representation: People from all around the world can get hired by almost any business these days. So, the data should include everyone. That means considering different kinds of people from many countries and places.
- Use inclusive terminology and language: Make sure the words used in the data are friendly to everyone. This helps the AI system learn about being fair to people with different backgrounds and identities.
- A diverse dataset: Make sure the data used to train AI includes diverse information. So that would include race, gender, age, education, and experiences.
- Diversity in job descriptions: Teach the AI system about many job titles and roles. This way, it won’t have biases against certain jobs. Use diverse job titles and descriptions for training.
Matt Little, the managing director at Festoon House, adds:
“At Festoon House, integrating AI into our hiring processes was essential to improving hiring processes. But at the same time, we were aware of the potential for bias to be introduced through AI algorithms. We developed strategies to mitigate the bias. One of these strategies was to curate training data to ensure that it was varied and representative. We worked with our experts to identify and remove any bias in the training data and fine-tune our algorithms.
The outcomes were encouraging, we increased the number of diverse candidates advancing through our recruitment process. While the quality of hires was high, we also achieved greater inclusivity.”
2. Regular Assessment of the AI Hiring System
Checking the AI hiring system regularly can find and fix biases. Testing and reviewing the system helps make sure it treats everyone fairly when hiring.
To ensure your assessment process is successful, take these steps:
- Use bias detection tools: Use special tools to find and fix bias in your AI hiring system. These tools help make sure the system is working well and being fair to everyone.
- Conduct data quality checks: Regularly check if the data used to train the AI is accurate and current. Make sure it aligns with your organization’s goal of fair hiring.
- Benchmark against industry standards: Make sure your AI hiring system follows the right rules and fairness standards used in the industry.
John Xie CEO at Taskade, adds:
”The one strategy that helped us best reduce the impact of AI bias when hiring new candidates was implementing quarterly audits and reviews of our AI systems. The results have been impressive because we have increased the number of diverse hires.”
3. Involve External Experts
Ask outside experts to check your AI systems. These external auditors should know a lot about AI and be fair and honest.
External experts can look at your AI system without any bias. So, they might see things others didn’t. Having these experts also shows everyone that your organization wants to be fair in hiring.
4. Involve Human Recruiters
Even though AI helps in hiring, it’s important to have people making the final decisions. Humans can understand feelings in a way AI can’t, so they can make choices with more understanding.
Human recruiters can think about whether a candidate fits in with the company’s culture and has good communication skills. These things are important but can’t be measured by AI. To ensure there’s good human involvement in the process, do this:
- Create a diverse review panel: Create a team of recruiters from diverse backgrounds and viewpoints to review candidates.
- Have an AI hiring review criteria document: Make a guide with your hiring team that tells the AI what to look for. There should also be a human in charge to check if the AI’s suggestions match the guide.
By creating the balance between AI and human involvement, you’ll be sure that the final hiring decisions are fair and equal.
5. Use of Blind Hiring Strategy
Blind hiring is a way to reduce AI bias. So, this means not knowing personal details about a candidate, like their name, where they went to school, or where they live. This helps make the hiring process more fair and equal for everyone.
Instead, the AI hiring system will only focus on the candidate’s previous work experience, and how their skills are important to the job they’re applying for.
6. Get Feedback from your Candidates
Ask applicants about their experience with the AI system. Their feedback helps make the system better. It also shows them that you care about being fair and inclusive.
From their feedback, you get the chance to make your candidate experience better. To get the feedback from your candidates, create a survey and ask questions such as:
- Did you experience any bias during the interview process?
- Are there questions that made you feel uncomfortable?
- What do you feel our organization can do to improve our AI hiring process?
- On a scale of 1-10, how would you rate the whole process?
Martyna Jasinska the HR Specialist and recruiter at ePassportPhoto, adds:
”Last year we took candidate feedback seriously, creating an open channel for dialogue about their experience with our AI hiring system. This holistic approach bore fruit – we celebrated a 15% spike in diversity hires within twelve months, saw a significant 20% dip in feedback pointing to hiring biases, and proudly felt the resonance of our strengthened employer brand in the talent marketplace.”
7. Create a DEI Dashboard
Create a DEI dashboard to monitor how your company is stopping unfairness in hiring through AI. This board can track progress in areas like race, age, gender, and more. It helps keep things fair for everyone.
Here’s an example: let’s say that from your data your job ads are unfair to women, and that’s why you’re not hiring more women.
For this problem, the correct hiring tool can help you write job descriptions that are appealing to women. For example, you can use Ongig’s Text Analyzer to easily find biased words in your job descriptions so you can remove or replace them with more gender-inclusive alternatives.
David Godlewski, CEO at Intelliverse, adds:
“We’ve invested in a dashboard that monitors AI fairness to counter AI bias in our hiring process. The dashboard, crafted in collaboration with experts, keeps a close eye on fairness metrics throughout our hiring stages. They help us spot and correct potential biases as they happen, making sure our AI algorithms treat all candidates fairly, regardless of gender, ethnicity, or other factors.
The results speak for themselves. We’ve made our hiring process fairer and boosted diversity and inclusion within our organization. Our strategy has also allowed us to perfect our algorithms and provide equal opportunities for everyone. This has built trust with both our employees and candidates, showcasing our commitment to ethical and equitable AI-driven hiring practices.”
WHY I WROTE THIS:
At Ongig, we want to help you create job postings that welcome everyone. So, we have a tool called Text Analyzer that makes sure your job descriptions are fair and open to people from different backgrounds. We believe everyone should have the same chances at work, no matter where they come from.
With Text Analyzer, your job ads are fair and equal for everyone. Let’s work together to make a workplace where everyone is given the same opportunities. Book a demo today to learn how you can write inclusive job descriptions.
SHOUT-OUTS:
- Amazon Scraped ‘Sexist AI Tool’ by (BBC)
- David Godlewski, CEO at Intelliverse
- Martyna Jasinska the HR Specialist and recruiter at ePassportPhoto
- John Xie CEO at Taskade
- Matt Little, the managing director at Festoon House
