How AI Supports Diversity Recruitment Strategies

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Duration: 42 min

How AI Supports Diversity Recruitment Strategies

Explore the role of AI in bias mitigation in recruitment, talent management, candidate attraction, to enhance Diversity and Inclusion.

Ruth Moquer-Torcy, Alliance & Partnership Manager SEU and Mihai Rotaru, Head of R&D at Textkernel explain what could be the role of AI in bias mitigation in recruitment, talent management, candidate attraction, to enhance Diversity and Inclusion.

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Reducing Bias to increase Diversity in the hiring process

To build a strong diverse and inclusive policy takes courage because you will face a lot of challenges. Your management is waiting for results, you’re afraid of hiring the wrong person and you don’t even know how to source the talent that you need. How will you manage diversity? If you have to change all your practices and process, will you find resistance to change? For sure, the response will be yes, somewhere. 

If you receive hundreds of applications it’s impossible to review them one by one, then if you make a choice and you discriminate. It’s a natural function.

So, sometimes implicitly, we choose what we know. This is what we call the ‘more likely effect’, you choose what you feel comfortable with.

Although it seems difficult, there are five paths you can take to build a diverse policy in your organization. Technology can help. Using the right method and the right tools, you will be set for success.

Textkernel's 37 degree angle crop: a stylized image, featuring a cropped version of the brand's iconic 37 degree angle.

How AI supports diversity recruitment strategies

Recruiters and hiring managers have very limited time to look at large amounts of CVs. This does not apply to AI. In seconds it can scan the entire content of documents. It doesn’t matter how long a resume is and most importantly, no information is lost in the process.

It is also an opportunity to bring implicit information that might not be stated in the CV. For example, calculating years of experience or experiencing a certain domain, leadership, or entrepreneurship experience are all Meta elements that AI can help extract from these documents.

Having access to information, a recruiter can make a more inclusive decision when they make the selection. But it’s also possible to hide information. Discriminatory elements like age, name, profile photos or even attributes can sometimes bring false biases. For example, choosing certain schools or discriminating a certain location, and so on.

AI can detect discriminatory phrases in job ads, for example, and offer alternatives or rewriting that content to appeal to a larger set of job seekers. This has been actually about trying to extract information from the document, that information is text but there is another level that AI can help and that is when it moves to the semantic levels.

The semantic search can identify spelling variations so in this case, the masculine and the feminine form of that job title, so it can help reach a larger set of candidates.

Going one step forward, many products also offer normalization such as job titles. Being able to understand these documents also offers an opportunity to create uniform profiles so that when recruiters or hiring managers can compare CVs without being distracted by differences in the presentation layout and where the information is located in the document.

Another way that Diversity and Inclusion can be enhanced is by making sure that the profiles on the database are as up-to-date as possible. Especially in the corporate environment where the CVs of the people usually expire because they have been working for a while in the company. In this case, it’s possible to enrich the profiles based on other sources.

The example on the slide above is a performance report and it extracts the skills that are mentioned in that portfolio. The skills can then be used to enrich the employee’s profile and therefore compete with anyone that already had the same skills on their profile.
AI can also help when recruiters are searching for people and a good semantic search allows the recruiter to reach a diverse set of candidates. The simplest thing that can be done through is by having a search product that offers simultaneous access to many sources. So, you being able to type a query and firing that query among several sources allows you to reach a more diverse set of job seekers.

We hope we’ve made clear how important Diversity and Inclusion is for organizations and how AI can help you implement and manage this, starting on your HR and recruiting processes.

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